THE KILO−PARSEC PROPERTIES OF BLAZARS

A Dissertation

Submitted to the Faculty

of

Purdue University

by

Nathaniel Jonathan Cooper

In Partial Fulfillment of the

Requirements for the Degree

of

Doctor of Philosophy

December 2010

Purdue University

West Lafayette, Indiana ii

To my wife Kaliroi, my son Johannes, and my Mom and Dad. iii

ACKNOWLEDGMENTS

First and foremost, I thank my advisor Matthew Lister. He suggested this disser- tation topic and without his guidance and patience this dissertation would not have been possible. I thank my committee member and Physics 670F professor, Stephen Durbin. Building the radio telescope in his class helped guide me to radio astronomy and his advice has always been invaluable. I also extend my thanks to committee member John Finley, he came through for me in when I was in a tight spot getting my paperwork submitted for my dissertation talk at the 216th AAS meeting, and he was always very helpful in Journal Club with his comments to my presentations. I thank my committee member Sergei Khlebnikov, who was also my professor in Introduction to Mechanics, Intermediate Optics, and Advanced Statistical Mechanics. His sense of humor made his classes a wonderful and insightful experience. And thanks to the other faculty and staff at Purdue, especially Andrew Hirsch my Sophomore Seminar and Science & Society professor and Ephraim Fischbach my Theoretical Methods of Physics professor both of whom gave the right advice at the right time to keep me on track, Russ Coverdale my undergraduate advisor who helped me in too many ways to count, Andrzej Lewicki for his guidance while I was a Teaching Assistant, Brian Todd for helping with my Preliminary Defense and Sandy Formica and Carol Buuck for helping me keep my i’s dotted and t’s crossed. I thank my family and friends for their support throughout the process of writing this dissertation: To my mom for always encouraging my interest in science, to my dad who always did his best to explain phenomena to me when I was a child, to my wife, Kaliroi, and mother−in−law, Eftihia, whose support has been unwavering, and iv to my high school friend and US Navy buddy John Jansen and my long time friend Jim Drury they helped in ways large and small too many time to mention. I thank Deborah Beck, my high school physics teacher. I always wanted to be a scientist and she helped me find out what kind I wanted to be. If she had not let me make up several labs by using parts in my dad’s garage, I would not be writing this dissertation. And a special thanks to Brandon Hogan, Sarma Kuchibhotla, Mihai Cara, Preeti Kharb, and Talvikki Hovatta for their guidance in this endeavor. This research was supported by NSF grant 0807860-AST, NASA-Fermi grant NNX08AV67G and the Purdue Research Foundation, and made use of the follow- ing resources: The NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. The Very Large Array (VLA), which is operated by The National Radio Astronomy Observatory (NRAO). The NRAO is a facility of the National Science foundation, operated under coopera- tive agreement with Associated Universities, INC. v

TABLE OF CONTENTS

Page LIST OF TABLES ...... vii LIST OF FIGURES ...... ix SYMBOLS ...... xi ABBREVIATIONS ...... xii ABSTRACT ...... xiii 1 INTRODUCTION ...... 1 1.1 Active Galactic Nuclei ...... 1 1.1.1 The Anatomy of AGNs ...... 3 1.1.2 AGN Spectra ...... 8 1.1.3 Radio Quiet AGNs ...... 9 1.1.4 Radio Loud AGNs ...... 10 1.2 Relativistic Effects in Blazar Research ...... 14 1.2.1 Relativistic Beaming ...... 15 1.2.2 Superluminal Motion ...... 15 1.2.3 Doppler Boosting ...... 17 1.3 Unification Schemes ...... 18 1.4 The MOJAVE Survey ...... 20 1.5 Radio Telescopes used in MOJAVE ...... 20 1.5.1 The Very Large Base−line Array ...... 21 1.5.2 The Very Large Array ...... 21 1.6 Goals of this Dissertation ...... 22 2 KILOPARSEC PROPERTIES ...... 25 2.1 VLA Observations ...... 25 2.1.1 Images Acquired in the Fall 2004 − AL634 ...... 26 2.1.2 Images Acquired in June 2007 − AC874 ...... 27 2.1.3 Data Obtained from NRAO Archives and Previous Studies . 28 2.1.4 Observation and Image Data ...... 28 2.2 MOJAVE Sample Statistics ...... 32 2.3 Extended Luminosity v. Intrinsic Power ...... 44 3 JET GEOMETRY − SIMPLE BENDS ...... 59 3.1 Previous Simple Bend Monte Carlo Simulations ...... 59 3.2 Simulating the MOJAVE Sample Population ...... 60 vi

Page 3.2.1 Simulating General MOJAVE Variables ...... 61 3.2.2 Simulating φ and ζ...... 66 3.2.3 Simulations with a Uniform Distribution of ζ...... 70 3.2.4 Simulations with a Gaussian Distribution of ζ ...... 75 3.2.5 Simulations with a Power−law Distribution of ζ...... 78 3.3 Summary ...... 81 4 γ−RAY EMISSION vs. EXTENDED RADIO EMISSION ...... 85 4.1 γ−ray−Radio Emission Models ...... 86 4.2 Observations ...... 86 4.3 Comparison with Previous Analysis ...... 87 4.4 Partial Correlation Analysis ...... 88 4.5 Jet Power and γ−ray Luminosity ...... 92 4.6 Monte Carlo Simulations of Lγ vs. MOJAVE Lγ ...... 92 4.7 Calculating Correlations with Censored Data ...... 93 4.8 Core γ−ray Emission vs. Lobe γ−ray Emission ...... 102 4.9 Results ...... 102 5 SUMMARY ...... 105 5.1 Thesis Goals and Results ...... 105 5.1.1 Image Catalog and Sample Statistics ...... 106 5.1.2 Jet Misalignment Angles ...... 107 5.1.3 Radio−γ−ray Correlation ...... 108 5.2 Future Work ...... 110 5.2.1 eMERLIN Intermediate Scale Jet Survey ...... 110 5.2.2 Expanding the Search for FRII BL Lacs ...... 110 5.2.3 Radio Morphology Survey Based on Fermi Selection Criteria 111 A 1.4 GHZ VLA IMAGES OF THE MOJAVE SAMPLE POPULATION . 113 LIST OF REFERENCES ...... 249 VITA ...... 255 vii

LIST OF TABLES

Table Page 2.1 A−Configuration VLA Observations of MOJAVE Sources at 1.4 GHz . 29 2.1 A−Configuration VLA Observations of MOJAVE Sources at 1.4 GHz . 30 2.1 A−Configuration VLA Observations of MOJAVE Sources at 1.4 GHz . 31 2.2 MOJAVE VLA 1.4 GHz Image Parameters ...... 36 2.2 MOJAVE VLA 1.4 GHz Image Parameters ...... 39 2.2 MOJAVE VLA 1.4 GHz Image Parameters ...... 40 2.3 MOJAVE VLA 1.4 GHz Image Measurements ...... 41 2.3 MOJAVE VLA 1.4 GHz Image Measurements ...... 42 2.3 MOJAVE VLA 1.4 GHz Image Measurements ...... 43 2.4 Single Dish and Short Base−line Observations of MOJAVE Sources at 1.4 GHz ...... 46 2.4 Single Dish and Short Base−line Observations of MOJAVE Sources at 1.4 GHz ...... 47 2.4 Single Dish and Short Base−line Observations of MOJAVE Sources at 1.4 GHz ...... 48 2.4 Single Dish and Short Base−line Observations of MOJAVE Sources at 1.4 GHz ...... 49 2.4 Single Dish and Short Base−line Observations of MOJAVE Sources at 1.4 GHz ...... 50 2.4 Single Dish and Short Base−line Observations of MOJAVE Sources at 1.4 GHz ...... 51 2.4 Single Dish and Short Base−line Observations of MOJAVE Sources at 1.4 GHz ...... 52 2.4 Single Dish and Short Base−line Observations of MOJAVE Sources at 1.4 GHz ...... 53 2.4 Single Dish and Short Base−line Observations of MOJAVE Sources at 1.4 GHz ...... 54 viii

Table Page

2.4 Single Dish and Short Base−line Observations of MOJAVE Sources at 1.4 GHz ...... 55 2.4 Single Dish and Short Base−line Observations of MOJAVE Sources at 1.4 GHz ...... 56 2.4 Single Dish and Short Base−line Observations of MOJAVE Sources at 1.4 GHz ...... 57 3.1 χ2 of ζ Monte Carlo Simulations with Gaussian Γ Distributions .... 82 3.1 χ2 of ζ Monte Carlo Simulations with Gaussian Γ Distributions .... 83 3.2 χ2 of ζ Monte Carlo Simulations with Power Law Γ Distributions . . . 84 4.1 ASURV Spearman Ranks for γ−ray to Radio Emission ...... 95 4.2 ASURV Spearman Ranks for γ−ray Emission, de−Boosted by δ2−α, to Radio Emission ...... 96 4.3 ASURV Spearman Ranks for γ−ray Emission, de−Boosted by δ3−2α, to Radio Emission ...... 97 ix

LIST OF FIGURES

Figure Page 1.1 3C 273 Spectrum from Schmidt [1963] ...... 2 1.2 AGN model taken from Urry & Padovani [1995]...... 5 1.3 WSRT 0.6 GHz image of FR I 3C 31 (0104+321), taken from Leahy[2003]. 12 1.4 VLA 5 GHz image of FR II Cygnus A (1957+405), taken from Perley, Dreher, & Cowan [1984]...... 13 1.5 1.4 GHz VLA-A image of radio quasar 2201+315, taken from Cooper, Lister & Kochancyzk [2007]...... 13 1.6 1.4 GHz VLA-A images of Blazars, taken from Cooper, Lister & Kochancyzk [2007]...... 14 1.7 Superluminal Motion World−line Diagram ...... 16 1.8 Unified Scheme Diagram ...... 19 2.1 MOJAVE Redshift Distribution ...... 33 2.2 MOJAVE Luminosity Distribution ...... 34 2.3 MOJAVE Core Prominence Distribution with Upper Limits ...... 37 2.4 MOJAVE Core Prominence Distribution by Optical Type ...... 38 2.5 NVSS VLA−D flux density vs. MOJAVE VLA−A flux density .... 45 3.1 MOJAVE ∆PA Distribution ...... 61 3.2 Simulated θ Distribution, using a Gaussian Γ Distribution ...... 64 3.3 Simulated θ Distribution, using a Power Law Γ Distribution ...... 65 3.4 χ2 vs. FWHM ...... 67 3.5 χ2 vs. Index ...... 68

2 3.6 χ vs. ζmax ...... 69 ◦ 3.7 Simulated ∆PA, ζ Uniform Distribution ζmax = 11.25 , Gaussian Γ Dis- tribution ...... 71 ◦ 3.8 Simulated ∆PA, ζ Uniform Distribution ζmax =1.25 , Gaussian Γ Distri- bution ...... 72 x

Figure Page

◦ 3.9 Simulated ∆PA, ζ Uniform Distribution ζmax = 9.5 , Power Law Γ Dis- tribution ...... 74 ◦ ◦ 3.10 Simulated ∆PA, ζ Gaussian Distribution ζpeak =0.25 , 10 FWHM, Gaus- sian Γ distribution ...... 76 ◦ ◦ 3.11 Simulated ∆PA, ζ Gaussian Distribution ζpeak = 4 , 1 FWHM, Power Law Γ Distribution ...... 77 3.12 Simulated ∆PA, ζ Power Law Distribution α = 0.25, Gaussian Γ distri- bution ...... 79 3.13 Simulated ∆PA, ζ, Power Law Distribution α = −0.1, Power Law Γ dis- tribution ...... 80

4.1 z vs. Lc ...... 89

4.2 z vs. Lγ ...... 90

4.3 z vs. Lc ...... 91

4.4 Lext vs. Lγ ...... 98

4.5 Sext vs. Sγ ...... 99

4.6 Lc vs. Lγ ...... 100

4.7 Sc vs. Sγ ...... 101 A.1 AL634 Images ...... 114 A.2 AC874 Images ...... 174 A.3 Archival Images ...... 180 xi

SYMBOLS

β, Intrinsic jet speed in units of c

βapp, Apparent jet speed in units of c Γ, Bulk jet Lorentz factor δ, Relativistic Doppler factor

Lcore, Radio luminosity of the AGN core structure

Lext, Radio luminosity of the AGN extended jet structure

Lγ , Gamma−ray luminosity of the AGN 33 −1 L⊙, Solar luminosity, 3.84 × 10 erg s

33 M⊙, Solar mass, 1.99 × 10 g M, mass φ, Azimuthal angle of a jet on the plane of the sky θ, Viewing angle, i.e. the angle of the jet with respect to observer’s line of sight v, velocity ζ, Intrinsic bend angle of a jet xii

ABBREVIATIONS

AGN Active Galactic Nuclei GR General Relativity IGM Intergalactic Medium ISM Interstellar Medium mas milli−arcsecond MHD Magnetohydrodynamics SPG Sample Population Generator VLA Very Large Array radio telescope VLBA Very Large Baseline Array radio telescope xiii

ABSTRACT

Cooper, Nathaniel J. Ph.D., Purdue University, December 2010. The Kilo−Parsec Properties of Blazars. Major Professor: Matthew L. Lister.

In this dissertation, we explore the properties of Active Galactic Nuclei (AGN) on kiloparsec scales at a radio frequency of 1.4 GHz. These properties include flux density, luminosity, and morphology. We compare these kiloparsec scale properties to similar properties on the parsec scale at 15 GHz, such as jet misalignment angle and other parsec scale properties, such as γ−ray flux density and luminosity. The AGN studied are the 135 from the Monitoring Of Jets in Active galaxies using VLBA Experiments (MOJAVE) survey, MOJAVE−I sample. Using Monte Carlo Simulations with matching sample statistics, We find that the most likely distribution of intrinsic pc−to−kpc scale bend angles is a uniform distribution with a range of 0◦− ∼ 10◦. The maximum bend angle is unlikely to be < 5◦ or > 30◦. Furthermore, power law distributions with an index > 1.25 or < −0.5 are ruled out at the 95% confidence level. Narrowly peaked Gaussian distributions are likewise excluded.

Using the ASURV statistics package, We find that gamma−ray (Lγ) and kpc−scale radio luminosities (Lext) are strongly correlated. Since Lext is correlated with jet power, it is likely that this is indicative of a mutual dependence of intrinsic γ−ray and extended radio emission on jet power. Partial correlation coefficients increase if Lγ is de−boosted by either the synchrotron−self Compton or external Compton models. Furthermore, no convincing correlation between Lγ and unresolved VLA core luminosity (Lc) is present. Based on previous findings that use median VLBA flux densities a correlation with Lγ may be present. However, considering that the VLA data are from a single epoch and not taken simultaneously with the γ−ray data, xiv

this greatly reduces the chances of detecting Lc − γ−ray correlations after redshift bias is factored out. Although a recent discovery of extended γ−ray emission from

Centaurus A could suggest a contribution to the Lγ−Lext correlation, this emission is diffuse and most MOJAVE sources are at large luminosity distances. The presence of diffuse γ−ray emission is therefore unlikely to affect our conclusions regarding the

Lext and Lγ correlation. 1

1. INTRODUCTION

This dissertation is concerned with the properties of active galactic nuclei(AGNs), which often produce energetic plasma outflows. In this dissertation, I examine various properties, such as jet power, jet speed, viewing angle, galactic environment, etc., that may affect the morphology of blazar jets at the kiloparsec scale. For the convenience of readers who may not be acquainted with blazar research, or active galactic nuclei in general, I provide a brief description of these objects and their properties below. Readers who are familiar with AGN research may want to start at section §1.3 where I discuss the goals of this dissertation.

1.1 Active Galactic Nuclei

AGNs are the highly luminous centers of some galaxies. Based on their accretion duty cycle approximately 0.6% of galaxies have an active nucleus [Greene & Ho,

7 2007, 2009]. This assumes a central engine mass of 10 M⊙, and the length of the duty cycle decreases with mass. Of those galaxies with an active nucleus, only ∼ 10% form jets [Peterson, 1997]. These jets are the most distinctive feature of AGNs, and consist of high energy plasma that can extend up to a few million light−years. The accepted model of AGN, and similar jet−forming phenomena such as x−ray binaries and T−Tauri stars, is the accretion of matter with initial angular momentum into a deep gravitational well. The conditions that create AGN are the most extreme in observational astro- physics for long−lived phenomena. AGN continuum spectra can range from radio to

α γ−ray wavelengths, and the spectrum’s power law behavior (Sν ∝ ν , where Sν is flux at an observed frequency, ν is frequency and α is the spectral index) indicates that the radiation is non−thermal in origin. AGNs have cosmologically redshifted 2

emission line spectra that indicate distances ∼ 107−9 parsecs away (Fig−1), accord- ing to Hubble’s Law. Many AGN have UV/Optical line spectra whose flux can be several percent of the continuum flux and emission (to a lesser degree absorption) line widths that correspond to gas cloud velocities ∼ 10, 000 km s−1. Their luminosities range from ∼ 1042 erg s−1 to ∼ 1048 erg s−1. This is up to 104 times brighter than an average galaxy, so the nucleus can easily outshine its host galaxy. Furthermore, the central engine that drives these objects is unresolved on a scale as small as 0.01 pc [Kellermann, Zensus & Cohen, 1997]. Such a high amount of power output confined to such a small region of space suggests that AGNs are powered by the in−fall of

6−10 matter from an accretion disk onto a super−massive black hole (∼ 10 M⊙) at the center of the host galaxy [Krolik, 1999]. Therefore, AGNs are excellent laboratories for conditions that we cannot reproduce here on Earth.

Figure 1.1. Spectrum of quasar 3C 273 taken from Schmidt [1963], showing the red- shifted Balmer series. For example, the Hβ line is shifted from 486 nm to 560 nm. This corresponds to a redshift of 0.158. 3

There are a variety of AGN types, and their classification depends on such factors as kiloparsec−scale morphology, UV/Optical spectra, radio brightness, variability and polarization. Historically, astronomers saw the various species of AGNs (such as lower luminosity, radio−quiet Seyferts and higher luminosity, radio−quiet Quasars) as distinct objects, because only extreme objects in each class were visible to early observers. However, as observations on these objects increased in sensitivity and population surveys increased in number, it became apparent that these objects were related to each other in some way. This gave rise to various unification schemes [Urry & Padovani, 1995]. I discuss the prevalent unification scheme below. My research seeks to refine it, however, it is first necessary to provide the details of AGN classification.

1.1.1 The Anatomy of AGNs

Numerous radio imaging surveys of AGNs [Kharb, Lister & Cooper, 2010, Cooper, Lister & Kochancyzk, 2007, Rector & Stocke, 2001, Condon et al., 1996, Perlman & Stocke, 1994, Murphy, Browne & Perley, 1993, Antonucci & Ulvestad, 1985, Linfield & Perley, 1984] consistently identify certain morphological structures, such as jets, lobes, halos and cores. The study of these structures gives observers insight into the physical processes occurring in and around AGNs. Additionally, AGNs have a distinct anisotropic structure (Fig−2) which makes measurement of quantities like luminosity and jet speed highly sensitive to viewing angle. The relativistic effects of Doppler boosting and superluminal motion are a major cause (see §1.1.5). The type and size of structures seen can give us an estimate of the viewing angle to the AGN. Therefore, accurately knowing the three−dimensional anatomy of AGNs is vital to their study. Figure 2 shows a cartoon model of an AGN. The central engine is a super−massive

2 14 black hole, whose Schwartzschild radius, Rs = 2GM/c ,isRs =3 × 10 M9 cm, where 9 14−15 M9 is mass in units of 1 × 10 M⊙. Next, an accretion disk extends ∼ 10 cm out 4

from the black hole. Friction created by the rapid rotation of gas in the accretion disk generates a plasma that creates the B−field surrounding the AGN and the electrons that constitute the AGNs jets. Above the accretion disk are rapidly moving clouds of gas ∼ 1016cm out that are responsible for the broad emission lines. A dust cloud with a torus or warped disk geometry may extend ∼ 1017cm, and obscure the broad emission lines for an observer with a transverse line of sight. Above the broad line clouds are slower−moving narrow line clouds that can extend as far as 1020cm. Finally, the jets are highly collimated emission regions that form along the rotation axis of the accretion disk and extend out to 1024 cm [Urry & Padovani, 1995].

Cores

The core is an unresolved bright emission region observed in the center of all radio−loud AGNs. The central engine: the super−massive black hole, accretion disk and ’nozzle’ that collimates the jets are all contained in the core. Very Long Baseline Interferometry (VLBI) radio telescopes, with milli−arcsecond (mas) angular resolution, have been unable to completely resolve this central region. Very Large Array (VLA) flux density measurements of the core, with arcsecond scale angular resolution, are typically very close to the total flux density of the VLBI structure. The core usually has a flat radio spectral index (α from 0 to -0.7). This is caused by the superposition of continuum emission from several different jet regions (e.g., Cotton et al. 1980). Astronomers call this phenomenon the ’Cosmic Conspiracy’, because the individual synchrotron self absorbed regions have synchrotron peaks spaced in ν in just the right way that the total spectrum appears flat. Extended structures, such as the jets and lobes discussed below, tend to have steeper spectral indices (i.e., larger in magnitude) than the cores because the individual emission regions can be resolved by the telescope. In certain AGNs the core can vary rapidly in continuum flux with a period on the order of days [Urry, 1993]. Simple light travel time estimates [Rybicki & Lightman, 5

Figure 1.2. AGN model taken from Urry & Padovani [1995].

1979] constrain the size of the central engine to a maximum of a few light−days across. VLBI measurements of low redshift radio galaxies have achieved resolutions of 0.01 parsecs (about 3 light−days), and were unable to resolve the core. 6

Jets

Bridle & Perley [1984] define a jet as a feature at least four times as long as it is wide, separable at high resolution from other extended structures, and aligned with the core where closest to it. Jets form when plasma created by the heat of the in−falling gas of the accretion disk is swept up along the magnetic field [Blandford & Rees, 1974]. Electrons and possibly positrons or protons in the plasma oscillate rela- tivistically around the magnetic field lines, creating incoherent synchrotron radiation. This synchrotron radiation is the primary emission mechanism in the radio regime. Magnetohydrodynamic (MHD) and general relativistic (GR) conditions close to the black hole can act as a nozzle and eject gas at very high speeds (super Alfv´en and sometimes relativistic) [Meier, Koide & Uchida, 2001]. On parsec scales, we see a variety of interesting behavior. Plasma ejected from jets can follow both ballistic or non−ballistic trajectories [Kellermann et al., 2004]. Be- cause some jets are relativistic, jets that are pointed toward the observer are Doppler boosted (e.g., Rybicki & Lightman 1979). Doppler boosting causes the observed lu- minosity to be greater than the intrinsic luminosity in the source’s reference frame. These jets can also exhibit superluminal motion. In superluminal motion, the ap- parent time duration of the signal from the the source is compressed (see §1.2.2), creating an ideal circumstance to study jet kinematics, as several decades of evolu- tion are compressed into smaller time scales. Counter−jets (jets that are pointed away from the observer) are often not detected in relativistic jets, because Doppler boosting greatly diminishes the apparent luminosity for receding velocities with respect to the observer. As the jet transitions to kiloparsec scales, the plasma flows become subsonic (for more powerful Fanaroff−Riley II radio galaxies this may not be the case) and bound- ary conditions with the intergalactic medium stabilize. Jets at this scale can show some curvature, but they display very little evolution. Jets contain bright spots, called knots, that are likely shock fronts. AGN are classified, in part, by their morphology 7

on this scale, due to the development of the classification schemes before significant numbers of higher resolution images became available.

Lobes

Jets of high luminosity objects typically terminate in large blobs of radiation called lobes. Bow shocks, where the ram pressure driving the jet ceases to dominate the pressure of the intergalactic medium (IGM), create these lobes. The bow shocks create bright features called hot spots, and then disperse the jet into filamentary structures that flow backward toward the core. Although in some AGN the receding jet cannot be seen due to relativistic beaming, the two hot spots are often seen to lie along the same line on opposite sides of the the core. This gives strong indication that the counter jet is present, although its surface brightness is below the sensitivity of the telescope, or it is obscured from view. The synchrotron cooling time of electrons

−1 in a hot spot is 3γe M9 s, where γe is the Lorentz factor of the oscillating electron. However, the lifetime of a jet is 107yr. Without a continuous supply of electrons, the jet would rapidly fade. Lower luminosity objects’ jets tend not to be as highly collimated and diminish in surface brightness with distance from the core, until they gradually disappear below the noise level in radio images.

Halos

In AGNs seen at low angles of incidence with respect to the jet, the centroid of the extended emission can coincide with the core. The more diffuse plume−like emission from low luminosity jets or the lobes from high luminosity jets then forms a halo around the core. These halos are quite irregular in shape as they depend on the hydrodynamic conditions at the terminal end of the jet and the viewer’s orientation. The emission in halos is difficult to detect if it is low level and diffuse on scales larger than the restoring beam of the telescope [Cooper, Lister & Kochancyzk, 2007]. 8

1.1.2 AGN Spectra

Early surveys classified AGNs on the basis of their emission line spectra (called simply line spectra) and their luminosities. Though MOJAVE does not monitor line spectra, the ability to detect these spectra and their characteristics still play a strong role in AGN classification. It is therefore appropriate to make a few comments about AGN line spectra now before AGN classification is discussed. AGN spectra are distinct from the spectra of stars and other galaxies, as AGN spectra are very prominent with equivalent line widths ∼ 100A.˚ Also, stars tend to have strong absorption lines, whereas most AGN do not (Broad Absorption Line QSOs are an exception). The continuum spectrum of the AGN drowns out the continuum of host galaxy starlight and diminishes the absorption lines. Perhaps the most inter- esting thing about AGN line spectra are that lines in some objects are quite broad, corresponding to velocities ∼ 104km sec−1, whereas other lines only correspond to velocities ∼ 100km sec−1. Observational evidence places the origin of broad emission lines and narrow emission lines into two separate regions (see §1.1.1).

The Broad Line Region

The current paradigm for AGN morphology places the high velocity gas clouds that form broad emission lines via Doppler broadening just above the accretion disk on either side of the central black hole. Not all AGNs exhibit broad lines. Observational evidence suggests that a combination of obscuration from electron scattering and dust clouds [Antonucci, 1984, Antonucci & Miller, 1985, Miller, Goodrich & Mathews, 1991] due to orientation is the culprit. These dust clouds form a torus or warped disk just outside the accretion disk that block the broad line clouds when viewing the AGN nearly perpendicular to the accretion disk rotation axis. There are some exceptions; the BL Lac class seems to completely lack a broad line region. 9

The Narrow Line Region

For AGN with detectable line spectra, the narrow lines corresponding to low velocity gas clouds are common to all classes. Lack of obscuration suggests that the narrow line clouds are farther out from the accretion disk than the broad line clouds. Only Doppler boosted continuum emission viewed at very low angles with respect to the jet would swamp this line emission.

1.1.3 Radio Quiet AGNs

Radio quiet AGNs have ratios of 5 GHz radio flux to B−band optical flux less than 10 [Kellermann et al., 1989], and constitute roughly 90% of the AGN population. MOJAVE does not monitor these AGN, however the study of them factors heavily into AGN unification. Therefore it is useful to have some familiarity with these objects when discussing AGN unification. The first AGN unification theory was between Seyfert galaxies and quasars when it was realized that they were the same phenomena that formed a continuum of luminosities [Weedman, 1977]. The Seyfert galaxies also have the distinction of being the first AGNs discovered. In 1908 E.A. Fath obtained the spectrum from Lick Observatory of NGC 1068 and discovered strong emission lines [Peterson, 1997]. It was not until 1943 that Carl Seyfert recognized these AGN as a distinct class.

Seyfert Galaxies

Seyfert galaxies in general have low luminosities, MB > −21.5 + 5log h0 where

MB is optical B−band absolute magnitude and h0 is the Hubble constant in units of −1 −1 100km s Mpc . For h0 =0.75, a Seyfert galaxy would be about 4.5 times brighter than the Milky Way, assuming an M = −20.5. Seyferts are further classified by the presence or absence of broad emission lines. Those with broad lines are designated 10

Seyfert I (Sy I) and those without Seyfert II (Sy II) [Peterson, 1997]. Narrow emission lines are common to both classes. Seyfert galaxies are associated with spiral galaxies. Morphologically, Sy I or II looks like a spiral galaxy with a very bright nucleus. In the radio, these objects are faint and have irregular morphology. Some can have faint plumes of radio emission, while others have blotchy radio emission.

Radio Quiet Quasars

Although more luminous, MB < −21.5 + 5log h0, radio quiet quasars (QSOs) share many common features with Sy Is. Their emission spectra are similar, except that in QSOs stellar spectra ranges from weak to undetectable. Many QSOs have high z and are not resolved in the optical. Additionally, the narrow lines are weaker than broad lines compared to Sy Is [Peterson, 1997].

1.1.4 Radio Loud AGNs

The focus of this dissertation will be radio loud AGNs. These objects consti- tute roughly 10% of the total AGN population. Apart from the difference in radio brightness, these objects have a lot in common with radio quiet AGN. At shorter wavelengths their continuum emission are similar, remaining quite flat for eight or more decades. Both groups have similar spectra. However, radio loud AGN are usually associated with giant elliptical galaxies.

Radio Galaxies

Fanaroff & Riley [1974] discovered that radio galaxies could be split into two populations. Those radio galaxies with luminosity at 408 MHz < 1025W Hz−1 were deemed FR I, and those with luminosity greater than the above threshold were deemed

FR II. This classification was originally morphological; the FR Is had a ratio RF R < 11

0.5, where RF R is the distance between regions of greatest surface brightness on either side of the central galaxy to the total extent of the emission. Ledlow & Owen [1996] also found that FR Is and FR IIs are distinct in host galaxy optical luminosity as well. Since optical luminosity is ∝ M, depth of the gravity well and fueling efficiency may be the major contributors of the FRI/FRII dichotomy. Additional factors such as interstellar gas density and pressure, and extent of the ISM, all functions of optical luminosity which effect the environment of the host galaxy, may also play a role in the FRI/FRII dichotomy. Furthermore, Ledlow & Owen [1996] found that the break in radio luminosity between FRI and FRII occurred between 1024−26.5W Hz−1.

FR I Radio Galaxies

FR Is have prominent cores (the core is brighter than the jets). They have diffuse jets that tend to fade away with distance, and no terminal hot spots. These jets may also have irregular bends (see Fig. 3). On the kiloparsec scale these jets are two−sided, but on parsec scales some do show one−sided morphology. This indicates that the plasma is ejected relativistically near the core and decelerates further down stream. The emission spectra of FR Is only show narrow lines.

FR II Radio Galaxies

The more luminous FR IIs are lobe dominated; they were originally classified as having RF R > 0.5 (i.e., the distance between areas of greatest surface brightness was more than half the total extent of emission). They have highly collimated jets that end in bright hot spots, and can extended ∼ 104−6 kiloparsecs from the core. These jets sometimes show bends when entering the lobes as they experience turbulence with the filamentary emission of the lobes. FR II spectra sometimes display broad lines. 12

Figure 1.3. WSRT 0.6 GHz image of FR I 3C 31 (0104+321), taken from Leahy [2003].

Radio Loud Quasars

These quasars were the first quasars detected and form the extreme end of their class in terms of luminosity. Radio quasar spectra are similar to QSO spectra. They are highly core dominated (see Fig. 7). The radio morphology of quasars is diverse; some have jets (see Fig. 6) some have lobes with the absence of jets, while others have halos, and still others are cores with no extended features. These varied morphologies, and superluminal parsec−scale jet speeds [Cohen et al., 2007] are primarily caused by viewing the jets and lobes of the AGN at low angles of incidence with respect to the viewer. Radio quasars are the largest population (N = 101 or 75% of the MOJAVE sample) of AGN in the MOJAVE program. 13

Figure 1.4. VLA 5 GHz image of FR II Cygnus A (1957+405), taken from Perley, Dreher, & Cowan [1984].

2201+315

31 46 15

00

45 45

30 DECLINATION (J2000) 15

00

22 03 18 17 16 15 14 13 12 RIGHT ASCENSION (J2000)

Figure 1.5. 1.4 GHz VLA-A image of radio quasar 2201+315, taken from Cooper, Lister & Kochancyzk [2007].

Blazars

This extreme class of objects is the rarest of the AGNs. This class consists of two sub−classes, flat spectrum radio quasars (FSRQs) and BL Lacertae objects (BL 14

Lacs or BLOs). The distinguishing feature between the two sub−classes is that BL Lacs show very weak, if any, line spectra. Both FSRQs and BL Lacs are highly core dominated, show higher polarization than other AGNs [Lister, 2001], and have rapid intra−day continuum variability. On parsec scales their inner jets display large superluminal motions [Cohen et al., 2007]. Morphologically, BLOs are mostly halos or cores. FSRQs show a wider range of features, but are more compact than radio galaxies. All of these factors indicate that we are viewing these objects at very small angles.

0300+470 0234+285 47 16 35 28 48 25 30 20 25 15 20 10 15 05 10 DECLINATION (J2000) DECLINATION (J2000) 00 05 47 55 00 50 03 03 37.0 36.5 36.0 35.5 35.0 34.5 34.0 33.5 02 37 53.5 53.0 52.5 52.0 51.5 51.0 RIGHT ASCENSION (J2000) RIGHT ASCENSION (J2000) (a) BL Lac 0300+470 (b) Quasar 0234+285

Figure 1.6. 1.4 GHz VLA-A images of Blazars, taken from Cooper, Lister & Kochancyzk [2007].

1.2 Relativistic Effects in Blazar Research

AGN are extremely powerful objects capable of ejecting plasma at a significant fraction of the speed of light (c). In light of this, it is important to keep in mind how the great speeds of the jet and the jet’s orientation to the observer effect our measurements. Indeed, the purpose of this dissertation is to ascertain several intrinsic properties in light of the fact that they are distorted by their relativistic nature. Below I discuss three relativistic effects cogent to this dissertation, relativistic beaming, Doppler boosting and superluminal motion. Rybicki & Lightman [1979], chapter 15

4, has an excellent section discussing these effects in greater detail, as do [Urry & Padovani, 1995, Kellermann et al., 2007].

1.2.1 Relativistic Beaming

Relativistic beaming is the result of aberration of light due to Lorentz transforma- tions of velocity. Consider an object traveling at an angle θ′ in the rest frame (S′) of a system; The angle θ the object is traveling in an observer frame (S) with a velocity of β with respect to S′ is:

sin θ′ sin θ = (1.1) Γ(1 + β cos θ′) Γ is the Lorentz factor,

Γ=1/ (1 − β2) (1.2) p For a photon emitted at θ′ = π/2 in a system such that β ∼ 1, θ′ becomes ∼ 1/Γ. For example, as an object moves relativistically, isotropically emitting photons in its rest frame, an observer would expect to see the emission swept into a cone of half−angle 1/Γ.

1.2.2 Superluminal Motion

As its name suggests, superluminal motion is an effect where an object appears to be traveling faster than c. Superluminal motion is caused by the light signals emitted by the object being very closely followed by the object itself when moving at a very small viewing angle, therefore superluminal motion is also associated with relativistic beaming. The world−line diagram (Fig. 6) shows the geometry of superluminal motion. A blob of plasma (traveling close to c in the observer frame) emits a photon at a time t = 0 in the viewer’s reference frame. The blob travels toward the viewer at a speed β, path length L, and at an angle θ, before emitting a second photon a 16

time δt=(L/βc)(1 − cos θ) later. Projected on the plane of the sky, the viewer sees the plasma blob travel a distance βcδtsin θ. The apparent speed βapp is:

βapp = β sin θ/(1 − β cos θ) (1.3)

An intrinsic speed of 0.9 at a viewing angle of 10◦ (both these values are modest

for a blazar) gives a βapp of 1.4c.

Figure 1.7. A world−line diagram illustrating the time contraction that causes ap- parent superluminal motion. An event, represented by the blue bursts, occurs in a system traveling close to c with respect to an observer. The light signals from the events arrive at the observer located on the ordinate axis. The observer’s inertial reference frame is represented by the solid axes. The event’s inertial reference frame is represented by the dashed axes. Dashed lines represent the speed of light. The time intervals are to scale. 17

1.2.3 Doppler Boosting

Doppler boosting is also a consequence of relativistic beaming. As with superlu- minal motion, an object will follow its own light signals closely. In turn this causes time intervals in the observer frame (S) to be shorter than in the rest frame (S′).:

t = δ−1t′ (1.4)

Note that time dilation is accounted for and δ is the relativistic Doppler factor:

δ = (Γ(1 − β cos θ))−1 (1.5)

The inverse transformation (i.e., from S to S′) is simply.:

δ = (Γ(1+ β cos θ′))−1 (1.6)

Subsequently, since frequency, ν ∝ 1/t and cycles per time is constant:

ν = δν′ (1.7)

Furthermore, we can rewrite equation 1.1.:

sin θ = δ sin θ′ (1.8)

Differentiating this, the solid angle dΩ becomes:

dΩ= δ2dΩ′ (1.9)

With this frame work I can now address how luminosity is boosted when the

3 emitting plasma is beamed. Applying Liouville’s Theorem, specific intensity, Iν/ν 3 is Lorentz invariant. Subsequently, specific flux density Sν /ν is also Lorentz invari- ant since flux density is a moment of specific intensity. Consequently, by applying equation 1.7: 3−α Sobs = δ Si (1.10)

−α where δ is the ratio of Sobs, observed flux density, to Si, intrinsic flux density, due to the power law spectrum of flux density, discussed in §1.1. 18

1.3 Unification Schemes

As astronomers obtained more observations of AGNs, the features by which we classified them showed considerable overlap (e.g., a weak QSO is indistinguishable from a strong Sy). It appeared that AGN share an underlying mechanism and that they appear diverse due to the circumstances of how we observe them, (§1.2.1). The first AGN to be unified were the Sy I & IIs and QSOs. They fall upon a continuum of luminosities. Strong evidence shows obscuring regions around the nuclei of Seyferts and some QSOs, and the only difference between Sy Is and Sy IIs are the absence of broad lines in Sy IIs (§1.2.3). Therefore, we see Sy IIs at the highest angles with respect to the jet, such that the dust torus around the accretion disk blocks the broad lines from our view. We see Sy Is at intermediate angles as the broad lines become visible but the emission close to the core is not Doppler boosted. QSOs are seen at the lowest angles; both types of lines are visible and the emission close to the core is beamed (increasing the apparent luminosity). The radio loud unification scheme (Fig. 7) [Urry & Padovani, 1995] is more complex and more controversial. Unlike Sy I & IIs, which come from one parent population, FRs show distinct differences in luminosity and morphology (§1.2.4). This suggests FRs come from two parent populations, FR Is having a weaker central engine and FR IIs a stronger central engine. To further complicate matters, there are a handful of objects that show overlap between the two classes (e.g., LO96), such as objects that have lower FR I luminosity but show lobe−dominated FR II morphology [Leahy et al., 1997]. There are various hypotheses for this overlap, such as FR IIs that evolve into FR Is, or that FR Is and FR IIs can transition back and forth, but there are no conclusive explanations. The predominant unified scheme for radio−loud AGNs splits them into branches. FR Is and FR IIs form the parent populations, delineated by luminosity. At low luminosities, FR Is are seen edge−on, and as the viewing angle decreases we see radio quasars and then BL Lac objects at very small viewing angles. At high luminosities we 19

see FR IIs at high viewing angles, then radio quasars at moderate viewing angles and then FSRQs at small viewing angle. This accounts for broad line obscuration in radio galaxies, the varied array of radio quasar morphologies, and the high luminosities of blazars due to Doppler boosting. However it is complicated by the ambiguity between some FR Is and IIs, especially since recent observations attribute FR II properties to some BL Lacs [Landt & Bignall, 2008]. The term ’quasar’ refers to several groups of AGN with diverse properties (radio−quiet, radio−loud, flat spectrum, and steep spectrum). FSRQs account for 97% (98 of 101) of the quasars in the MOJAVE sample. In this dissertation, unless stated otherwise, ’quasar’ and its abbreviation QSO will refer to FSRQs.

Figure 1.8. Diagram of the unified scheme, as discussed in Urry & Padovani [1995]. The Ordinate shows increasing viewing angle to the top and the Abscissa shows increasing power of the central engine from left to right. As you can see, the term quasar refers to a diverse group of objects. 20

1.4 The MOJAVE Survey

This dissertation is based on the MOJAVE sample of highly beamed relativistic jets [Lister & Homan, 2005]. MOJAVE1 (Monitoring Of Jets in AGN with VLBA Experiments) is a long term survey of the 135 brightest radio-loud, compact AGN in the northern sky. MOJAVE builds upon the VLBA 2 cm Survey (1994-2002), with a more statistically complete population of AGNs monitored, to study the kinematics and polarization of these objects. MOJAVE provides improvements over past surveys in terms of angular resolution, sample size and statistical completeness. The selection criteria are:

• J2000 declination > −20◦

• Galactic latitude |b| > 2.5◦

• VLBA 2 cm correlated flux density exceeding 1.5 Jy2 (2 Jy for declination south of Dec = 0◦) at any epoch between 1994.0 and 2004.0.

These selection criteria are optimal for sources that have highly beamed relativis- tic jets (i.e., blazars). By using parsec−scale (VLBA) flux densities, we exclude the more diffuse emission in the kiloparsec scale jet, which is more prominent in radio galaxies, and the short wavelength further excludes kiloparsec scale emission due to its steep power law continuum spectrum (§1.1) of AGNs [Lister & Marscher, 1997]. Furthermore, the MOJAVE selection criteria are ideal for studying correlations be- tween gamma−ray and radio emission, because gamma−ray variability suggests that they originate within the parsec−scale.

1.5 Radio Telescopes used in MOJAVE

λ The laws of optics make radio imaging a technological challenge because ∆Θ ∼ D where ∆Θ is angular resolution, D is the aperture diameter and λ is wavelength. To

1http:www.physics.purdue.edu/astro/MOJAVE 2A Jansky (Jy)= 10−23ergs−1cm−2Hz−1 is a standard unit for flux density in astronomy 21

get 1.5” of resolution at λ = 20cm, the aperture would have to be approximately 30km across! Obviously, building a single dish that big would be prohibitively expensive, and quite impractical. Therefore, radio astronomers use interferometers to collect data and astronomers process that data in Fourier space to produce high resolution images.

1.5.1 The Very Large Base−line Array

The Very Large Base−line Array3 is an array of ten 25m antennas located from St. Croix, U.S. Virgin Islands, across the U.S. to Mauna Kea, Hawaii. The closest antennas are 200km apart and it has an effective aperture of 8000km. This gives the VLBA an angular resolution of 0.5−1.4 milli−arcseconds (mas) at λ = 2cm, MO- JAVE’s observation wavelength [Lister & Homan, 2005]. This amount of resolution corresponds to parsec scales at the typical distances of blazars.

1.5.2 The Very Large Array

Located in the San Augustin highlands in New Mexico; The Very Large Array4 is an array of 27, 25m antennas in a Y configuration. It is currently being upgraded to increase its sensitivity and will be renamed the EVLA after completion. Each antenna can be relocated allowing the telescope to be configured to change its angular resolution. These configurations are lettered A through D (with sub-configurations like AB, BC, CD). The A configuration has the highest resolution and D the lowest. However, the smaller baselines of the D array give it higher sensitivity, making it better for observing faint, extended objects. At A configuration and λ = 20cm, the VLA has angular resolution of 1.5”, or kiloparsec scales for typical AGNs.

3The VLBA is a facility of the National Radio Astronomy Observatory, operated by Associated Universities Inc., under cooperative agreement with the National Science Foundation 4The VLA is a facility of the National Radio Astronomy Observatory, operated by Associated Universities Inc., under cooperative agreement with the National Science Foundation 22

Each VLA antenna has 2 intermediate frequency filters and a polarization splitter that allow the VLA to simultaneously take data at two different frequencies in the same receiver band at two different polarizations. These 4 possible combinations of frequency and polarization are called IFs and are designated A,B,C, and D. A and C receive right−hand polarization and B and D left−hand. The EVLA will have a different IF configuration, but only 6 AGNs in this dissertation have images made partially with EVLA antennas. In spectral line mode the user has the option of setting the number of channels per IF and their bandwidth. The VLBA antennas are similar in design to the VLA antennas.

1.6 Goals of this Dissertation

Not much is known about the behaviors of blazar jets in the kiloparsec scale, be- cause few have bright extended emission to study. Furthermore, the selection criteria for other large AGN surveys (e.g. Cassaro et al. [1999], Condon et al. [1996], Conway & Murphy [1993]) have not been targeted toward blazars. It is therefore necessary to obtain deep images (i.e., images that have a long integration time on source) to image this extended emission. With these images and those taken on the parsec scales we can create models and test them against numerical simulations. This dissertation was designed to:

• Use VLA A configuration data along with MOJAVE’s VLBA data to quantify misalignment between parsec and kiloparsec scales. Monte Carlo simulations will be used to see if any jet geometries (e.g. single bend, helical) are excluded.

• Look for correlations of jet misalignment to other measured quantities, such as jet speed, fractional polarization, luminosity, class , core dominance etc,.

• Check the correlation of extended emission to total jet power (e.g. Giovan- nini et al. 1988) to verify the upper envelope between maximum jet speed and parsec−scale luminosity observed by Cohen et al. [2007]. This provides a con- 23

straint for those numerical models that take full MHD and GR effects in to account (e.g. Kato, Mineshige & Shibata 2004).

• Check the correlation of extended emission luminosity to γ−ray luminosity. Current models predict that γ−ray emissions come from the inner, parsec−scale region of the jet [Dermer, 1995, Dermer & Schlickeiser, 1993]. However, mea- surements of correlation, to date, have not been made with a statistically com- plete, core flux density selected sample in the radio regime, and have not ac- counted for beaming effects.

• Look for the relationship between degree of jet bending and viewing angle, using both actual and simulated data.

• Looked for evidence of swinging jet nozzles or jet precession. 24 25

2. KILOPARSEC PROPERTIES

In this chapter I present measurements made by the VLA, MERLIN, Green Bank 90-m, RATAN-600 and other telescopes. These telescopes have angular resolutions ranging from 1.5 ′′ (VLA) to 10 ′ (Green Bank 90-m) which corresponds to kiloparsec scales or greater at the typical distances of the MOJAVE sources. The kiloparsec scale structures include jets, hot spots, lobes and halos. The bulk flow on the kilo- parsec scales is believed to have decelerated, so beaming effects are lessened. The radio luminosity measured on kiloparsec scales may reflect the intrinsic properties of the AGN better than parsec scale measurements where beaming effects are more pronounced.

2.1 VLA Observations

The effort to acquire high dynamic range (i.e., high signal−to−noise ratio), kilo- parsec scale images took place in four stages. First, the MOJAVE team obtained VLA A configuration, λ = 20cm (L−band) data for 60 AGNs in the sample of 135 MOJAVE sources. Next, I searched Internet databases (such as NED and ADS) for suitable images with similar dynamic range and angular resolution. I then carried out targeted VLA observations of 7 AGNs (mostly used in previous surveys by other astronomers as calibrators) that lacked high dynamic range images in the L−band1. These data, as well as archival data on the remaining sources, were then calibrated and imaged.

1Because it offers higher angular resolution, C−band (λ = 6cm) is more popular for AGN jet images. However, the extended structure is fainter at C−band owing to the power−law behavior of AGN continuum emission. 26

2.1.1 Images Acquired in the Fall 2004 − AL634

Data on the first series of VLA observations were published by Cooper, Lister & Kochancyzk [2007]. The A−array typically yields a restoring beam of 1.5′′ (FWHM), at λ = 20cm. To minimize the possible effects of radio interference, and to improve the dynamic range, the data were recorded in spectral line mode, with 8 channels per IF. Right− and left−hand circular polarization data at 1.36 GHz and 1.44 GHz were each assigned to one of four IFs, each having bandwidth of 25 MHz. The observations took place on six separate dates between 2004 September 19 and 2004 November 24 (Table 1). To maximize (u,v) coverage, two scans of approximately five−minutes duration, separated in hour angle, were made on each source. This yielded typical r.m.s. noise levels of 0.14 mJy beam−1 and dynamic ranges of ∼ 15000 : 1. Two sources, 0059+581 and 0109+224, had less than 10 minutes integration time, due to scheduling constraints. Data on three sources (0016+731, 1150+812, 1458+718) had poor (u,v) coverage due to their high declinations. The AL634 data were used for 0016+731 and 1150+812, because only 1458+718 had better data available in the archives. Calibration of the data was performed in AIPS 2, and further imaging and self- calibration steps were carried out with Difmap 3. For each source, the flux density of the core component was determined by fitting a Gaussian component to the FITS image using JMFIT, with the Gaussian dimensions set to the size and angle of the restoring beam. The AIPS task SLICE was used to determine if there was a secondary component close to the peak Gaussian. A second Gaussian was fit by setting the verb NGAUSS to two for those sources with a secondary component (see Table 2). The total flux density was determined by summing the flux density within a box fitted around the extent of the source using TVBOX and IMSTAT in AIPS. After the total flux (Stotal) and core flux (Score) were obtained, the flux density of the extended

2AIPS is copyrighted by Associated Universities, Inc. using the GNU copyright form. 3DIFMAP was written by Martin Shepard at Caltech, and is part of the Caltech VLBI software package. 27

structure (Sext) is simply: Sext = Stotal − Score. The r.m.s. noise was measured in a blank sky region away from the source, also using TVBOX and IMSTAT. These values are listed in Table 2, and the distribution of extended flux density values is shown in Figure x. The images of several sources (0202+149, 0212+735, 0552+398, 0642+449, 1324+224, 1417+385 and 2209+238) required further analysis to confirm the presence of very faint extended emission. The core component was subtracted from the data, and the residual image was inspected for emission above 3 times the r.m.s. noise level. This was found for all but two sources, 0642+449 and 2209+238. For these two sources we set an upper limit on extended emission equal to 3 times the r.m.s. noise. We cannot rule out the presence of low−level diffuse emission on larger angular scales than the restoring beam, however.

2.1.2 Images Acquired in June 2007 − AC874

The MOJAVE team published the AC874 data in Kharb, Lister & Cooper [2010]. For consistency with Cooper, Lister & Kochancyzk [2007], We used the VLA in A configuration in spectral line mode with 4 channels per IF at a bandwidth of 25 MHz per IF, and assigned right− and left−hand circular polarization data at 1.38 GHz and 1.46 GHz to the four IFs. We used two scans of 9 minutes, separated in hour−angle for improved (u,v) coverage. The time on source was greater than Cooper, Lister & Kochancyzk [2007] because I suspected weaker extended emission around these sources (i.e., they were listed by NRAO as uninteresting point sources and relegated to phase calibrators). The resultant r.m.s. noise level was typically 0.06 mJy beam−1, less than half that in AL634. Ten EVLA antennas were active at the time of the observation, 30 June 2007, however I flagged one EVLA antenna (EVLA N64) which had technical problems for the entire observation. Since EVLA antennas were used, the calibration process was slightly different than that used for AL634 data. The NRAO has these extra steps posted on their 28 website at http://www.vla.nrao.edu/astro/guides/evlareturn/postproc/index.shtml. These steps are to minimize closure errors on VLA−EVLA baselines, and consist of first calculating antenna positions and updating the CL table with AIPS task VLANT, then running an extra baseline calibration loop using AIPS tasks CALIB, CLCAL then BLCAL. Running BLCAL creates a BL table. The rest of the calibration was carried out per the AIPS cookbook with the exception of using the BL table (i.e., setting the adverb BLVER = 1 where appropriate). Self−calibration and imaging were unaffected.

2.1.3 Data Obtained from NRAO Archives and Previous Studies

I selected archival data to be as similar to AL634 and AC874 as possible. My highest priority was integration time; most sources had a minimum of 10 minutes of integration time. All archival source observations were made in continuum mode. The procedure for calibration was the same for the AL 634 data above, since the archival data did not include any EVLA antennas. Archival data and 21 previously un−published images were originally published in Kharb, Lister & Cooper [2010].

2.1.4 Observation and Image Data

Table 1 contains observation date, number of antennas and time on source ob- served with the VLA in its A−array. Sixty MOJAVE sources are those reported in Cooper, Lister & Kochancyzk [2007]. Seven more sources were measured in summer of 2007, and data for the remaining 68 sources were retrieved from the VLA archive and previous literature (e.g., Murphy, Browne & Perley 1993). These data were reported in Kharb, Lister & Cooper [2010]. 29

Table 2.1. A−Configuration VLA Observations of MOJAVE Sources at 1.4 GHz

Source Observation Date Number of Antennas Time on Source Reference Program Code (minutes) (1) (2) (3) (4) (5) (6)

0003−066 2004 Nov 09 25 17 CLK07 AL634 0007+106 2004 Nov 09 25 17 CLK07 AL634 0016+731 2004 Nov 03 25 13 CLK07 AL634 0048−097 2004 Nov 10 25 5 CEA99 AB1141 0059+581 2004 Sep 19 24 5 CLK07 AL634 0106+013 2004 Sep 19 24 11 CLK07 AL634 0109+224 2004 Sep 19 24 8 CLK07 AL634 0119+115 2004 Sep 19 24 10 CLK07 AL634 0133+476 2004 Sep 19 24 11 CLK07 AL634 0202+149 2004 Sep 19 24 11 CLK07 AL634 0202+319 2004 Sep 19 24 11 CLK07 AL634 0212+735 2004 Sep 19 24 11 CLK07 AL634 0215+015 2004 Sep 19 23 11 CLK07 AL634 0224+671 2004 Sep 19 24 11 CLK07 AL634 0234+285 2004 Sep 19 24 11 CLK07 AL634 0235+164 2004 Sep 19 24 11 CLK07 AL634 0238−084 2004 Nov 09 24 18 CLK07 AL634 0300+470 2004 Nov 03 25 13 CLK07 AL634 0316+413 1996 Dec 07 27 34 PEA90 BT024 0333+321 2004 Sep 19 24 10 CLK07 AL634 0336−019 2004 Sep 19 22 11 CLK07 AL634 0403−132 2004 Sep 19 18 11 CLK07 AL634 0415+379 1982 Jun 14 27 140 LF84 LINF 0420−014 2004 Nov 03 25 12 CLK07 AL634 0422+004 2004 Sep 19 23 11 CLK07 AL634 0430+053 1986 May 27 26 15 WBU87 AB379 0446+112 2004 Sep 19 23 11 CLK07 AL634 0458−020 2004 Sep 19 23 11 CLK07 AL634 0528+134 2004 Sep 19 22 11 CLK07 AL634 0529+075 2004 Sep 19 23 11 CLK07 AL634 0529+438 2004 Sep 19 23 12 CLK07 AL634 0552+398 2004 Nov 24 24 11 CLK07 AL634 0605−085 2004 Nov 24 24 11 CLK07 AL634 0607−157 2004 Nov 24 24 11 CLK07 AL634 0642+449 2004 Nov 24 24 13 CLK07 AL634 0648−165 2004 Nov 24 24 12 CLK07 AL634 0716+714 2004 Nov 03 24 13 CLK07 AL634 0727−115 1989 Jan 12 27 15 KLC10 AH338 0730+504 2007 Jun 30 25 21 KLC10 AC874 0735+178 1993 Jan 04 27 87 PS94 AS490 0736+017 1983 Sep 12 26 9 KLC10 AA025 0738+313 1984 Dec 24 27 10 MBP93 AB310 0742+103 1986 May 17 27 9 KLC10 AY012 0748+126 1984 Dec 24 27 10 MBP93 AB310 0754+100 1984 Dec 24 27 11 MBP93 AB310 0804+499 1984 Dec 24 27 10 MBP93 AB310 0805−077 2007 Jun 30 25 21 KLC10 AC874 0808+019 1983 Sep 18 26 14 AU85 AA025 0814+425 1984 Dec 24 27 9 MBP93 AB310 30

Table 2.1 (cont’d)

Source Observation Date Number of Antennas Time on Source Reference Program Code (minutes) (1) (2) (3) (4) (5) (6)

0823+033 1984 Dec 24 27 12 MBP93 AB310 0827+243 1987 Sep 08 27 38 PEA93 AV150 0829+046 2002 Feb 22 27 17 GEA04 AG618 0836+710 2004 Nov 03 25 13 CLK07 AL634 0838+133 1992 Dec 05 27 50 BEA94 AH480 0851+202 2003 Aug 16 26 88 PS94 AS764 0906+015 1989 Jan 29 26 11 MBP93 AS358 0917+624 2003 Aug 03 27 39 MBP93 AC681 0923+392 1990 May 18 26 19 MBP93 AS396 0945+408 1984 Dec 24 27 9 MBP93 AB310 0955+476 1990 Apr 14 27 16 XEA95 AS404 1036+054 2007 Jun 30 25 21 KLC10 AC874 1038+064 2001 Feb 20 27 20 HUO83 GX007A 1045−188 2007 Jun 30 25 22 KLC10 AC874 1055+018 1992 Nov 19 26 18 MBP93 AB631 1124−186 1994 May 22 27 5 KLC10 AD337 1127−145 2001 Feb 07 27 102 SEA02 AH730 1150+812 2004 Nov 03 25 13 CLK07 AL634 1156+295 1983 Sep 18 26 26 AU85 AA025 1213−172 2007 Jun 30 25 22 KLC10 AC874 1219+044 2007 Jun 30 25 20 KLC10 AC874 1222+216 2004 Nov 20 24 15 CLK07 AL634 1226+023 1990 Mar 23 27 207 CEA93 AM297 1228+126 1999 Jul 18 27 25 O10 AB920 1253−055 2001 Jan 11 27 200 AEA94 W055 1308+326 2004 Nov 20 25 15 CLK07 AL634 1324+224 2004 Nov 20 25 15 CLK07 AL634 1334−127 1986 Mar 18 27 5 KLC10 AD176 1413+135 2004 Oct 29 25 34 PS94 AC741 1417+385 2004 Nov 20 25 15 CLK07 AL634 1458+718 1987 Aug 15 27 12 AG95 AF147 1502+106 2004 Nov 20 25 15 CLK07 AL634 1504−166 1986 May 17 27 7 KLC10 AY012 1510−089 1986 May 17 27 7 CHTH AY012 1538+149 2004 Nov 20 24 12 CLK07 AL634 1546+027 1984 Dec 24 27 8 MBP93 AB310 1548+056 1984 Dec 24 27 9 KLC10 AB310 1606+106 1984 Dec 24 27 9 MBP93 AB310 1611+343 1984 Dec 24 27 12 MBP93 AB310 1633+382 1984 Dec 24 27 11 MBP93 AB310 1637+574 1984 Dec 23 27 9 MBP93 AB310 1638+398 1992 Nov 05 26 8 XEA95 AX001 1641+399 1984 Dec 24 27 12 MBP93 AB310 1655+077 1984 Dec 24 27 5 MBP93 AB310 1726+455 1986 Apr 01 27 46 KLC10 AK139 1730−130 1986 May 27 27 12 KLC10 AB379 1739+522 1991 Aug 24 26 6 REA95 AC301 1741−038 1992 Nov 11 24 13 KLC10 AL269 1749+096 1983 Sep 12 25 29 AU85 AA025 31

Table 2.1 (cont’d)

Source Observation Date Number of Antennas Time on Source Reference Program Code (minutes) (1) (2) (3) (4) (5) (6)

1751+288 1999 Jul 10 27 9 KLC10 AS659 1758+388 1990 May 18 26 3 XEA95 AS396 1800+440 1990 May 18 26 19 XEA95 AS396 1803+784 2004 Nov 09 25 16 CLK07 AL634 1807+698 1994 Apr 19 27 41 CEA99 AB700 1823+568 2000 Nov 05 27 8 MBP93 AM672 1828+487 1984 Dec 23 27 10 MBP93 AB310 1849+670 2004 Nov 09 25 17 CLK07 AL634 1928+738 2004 Nov 03 25 12 CLK07 AL634 1936−155 1986 Mar 16 20 90 KLC10 AD167 1957+405 1987 Aug 18 27 179 CEA89 AC166 1958−179 1987 Aug 31 27 42 KLC10 AA072 2005+403 1995 Aug 02 27 21 KLC10 AK4010 2008−159 1990 Jul 05 26 17 KLC10 AK240 2021+317 1995 Aug 02 27 21 KLC10 AK4010 2021+614 2002 Apr 19 27 10 KLC10 AW579 2037+511 1995 Aug 02 27 21 KLC10 AK4010 2121+053 1984 Dec 24 27 11 MBP93 AB310 2128−123 1986 May 17 27 8 KLC10 AY012 2131−021 1994 Apr 18 27 48 RS01 AB700 2134+004 1994 Apr 18 27 12 MBP93 AB700 2136+141 1995 Aug 11 27 20 KLC10 AH528 2145+067 2004 Nov 21 24 11 CLK07 AL634 2155−152 2004 Nov 21 24 12 CLK07 AL634 2200+420 2004 Nov 21 24 13 CLK07 AL634 2201+171 2004 Nov 21 24 13 CLK07 AL634 2201+315 2004 Nov 21 24 11 CLK07 AL634 2209+236 2004 Nov 21 24 11 CLK07 AL634 2216−038 2004 Nov 21 24 11 CLK07 AL634 2223−052 2004 Nov 21 24 11 CLK07 AL634 2227−088 2004 Nov 21 24 11 CLK07 AL634 2230+114 2004 Nov 21 24 11 CLK07 AL634 2243−123 2004 Nov 21 24 11 CLK07 AL634 2251+158 2004 Nov 21 24 13 CLK07 AL634 2331+073 2004 Nov 09 25 15 CLK07 AL634 2345−167 2004 Nov 09 25 16 CLK07 AL634 2351+456 2004 Nov 09 25 17 CLK07 AL634

Note. — Columns are as follows: (1) IAU Name (B1950.0); (2) Date of obsevation; (3) The number of antennas used that were not flagged; (4) Combined time on source in minutes; (5) Reference to published image where, KLC10 = Kharb, Lister & Cooper 2010, O10 = Owen 2010, CLK07 = Cooper, Lister & Kochancyzk 2007, GEA04 = Giroletti,et al. 2004, CH TH = Cheung 2004, SEA02 = Siemiginowska et al. 2002, RS01 = Rector & Stocke 2001, CEA99 = Cassaro et al. 1999, AG95 = Akujor & Garrington 1995, XEA95 = Xu, et al. 1995, AEA94 = Akujor et al. 1994, BEA94 = Bogers et al. 1994,PS94 = Perlman & Stocke 1994, CEA93 = Conway et al. 1993, MBP93 = Murphy, Browne & Perley 1993, PEA93 = Price et al. 1993, PEA90 = Pedlar et al. 1990, CEA89 = Carilli et al. 1989, WBU87 = Walker, Benson, & Unwin 2003, AU85 = Antonucci & Ulvestad 1985, LF84 = Linfield & Perley 1984, HUO83 = Hintzen, Ulvestad & Owen 1983; (6) NRAO data archive observation code. 32

2.2 MOJAVE Sample Statistics

The following histograms show the distribution of several measurements that will be referred to throughout this dissertation. These distributions show some of the differences of the various classes of AGN in terms of measured quantities; These distributions are especially important for creating Monte−Carlo simulations of the MOJAVE population. Furthermore, these plots are important for identifying sta- tistical outliers when constraining parameters for simulations and identifying which sources to exclude from certain analysis as well as quantifying the reasons. Redshift (z) is proportional to cosmological distance via Hubble’s Law. Since MOJAVE is a flux density limited sample, AGN in the sample population will mostly be bright, distant AGN, however some AGN that happen to be much less bright but nearby will also be included. Figure 2.1 shows that all 8 radio galaxies in the MOJAVE population have z< 0.25, additionally BLOs tend have smaller redshifts than QSOs. The MOJAVE redshift distribution is similar to the Murphy, Browne & Perley [1993] distribution, except that their sample includes 12 more BLOs with measured redshift than MOJAVE and they are more sharply peaked at z < 0.4. The luminosity distribution (Figure 2.2) of the MOJAVE population is similar in terms of range of luminosities to that of previous blazar surveys that are flux density limited (e.g., Antonucci & Ulvestad 1985, Murphy, Browne & Perley 1993). The formula for calculating luminosity from flux density is:

2 Lc,ext =4πdLSc,ext (2.1) where dL is luminosity distance [Hogg, 1999] and Sc,ext is either core (c) or extended (ext) flux density. Comparing the extended luminosities of BLOs and QSOs with Kolmogorov−Smirnov (K−S) tests and the ASURV4 package’s two sample test yields a statistically significant difference between BLOs and QSOs at > 99% confidence, furthermore Mann−Whitney and K−S tests for core luminosity yield a statistically significant difference between QSOs and BLOs at > 99% confidence; BLOs tend to

4Rev 1.2 LaValley, Isobe & Feigelson 1992, using methods presented in Feigelson & Nelson 1985 33

Figure 2.1. Distribution of optical host galaxy redshifts AGNs in the MOJAVE sam- ple from NED (http://nedwww.ipac.caltech.edu). Left: The Distribution of the 119 Quasars (white) and BL Lacs (Shaded). Right: All 127 AGNs with redshifts. The 119 Quasars and BL Lacs are white and the 8 galaxies are shaded. There are 8 MOJAVE AGNs that have no measured redshift, and are not plotted.

have smaller luminosities. Considering that MOJAVE is a flux density limited sample, MOJAVE BLOs tend to have smaller redshifts as well, since redshift is proportional to cosmological distance. These results are also consistent with past flux density limited surveys, Antonucci & Ulvestad [1985], Murphy, Browne & Perley [1993]. However, Kharb, Lister & Cooper [2010] found that six of 22 BLOs have FRII radio powers (log Lext > 26 at 1.4 GHz), and four of these BLOs have quasar−like hot spots (0235+164, 0716+714, 0808+019, 2131−021). Additionally, 5 BLOs fall in the intermediate FRI/II range (24.5 < log Lext < 26 at 1.4 GHz); two of these also have quasar−like hot spots (0823+033 and 1803+784). Of the remaining seven BLOs with FRI extended luminosities, log Lext < 24.5 (4 BLOs have unknown redshifts, so luminosities cannot be determined), three have hot spots (0754+100, 0851+202, 1807+698). The Kharb, Lister & Cooper [2010] finding that a significant proportion of MO- JAVE BLOs that exhibit FRII like luminosities or hot spots is consistent with that of Landt, Perlman & Padovani [2006]. Additionally, Rector & Stocke [2001] find that 34

radio−selected BLOs’ Lext are statistically higher than X−ray selected BLOs, and FR1s and X−ray selected BLOs having weak or no emission lines, whereas many radio selected BLOs have strong emission lines in at least a single epoch. They con- clude that many 1 Jy sample Stickel et al. [1991] BLOs are more likely FRIIs. In fact, Cara & Lister [2008] found that the intrinsic parent luminosity function (PLF) including both MOJAVE QSOs and BLOs was similar to the PLF of just MOJAVE QSOs. Conversely, Haywood et al. [2007] state that out of their candidates for FR1 QSOs, only one has conclusive FR1−type double lobe morphology.

Figure 2.2. Distribution of 119 MOJAVE QSO/BLO luminosities (4 BLOs lack red- shifts). Left: VLA-A 1.4 GHz extended luminosities. Right: VLA-A 1.4 GHz core luminosities. For the extended luminosities, ASURV two sample tests and the Kolmogorov-Smirnov test yield a statistically significant difference between QSOs and BLOs at > 99% confidence. For core luminosities both Mann-Whitney and Kolmogorov-Smirnov tests yield a statistically significant difference between QSOs and BLOs at > 99% confidence.

Figures 2.3 and 2.4 show the distribution of the ratio of core flux density to extended flux density, or core prominence ratio (Rc). The formula for Rc is:

Sc αcore−αext Rc = (1 + z) (2.2) Sext 35

where αcore is the spectral index of the core and is set to 0 and αext is the spec- tral index of the extended emission and is set to 0.7. The 1+z term is called the k−correction and accounts for the power law behavior of the flux density (§1.1) and

redshift between the observer frame and rest frame of the emission. Since Sc is beamed

and Sext is unbeamed, Rc is often used as a statistical indicator of beaming and by

extension orientation of the jet, i.e., higher Rc indicates higher beaming and therefore smaller viewing angles.

The distribution of Rc for the MOJAVE population does indicate a prevalence of

highly beamed sources. The mean value of log Rc for the MOJAVE sample is 1.3; the core flux density is about 20 times greater, on average, than extended flux density in the source’s rest frame. Additionally, most of the sources with Rc < 0 (3C 111, M87, Cygnus A) are nearby radio galaxies that are coincidentally close enough to meet the MOJAVE flux density limit. Figure 2.4 show that BLOs and QSOs have a similar

distribution of Rc and that the radio galaxies typically have core prominence ratios < 1. 36

Table 2.2. MOJAVE VLA 1.4 GHz Image Parameters

Source Bmax Bmin φ r.m.s. Speak Contmin (B1950) (arcsec) (arcsec) (degrees) (mJy/beam) (Jy/beam) (1) (2) (3) (4) (5) (6) (7)

0003−066 1.92 1.41 23.6 0.19 2.625 0.040 0007+106 1.62 1.46 43.6 0.04 0.075 0.500 0016+731 1.97 1.14 −66.9 0.39 0.400 0.320 0048−097 1.91 1.35 −4.4 0.20 0.564 0.125 0059+581 1.64 1.35 −45.1 0.12 1.559 0.050 0106+013 1.64 1.49 9.6 0.16 2.759 0.025 0109+224 1.49 1.42 −63.5 0.08 0.361 0.125 0119+115 1.53 1.44 −34.8 0.10 1.189 0.050 0133+476 1.55 ,1.41 −61.2 0.11 1.878 0.030 0202+149 1.58 1.42 −40.5 0.16 3.829 0.025 0202+319 1.55 1.37 −60.2 0.13 0.648 0.080 0212+735 1.83 1.44 −14.0 0.11 2.458 0.030 0215+015 1.74 1.43 −26.9 0.08 0.417 0.120 0224+671 1.69 1.42 −22.1 0.11 1.476 0.040 0234+285 1.47 1.35 −54.3 0.09 2.277 0.050 0235+164 1.51 1.38 −35.7 0.06 1.502 0.030 0238−084 1.95 1.43 −16.5 0.07 1.077 0.025 0300+470 1.47 1.41 −36.4 0.08 1.167 0.030 0316+413 1.44 1.23 −34.2 0.68 21.238 0.021 0333+321 1.50 1.36 −41.0 0.11 2.997 0.025 0336−019 1.74 1.44 2.2 0.20 2.902 0.025 0403−132 3.62 1.44 1.3 0.34 3.998 0.050 0415+379 1.60 1.47 78.4 0.58 1.025 0.250 0420−014 1.72 1.41 −4.6 0.11 2.875 0.025 0422+004 1.71 1.40 −16.7 0.13 1.083 0.100 0430+052 2.58 1.69 −88.7 0.17 2.816 0.063 0446+112 1.57 1.38 −28.7 0.16 1.525 0.025 0458−020 1.78 1.41 −18.9 0.10 0.996 0.070 0528+134 1.62 1.36 −33.2 0.13 2.203 0.030 0529+075 1.70 1.35 −26.6 0.09 1.516 0.050 0529+438 1.50 1.36 −23.9 0.10 0.644 0.060 0552+398 1.50 1.34 −10.9 0.15 1.537 0.040 0605−085 1.99 1.37 −2.8 0.16 1.170 0.060 0607−157 2.27 1.36 −1.2 0.18 3.009 0.020 0642+449 1.50 1.34 −13.7 0.07 0.644 0.060 0648−165 2.34 1.34 −8.3 0.16 2.084 0.030 0716+714 2.00 1.46 61.7 0.07 0.646 0.060 0727−115 1.98 1.29 14.0 0.29 2.115 0.040 0730+504 1.49 1.20 −35.6 0.05 0.672 0.023 0735+178 1.64 1.45 −45.0 0.25 2.945 0.025 0736+017 1.59 1.29 −11.6 0.29 2.329 0.042 0738+313 1.35 1.24 −87.6 0.19 2.160 0.027 0742+103 1.53 1.29 −7.1 0.23 3.612 0.020 0748+126 1.33 1.32 −83.4 0.17 1.430 0.036 0754+100 1.35 1.34 −53.3 0.17 2.070 0.025 0804+449 1.35 1.20 79.7 0.05 0.640 0.023 0805−077 1.87 1.35 16.2 0.05 1.424 0.011 0808+019 1.61 1.31 −11.5 0.09 0.449 0.10 0814+425 1.33 1.20 78.8 0.10 1.570 0.019 37

Figure 2.3. Distribution of core−to−extended luminosity ratio (source frame) for 127

AGN in the MOJAVE sample with redshifts. Sources with extended emission (Sext) detections are in white and upper−limit Sext sources are shaded. Sext upper−limits set at three times the r.m.s noise level of the image. Of the negative outliers: 3C 111, M87, Cygnus A are nearby radio galaxies 0838+133 and 1222+216 are FSRQs and 1828+487 is a compact steep spectrum quasar. 38

Figure 2.4. Distribution of core−to−extended luminosity ratio (source frame). Left: 123 Blazars with 101 QSOs in white and 22 BLOs shaded. Right: 135 AGN in the MOJAVE sample with Blazars in white and Galaxies optical class shaded. Blazars include QSOs, BLOs and objects of unknown optical class, since they are most likely blazars. A redshift of 1 was assumed for the 4 unidentified sources and 4 BLOs without redshifts. The negative outliers, 3C 111, M87, Cygnus A are all nearby radio galaxies. The three QSOs with a Rc < 0 are 0838+133 (3C 207), 1222+216 (4C +21.35) , 1828+487 (3C 380). 0838+133 and 1222+216 have a two−sided halo morphology with bright hot-spots on either side of the core. 1828+487 is the closer (z = 0.692) of two compact steep spectrum quasars in the MOJAVE sample and has an extensive two−sided halo. 39

Table 2.2 (cont’d)

Source Bmax Bmin φ r.m.s. Speak Contmin (B1950) (arcsec) (arcsec) (degrees) (mJy/beam) (Jy/beam) (1) (2) (3) (4) (5) (6) (7)

0823+033 1.34 1.33 12.4 0.12 1.330 0.028 0827+243 1.38 1.33 −23.1 0.19 0.770 0.075 0829+046 1.82 1.47 29.1 0.21 0.784 0.080 0836+710 2.24 1.43 80.9 0.19 3.144 0.190 0838+133 1.35 1.23 −33.8 0.05 0.225 0.064 0851+202 1.34 1.28 29.5 0.17 1.568 0.025 0906+015 1.54 1.15 6.2 0.26 0.922 0.085 0917+624 1.27 1.12 −16.2 0.10 1.168 0.026 0923+392 1.67 1.14 47.0 0.36 2.349 0.120 0945+408 1.38 1.22 −488.8 0.25 1.230 0.061 0955+476 1.60 1.35 65.1 0.14 0.646 0.065 1036+054 1.42 1.30 4.1 0.06 0.892 0.021 1038+064 5.25 3.72 −6.3 0.20 1.465 0.040 1045−188 2.13 1.23 −8.1 0.05 0.724 0.021 1055+018 1.96 1.33 −38.0 0.16 2.684 2.50 1124−186 4.21 3.06 −87.4 0.45 0.668 0.200 1127−145 2.63 1.60 84.5 0.83 5.489 0.05 1150+812 2.87 1.49 −55.3 0.65 1.874 0.035 1156+295 1.35 1.20 −2.9 0.19 1.406 0.07 1213−172 2.33 1.24 −18.7 0.09 1.658 0.021 1219+044 1.55 1.34 3.9 0.08 0.549 0.042 1222+216 1.45 1.41 24.4 0.08 0.930 0.050 1226+023 1.69 1.34 −3.0 1.75 32.602 0.027 1228+126 1.77 1.66 −54.7 80.0 3.524 6.8 1253−055 1.50 1.50 0.0 0.96 10.127 0.028 1308+326 1.43 1.37 −46.2 0.19 1.327 0.050 1324+224 1.44 1.41 −15.0 0.15 1.127 0.080 1334−127 1.73 1.22 −1.3 0.07 2.008 0.050 1413+135 1.30 1.23 −11.1 0.11 1.067 0.031 1417+385 1.46 1.37 −42.4 0.07 0.506 0.080 1458+718 2.78 1.31 74.2 1.60 6.310 0.075 1502+106 1.62 1.39 −30.3 0.08 1.807 0.025 1504−166 2.21 1.23 22.7 0.59 2.357 0.075 1510−089 1.91 1.26 14.6 0.01 1.417 0.075 1538+149 1.65 1.37 −41.1 0.09 1.458 0.025 1546+027 1.41 1.36 23.8 0.11 1.150 0.029 1548+056 1.52 1.47 39.5 0.16 2.106 0.021 1606+106 2.03 1.83 67.5 0.38 1.350 0.084 1611+343 1.30 1.21 81.2 0.34 2.830 0.036 1633+382 1.30 1.21 80.6 0.19 2.170 0.027 1637+574 1.34 1.26 −78.5 0.17 0.996 0.050 1638+398 1.55 1.12 77.1 0.31 1.160 0.080 1641+399 1.29 1.19 82.2 1.50 8.500 0.053 1655+077 1.35 1.34 −29.3 0.11 1.160 0.029 1726+455 1.31 1.16 39.9 0.15 0.998 0.045 1730−130 1.75 1.33 3.3 0.41 6.115 0.020 1739+522 1.39 1.13 31.2 0.12 1.593 0.042 1741−038 1.79 1.30 −38.1 0.15 1.681 0.050 1749+096 1.53 1.35 35.7 0.24 0.773 0.042 40

Table 2.2 (cont’d)

Source Bmax Bmin φ r.m.s. Speak Contmin (B1950) (arcsec) (arcsec) (degrees) (mJy/beam) (Jy/beam) (1) (2) (3) (4) (5) (6) (7)

1751+288 1.54 1.32 77.1 0.18 0.263 0.200 1758+388 2.82 1.10 −79.7 0.16 0.324 0.150 1800+440 3.27 1.27 −59.0 0.33 0.498 0.200 1803+784 2.93 1.47 50.7 0.11 1.972 0.040 1807+698 2.15 1.29 −68.4 0.09 1.176 0.075 1823+568 2.68 1.60 −89.4 0.56 0.851 0.040 1828+487 1.36 1.21 −84.4 0.59 4.626 0.039 1849+670 3.39 1.50 55.9 0.12 0.469 0.150 1928+738 1.50 1.50 0.0 0.37 3.434 0.040 1936−155 3.08 1.18 41.2 0.21 1.070 0.055 1957+405 1.30 ...... 6.0 36.223 0.110 1958−179 2.51 1.29 21.5 0.24 1.830 0.040 2005+403 1.45 1.04 77.2 0.61 2.428 0.075 2008−159 4.02 2.18 82.1 0.14 0.545 0.075 2021+317 1.42 1.11 85.2 0.74 2.973 0.075 2021+614 2.26 1.35 −26.1 0.19 2.252 0.025 2037+511 1.40 1.05 2.0 0.77 4.612 0.050 2121+053 1.42 1.36 29.6 0.14 1.080 0.038 2128−123 1.90 1.21 −19.2 0.19 1.367 0.042 2131−021 1.63 1.23 −8.1 0.11 1.293 0.042 2134+004 1.40 1.32 3.3 0.48 4.820 0.030 2136+141 1.61 1.39 19.4 0.14 1.180 0.050 2145+067 1.73 1.45 35.4 0.17 2.840 0.025 2155−152 2.29 1.48 18.9 0.16 2.615 0.025 2200+420 1.52 1.45 87.9 0.07 1.975 0.020 2201+171 1.63 1.44 49.9 0.06 0.820 0.050 2201+315 1.57 1.43 74.0 0.11 1.520 0.040 2209+236 1.57 1.43 58.7 0.07 0.426 0.075 2216−038 1.93 1.47 27.3 0.15 1.725 0.160 2223−052 1.94 1.45 26.3 0.32 6.713 0.040 2227−088 2.08 1.46 24.7 0.07 0.919 0.040 2230+114 1.70 1.46 39.8 0.38 6.572 0.040 2243−123 2.19 1.46 20.1 0.10 2.250 0.025 2251+158 1.65 1.44 37.7 0.44 12.564 0.030 2331+073 1.69 1.45 36.2 0.06 0.601 0.050 2345−167 2.27 1.45 17.8 0.07 1.916 0.030 2351+456 1.54 1.39 −65.5 0.05 2.250 0.025

Note. — Columns are as follows: (1) IAU B1950 names of the MOJAVE source; (2) Semi−major axis of the image restoring beam in arcseconds; (3) Semi−minor axis of the image restoring beam in arcseconds; (4) Azimuth of the restoring beam in degrees; (5) r.m.s. noise of the image, derived using IMSTAT in mJy/beam; (6) Peak flux density of the image in Jy/beam; (7) Minimum contour of the image in % peak flux density. 41

Table 2.3. MOJAVE VLA 1.4 GHz Image Measurements

Source Redshift Score Sext Stotal log(Rc) CoreFWHM NGauss ∆PA (B1950) (Jy) (Jy) (Jy) (arcsec) (degrees) (1) (2) (3) (4) (5) (6) (7) (8) (9)

0003−066 0.347 2.661 0.040 2.700 1.74 1.95 1 93 0007+106 0.089 0.077 0.018 0.095 0.61 1.63 1 45 0016+731 1.781 0.402 0.001 0.402 2.23 1.97 1 130 0048−097 ... 0.571 0.136 0.707 0.41 1.92 1 147 0059+581 0.644 1.567 0.028 1.595 1.60 1.65 1 − 0106+013 2.099 2.810 0.529 3.339 0.38 1.67 2 54 0109+224 0.256 0.363 0.004 0.367 1.90 1.50 1 11 0119+115 0.570 1.242 0.114 1.357 0.90 1.56 1 27 0133+476 0.859 1.882 0.009 1.891 2.15 1.55 1 10 0202+149 0.405 3.857 0.001 3.858 3.44 1.58 1 − 0202+319 1.466 0.653 0.012 0.665 1.47 1.56 1 5 0212+735 2.367 2.471 0.001 2.473 2.95 1.83 1 131 0215+015 1.715 0.440 0.080 0.520 0.44 1.81 2 12 0224+671 0.523 1.486 0.149 1.635 0.87 1.69 1 171 0234+285 1.213 2.330 0.100 2.430 1.13 1.48 1 18 0235+164 0.940 1.515 0.026 1.541 1.57 1.51 1 18 0238−084 0.005 1.111 0.111 1.222 0.10 1.95 1 151 0300+470 ... 1.171 0.066 1.237 1.04 1.47 2 77 0316+413 0.018 21.404 1.098 22.502 1.29 1.44 1 20 0333+321 1.263 3.016 0.072 3.088 1.38 1.50 1 23 0336−019 0.852 2.925 0.070 2.996 1.43 1.75 1 83 0403−132 0.571 4.334 0.009 4.343 2.54 3.74 1 47 0415+379 0.049 1.022 5.701 6.723 −0.76 1.60 1 9 0420−014 0.914 2.907 0.070 2.977 1.42 1.73 1 6 0422+004 ... 1.088 0.005 1.093 2.13 1.72 1 157 0430+052 0.033 2.954 0.149 3.103 1.29 2.65 1 41 0446+112 ... 1.555 0.016 1.572 1.77 1.58 1 104 0458−020 2.286 1.099 0.104 1.203 0.66 1.83 1 91 0528+134 2.060 2.244 0.061 2.305 1.23 1.64 1 118 0529+075 1.254 1.531 0.140 1.672 0.79 1.70 2 132 0529+438 1.162 0.651 0.023 0.673 1.23 1.50 1 43 0552+398 2.363 1.547 0.002 1.548 2.65 1.51 1 − 0605−085 0.872 1.198 0.126 1.323 0.79 1.99 2 10 0607−157 0.324 3.022 0.001 3.022 3.66 2.27 1 − 0642+449 3.396 0.648 <0.001 0.648 >3.01 1.50 1 − 0648−165 ... 2.125 0.011 2.136 2.08 2.35 1 1 0716+714 0.310 0.631 0.431 1.062 0.08 1.99 2 100 0727−115 1.591 2.136 0.027 2.163 1.62 1.98 1 − 0730+504 0.720 0.689 0.088 0.777 0.73 1.50 2 128 0735+178 ... 2.990 0.021 3.011 1.94 1.65 1 88 0736+017 0.191 2.340 0.041 2.381 1.71 1.60 1 23 0738+313 0.631 2.155 0.065 2.220 1.37 ...... 10 0742+103 2.624 3.617 0.008 3.625 2.29 1.53 1 87 0748+126 0.889 1.430 0.027 1.457 1.53 ...... 15 0754+100 0.266 2.074 0.007 2.081 2.40 ...... 77 0804+449 1.436 0.643 0.005 0.648 1.84 ...... − 0805−077 1.837 1.585 0.060 1.645 1.11 1.90 1 54 0808+019 1.148 0.459 0.017 0.476 1.19 1.63 1 18 0814+425 0.245 1.571 0.066 1.637 1.31 ...... 174 42

Table 2.3 (cont’d)

Source Redshift Score Sext Stotal log(Rc) CoreFWHM NGauss ∆PA (B1950) (Jy) (Jy) (Jy) (arcsec) (degrees) (1) (2) (3) (4) (5) (6) (7) (8) (9)

0823+033 0.506 1.325 0.004 1.329 2.40 ...... − 0827+243 0.940 0.770 0.066 0.837 0.86 1.38 1 64 0829+046 0.174 0.803 0.140 0.943 0.71 1.84 1 91 0836+710 2.218 3.340 0.073 3.413 1.31 2.27 1 6 0838+133 0.681 0.232 2.334 2.566 −1.16 1.42 2 18 0851+202 0.306 1.570 0.011 1.581 2.08 1.35 1 9 0906+015 1.024 0.925 0.054 0.970 1.02 1.54 1 8 0917+624 1.446 1.171 0.013 1.183 1.70 1.28 1 107 0923+392 0.695 2.902 0.293 3.195 0.84 1.89 1 16 0945+408 1.249 1.228 0.095 1.323 0.87 ...... 82 0955+476 1.882 0.646 0.031 0.677 1.00 1.60 1 146 1036+054 0.473 0.943 0.062 1.005 1.07 1.44 1 124 1038+064 1.265 1.490 0.010 1.500 1.94 5.35 1 20 1045−188 0.595 0.757 0.510 1.267 0.03 2.2 1 21 1055+018 0.890 2.701 0.227 2.928 0.88 1.96 1 114 1124−186 1.048 0.673 0.030 0.703 1.13 4.21 1 36 1127−145 1.184 5.493 0.115 5.607 1.44 2.63 1 22 1150+812 1.250 1.891 0.089 1.980 1.08 2.88 1 94 1156+295 0.729 1.557 0.186 1.743 0.76 1.47 1 30 1213−172 ... 1.889 0.084 1.973 1.14 2.43 1 149 1219+044 0.965 0.571 0.184 0.754 0.29 1.60 2 − 1222+216 0.432 1.133 0.927 2.061 −0.02 1.82 1 85 1226+023 0.158 32.788 17.852 50.640 0.22 1.69 1 16 1228+126 0.004 3.680 52.410 56.090 −1.16 ...... 136 1253−055 0.536 10.587 2.046 12.633 0.58 1.57 1 44 1308+326 0.996 1.334 0.069 1.404 1.08 1.43 1 75 1324+224 1.400 1.136 0.002 1.138 2.43 1.44 1 106 1334−127 0.539 2.055 0.166 2.221 0.96 1.74 2 41 1413+135 0.247 1.078 0.006 1.084 2.20 1.31 1 159 1417+385 1.831 0.520 0.002 0.523 2.02 1.49 1 41 1458+718 0.905 7.400 0.216 7.615 1.34 3.05 1 153 1502+106 1.839 1.816 0.038 1.854 1.36 1.62 1 43 1504−166 0.876 2.394 0.012 2.406 2.11 2.23 1 1 1510−089 0.360 1.447 0.180 1.627 0.81 1.93 1 165 1538+149 0.605 1.668 0.068 1.736 1.25 1.77 1 3 1546+027 0.414 1.147 0.019 1.166 1.68 ...... 8 1548+056 1.422 2.560 <0.001 2.560 >3.06 ...... − 1606+106 1.226 1.347 0.027 1.374 1.46 ...... 61 1611+343 1.397 2.833 0.021 2.854 1.86 ...... 28 1633+382 1.814 2.170 0.032 2.202 1.52 ...... 108 1637+574 0.751 1.013 0.071 1.084 0.99 1.34 1 84 1638+398 1.666 1.171 0.027 1.198 1.35 1.55 1 150 1641+399 0.593 7.955 1.477 9.431 0.59 ...... 39 1655+077 0.621 1.165 0.211 1.376 0.60 ...... 45 1726+455 0.717 1.003 0.053 1.056 1.11 1.31 1 57 1730−130 0.902 6.135 0.518 6.654 0.88 1.75 1 89 1739+522 1.375 1.611 0.024 1.636 1.56 1.40 1 113 1741−038 1.054 1.697 0.001 1.697 3.36 1.79 1 67 1749+096 0.322 0.903 <0.001 0.903 >2.79 ...... − 43

Table 2.3 (cont’d)

Source Redshift Score Sext Stotal log(Rc) CoreFWHM NGauss ∆PA (B1950) (Jy) (Jy) (Jy) (arcsec) (degrees) (1) (2) (3) (4) (5) (6) (7) (8) (9)

1751+288 1.118 0.275 0.007 0.282 1.35 1.57 1 51 1758+388 2.092 0.334 0.001 0.335 2.10 2.83 1 4 1800+440 0.663 0.531 0.258 0.789 0.16 3.32 1 36 1803+784 0.680 1.985 0.018 2.004 1.88 2.94 1 74 1807+698 0.051 1.205 0.367 1.572 0.50 2.02 1 19 1823+568 0.664 0.996 0.083 1.079 0.92 3.06 1 107 1828+487 0.692 6.029 7.610 13.639 −0.26 1.70 2 169 1849+670 0.657 0.471 0.102 0.573 0.51 3.39 1 99 1928+738 0.302 3.444 0.133 3.577 1.33 1.50 1 1 1936−155 1.657 1.081 0.009 1.089 1.80 3.10 1 34 1957+405 0.056 0.811 414.189 415.000 −2.73 ...... 9 1958−179 0.650 1.840 0.001 1.841 3.07 2.51 1 − 2005+403 1.736 2.467 0.010 2.476 2.10 1.45 1 10 2008−159 1.180 0.551 0.007 0.559 1.64 4.02 1 2 2021+317 ... 3.066 0.130 3.196 1.16 1.44 1 − 2021+614 0.227 2.254 0.001 2.255 3.25 2.26 1 − 2037+511 1.686 4.616 1.002 5.619 0.36 1.41 2 113 2121+053 1.941 1.084 0.005 1.089 2.01 ...... − 2128−123 0.501 1.425 0.030 1.454 1.56 1.91 1 19 2131−021 1.285 1.355 0.164 1.519 0.67 1.65 2 29 2134+004 1.932 1.346 0.174 1.520 0.57 1.63 1 32 2136+141 2.427 1.140 <0.001 1.140 >2.60 1.61 1 − 2145+067 0.990 2.866 0.028 2.894 1.80 1.73 1 166 2155−152 0.672 2.699 0.301 2.999 0.80 2.35 1 19 2200+420 0.069 1.992 0.011 2.004 2.23 1.52 1 39 2201+171 1.075 0.875 0.072 0.947 0.87 1.71 1 138 2201+315 0.295 1.537 0.328 1.865 0.59 1.58 1 32 2209+236 1.125 0.428 <0.001 0.428 >3.09 1.58 1 − 2216−038 0.901 1.765 0.305 2.070 0.57 1.96 1 47 2223−052 1.404 7.128 0.077 7.205 1.70 1.97 1 124 2227−088 1.560 0.927 0.010 0.936 1.69 2.08 1 34 2230+114 1.037 6.991 0.138 7.129 1.49 1.71 1 3 2243−123 0.632 2.269 0.026 2.295 1.80 2.19 1 15 2251+158 0.859 14.091 0.824 14.915 1.05 1.65 1 14 2331+073 0.401 0.608 0.038 0.646 1.11 1.70 1 26 2345−167 0.576 1.994 0.140 2.134 1.02 2.32 1 86 2351+456 1.986 2.346 0.007 2.353 2.19 1.55 1 18

Note. — Columns are as follows: col (1) IAU B1950 name; (2) Optical redshift, obtained from NED; (3) Core flux density in Jy derived using AIPS task JMFIT; (4) Extended flux density in Jy derived using AIPS verb IMSTAT; (5) Total flux density in Jy derived using AIPS verb IMSTAT; (6) Core prominence ratio of the source, rest frame; (7) Semi−major axis of elliptical Gaussian used in AIPS to determine Score, not included in some archival data; (8) Number of elliptical Gaussians used in AIPS to determine Score, not included in some archival data; (9) Misalignment angle between parsec−scale and kiloparsec−scale jets, from Kharb, Lister & Cooper 2010. 44

2.3 Extended Luminosity v. Intrinsic Power

Giovannini et al. [1988] state that extended luminosity is a good indicator of intrinsic jet power. Specifically they found a strong correlation between the core luminosity in both FR I & II radio galaxies, which, unlike blazars, is anti−beamed (i.e., beamed in the plane of the sky), and the lobe luminosity. Generally, more powerful jets are expected to produce more powerful lobes. Furthermore, work done on the interstellar medium (ISM) by the AGN jet pro- duces X−ray emission [McNamara et al., 2000]. Measuring these x−ray emissions provides a direct way of modeling the jet power. Using 1.4 GHz, VLA D array data (NVSS), which has greater sensitivity to diffuse emission than VLA A array, the correlation between radio luminosity and jet power is supported by such measure-

ments [Cavagnolo et al., 2010]. Therefore, extended luminosity (Lext) may be used as a proxy for mechanical jet power, which is an intrinsic property of the jet. By

checking correlations of Lext to other measurements, I can examine whether these measurements are correlated with unbeamed jet power.

In order to use Lext as a proxy for jet power, it is important to detect as much extended flux density as possible. Simultaneously it is important to have good angular resolution so that core emission can be resolved separately from the extended emission. Greater angular resolution can also give insight into jet geometry [Conway & Murphy, 1993]. However, angular resolution is proportional to telescope diameter5. Conversely, an extended source emits less power on longer baselines. Furthermore, viewing an object at a greater ν increases resolution but usually results in lower flux density (§1.1). As a compromise between these conflicting laws, we chose 1.4 GHz. I plotted MOJAVE VLA−A total flux density vs. NVSS total flux density (both at 1.4 GHz) in Figure 2.5, to examine if the loss of sensitivity due to the longer

baselines significantly affects the detection of Sext. The resulting least squares fit of the VLA−A vs. VLA−D plot yields a slope of 1.03 and an intercept of −0.02. This

5Which is determined by the longest baseline between antennas in an interferometer. 45

is very close to a direct SV LA−D = SV LA−A relationship. Consequently, there is more information lost in terms of lower angular resolution using VLA−D array, than flux density information lost using VLA−A array. The scatter around the fitted line is most likely due to the fact that these data were not obtained simultaneously and the sources are highly variable. The use of any other configuration or frequency would only result in a loss of either flux density or morphological information.

Figure 2.5. Plot of NVSS VLA−D flux densities vs. MOJAVE VLA−A flux densities. The red dashed line is a least squared fit with a slope of 1.03 and an intercept of −0.02. 46

Table 2.4. Single Dish and Short Base−line Observations of MOJAVE Sources at 1.4 GHz

Source Stotal Survey Name mJy (1) (2) (3)

0003−066 2050 NVSS 1630 DIXON 1555 KUEHR 1530 PKSCAT90 1460 DIXON 0007+106 300 NORTH20CM 101 NVSS 98 DIXON 0016+731 1136 NVSS 1100 KUEHR 0048−097 1100 DIXON 1100 PKSCAT90 970 KUEHR 893 FIRST 815 ROXA 814 NVSS 590 DIXON 0059+581 2096 NORTH20CM 848 NVSS 0106+013 4039 NORTH20CM 2621 NVSS 1898 KUEHR 1400 DIXON 1300 PKSCAT90 0109+224 299 NORTH20CM 385 NVSS 0119+115 1200 DIXON 1200 PKSCAT90 1184 NVSS 1059 NORTH20CM 900 KUEHR 0133+476 2056 KUEHR 1395 NORTH20CM 1137 NVSS 0202+149 4510 NORTH20CM 4067 NVSS 3821 KUEHR 3700 PKSCAT90 3600 DIXON 0202+319 947 NORTH20CM 900 DIXON 900 KUEHR 657 NVSS 0212+735 2618 NORTH20CM 2400 KUEHR 2271 NVSS 0215+015 750 NVSS 626 NORTH20CM 540 PKSCAT90 47

Table 2.4 (cont’d)

Source Stotal Survey Name mJy (1) (2) (3)

0224+671 1539 NVSS 1442 NORTH20CM 0234+285 2334 NORTH20CM 2197 NVSS 1720 KUEHR 0235+164 2355 NORTH20CM 1941 NVSS 1440 KUEHR 0238−084 1017 FIRST 913 NVSS 850 PKSCAT90 0300+470 1654 NORTH20CM 963 NVSS 0316+413 22829 NVSS 14442 KUEHR 13490 DIXON 8900 DIXON 21198 NORTH20CM 14000 DIXON 22000 DIXON 12540 DIXON 0333+321 3990 DIXON 3082 NORTH20CM 2677 NVSS 0336−019 2800 DIXON 2424 NVSS 2245 NORTH20CM 2130 PKSCAT90 2026 KUEHR 1500 DIXON 0403−132 4218 NVSS 4217 KUEHR 4000 PKSCAT90 3700 DIXON 3300 DIXON 0415+379 7726 NVSS 13532 NORTH20CM 15510 DIXON 14870 DIXON 15000 DIXON 0420−014 2726 NVSS 2240 PKSCAT90 1940 DIXON 1894 NORTH20CM 1700 DIXON 950 KUEHR 0422+004 750 PKSCAT90 520 NORTH20CM 493 NVSS 48

Table 2.4 (cont’d)

Source Stotal Survey Name mJy (1) (2) (3)

0430+052 6008 KUEHR 5590 DIXON 4400 DIXON 4360 DIXON 4200 DIXON 3848 NORTH20CM 3800 PKSCAT90 3439 NVSS 0446+112 1300 PKSCAT90 847 NVSS 780 KUEHR 726 NORTH20CM 0458−020 2264 NVSS 2200 DIXON 2200 PKSCAT90 2073 KUEHR 1999 NORTH20CM 0528+134 1949 NORTH20CM 1556 NVSS 0529+075 2729 NVSS 2323 NORTH20CM 0529+438 484 NORTH20CM 434 NVSS 0552+398 1754 NORTH20CM 1516 NVSS 0605−085 2760 KUEHR 2530 DIXON 2530 PKSCAT90 2500 DIXON 1905 NVSS 0607−157 2742 NVSS 2400 DIXON 2200 KUEHR 2100 PKSCAT90 0642+449 595 NORTH20CM 452 NVSS 0648−165 1777 NVSS 1700 PKSCAT90 1600 DIXON 0716+714 806 NORTH20CM 727 NVSS 0727−115 2760 NVSS 1700 DIXON 900 DIXON 0730+504 790 FIRST 770 NVSS 440 DIXON 386 NORTH20CM 0735+178 2600 DIXON 49

Table 2.4 (cont’d)

Source Stotal Survey Name mJy (1) (2) (3)

2600 DIXON 2258 NVSS 2244 KUEHR 2000 PKSCAT90 1873 NORTH20CM 1102 FIRST 0736+017 2610 KUEHR 2480 NORTH20CM 2200 PKSCAT90 1964 NVSS 0738+313 2363 KUEHR 2284 NVSS 2071 FIRST 1972 NORTH20CM 0742+103 3506 NVSS 3500 PKSCAT90 3380 KUEHR 3278 NORTH20CM 0748+126 1770 NORTH20CM 1700 KUEHR 1543 FIRST 1453 NVSS 0754+100 1051 NORTH20CM 1035 FIRST 956 NVSS 0804+449 1115 NVSS 1030 KUEHR 930 FIRST 892 NORTH20CM 750 DIXON 0805−077 1595 NVSS 1375 KUEHR 1200 DIXON 1200 DIXON 1200 PKSCAT90 0808+019 700 DIXON 598 NVSS 419 NORTH20CM 0814+425 2580 DIXON 1742 KUEHR 1472 NORTH20CM 1091 ROXA 1091 NVSS 1005 FIRST 0823+033 1401 ROXA 1400 NVSS 1354 NORTH20CM 1200 KUEHR 1179 FIRST 50

Table 2.4 (cont’d)

Source Stotal Survey Name mJy (1) (2) (3)

810 PKSCAT90 0827+243 886 FIRST 739 ROXA 739 NVSS 694 NORTH20CM 0829+046 1242 ROXA 1241 NVSS 930 NORTH20CM 739 FIRST 0836+710 4243 NORTH20CM 3900 KUEHR 3823 NVSS 0838+133 2900 DIXON 2800 PKSCAT90 2777 FIRST 2743 KUEHR 2676 NORTH20CM 2670 DIXON 2613 NVSS 2600 DIXON 2570 DIXON 0851+202 2281 NORTH20CM 2230 KUEHR 1900 DIXON 1512 NVSS 1182 FIRST 0906+015 1300 PKSCAT90 1140 KUEHR 961 NORTH20CM 760 ROXA 760 NVSS 572 FIRST 0917+624 1242 FIRST 1227 NORTH20CM 1020 KUEHR 946 NVSS 0923+392 2959 FIRST 2900 DIXON 2885 ROXA 2885 NVSS 2830 KUEHR 2716 NORTH20CM 0945+408 1815 KUEHR 1600 ROXA 1600 NVSS 1537 FIRST 1491 NORTH20CM 0955+476 7784 FIRST 687 NORTH20CM 51

Table 2.4 (cont’d)

Source Stotal Survey Name mJy (1) (2) (3)

604 ROXA 604 NVSS 1036+054 640 NVSS 430 FIRST 374 NORTH20CM 1038+064 1405 NVSS 1355 NORTH20CM 1329 FIRST 1045−188 1155 NVSS 1100 KUEHR 1100 PKSCAT90 1055+018 3465 KUEHR 3360 PKSCAT90 3354 FIRST 3220 NVSS 3135 NORTH20CM 1124−186 536 NVSS 1127−145 6654 KUEHR 6400 PKSCAT90 6200 DIXON 5622 NVSS 1150+812 1400 KUEHR 1380 NORTH20CM 1343 NVSS 1156+295 2031 NVSS 1953 FIRST 1754 NORTH20CM 1213−172 1700 DIXON 1670 KUEHR 1662 NVSS 1500 DIXON 1500 PKSCAT90 1219+044 1000 DIXON 1000 PKSCAT90 801 FIRST 800 NVSS 667 NORTH20CM 1222+216 2094 NVSS 1974 NORTH20CM 1666 FIRST 1500 DIXON 1500 PKSCAT90 1226+023 54992 ROXA 50100 NORTH20CM 42212 KUEHR 42000 PKSCAT90 41200 DIXON 40900 DIXON 39620 DIXON 52

Table 2.4 (cont’d)

Source Stotal Survey Name mJy (1) (2) (3)

36983 FIRST 33560 DIXON 16369 FIRST 54991 NVSS 1228+126 254000 DIXON 220000 PKSCAT90 217405 KUEHR 190000 DIXON 54728 FIRST 138487 NVSS 33816 FIRST 22373 NORTH20CM 12565 FIRST 1253−055 11600 PKSCAT90 10862 NORTH20CM 10708 FIRST 10530 DIXON 10400 DIXON 10240 KUEHR 9711 NORTH20CM 8670 DIXON 9754 NVSS 1308+326 1687 ROXA 1687 NVSS 1611 NORTH20CM 1506 FIRST 1150 KUEHR 1324+224 1227 FIRST 850 NVSS 235 NORTH20CM 1334−127 2676 NVSS 1800 DIXON 1413+135 1206 NORTH20CM 1179 FIRST 1092 NVSS 1417+385 789 ROXA 708 NORTH20CM 657 FIRST 612 NVSS 460 DIXON 1458+718 8500 DIXON 8460 KUEHR 7680 NORTH20CM 7468 NVSS 1502+106 1774 NVSS 1753 FIRST 1663 KUEHR 1554 NORTH20CM 1504−166 2943 KUEHR 53

Table 2.4 (cont’d)

Source Stotal Survey Name mJy (1) (2) (3)

2711 NVSS 2700 DIXON 2700 PKSCAT90 1510−089 3412 KUEHR 3300 PKSCAT90 3000 DIXON 2700 NVSS 1538+149 1670 KUEHR 1483 FIRST 1446 NORTH20CM 1387 NVSS 1546+027 1157 FIRST 1144 NORTH20CM 836 ROXA 835 NVSS 770 PKSCAT90 710 KUEHR 1548+056 2880 KUEHR 2800 DIXON 2752 FIRST 2303 NVSS 1958 NORTH20CM 1606+106 1697 NORTH20CM 1600 DIXON 1600 PKSCAT90 1470 KUEHR 1402 FIRST 1400 DIXON 1392 NVSS 1611+343 4025 ROXA 4024 NVSS 3606 FIRST 3100 DIXON 2871 NORTH20CM 2694 KUEHR 1633+382 2726 NVSS 2694 FIRST 2123 KUEHR 1900 NORTH20CM 1637+574 1230 NORTH20CM 1199 NVSS 1092 FIRST 997 KUEHR 1638+398 1109 FIRST 976 NVSS 820 DIXON 780 DIXON 710 KUEHR 657 NORTH20CM 54

Table 2.4 (cont’d)

Source Stotal Survey Name mJy (1) (2) (3)

1641+399 8100 DIXON 7974 KUEHR 7886 NORTH20CM 7099 ROXA 7099 NVSS 6970 DIXON 6599 FIRST 6430 DIXON 1655+077 1731 NORTH20CM 1413 NVSS 1726+455 947 FIRST 914 NVSS 425 NORTH20CM 1730−130 5990 NVSS 5990 DIXON 5300 DIXON 5200 PKSCAT90 1739+522 1979 NORTH20CM 1554 FIRST 1375 KUEHR 807 NVSS 1741−038 2080 DIXON 1700 KUEHR 1411 NVSS 1348 NORTH20CM 1170 PKSCAT90 1749+096 725 KUEHR 623 NVSS 612 NORTH20CM 1751+288 648 NORTH20CM 414 NVSS 1758+388 510 NORTH20CM 326 NVSS 1800+440 883 NORTH20CM 727 NVSS 690 KUEHR 1803+784 2223 NVSS 1900 KUEHR 1868 NORTH20CM 1807+698 2690 DIXON 2267 KUEHR 2261 NORTH20CM 1885 NVSS 1823+568 1478 NORTH20CM 1442 NVSS 1400 KUEHR 1828+487 15000 DIXON 14645 NORTH20CM 14443 KUEHR 55

Table 2.4 (cont’d)

Source Stotal Survey Name mJy (1) (2) (3)

14390 DIXON 14060 DIXON 13753 NVSS 1849+670 901 NORTH20CM 517 NVSS 1928+738 3950 NVSS 3908 NORTH20CM 3200 KUEHR 1936−155 800 KUEHR 608 NVSS 600 DIXON 600 PKSCAT90 1957+405 1900000 DIXON 1255000 DIXON 858423 NVSS 739767 NVSS 1958−179 550 NVSS 500 KUEHR 2005+403 2470 NVSS 2008−159 600 KUEHR 546 NVSS 2021+317 3367 NVSS 2430 DIXON 1899 NORTH20CM 2021+614 2185 KUEHR 2134 NORTH20CM 2093 NVSS 2037+511 6081 NVSS 5440 DIXON 2121+053 1142 NORTH20CM 794 NVSS 2128−123 1800 DIXON 1800 PKSCAT90 1769 NVSS 1757 KUEHR 2131−021 2206 NORTH20CM 1875 KUEHR 180 PKSCAT90 1690 NVSS 1620 FIRST 2134+004 3728 NORTH20CM 3712 FIRST 3473 ROXA 3473 NVSS 3270 DIXON 3268 KUEHR 3130 PKSCAT90 2136+141 1150 NORTH20CM 1132 NVSS 56

Table 2.4 (cont’d)

Source Stotal Survey Name mJy (1) (2) (3)

1050 KUEHR 2145+067 3110 DIXON 3000 PKSCAT90 2884 NORTH20CM 2727 KUEHR 2589 NVSS 2155−152 3021 NVSS 1260 PKSCAT90 2200+420 6051 NVSS 4688 NORTH20CM 4500 KUEHR 3600 DIXON 2201+171 992 NORTH20CM 790 DIXON 592 NVSS 2201+315 2878 NVSS 2183 KUEHR 1977 NORTH20CM 2209+236 557 NVSS 503 NORTH20CM 2216−038 2218 NVSS 1541 NORTH20CM 900 DIXON 900 PKSCAT90 870 KUEHR 2223−052 7411 NVSS 6367 NORTH20CM 6345 KUEHR 6200 PKSCAT90 6020 DIXON 6000 DIXON 5970 DIXON 2227−088 1250 KUEHR 1210 DIXON 1100 DIXON 1100 PKSCAT90 973 FIRST 968 NVSS 2230+114 7202 NVSS 6971 KUEHR 6900 PKSCAT90 6700 DIXON 6634 NORTH20CM 6110 DIXON 2243−123 1882 NVSS 2251+158 13901 NORTH20CM 13000 DIXON 12800 DIXON 12200 PKSCAT90 57

Table 2.4 (cont’d)

Source Stotal Survey Name mJy (1) (2) (3)

12080 DIXON 11977 KUEHR 11870 DIXON 12657 NVSS 2331+073 631 NVSS 602 NORTH20CM 2345−167 2642 NVSS 2275 KUEHR 2050 DIXON 1200 DIXON 1200 PKSCAT90 2351+456 2140 KUEHR 1872 NVSS 1836 NORTH20CM

Note. — Columns are as follows: (1) IAU Name (B1950.0); (2) Total flux density in mJy; (3) Reference to pub- lished image where, DIXON = Dixon Master List of Radio Sources (Version 43, Dixon R.S.), FIRST = The FIRST Sur- vey Catalog of 1.4−GHz Radio Sources (White R.L. et al. 1997; July 5 2000 Version), KUEHR = Extragalactic Ra- dio Sources at 5 GHz (Kuehr H. et al. 1981), NORTH20CM = The 20−cm Northern Sky Catalog (White, R.L. and Becker, R.H. 1992), NVSS = The NRAO VLA Sky Survey (Condon, J.J. et al. At http://www.cv.nrao.edu/nvss/), PKSCAT90 = Parkes Catalog 1990: The Southern Radio Source Database (Wright, A.E. and Otrupcek, R. 1990), ROXA = ROXA (Radio−Optical−X−ray at ASDC) Blazars Catalog (Turriziani S. et al. 2007). 58 59

3. JET GEOMETRY − SIMPLE BENDS

Establishing the three−dimensional geometry of blazar jets is challenging because they are seen at small viewing angles. When projected on the plane of the sky, a slight bend or helicity can cause greatly exaggerated misalignment angles (∆PA) between parsec and kiloparsec scale jets. However, jet geometry is important in constraining MHD and environmental conditions [Meier, Koide & Uchida, 2001]. In this chapter, I discuss Monte Carlo simulations that I have performed to constrain which jet geometries can best reproduce the MOJAVE sample ∆PA distribution.

3.1 Previous Simple Bend Monte Carlo Simulations

Pearson & Readhead [1988] found a bimodal distribution in the angle of misalign- ment between AGN parsec scale jets and kiloparsec scale jets (∆PA), in a population of 18 sources. The distribution of ∆PA peaked at < 30◦ and at 90◦. They speculated that this bimodal distribution is the result of a simple bend in the jet, of ∼ 15◦, that is exaggerated due to projection effects. Conway & Murphy [1993] expanded the Pearson & Readhead [1988] sample to 44 sources, and also found a bimodal distribution of ∆PA peaked at <15◦ and 90◦ to 105◦. The peak at 90◦ to 105◦ was nearly the same magnitude as the <15◦ peak. Conway & Murphy [1993] tested the simple bend and helical jet hypotheses by performing Monte−Carlo simulations. They used the following formula to calculate ∆PA:

sin ζ sin φ tan∆P A = (3.1) cos ζ sin θ + sin ζ cos θ cos φ where ζ is the intrinsic bend angle of the jet, θ is our viewing angle to the inner jet and φ is the azimuth angle in the plane of the sky. They made following assumptions in their simulation: 60

• A fixed value of ζ = 20◦

• θ has a fixed ratio to ζ (e.g., 0.25, 0.5, 1.0, 1.5, 2.0)

• φ randomly varies in a uniform distribution from 0◦−180◦

• Since θ and ζ have a random distribution, the result would be a linear combi- nation of the ∆PA probability distributions created by the above assumptions.

They conclude that a simple bend geometry cannot reproduce the bimodal distribu- tion in ∆PA, such that the peak near 90◦ is the same magnitude as the primary peak at smaller angles. Appl, Sol & Vicenta [1996] collected a larger population (N=155), but without regarding selection criteria. They find that the secondary peak near 90◦ varies in size according to sub−population selected by optical class and redshift. They also find that, while the simple bend model doesn’t fit well to data with single populations, the simple bend model cannot be dismissed. Furthermore, the ∆PA distribution in Kharb, Lister & Cooper [2010] (Fig. 1) shows only a weak secondary peak at 90◦ to 110◦ in a flux−limited population of 118 AGN1. Statistical fluctuations could account for a weak secondary peak in a simple bend model.

3.2 Simulating the MOJAVE Sample Population

To test the hypothesis that the secondary peak may be caused by statistical fluc- tuations in a simple bend model, I performed Monte Carlo simulations using equation 3.1. This requires generating the three variables in Eq. 3.1: θ,ζ and φ. Generating random distributions of ζ and φ is fairly straightforward and is discussed in greater detail below. However, generating θ is more complex because it is affected by the flux density−limited selection criteria of the MOJAVE sample. The Monte Carlo simulation has to account for these effects to produce a realistic ∆PA distribution.

117 AGN have core or core−halo morphologies such that position angles could not be reliably determined 61

Figure 3.1. Distribution of ∆PA for 118 MOJAVE AGN from Kharb, Lister & Cooper [2010]. 17 AGNs have core or core−halo morphologies that make measuring kpc−scale jet angles unreliable.

3.2.1 Simulating General MOJAVE Variables

All three blazar populations of interest in this chapter are VLBI flux density lim- ited at frequencies above 5 GHz (i.e., Lister et al. 2009, Conway & Murphy 1993, Pearson & Readhead 1988), which implies a strong favoritism toward highly relativis- tic jets (See §1.2). Relativistic aberration of light bends the electromagnetic field of rest−frame isotropic emissions into a cone of θ< Γ−1 in the observer frame [Rybicki & Lightman, 1979]. So for a modestly relativistic jet of Γ = 5, we might expect θ to be < 11.5◦ and a Doppler factor (δ) of at least 5. Considering that observed flux

p density (Sobs) is Doppler boosted from intrinsic flux density (Si) by a factor of δ (p is 2−3), θ is biased to angles < Γ−1. 62

Since we are dealing with a flux−limited sample, accordingly, along with θ, the Monte Carlo simulation must also generate redshift (z), (Γ) and intrinsic luminosity

(Li). These are used to calculate δ, luminosity distance (dL), and beamed VLBA core flux density (SV LBA) to realistically account for the observational bias in θ. To this end, I adapted a MOJAVE sample population generator (SPG, see also Lister & Marscher 1997, Cara & Lister 2008) that also serves as the basis for other Monte Carlo simulations in my dissertation (i.e., the radio to −γ−ray luminosity simulator). The features of the SPG common to all Monte Carlo simulations in this dissertation are discussed in this subsection. The SPG creates a maximum of 2 × 109 two−sided jets by randomly generat- ing redshift (z), intrinsic luminosity (Li), bulk Lorentz factor (Γ) and θ from their appropriate probability distributions. SPG uses a uniform, 64−bit random number generator (RNG), uni64() in the C programming language. The SPG uses C functions gasdev() and powerlaw() from Numerical Recipes [Press et al., 2007] to convert the uniform random deviates to Gaussian and power−law distributions respectively. For more robust random number generation I changed the 9 digit RNG seeds before each set of simulations. SPG generates z by inputting a uniformly distributed random number from 0 to 1, taking its base−10 logarithm and then inputs the result into a spline derived from the fitted density evolution function calculated in Cara [2008]. The SPG allows a range of z from 0.04 to 4 (based on MOJAVE sample statistics, see Fig. 2.1). Luminosity distance (dL) is then calculated by inputting z into a fitted spline based on a ΛCDM −1 −1 cosmology (Ho = 71 km s Mpc , ΩM =0.27 and ΩΛ =0.73). To expedite an initial, thorough exploration of the parameter space, I set the SPG to generate Γ using a Gaussian distribution with a peak at 8 a FWHM of 10 and a minimum cut−off of 2. The viewing angle cos θ is generated using a uniform distribution with a range of 0−1. Intrinsic jet speed, β, is calculated using equation

1.2 and βapp is calculated using equation 1.4. δ, a function of β and θ, is calculated using formula 1.3. 63

Li is generated using the luminosity function for the MOJAVE parent population [Cara & Lister, 2008] and scaled by a factor of Γχ (where χ = 1.25, Lister & Marscher

1997). SV LBA is calculated using

p 3−p Liδ (1 + z) SV LBA = 2 , (3.2) dL where p is the boosting index and is set to 2 [Rybicki & Lightman, 1979, Urry &

Padovani, 1995]. Then the SPG selects the first 135 sources whose SV LBA meets the MOJAVE selection criteria (See §1.2). Since the MOJAVE sample is highly beamed, the flux density limit will cause a non−uniform distribution of θ. Indeed, repeated simulations consistently showed a Poisson−shaped distribution of θ peaked at 2◦ (See Fig. 3.2). Once the parameters for the ζ distributions were narrowed (See §3.2.3−5, below), the simulations were performed again, but with a power law distribution of Γ with an index of −1.5 and a range of 3 to 50 [Lister et al., 2009]. A comparison of θ distributions resulting from both the Gaussian and power law distributions of Γ (Fig. 2 & 3, respectively) show that the θ distributions are consistent within 1σ and that the parameter space selected for the ζ distributions is valid. 64

Figure 3.2. The distribution of mean θ generated using the MOJAVE SPG, derived from 1000 populations of 135 sources using a Gaussian distribution of Γ. The error bars signify 1σ fluctuations. θ is originally generated with a uniform distribution with a range of 0◦ − 90◦. However since the 135 sources are selected each time on the basis of Doppler boosted flux density, SV LBA, a non−uniform θ distribution results. 65

Figure 3.3. The distribution of mean θ generated using the MOJAVE SPG, derived from 1000 populations of 135 sources using a power law distribution of Γ. The error bars signify 1σ fluctuations. θ is originally generated with a uniform distribution with a range of 0◦ − 90◦. However since the 135 sources are selected each time on the basis of Doppler boosted SV LBA, a non−uniform θ distribution results. 66

3.2.2 Simulating φ and ζ

Whereas θ is a variable of equation 3.1 that is important in other applications, φ and ζ are specific to the Simple Bend Model. φ and ζ do not suffer any strong selection biases, and generating their distributions is straightforward. However, there are some important points to make about their generation. Naturally, φ’s range from 0◦− 360◦. Including values of φ > 180◦ in formula 3.1 generates ∆PAs < 0◦. Allowing φ to vary from 0◦− 360◦ only creates quadrant ambi- guities in ∆PA, which only further complicates the source code for these simulations without adding any useful information. Therefore, I chose φ to vary in a uniform distribution from 0◦− 180◦, similar to Conway & Murphy [1993]. As an ansatz to what the distribution of ζ may be, I used uniform, Gaussian and power−law distributions. Unlike Conway & Murphy [1993], I allowed ζ to vary inde- pendently from θ. For each distribution, I created populations using several different sets of parameters, since little work has been done to observationally constrain ζ. Figures 3.4−3.6 show χ2 plotted against the varying parameter for each set of

ζ and Γ distributions, i.e., index for a power law distribution, ζmax for a uniform distribution and FWHM for a Gaussian distribution at a set peak. These figures show that χ2 tests yield the most probable outcome for distributions of ζ that are close to ◦ ◦ uniform. Furthermore, distributions that include 20 < ζmax < 5 are increasingly unlikely to yield the measured MOJAVE ∆PA distribution. Using bins of 20◦ over a range of 180◦ yields 8 degrees of freedom. The χ2 values in Tables 1 and 2 are not reduced and were calculated using Numerical Recipes [Press et al., 2007]. 67

(a) (b)

Figure 3.4. Left: Plot of χ2 vs. FWHM(deg) for Gaussian ζ distribution peaked at 4◦ and a power law Γ distribution. The rapid decline of χ2 as FWHM increase indicates that flatter distributions are more likely to create the observed ∆PA distribution in the MOJAVE sample. Right: Plot of χ2 vs. FWHM(deg) for Gaussian ζ distribution peaked at 5◦ and a Gaussian Γ distribution. The rapid decline of χ2 as FWHM increase indicates that flatter distributions are more likely to create the observed ∆PA distribution in the MOJAVE sample. 68

(a) (b)

Figure 3.5. Left: Plot of χ2 vs. Index for power law ζ distribution and a power law Γ distribution. χ2 with a minimum near an index of 0 indicates that flatter distributions are more likely to create the observed ∆PA distribution in the MOJAVE sample. Right: Plot of χ2 vs. Index of Power Law ζ distribution and a Gaussian Γ distribution. The rapid increase of χ2 as index increases indicates that flatter distributions are more likely to create the observed ∆PA distribution in the MOJAVE sample. 69

(a) (b)

2 Figure 3.6. Left: Plot of χ vs. ζmax (deg) for uniform ζ distribution and a power law Γ distribution. χ2 is minimum near 9.5◦ however, χ2 yields statistically significant matches to ∆PA distribution in the MOJAVE sample up to ∼ 20◦. Right: Plot of χ2 vs. FWHM(deg) for uniform ζ distribution and a Gaussian Γ distribution. The

2 ◦ relative minimum of χ at approximately ζmax = 10.25 indicates that distributions ◦ ◦ with 20 <ζmax < 5 are more likely to create the observed ∆PA distribution in the MOJAVE sample. 70

3.2.3 Simulations with a Uniform Distribution of ζ

◦ ◦ First, I used a uniform distribution of ζ with ζmin =0 and upper−limits of 1.25 , 2.5◦, 5◦, 7.5◦, 10◦, 20◦ and 30◦. Each set of simulations used 1000 populations of 135 sources. To be consistent with Kharb, Lister & Cooper [2010], I plotted the mean ∆PAs in histograms with bins of 20◦; the error bars signify 1σ fluctuations. As stated above, ζ was allowed to vary independently from θ, since there is no reason to expect the two variables should be related. Conway & Murphy [1993] found that if θ was greater than or equal to ζ than no ∆PA > 90◦ would result. The greater θ became with respect to ζ, the sharper the ∆PA distribution would peak at low angles. Since θ selected on the basis of relativistic beaming has a Poisson distribution peaked at 2◦, I selected the upper limits in ζ, from 2.5◦ to 30◦, such that

the distribution of ∆PA ought to become more sharply peaked at lower angles as ζmax was increased. Next, I performed χ2 tests of the simulated ∆PAs against the measured ∆PAs. I plotted χ2 vs. maximum ζ, and found that the maximum likelihood for a match between the simulated and measured data occurred close to a maximum ζ of 10◦. I then performed additional simulations, using the same procedure, with maximum ζ of 8.75◦, 11.25◦ and 12.5◦. Figure 3.7 shows the 11.25◦ maximum ζ simulation which yields the greatest likelihood of a match between the simulation using a Gaussian Γ distribution and measured data with χ2 = 6.12(P = 0.634). For reference, the least

◦ 2 likely uniform distribution (ζmax =1.25 ) is shown in Figure 3.8. The χ tests show ◦ that a ζmax >= 30 is excluded at greater than the 95% confidence level, likewise a ◦ ζmax <=5 is excluded at greater than a 99% confidence level. 71

Figure 3.7. The distribution of mean ∆PA in degrees generated using the MOJAVE SPG, 1000 populations of 135 sources, and a Gaussian Γ distribution. ζ is generated ◦ using a uniform distribution, ζmax = 11.25 in gray. The MOJAVE ∆PA distribution is in white. The error bars signify 1σ fluctuations. This distribution of ζ yields the greatest likelihood of matching the MOJAVE ∆PA data for uniform distributions generated using a Gaussian Γ distribution. 72

Figure 3.8. The distribution of mean ∆PA in degrees generated using the MOJAVE SPG, 1000 populations of 135 sources, and a Gaussian Γ distribution in gray. The MOJAVE ∆PA distribution is in white. ζ is generated using a uniform distribution, ◦ ζmax = 1.25 . The error bars signify 1σ fluctuations. This distribution of ζ yields the least likelihood of matching the MOJAVE ∆PA data for uniform distributions generated using a Gaussian Γ distribution. 73

Once I narrowed down the optimal range of ζ, I repeated the procedure using a power law distribution of Γ, as described in §3.2.1 above, but with maximum ζ set at ◦ ◦ ◦ ◦ ◦ 1.25 , 10.5 , 11.25 , 12 and 20 . In this initial set of Monte Carlo simulations, ζmax of 10.5◦ yields the greatest likelihood of a match between the simulated and measured

2 data with χ = 6.68(P = 0.572, See Table 3.2). Since the optimal ζmax had shifted to a slightly lower angle, I performed additional simulations with maximum ζ of 10◦, ◦ ◦ ◦ ◦ ◦ 9.5 , 9.25 ,9 ,8 and 7 , to better constrain the new optimal ζmax. In the follow−up ◦ set of Monte Carlo simulations, ζmax of 9.5 yields the greatest likelihood of a match 2 between the simulation and measured data with χ = 6.52(P = 0.589). As ζmax is lowered from 10.5◦ to 9◦ the fraction of sources in the first bin increases. Figure 3.9 ◦ shows the ∆PA distributions for ζmax of 9.5 and the measured MOJAVE ∆PA to show that the 1σ error bars are consistent with the MOJAVE data. 74

Figure 3.9. The distribution of mean ∆PA in degrees generated using the MOJAVE SPG, 1000 populations of 135 sources. ζ is generated using a uniform distribution, ◦ ζmax = 9.5 in gray. The MOJAVE ∆PA distribution is in white. The error bars signify 1σ fluctuations. This distribution of ζ yields the least likelihood of matching the MOJAVE ∆PA data for uniform distributions generated using a power law Γ distribution. 75

3.2.4 Simulations with a Gaussian Distribution of ζ

Upon completion of of the uniform distribution simulations, I performed simula- tions using Gaussian distributions. Based on the most likely upper values of ζ in the ◦ ◦ uniform distribution simulations, the peak of the Gaussian (ζpeak) was set at 2.5 , 5 , 7.5◦ and 10◦. I set the full width half−maximum parameter at 1.25◦, 2.5◦, 5◦, 7.5◦ and 10◦. This combination of parameters allowed me to see if sharply peaked or flat distributions were more similar to the MOJAVE ∆PA distribution, and if a peak at higher or lower ζ was also more similar to the MOJAVE ∆PA distribution.

For Gaussian distributions at a fixed ζpeak, the larger FWHMs yielded ∆PA distributions more similar to the measured data. Likewise, for Gaussian distribu- tions at a fixed FWHM, the smaller ζpeak yielded ∆PA distributions more similar ◦ ◦ to the measured data. Therefore, the 2.5 ζpeak, 10 FWHM, ζ simulation yields the greatest likelihood of a match between the simulation and measured data with χ2 = 6.81(P = 0.557), however since the peak is so close to zero and the FWHM is so broad, the distribution is very similar to the 0◦ − 10◦ uniform distribution. Figure ◦ ◦ 3.10 shows the ∆PA distribution of the 2.5 ζpeak, 10 FWHM ζ distribution with the MOJAVE ∆PA distribution, a comparison to Figure 3.7 shows their similarity. Next, I performed the simulations for a Gaussian ζ distribution and power law Γ distribution. Upon examining the ζ distributions with low peak angles and wide FWHM, I decided to use larger peak angles. This prevented simulations where the Gaussian distribution of ζ was too close to a uniform distribution, as stated above. ◦ ◦ My parameter space for the Gaussian ζ distribution were for a ζpeak of 4 and 6 , ◦ ◦ ◦ ◦ ◦ ◦ ◦ the FWHM were set to 1 , 2 &4 for ζpeak of 4 and 4 &6 for ζpeak of 6 . Again, as with the Monte Carlos performed with a Gaussian Γ distribution, the lower ζmax with the wider FWHM yields the best fit to the MOJAVE ∆PA distribution. The ◦ ∆PA distribution of the best Gaussian ζ distribution is ζpeak of 4 and a FWHM of 4◦ (χ2 =6.90, p= 0.547). Figure 3.11 shows the ∆PA distribution of the least likely 76

◦ ◦ 2 Gaussian ζ distribution, ζpeak of 4 and a FWHM of 1 (χ = 13.0, p= 0.110). The ∆PA distribution becomes more flat as the FWHM decreases.

Figure 3.10. The distribution of mean ∆PA in degrees generated using the MOJAVE SPG, 1000 populations of 135 sources, and a Gaussian Γ distribution. ζ is generated ◦ ◦ using a Gaussian distribution, ζpeak =2.5 and a FWHM of 10 in gray. The MOJAVE ∆PA distribution is in white. The error bars signify 1σ fluctuations. This distribution of ζ yields the greatest likelihood of matching the MOJAVE ∆PA data for Gaussian distributions. 77

Figure 3.11. The distribution of mean ∆PA in degrees generated using the MOJAVE SPG, 1000 populations of 135 sources, and a power law Γ distribution. ζ is generated ◦ ◦ using a Gaussian distribution, ζpeak =4 and a FWHM of 1 in gray. The MOJAVE ∆PA distribution is in white. The error bars signify 1σ fluctuations. This distribution of ζ yields the least likelihood of matching the MOJAVE ∆PA data for Gaussian distributions. 78

3.2.5 Simulations with a Power−law Distribution of ζ

Finally, I performed simulations using a power law distribution. Again, based on the most likely upper ζs in the uniform distribution simulations, I set the range of ζ from 1′′ to 10◦. I chose the lower limit of 1′′ because the power law distribution algorithm could not handle zero, however ζ had to be suitably low. The range of the index of the power law, α, is −2.5, −1.25, −0.5, 0.25, 0.5, 1.25 and 2.5. This range of indices allowed me to see if sharply peaked or flat distributions were more likely to be similar to the MOJAVE ∆PA distribution. Indeed, the χ2 value reaches a minimum between α −0.5 and 0.25 (See Figure 3.12), which means that flatter distributions of ζ are more likely to produce a MOJAVE−like ∆PA distribution. Upon constraining the ζ power law index to close to 0, I performed the ζ Monte Carlo simulations with a power law Γ distribution. These simulations were performed with power law indices of 0.5, 0.25, 0.1, −0.1, −0.25. A power law index of −0.1 (Figure 3.13) yielded the most MOJAVE−like ∆PA distribution (χ2 = 6.62, p= 0.578). This is virtually identical to the uniform distribution described in §3.2.3 with ◦ ζmax = 10.5 79

Figure 3.12. The distribution of mean ∆PA in degrees generated using the MOJAVE SPG, 1000 population of 135 sources, and a Gaussian Γ distribution. ζ is generated using a power law distribution, α = 0.25 in gray. The MOJAVE ∆PA distribution is in white. The error bars signify 1σ fluctuations. This distribution of ζ yields the greatest likelihood of matching the MOJAVE ∆PA data for power law distributions. 80

Figure 3.13. The distribution of mean ∆PA in degrees generated using the MOJAVE SPG, 1000 population of 135 sources, and a power law Γ distribution. ζ is generated using a power law distribution, α = −0.1 in gray. The MOJAVE ∆PA distribution is in white. The error bars signify 1σ fluctuations. This distribution of ζ yields the greatest likelihood of matching the MOJAVE ∆PA data for power law distributions. 81

3.3 Summary

In this chapter, I used the simple bend jet model introduced in Conway & Murphy [1993] to test whether jets with simple bends, under various distributions, can create a ∆PA distribution similar to the MOJAVE ∆PA distribution. This analysis improves upon previous analyzes for three reasons: The MOJAVE sample is larger (N=118 vs. N=44) than the previous sample and has more rigorous selection criteria, I allow θ to be selected on the basis of flux density to account for selection bias, and ζ is selected independent of θ. I have effectively ruled out certain scenarios at the 95% confidence level (See Tables 3.1 and 3.2). These include power law distributions with α> 1.25 or < −0.5, narrowly ◦ peaked Gaussian distributions and uniform distributions with ζmax > 30 . I also found that several scenarios yield statistically significant (>5% likelihood) matches to the MOJAVE data. These higher likelihood scenarios had some common features: they ◦ ◦ ◦ are all flatter distributions with a range from ζmin =0 to ζmax of 5 − 20 . By Occam’s razor, the simplest model here (uniform ζ distribution) gives the best fit, since for Gaussian ζ distributions the broader FWHM gives the best fit and for power law ζ distributions flattest distributions also give the best fit. Furthermore, more complicated helical models are not necessary to fit the MOJAVE ∆PA distri- bution. Therefore, the intrinsic ζ distribution is likely uniform with a range of 0◦ to ∼ 10◦. 82

Table 3.1. χ2 of ζ Monte Carlo Simulations with Gaussian Γ Distributions

Distribution parameter 1 parameter 2 χ2 Probability (1) (2) (3) (4) (5)

Uniform ζmax = 30 − 16.5 0.036

Uniform ζmax = 20 − 10.8 0.211

Uniform ζmax = 12.5 − 6.42 0.600

Uniform ζmax = 11.25 − 6.12 0.634

Uniform ζmax = 10 − 6.13 0.633

Uniform ζmax = 8.75 − 6.81 0.557

Uniform ζmax = 7.5 − 8.67 0.371

Uniform ζmax = 5 − 21.5 0.006

Uniform ζmax = 2.5 − 104 5.79e−19

Uniform ζmax = 1.25 − 481 1.05e−98 Power Law α = 2.5 − 19.8 0.011 Power Law α = 1.25 − 16.2 0.040 Power Law α = 0.5 − 10.1 0.257 Power Law α = 0.25 − 7.79 0.454 Power Law α = −0.5 − 19.5 0.013 Power Law α = −1.25 − 1153 1.17e−243 Power Law α = −2.5 − >1.50e3 <1e−250

Gaussian ζpeak = 10 FWHM = 10 19.0 0.015

Gaussian ζpeak = 10 FWHM = 7.5 22.5 0.004

Gaussian ζpeak = 10 FWHM = 5 25.4 0.001

Gaussian ζpeak = 10 FWHM = 2.5 26.1 0.001

Gaussian ζpeak = 10 FWHM = 1.25 26.3 9.27e−4

Gaussian ζpeak = 7.5 FWHM = 10 12.2 0.143

Gaussian ζpeak = 7.5 FWHM = 7.5 14.8 0.063

Gaussian ζpeak = 7.5 FWHM = 5 18.9 0.0152

Gaussian ζpeak = 7.5 FWHM = 2.5 21.7 0.005

Gaussian ζpeak = 7.5 FWHM = 1.25 22.4 0.0042

Gaussian ζpeak = 5 FWHM = 10 8.01 0.432

Gaussian ζpeak = 5 FWHM = 7.5 8.01 0.432

Gaussian ζpeak = 5 FWHM = 5 9.71 0.286

Gaussian ζpeak = 5 FWHM = 2.5 14.3 0.075

Gaussian ζpeak = 5 FWHM = 1.25 15.3 0.054

Gaussian ζpeak = 2.5 FWHM = 10 6.81 0.557

Gaussian ζpeak = 2.5 FWHM = 7.5 8.16 0.418

Gaussian ζpeak = 2.5 FWHM = 5 12.3 0.120 83

Table 3.1 (cont’d)

Distribution parameter 1 parameter 2 χ2 Probability (1) (2) (3) (4) (5)

Gaussian ζpeak = 2.5 FWHM = 2.5 18.9 0.016

Gaussian ζpeak = 2.5 FWHM = 1.25 19.5 0.012

Note. — Columns are as follows: (1) Distribution of ζ in the Monte Carlo simultions; (2) First parameter of the distribution: Uniform = maximum ζ (degrees), Power Law = index, Gaussian = peak (degrees); (3) Second parameter of Distribution: Uniform = none, Power Law = none, Gaussian = FWHM (degrees); (4) χ2 value (not reduced, 8 de- grees of freedom) with the MOJAVE ∆PAs as the measured values and the Monte Carlo ∆PAs as the expected values; (5) Probability that the MOJAVE ∆PAs are drawn from the Monte Carlo’s ∆PA distribution (N>0.05). 84

Table 3.2. χ2 of ζ Monte Carlo Simulations with Power Law Γ Distributions

Distribution parameter 1 parameter 2 χ2 Probability (1) (2) (3) (4) (5)

Unifrom ζmax = 20 − 11.5 0.174

Unifrom ζmax = 12 − 7.26 0.508

Unifrom ζmax = 11.25 − 6.86 0.552

Unifrom ζmax = 10.5 − 6.68 0.572

Unifrom ζmax = 10 − 6.53 0.588

Unifrom ζmax = 9.5 − 6.52 0.589

Unifrom ζmax = 9.25 − 6.58 0.583

Unifrom ζmax = 9 − 6.75 0.564

Unifrom ζmax = 8 − 7.38 0.496

Unifrom ζmax = 7 − 8.46 0.390

Unifrom ζmax = 1.25 − 433 1.80e-88 Power Law α = −0.25 − 8.00 0.434 Power Law α = −0.1 − 6.62 0.578 Power Law α = 0.1 − 7.10 0.526 Power Law α = 0.25 − 8.27 0.407 Power Law α = 0.5 − 10.7 0.218

Gaussian ζpeak = 4 FWHM = 1 13.0 0.110

Gaussian ζpeak = 4 FWHM = 2 8.52 0.384

Gaussian ζpeak = 4 FWHM = 4 6.90 0.547

Gaussian ζpeak = 6 FWHM = 4 9.92 0.270

Gaussian ζpeak = 6 FWHM = 6 10.6 0.224

Note. — Columns are as follows: (1) Distribution of ζ in the Monte Carlo simultions; (2) First parameter of the distribution: Uniform = maximum ζ (degrees), Power Law = index, Gaussian = peak (degrees); (3) Second parameter of Distribution: Uniform = none, Power Law = none, Gaussian = FWHM (degrees); (4) χ2 value (not reduced, 8 degrees of freedom) with the MOJAVE ∆PAs as the measured values and the Monte Carlo ∆PAs as the expected values; (5) Probability that the MOJAVE ∆PAs are drawn from the Monte Carlo’s ∆PA distribution (N>0.05). 85

4. γ−RAY EMISSION vs. EXTENDED RADIO EMISSION

In its first 11 months of operation, the LAT instrument on board the The Fermi Gamma−Ray Observatory has detected 85 of 135 active galactic nuclei (AGN) in the radio−flux−limited MOJAVE sample, and has established upper−limits on the remaining 50 sources. I compare LAT 1FGL median γ−ray luminosities and photon fluxes against VLA−A array 1.4 GHz radio luminosities and flux densities for 125 MOJAVE sources with reliable redshifts. Accurately modeling the intrinsic AGN γ−ray luminosity function (GLF) is an important step in modeling extra-galactic γ−ray background light (EBL). However, AGN γ−ray emission is highly beamed. In order to model the GLF, it is necessary to know the beaming parameters such as intrinsic jet speed and viewing angle in the population. In this chapter, I calculated Spearman ranks (r) with censored data, and find the γ−ray luminosity to be correlated with extended radio luminosity. The Spearman rank is an unparametrized test for correlation; it does not fit the data to a straight line. The γ−ray versus VLA−A core radio luminosity correlation is inconclusive in my analysis owing to the VLA−A data being single epoch and non−synchronous with the γ−ray data; both core luminosity and γ−ray luminosity are highly variable. The

possibility of a core luminosity (Lcore)− γ−ray luminosity (Lγ) relation is supported

by earlier findings between very long baseline interferometry luminosity (LV LBI )−Lγ and using median values of multi−epoch surveys [Pushkarev, Kovalev, & Lister, 2010].

Since the extended jet luminosity (Lext) is believed to be related to unbeamed jet power, γ−ray emission may be a common feature of the most powerful AGN jets. The correlation between radio jet luminosity and γ−ray luminosity is a critical aspect of models involving the EBL, since the EBL is likely composed of unresolved AGN. These findings support an intrinsic radio−γ−ray correlation and may improve methods for modeling the intrinsic gamma−ray luminosity of blazars, since scaling the radio 86

luminosity function is a typical starting point for calculating the γ−ray luminosity function of AGN.

4.1 γ−ray−Radio Emission Models

A common class of models for the high−energy emission from relativistic jets in ac- tive galactic nuclei (AGN) involves the up-scattering of photons via inverse−Compton processes. Both the synchrotron self Compton (SSC) and external Compton (EC) models predict a correlation between gamma−ray and radio emission [Sikora, Begel- man, & Rees, 1994, Dermer & Schlickeiser, 1993, Bloom & Marscher, 1993, Maraschi, Ghisellini & Celotti, 1992]. Based on light travel time arguments due to rapid vari- ability, these models suggest that the γ−ray emission originates within the optically thick VLBI core seen at cm−wavelengths. Recent VLBA observations support these models (e.g., Kovalev et al. 2009). Studying the kiloparsec−scale radio emission from beamed AGN jets has its ad- vantages. Since BL Lac jets reside in different host galaxy environments than those of flat spectrum radio quasars (FSRQs) [Kharb, Lister & Cooper, 2010], and the SSC and EC models are thought to dominate in different host environments, study- ing the correlation between extended radio emission and γ−ray emission is a way of evaluating unified models. In this chapter, I examine the relation between γ−ray emission and both core and extended radio structure at 1.4 GHz in the complete, radio−core−selected MOJAVE AGN sample [Lister et al., 2009].

4.2 Observations

In this chapter, I use the LAT 1FGL γ−ray data from Abdo et al. [2010]. The energy range of the data is 1 GeV to 100 GeV. A detection requires a test statistic (TS) greater than 25, which corresponds to approximately a 4−σ detection. Any photon flux with TS < 25 is treated as an upper limit. 87

The radio data consists of VLA observations of the MOJAVE sample. The sample’s selection criteria (§1.4) makes it ill suited for studying the correlation of gamma−ray and radio emission. Given the instrumental sensitivity and flux−limited sampling selection effects present, it is important when testing for correlations to fac- tor out the mutual redshift dependence of both the radio and γ−ray data. Although these data are not synchronous with the LAT γ−ray data, this is relevant only for the radio core luminosities, since the extended radio emission is not variable. I use the following formula for calculating γ−ray luminosities from the 1FGL fluxes [Ghisellini, Maraschi &Tavecchio, 2009]:

2 Sγ (ν1, ν2) Lγ =4πdL , (4.1) (1 + z)1−αγ where

αγhν1Fγ ν2 1−αγ Sγ (ν1, ν2)= ( ) − 1 , (4.2) 1 − αγ  ν1 

and αγ is the spectral index Ξ-1, where Ξ is the measured photon index from −2 −1 1 to 100 GeV, Sγ is the gamma−ray energy flux in erg cm s ,Fγ is the γ−ray −2 −1 photon flux in cm s , ν1 is the corresponding frequency for a 1 GeV photon, ν2 is

the corresponding frequency for a 100 GeV photon, h is Planck’s constant, dL is the luminosity distance in cm and z is the redshift. The γ−ray photon fluxes and indexes represent median values over the entire 1FGL LAT observation period (August 2008 to July 2009). The formula and parameters for calculating radio luminosities are discussed in §2.1.1 & §2.2.

4.3 Comparison with Previous Analysis

Abdo et al. [2009] compared the total VLA radio and γ−ray emission for 106 blazars in the LAT 3−month catalog and found a Spearman rank of r = 0.46 (p =

−6 2.5×10 ) for L8.4GHz to Lγ. My analysis improves on this initial study in several respects. First, Abdo et al. [2009] do not separate their radio emission into core and extended regions. The cores of blazars are highly beamed; thus the observed lumi- 88

nosity is much higher than the luminosity in the rest frame of the bulk flow of the jet. This makes it difficult to draw inferences to the underlying cause of the correla- tion, since intrinsically unrelated quantities can have, for example, a mutual beaming dependence. Indeed, the VLA observations of the MOJAVE sample were obtained at a lower frequency, 1.4 GHz and had a high dynamic range (typically 1:10,000 peak−to−r.m.s.; see Kharb, Lister & Cooper [2010], Cooper, Lister & Kochancyzk [2007]), as compared to the snapshot 8 GHz CLASS survey images used by Abdo et al. [2009]. This makes MOJAVE VLA radio data more amenable to distinguishing between core and extended regions, because the angular resolution is good (∼ 1.5′′) and the extended emission is brighter, given the steeper spectral index (∼ −0.7) of the extended region. Finally, their main selection criterion is that the high−confidence detections have 8.4 GHz flux densities above 100 mJy. The MOJAVE sample has a statistically complete population selected on the basis of radio core flux densities. The Abdo et al. [2009] radio data taken from the CLASS catalog is selected on the basis of spectral flatness. Since γ−ray emission comes from the core, it makes more sense to use a core selected population, and spectral flatness is more imprecise since sources with both bright lobes and bright cores can be omitted (e.g., 3C 207 & 3C 380).

4.4 Partial Correlation Analysis

The flux−density−limited selection criteria of MOJAVE creates a bias in the luminosity vs. redshift (z) correlation (Figs. 1−3). This affects the correlation

coefficients involving Lcore more than the those involving Lext, because the MOJAVE sample was selected on the basis of VLBA flux density and not single dish flux density. The mutual dependence on redshift was factored out using the following formula [Padovani, 1992]:

r12 − r13 × r23 r12,3 = (4.3) 2 2 1 − r13 × 1 − r23 p p 89

where the r values are correlation coefficients and the subscripts 1 and 2 represent

the parameters to be correlated (e.g., Lγ and Lext) and 3 represents the parameter that I wish to factor out (z).

−1 Figure 4.1. Plot of Redshift vs. log Lc (W Hz ) for the 125 MOJAVE AGN that have known redshifts. The VLBA flux density limit in sample selection criteria creates a

strong bias between redshift and Lc. Blue triangles are QSOs, red diamonds are BLOs and violet squares are galaxies. 90

Figure 4.2. Redshift vs. log Lγ (W). The down arrows are LAT upper−limits. I plot 125 MOJAVE AGN that have known redshifts. Since the sample population was selected on the basis of VLBA flux density, there is less bias between z and Lγ. Blue triangles are QSOs, red diamonds are BLOs and violet squares are galaxies. 91

−1 Figure 4.3. Redshift vs. log Lext (W Hz ). The down arrows are VLA upper−limits. I plot 125 MOJAVE AGN that have known redshifts. Since MOJAVE is selected on the bias of parsec scale flux density, there is less bias between redshift and Lext (kiloparsec scale radio luminosity). Blue triangles are QSOs, red diamonds are BLOs and violet squares are galaxies. 92

4.5 Jet Power and γ−ray Luminosity

Using a sample of radio galaxies from the B2 and 3C catalogs of mixed Fanaroff−Riley (FR) type, Giovannini et al. [1988] found a strong correlation between the total (core plus extended emission) integrated VLA (or WRST) luminosity and core luminosity. The cores of these radio galaxies are not appreciably beamed, since their jets lie at a much higher angle to the line of sight than blazars. Thus, the core luminosities of the Giovannini et al. [1988] sample are good indicators of intrinsic jet power. Since blazars are thought to be radio galaxy jets seen at small viewing angles [Urry & Padovani, 1995], this implies that the extended kiloparsec−scale emission of blazars would be a better indicator of intrinsic jet power than core emission, since the core emission is highly beamed. More recently, Cavagnolo et al. [2010] find, using X−ray

0.7 cavity analysis, that Pjet ∝ Pradio over 6 decades in Pradio, where Pjet,radio is jet and radio power respectively.

4.6 Monte Carlo Simulations of Lγ vs. MOJAVE Lγ

In order to test γ−ray−Lext correlations in the presence of beaming selection effects, I performed Monte−Carlo population simulations [Lister & Marscher, 1997]. By adopting an intrinsic evolving radio luminosity function, I modeled the core radio luminosity (Lcore) for the parent population [Cara & Lister, 2008]. Intrinsic properties such as redshift, intrinsic bulk Lorentz factor (Γ), and viewing angle were drawn from specified probability distributions using a random number generator (§3.2). I assumed randomly oriented two−sided jets in the parent population, and a parent Lorentz

−a factor distribution, N[Γ] ∝ Γ , for Γmin < Γ < Γmax, where Γmin = 3, Γmax = 50, and a= −1.5. The 135 brightest sources were selected out of a parent population of 2×109 sources, and the random number generator seed numbers were changed for each

27.9 −1 trial. The peak of the resulting Monte−Carlo Lcore distribution,∼ 10 W Hz , is consistent with the peak of the MOJAVE Lcore data. To model Lγ, I used the model from Dermer [1995], 93

2−αγ Lγ,SSC = K1Lr,iδ (4.4) and − 1 + cos θ 1 αγ L = K L δ3−2∗α (4.5) γ,EC 2 r,i  1+ β 

where Lγ,SSC is the synchrotron self Compton γ−ray luminosity in W, Lγ,EC is the

external Compton γ−ray luminosity in W, Lr,i is the intrinsic core radio luminosity −1 in W Hz , αγ is the γ−ray spectral index, δ is the Doppler factor, θ is the viewing angle, and β is the intrinsic jet speed. I assume that the intrinsic radio luminosity

is linearly proportional to Γ. K1 = 8.941 and K2 = 5.36 are linear proportionality constants chosen to fit the data. The range of γ−ray SSC luminosities given by the Monte−Carlo simulations are similar to those of the MOJAVE sample, ∼ 1036.5 to ∼ 1041.5 W. The EC luminosities ranged from ∼ 1034.5 to ∼ 1043 W, overlapping the MOJAVE γ−ray luminosities, but containing a slightly wider range of luminosities. Both the SSC and EC γ−ray emission are proportional to isotropic radiation

energy density (uiso) in the Dermer [1995] model. Above, I assume that intrinsic

radio luminosity is also proportional to uiso. Therefore, I substitute intrinsic radio luminosity multiplied by a constant for the isotropic energy density.

4.7 Calculating Correlations with Censored Data

Due to the large number of upper limits in the γ fluxes, the ASURV1 survival anal- ysis package was used in calculating the Spearman ranks for all correlations (Table 1). The 125 blazars in the MOJAVE survey with reliable redshift data were included in the luminosity correlations. All but 2 blazars were included in the flux−flux corre- lations. Blazars 0333+321 and 1739+522 did not have a LAT object associated with them. The correlation between the kiloparsec−scale radio luminosity and gamma−ray luminosity (Fig. 4.4) and flux (Fig. 4.5) supports the claim that more powerful radio jets have stronger gamma−ray emission. In fact, since the SSC and EC fluxes are

1Rev 1.2 [LaValley, Isobe & Feigelson, 1992], using methods presented in [Feigelson & Nelson, 1985] 94

proportional to δ2−α and δ3−2α respectively, it is possible to test these mechanisms

against Lext data using Doppler factors estimated from variability (δvar, e.g., Hovatta

et al. 2009), brightness temperature (δT e.g. Homan et al. 2009) or equipartition (e.g. Kuchibholta et al. 2010). I find that, for the 104 MOJAVE sources that have

both Sγ and δT , the partial correlation coefficient for Lγ vs. Lext (excluding mutual z correlation) increases to r= 0.444 (p < 0.0001, see Table 4.2) using the SSC model.

For the EC model, the partial correlation coefficient for Lγ vs. Lext (excluding mutual z correlation) increases to r= 0.405 (p < 0.0001, see Table 4.3). In this dissertation, any MOJAVE AGN not in the 1FGL LAT catalog is an upper limit, except the two objects mentioned above. The upper−limits were calculated by Kadler & B¨ock [2010]. To calculate the upper−limits, they added a source at the corresponding position to the model sources in the region of interest, selecting surrounding sources from the 1FGL catalog. When the significance of the additional source was low (TS< 25), they obtained the 2σ upper limit and looked for 2∆ log P = 4 as described in §4.4 of Abdo et al. [2010]. A Bayesian method was used for very low TS (< 1) in order not to underestimate the flux.

For Sext, upper limits are defined as Stotal−Score < 3∗r.m.s.. The correlation

coefficients, r, were calculated using ASURV to account for 39 upper limits in Sγ

and 5 upper limits in Sext. Figures 4.6 and 4.7 show Lcvs. Lγ and Sc vs. Sγ ,

respectively. The Sc outlier in Figure 4.7 is unidentified AGN 0446+112, which has a very quasar−like one−sided jet morphology. Correlation between the highly variable radio emission and highly variable γ−ray emission is inconclusive, however these data were taken at different epochs. A conclusive result would require taking near simultaneous radio and γ−ray data. 95

Table 4.1. ASURV Spearman Ranks for γ−ray to Radio Emission

Param 1 Param 2 Spearman Rank Probability

(1) (2) (3) (4)

Lγ Lext 0.536 <0.0001

Lγ z 0.636 <0.0001

Lext z 0.502 <0.0001

Lext δT 0.147 0.134

Lγ Lcore 0.650 <0.0001

Lcore z 0.899 <0.0001

Lcore Lext 0.603 <0.0001

Lcore δT 0.312 0.0014

Sγ Sext 0.269 0.0020

Sγ Score 0.127 0.146

Sγ δvar 0.642 <0.0001

Lγ Lext−z 0.325 0.0002

Lγ Lcore−z 0.232 0.0094

Note. — Columns are as follows: (1) First measured pa- rameter; (2) Second measured parameter; (3) Spearman rank calculated by ASURV using upper limits in both LAT and MOJAVE data; (4) Probability that correlation is co- incidence. Note: The last two rows are the partial correla- tion coefficients excluding mutual correlation on redshift using method in Padovani [1992]. 96

Table 4.2. ASURV Spearman Ranks for γ−ray Emission, de−Boosted by δ2−α, to Radio Emission

Param 1 Param 2 Spearman Rank Probability

(1) (2) (3) (4)

Lγ Lext 0.643 <0.0001

Lγ z 0.705 <0.0001

Lext z 0.535 <0.0001

Lγ Lext−z 0.444 <0.0001

Note. — Columns are as follows: (1) First measured parameter; (2) Second measured parameter; (3) Spearman rank calculated by ASURV using upper limits in both LAT and MOJAVE data; (4) Probability that correlation is coincidence. Note: The last row is the partial correlation coefficient excluding mutual correlation on redshift using method in Padovani [1992]. 97

Table 4.3. ASURV Spearman Ranks for γ−ray Emission, de−Boosted by δ3−2α, to Radio Emission

Param 1 Param 2 Spearman Rank Probability

(1) (2) (3) (4)

Lγ Lext 0.610 <0.0001

Lγ z 0.658 <0.0001

Lext z 0.535 <0.0001

Lγ Lext−z 0.405 <0.0001

Note. — Columns are as follows: (1) First measured parameter; (2) Second measured parameter; (3) Spearman rank calculated by ASURV using upper limits in both LAT and MOJAVE data; (4) Probability that correlation is coincidence. Note: The last row is the partial correlation coefficient excluding mutual correlation on redshift using method in Padovani [1992]. 98

Figure 4.4. Extended VLA scale luminosity (W Hz−1) vs. γ−ray luminosity (W). The down arrows are LAT upper−limits and left arrows are VLA upper limits. I used 125 MOJAVE AGN that have known redshifts. Since the sample population was selected on the basis of VLBA flux density, there is less bias between z and Lγ . Blue triangles are QSOs, red diamonds are BLOs and violet squares are galaxies. 99

Figure 4.5. Extended VLA scale flux density (Jy) vs. γ−ray flux (10−8 photons cm−2 s−1). The down arrows are LAT upper−limits and left arrows are VLA upper limits. I used 133 MOJAVE AGN that have Fermi LAT associated sources. Blue triangles are QSOs and unidentified AGN, red diamonds are BLOs and violet squares are galaxies. 100

Figure 4.6. VLA core Luminosity (W Hz−1) vs. log Lγ−ray luminosity (W). The down arrows are LAT upper−limits and left arrows are VLA upper limits. I used 125 MOJAVE AGN that have known redshifts. Since the sample population was selected on the basis of VLBA flux density, there is less bias between z and Lγ . Blue triangles are QSOs, red diamonds are BLOs and violet squares are galaxies. 101

Figure 4.7. VLA core flux density (Jy) vs. γ−ray flux (10−8 photons cm−2 s−1). The down arrows are LAT upper−limits. I used 133 MOJAVE AGN that have Fermi LAT associated sources. Blue triangles are QSOs, red diamonds are BLOs and violet squares are galaxies. 102

4.8 Core γ−ray Emission vs. Lobe γ−ray Emission

Until recently, the observational focus of the relationship between radio and γ−rays in AGN has been on the parsec scale. The Large Area Telescope (LAT) aboard the The Fermi Gamma−Ray Observatory recently detected gamma−ray emission from the radio lobes of Centaurus A [Cheung, 2009]. This emission comes from cosmic infrared/optical background photons being up−scattered by the relativistic electrons in the lobes [Georganopoulos et al., 2008]. This type of emission is not likely the cause of radio−γ−ray correlations discussed in this chapter, because this emission mechanism is too faint and diffuse to be detected at high luminosity distances. There are only 9 sources in the MOJAVE sample with z<0.1. Furthermore, this emission is non−variable, whereas blazar γ−ray emission is highly variable. This high vari- ability suggests a small emission region (due to light travel time arguments) which rules out the lobes as a large component. I have used the 11−month LAT median values of the highly variable component of the γ−ray emission for this analysis. Since most MOJAVE blazars are at greater luminosity distances than Centaurus A and this emission is highly variable, this faint, diffuse, and non−variable emission is unlikely to significantly influence this analysis.

4.9 Results

Using both 1FLG LAT γ−ray photon fluxes and VLA−A array 1.4 GHz fluxes, I calculated Spearman ranks with ASURV to flux and luminosity measurements us- ing 125 sources in the MOJAVE survey. Luminosity−redshift correlations were also measured so they could be factored out of the luminosity−luminosity correlations. I excluded eight sources with no or poor redshift data from the luminosity Spearman rank calculations, but all 133 MOJAVE−I sources with Fermi−LAT associations were used for the flux−flux Spearman rank calculations. These Spearman ranks are

in Table 1. Upper limits in both Sγ and Sext were included in the Spearman rank calculations. 103

The results of the statistical tests were as follows:

• Lγ and Lext are strongly correlated. Since Lext is correlated with jet power, it is likely that this is indicative of a mutual dependence of intrinsic γ−ray and extended radio emission on jet power. Partial correlation coefficients increase if

Lγ is de−boosted by either the SSC or EC models.

• No convincing Lγ and Lcore correlation is present. Based on previous findings that use median VLBA flux densities [Kovalev et al., 2009, Pushkarev, Ko- valev, & Lister, 2010], a correlation may be present. However, considering that the MOJAVE selection criteria is based on high−frequency VLBA flux density

which creates a strong correlation between Lc and z and favors AGN that have highly variable cores, the fact that these VLA data are single epoch and not taken simultaneously with the LAT data is the likely culprit for not seeing the

Lc − γ−ray correlation after redshift bias was factored out.

• The recent discovery of extended γ−ray emission from Centaurus A indicates

that this could also contribute to the Lγ−Lext correlation. However, given that this emission is diffuse and most MOJAVE sources are at large luminosity distances; it is unlikely to greatly affect our findings.

In addition, I performed Monte−Carlo simulations to look for Lγ−Lradio correla- tions in the presence of beaming selection effects. By making the assumption that both radio and γ−ray fluxes are proportional to isotropic rest−frame radiation en- ergy density, I generated AGN intrinsic luminosities and then beamed them using

SSC and EC models. The resulting simulated Lγ ’s are consistent with the 1FGL Lγ distribution. My findings support the correlation between radio jet luminosity and γ−ray lumi- nosity that is a critical aspect of models involving γ−ray extra-galactic background light (EBL). This may improve methods for modeling the intrinsic γ−ray luminosity of blazars, since scaling the radio luminosity function is a typical starting point for 104

calculating the γ−ray luminosity function of AGN. Furthermore, some models pre- dict that the γ−ray flux in AGN depends on external properties such as the external soft photon field impinging on the jet [Zbyszewska, 1994]. However, the Lγ−Lext correlation suggests that the overall energetics of the jet are closely tied to electron energy distribution and/or magnetic field strength. Considering that Kharb, Lister

& Cooper [2010] find that Lext and βapp are correlated in the MOJAVE−I sample (using the partial correlation analysis, Eq. 4.3, to factor out redshift) intrinsic jet speed may also be important for the Lγ −Lradio correlation. 105

5. SUMMARY

Since not much is known about the behavior of blazar jets on the kiloparsec scale (because few have bright extended emission to study), my primary goal of this dis- sertation is to begin to close that gap in our knowledge. The MOJAVE sample population is amenable to this goal, because the selection criteria favors blazars (127 out of the 135 AGN in the sample) whereas the selection criteria for other large AGN surveys (e.g. Cassaro et al. [1999], Condon et al. [1996], Conway & Murphy [1993]) have not been targeted specifically toward blazars. Furthermore, since MOJAVE is a long−term, multi−epoch survey, many of the parsec scale measurements necessary to make my analysis were already obtained (e.g., parsec scale images, βapp, δT ). To complete the kiloparsec data for this dissertation, it was necessary to obtain deep VLA images (i.e., images that have a long integration time on source) to image the faint extended emission. Although some of these images were available in the NRAO data archives or published in previous studies (See Table 2.1), many kilo- parsec scale images for MOJAVE blazars were made in snapshot mode and lacked the dynamic range needed to image the faint extended emission. With these deep VLA images and those taken on the parsec scales we can make measurements (e.g.,

Lext, ∆PA) and test models (i.e., Lradio vs. Lγ, simple jet bends) against numerical simulations.

5.1 Thesis Goals and Results

The MOJAVE kiloparsec−scale blazar jet survey was designed to look for corre- lations between properties measured on the parsec scale (i.e., VLBA data) vs. prop- erties measured on the kiloparsec scale (i.e., VLA data). I also collected previously published single dish data and NVSS data (See Table 2.3), with the aim of examining 106

if total VLA flux density agreed with single dish flux density. The argument that

Lext can be used as a proxy to jet power for a highly Doppler Boosted population depends heavily on imaging the maximum possible amount of extended emission. I find, in Figure 2.5, that VLA−A vs. VLA−D has a slope close to one. This supports the claim that 1.4 GHz VLA−A images are the best compromise for detecting faint emission while maintaining an acceptable level of angular resolution (∼ 1.5′′).

5.1.1 Image Catalog and Sample Statistics

Appendix A includes VLA−A images for every AGN in the MOJAVE−I sam- ple, and were collected by Cooper, Lister & Kochancyzk [2007] and Kharb, Lister & Cooper [2010]. The luminosity distributions measured from these images are similar to luminosity distributions from previous flux density limited AGN samples [An- tonucci & Ulvestad, 1985, Murphy, Browne & Perley, 1993]. The redshift distribution (collected from the NASA Extragalactic Database) is similar to that of Antonucci &

Ulvestad [1985], Murphy, Browne & Perley [1993]. The Rc distribution is similar to that of Murphy, Browne & Perley [1993]. These images were also used by Kharb, Lister & Cooper [2010] to find that six of

22 BLOs have FRII radio powers (log Lext > 26 at 1.4 GHz). Additionally, four of these BLOs have quasar−like hot spots (0235+164, 0716+714, 0808+019, 2131−021). Even though Haywood et al. [2007] state that out of their candidates for FR1 QSOs, only one has conclusive FR1−type double lobe morphology, the presence of FRII BL Lacs presents a challenge to the widely accepted Unification Scheme [Urry & Padovani, 1995].

Additionally, Kharb, Lister & Cooper [2010] find that Lext is correlated with βapp,

and forms an envelope similar to the one formed by LV LBA and βapp. Considering that extended emission is correlated to total jet power (e.g. Giovannini et al. 1988), this supports the upper envelope between maximum jet speed and parsec−scale luminosity observed by Cohen et al. [2007]. This provides a constraint for those numerical models 107 that take full MHD and GR effects in to account (e.g. Kato, Mineshige & Shibata 2004).

5.1.2 Jet Misalignment Angles

I investigate intrinsic bending between pc and Kpc−scales by using Monte Carlo simulations that generate ∆PA and comparing them against the measured ∆PA dis- tribution. These Monte Carlo simulations use the most up to date sample statistics to generate an artificial population selected using the MOJAVE selection criteria. Unlike previous surveys [Conway & Murphy, 1993, Appl, Sol & Vicenta, 1996], I use viewing angles that are selected based on MOJAVE selection criteria and are inde- pendent from the bending parameters of the jet. I also use measured ∆PA collected from a statistically complete sample with rigorous selection criteria. I find that the most likely distribution for the intrinsic bending angle (ζ) is a uniform distribution with a range of 0◦− ∼ 10◦. The maximum bend angle is unlikely to be < 5◦ or > 30◦. Furthermore power law distributions with an α> 1.25 or < −0.5 are ruled out at the 95% confidence level. Narrowly peaked Gaussian distributions are likewise excluded. A complete list of the parameter space tested in this dissertation in available in Tables 3.1 and 3.2. Furthermore, Kharb, Lister & Cooper [2010] did not see a prominent secondary peak at 90◦ like Pearson & Readhead [1988] and Conway & Murphy [1993], and hence, complicated helical bend models are not necessary to fit the data. A simple bend geometry suggests that jet misalignment is due to a MHD in- teraction with the ISM in the host galaxy, such as Kelvin−Helmholtz instabilities. This is supported by the finding of Kharb, Lister & Cooper [2010], who find that

∆PA is correlated with an environmental indicator, Lext/Mabs, where Mabs is abso- lute optical magnitude. They reason that since optical luminosity (parametrized here as Mabs) is closely related to AGN power and kiloparsec scale radio emission is af- fected by kiloparsec scale environment, Lext/Mabs serves as a parameter for kiloparsec 108

scale environmental interactions. Therefore ∆PA is correlated with kiloparsec scale environmental interactions. Using Occam’s razor, it is unlikely that the jet misalignment observed in the MO- JAVE sample is caused by jet precession or a swinging jet nozzles. These processes require a suitably large perturbation of the rotation of the central engine, which is be-

7−9 lieved to have mass on order of 10 M⊙. A likely mechanism for a swinging jet nozzle or jet precession is a binary super−massive black hole. The binary super−massive black hole model is believed to be behind periodic outbursts in MOJAVE BL Lac 0851+202 (OJ 287), which is also a FRII BL Lac candidate. However, evidence of binary super−massive black holes is lacking for the rest of the MOJAVE sample. Since every AGN does have a host galaxy, which contains an ISM which the jet will interact with as it transitions to kiloparsec scales, MHD interactions are the simpler explanation and is supported by the simple bend geometry.

5.1.3 Radio−γ−ray Correlation

Finally, I calculated Spearman ranks with ASURV to flux and luminosity mea- surements using both 1FLG LAT γ−ray photon fluxes and VLA−A array 1.4 GHz fluxes of 125 sources in the MOJAVE survey. Partial correlation factors were used to remove redshift bias from luminosity−luminosity correlations. I excluded eight sources with no or poor redshift data from the luminosity Spearman rank calcula- tions, but all 133 MOJAVE−I sources with Fermi−LAT associations were used for the flux−flux Spearman rank calculations. These Spearman ranks are in Table 4.1.

Upper limits in both Sγ and Sext were included in the Spearman rank calculations.

I find that Lγ and Lext are strongly correlated. Since Lext is correlated with jet power, it is likely that this is indicative of a mutual dependence of intrinsic γ−ray and extended radio emission on jet power. Partial correlation coefficients increase if

Lγ is de−boosted by either the SSC or EC models. Furthermore, no convincing Lγ and Lcore correlation is present. Based on previous findings that use median VLBA 109

flux densities [Kovalev et al., 2009, Pushkarev, Kovalev, & Lister, 2010], a correlation may be present. However, considering that VLA data are single epoch and not taken

simultaneously with the LAT data is the likely culprit for not seeing the Lc − γ−ray correlation after redshift bias was factored out. It is important to note that, although a recent discovery of extended γ−ray emission from Centaurus A could suggest a contribution to the Lγ −Lext correlation, this emission is diffuse and most MOJAVE sources are at large luminosity distances. It is unlikely to greatly affect our findings.

In addition, I performed Monte−Carlo simulations to test Lγ−Lradio correlations in the presence of beaming selection effects. By making the assumption that both radio and γ−ray emissions are proportional to isotropic rest−frame radiation energy density, I generated AGN intrinsic luminosities and then beamed them using both an SSC and EC models. The resulting simulated Lγ ’s are consistent with the 1FGL

Lγ’s. My findings support the correlation between radio jet luminosity and γ−ray lumi- nosity that is a critical aspect of models involving γ−ray extra-galactic background light (EBL). This may improve methods for modeling the intrinsic γ−ray luminosity of blazars, since scaling the radio luminosity function is a typical starting point for calculating the γ−ray luminosity function of AGN. Furthermore, some models pre- dict that the γ−ray flux in AGN depend on external properties such as the external

soft photon field impinging on the jet [Zbyszewska, 1994]. However, the Lγ−Lext correlation suggests that the overall energetics of the jet are closely tied to electron energy distribution and/or magnetic field strength. Considering that Kharb, Lister

& Cooper [2010] find that Lext and βapp are correlated in the MOJAVE−I sample (using the partial correlation analysis, Eq. 4.3, to factor out redshift) intrinsic jet

speed may also be important for the Lγ −Lradio correlation. 110

5.2 Future Work

The nature of science is that, as questions are answered, new questions arise. For the Kiloparsec−Scale Morphology Survey, I will discuss below three studies that can be done in the short term as a follow−up to this dissertation.

5.2.1 eMERLIN Intermediate Scale Jet Survey

Kharb, Lister & Cooper [2010] defined the Kpc−scale PA from the core to the brightest hot spot, whereas previous surveys have defined it as from the core to the hot spot on the same side as the pc jet. I am curious if intermediate scale images will support the Kharb, Lister & Cooper [2010] definition. eMERLIN is a VLBI radio telescope that extends across central England and has ∼ 150 mas resolution in the L−band. This resolution generates Hpc scale images. My next goal is to write a proposal to create eMERLIN images for all MOJAVE AGN with a DeltaPA > 160◦. Imaging jets on this scale will give evidence if the assumption made in Kharb, Lister & Cooper [2010] is valid. Furthermore, Gabuzda et al. [2010] are also obtaining 20 cm VLBI data on the whole sample, which will extend the pc jet PA somewhat further down the jet. I can expand the eMERLIN image survey to the entire MOJAVE sample to complement the Gabuzda et al. [2010] survey and the combined surveys may be used to create a more realistic three dimensional model of the jet, having sampled the jets at several different distance scales.

5.2.2 Expanding the Search for FRII BL Lacs

The Lext−Lγ correlations can be used to test if BL Lacs and FSRQs have different statistics, as a way of testing the Urry & Padovani [1995] Unified Scheme. However, 22 BL Lacs (18 with a usable redshift) are not enough to draw a statistically significant inference. The BL Lac population would have to be increased to at least 30 (with 111

a reliable redshift measurement) or more and in a way that is statistically complete with respect to selection criteria. I purpose to create a larger population of γ−bright BL Lacs to study radio properties which could also be used to look for more FR-II-like BL Lacs. I also intend for the imaging of the BL Lacs to be carried out in part by under- graduate students at Bard High School Early College (BHSEC), where I was recently hired as an assistant professor. This would be a great benefit to MOJAVE in terms of outreach, and BHSEC in terms of opportunities for the students.

5.2.3 Radio Morphology Survey Based on Fermi Selection Criteria

I also purpose to create a blazar morphology survey, similar to this dissertation, but based on the Fermi/LAT detected blazars instead of radio selected blazars. Since the sample size of the 1FGL catalog is so high, I intend to bin the images in terms of redshift with the intention of combining the data when it is all collected into one large catalog of blazar images and related data, sample statistics and analysis. APPENDIX 112 113

A. 1.4 GHZ VLA IMAGES OF THE MOJAVE SAMPLE POPULATION

This Appendix contains VLA−A 1.4 GHz images for the 135 AGN of the MOJAVE Sample Population. Chapter 2, table 1, contains information regarding the source of the images, the settings of the VLA when the image was taken and the method for data reduction. Please note that many times the archival images of a particular data file may not have been published previously. In the case when a previous image exists the paper referenced refers to the published image. Chapter 2, table 2, contains the data derived from these images, such as flux density and restoring beam parameters. In the image captions ∆PA [Kharb, Lister & Cooper, 2010] is defined as low angle for ∆PA< 60◦, near orthogonal for 60◦ to 120◦ and wide angle for > 120◦. 114

0003-066

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24 00 00 06 15.5 15.0 14.5 14.0 13.5 13.0 12.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of BL Lac Object 0003-066 with one sided jet morphology and a nearly orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007]. 115

0007+106

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Figure A.1. 1.4 GHz VLA−A image of Radio Galaxy 0007+106 with two sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 116

PLot file version 2 created 27-JUN-2008 18:55:12 0016+731 IPOL 1400.000 MHZ 0016+731.ICL001.1 73 28 00

27 45

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00 19 52 50 48 46 44 42 40 RIGHT ASCENSION (J2000) Peak flux = 4.0001E-01 JY/BEAM Levs = 4.000E-03 * (-0.320, 0.320, 0.640, 1.280, 2.560, 5.120, 10.24, 20.48, 40.96, 81.92)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0016+731 with core morphology and wide angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 117

0059+581 58 24 25

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Figure A.1. 1.4 GHz VLA−A image of FSRQ 0059+581 with one sided halo mor- phology. ∆PA is poorly defined. taken from Cooper, Lister & Kochancyzk [2007], continued. 118

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Figure A.1. 1.4 GHz VLA−A image of FSRQ 0106+013 with two sided jet morphology and near orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 119

0109+224

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30

25 01 12 06.5 06.0 05.5 05.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of BL Lac 0109+224 with core morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 120

0119+115 11 50 15

10

05

00

49 55

50

45

DECLINATION (J2000) 40

35

30

01 21 43.0 42.5 42.0 41.5 41.0 40.5 40.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0119+115 with one sided halo morphol- ogy and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 121

0133+476

47 51 40

35

30

25 DECLINATION (J2000)

20

15 01 37 00.0 36 59.5 59.0 58.5 58.0 57.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0133+476 with one sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 122

0202+149 15 14 30

25

20

15

10

05 DECLINATION (J2000)

00

13 55

02 04 51.5 51.0 50.5 50.0 49.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0202+149 with core morphology (Sext is above 3*r.m.s) and poorly defined ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 123

0202+319

32 13 15

00

12 45

30

15 DECLINATION (J2000) 00

11 45

30 02 05 09 08 07 06 05 04 03 02 01 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0202+319 with one sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 124

0212+735

73 49 50

45

40

35

30

DECLINATION (J2000) 25

20

15

02 17 35 34 33 32 31 30 29 28 27 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0212+735 with one sided jet morphology and wide angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 125

0215+015

01 45 05

00

44 55

50

45 DECLINATION (J2000) 40

35

30 02 17 50.0 49.5 49.0 48.5 48.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 02015+015 with two sided halo morphol- ogy and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 126

0224+671 67 21 30

15

00 DECLINATION (J2000)

20 45

02 28 54 52 50 48 46 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0224+671 with two sided jet morphology and nearly 180◦ ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 127

0234+285

28 48 25

20

15

10

05 DECLINATION (J2000) 00

47 55

50 02 37 53.5 53.0 52.5 52.0 51.5 51.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0234+285 with one sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 128

0235+164

16 37 20

15

10

05

00

36 55

DECLINATION (J2000) 50

45

40

35 02 38 40.5 40.0 39.5 39.0 38.5 38.0 37.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of BL Lac 0235+064 with FRII radio power

(log Lext > 26), one sided halo morphology, low angle ∆PA and hot spots, taken from Cooper, Lister & Kochancyzk [2007], continued. 129

0238-084

-08 15 00

05

10

15

20

25

DECLINATION (J2000) 30

35

40

45 02 41 06.0 05.5 05.0 04.5 04.0 03.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of radio galaxy 0238−064 with two sided jet morphology and wide angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 130

0300+470 47 16 35

30

25

20

15

10 DECLINATION (J2000)

05

00

03 03 37.0 36.5 36.0 35.5 35.0 34.5 34.0 33.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of BL Lac 0300+740 with one sided halo morphol- ogy and near orthogonal, taken from Cooper, Lister & Kochancyzk [2007], continued. 131

0333+321

32 18 40

35

30

25 DECLINATION (J2000)

20

15 03 36 31.0 30.5 30.0 29.5 29.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0333+321 with one sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 132

0336-019

-01 46 25

30

35

40 DECLINATION (J2000)

45

50 03 39 31.8 31.6 31.4 31.2 31.0 30.8 30.6 30.4 30.2 30.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0336−019 with one sided jet morphology and near orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 133

0403-132 -13 07 55

08 00

05

10

15

20 DECLINATION (J2000)

25

30

04 05 35.0 34.5 34.0 33.5 33.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0403−132 with one sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 134

0420-014

-01 20 15

30

DECLINATION (J2000) 45

21 00

04 23 17.5 17.0 16.5 16.0 15.5 15.0 14.5 14.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0420−014 with two sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 135

0422+004 00 36 30

25

20

15

10

05

00 DECLINATION (J2000) 35 55

50

45

04 24 48.5 48.0 47.5 47.0 46.5 46.0 45.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of BL Lac 0422+004 with one sided jet mor- phology and a wide angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 136

0446+112

11 21 45

30 DECLINATION (J2000) 15

00 04 49 09.5 09.0 08.5 08.0 07.5 07.0 06.5 06.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of unclassified object 0446+112 with one sided jet morphology and a near orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 137

0458-020 -01 59 00

05

10

15

DECLINATION (J2000) 20

25

05 01 13.8 13.6 13.4 13.2 13.0 12.8 12.6 12.4 12.2 12.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0458−020 with one sided halo morphol- ogy and a near orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 138

0528+134

13 32 10

05

00

31 55

50 DECLINATION (J2000) 45

40

35 05 30 57.5 57.0 56.5 56.0 55.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0528+134 with two sided jet morphol- ogy and a near orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 139

0529+075

07 33 15

00

32 45

30 DECLINATION (J2000)

15

05 32 41 40 39 38 37 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0529+075 with one sided jet morphology and a wide angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 140

0529+483

48 23 10

05

00

22 55

50

DECLINATION (J2000) 45

40

35

05 33 17.5 17.0 16.5 16.0 15.5 15.0 14.5 14.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0529+483 with one sided halo morphol- ogy and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 141

0552+398

39 49 00

48 55

50

45 DECLINATION (J2000)

40

35 05 55 32.0 31.5 31.0 30.5 30.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0552+398 with core morphology and undefined ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 142

0605-085

-08 34 40

45

50

55 DECLINATION (J2000)

35 00

05 06 08 00.6 00.4 00.2 00.0 59.6 59.4 59.2 59.0 58.8 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0605−085 with one sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 143

0607-157

-15 42 25

30

35

40

45 DECLINATION (J2000) 50

55

43 00 06 09 42.0 41.5 41.0 40.5 40.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0607−157 with core morphology and undefined ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 144

0642+449 44 51 30

25

20

15

DECLINATION (J2000) 10

05

06 46 33.0 32.5 32.0 31.5 31.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0642+449 with core morphology and undefined ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 145

0648-165 -16 37 25

30

35

40

45 DECLINATION (J2000)

50

06 50 25.5 25.0 24.5 24.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of unclassified object 0648−165 with one sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 146

0716+714 71 21 00

20 55

50

45

40

35

30 DECLINATION (J2000) 25

20

15

07 21 58 57 56 55 54 53 52 51 50 49 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of BL Lac 0716+714 with two sided halo mor-

phology, FRII radio jet power (log Lext > 26), hot spots and near orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 147

0836+710

70 53 50

48

46

44

42

40

DECLINATION (J2000) 38

36

34

32 08 41 26.0 25.5 25.0 24.5 24.0 23.5 23.0 22.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 0836+710 with one sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 148

PLot file version 1 created 11-OCT-2010 15:39:50 1150+812 IPOL 1400.000 MHZ 1150+812.ICLN.1 80 59 00

58 45

30 DECLINATION (J2000)

15

00

11 53 25 20 15 10 05 00 RIGHT ASCENSION (J2000) Peak flux = 1.8735E+00 JY/BEAM Levs = 1.873E-02 * (-0.100, 0.100, 0.200, 0.400, 0.800, 1.600, 3.200, 6.400, 12.80, 25.60, 51.20)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 1150+812 with one sided jet morphology and near orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 149

1222+216 21 23 15

00

22 45 DECLINATION (J2000)

30

12 24 56.5 56.0 55.5 55.0 54.5 54.0 53.5 53.0 52.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 1222+216 with two sided halo mor- phology and near orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 150

1308+326

32 21 00

20 55

50

45

40

DECLINATION (J2000) 35

30

25 13 10 30.0 29.5 29.0 28.5 28.0 27.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 1308+326 with two sided halo mor- phology and near orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 151

1324+224

22 11 05

00

10 55

50

45 DECLINATION (J2000) 40

35

30 13 27 02.0 01.5 01.0 00.5 00.0 26 59.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 1324+224 with core morphology and near orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 152

1417+385

38 22 10

05

00

21 55

50

45

40 DECLINATION (J2000)

35

30

25 14 19 48.5 48.0 47.5 47.0 46.5 46.0 45.5 45.0 44.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 1417+385 with one sided halo morphol- ogy and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 153

PLot file version 1 created 11-OCT-2010 16:00:14 1458+718 IPOL 1400.000 MHZ 1458+718.ICLN.2

71 40 45

30

15 DECLINATION (J2000)

00

14 59 14 12 10 08 06 04 02 RIGHT ASCENSION (J2000) Peak flux = 5.7528E+00 JY/BEAM Levs = 5.753E-02 * (-0.040, 0.040, 0.050, 0.100, 0.200, 0.400, 0.800, 1.600, 3.200, 6.400, 12.80, 25.60, 51.20)

Figure A.1. 1.4 GHz VLA−A image of Compact Steep Spectrum Quasar 1458+718 with two sided jet morphology and wide angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 154

1502+106

10 29 50

45

40

35 DECLINATION (J2000)

30

25 15 04 25.8 25.6 25.4 25.2 25.0 24.8 24.6 24.4 24.2 24.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 1538+149 with one sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 155

1538+149 14 48 00

47 55

50

45

DECLINATION (J2000) 40

35

15 40 50.4 50.2 50.0 49.8 49.6 49.4 49.2 49.0 48.8 48.6 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of BL Lac 1538+149 with one sided halo mor-

phology, FRII radio power (Lext > 26) and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 156

1803+784

78 28 45

30

15

00

DECLINATION (J2000) 27 45

30

15 18 01 00 00 55 50 45 40 35 30 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of BL Lac 1803+784 with one sided jet morphol-

ogy, FRI/II radio power (24.5 < Lext < 26), hot spots and near orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 157

1849+670

67 06 00

05 45

DECLINATION (J2000) 30

15

18 49 20 18 16 14 12 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 1849+670 with two sided jet morphology and near orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 158

1928+738

73 58 30

15

00

DECLINATION (J2000) 57 45

30

19 27 58 56 54 52 50 48 46 44 42 40 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 1928+738 with two sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 159

2145+067

06 57 50

45

40

35 DECLINATION (J2000)

30

25

21 48 06.4 06.2 06.0 05.8 05.6 05.4 05.2 05.0 04.8 04.6 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2145+067 with one sided jet morphology and wide angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 160

2155-152

-15 00 45

01 00

15 DECLINATION (J2000)

30

21 58 08.0 07.5 07.0 06.5 06.0 05.5 05.0 04.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2155−152 with two sided halo morphol- ogy and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 161

2200+420

42 16 55

50

45

40

35 DECLINATION (J2000) 30

25

20 22 02 45.0 44.5 44.0 43.5 43.0 42.5 42.0 41.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of BL Lac 2200+420 with core halo morphology

FRI radio power (Lext < 24.5) and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 162

2201+171

17 26 05

00

25 55

50

45

DECLINATION (J2000) 40

35

30 22 03 28.0 27.5 27.0 26.5 26.0 25.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2201+171 with two sided halo morphol- ogy and wide angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 163

2201+315

31 46 15

00

45 45

30 DECLINATION (J2000) 15

00

22 03 18 17 16 15 14 13 12 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2201+315 with two sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 164

2209+236 23 56 00

55 55

50

45

40

35 DECLINATION (J2000) 30

25

22 12 07.0 06.5 06.0 05.5 05.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2209+236 with core morphology and undefined ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 165

2216-038

-03 35 15

30

45 DECLINATION (J2000)

36 00

22 18 54.0 53.5 53.0 52.5 52.0 51.5 51.0 50.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2216−038 with two sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 166

2223-052

-04 56 40

45

50

55

57 00

05

10 DECLINATION (J2000)

15

20

25 22 25 48.5 48.0 47.5 47.0 46.5 46.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2223−052 (3C 446) with two sided halo morphology and wide angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 167

2227-088 -08 32 30

35

40

45

50

55

33 00

DECLINATION (J2000) 05

10

15

22 29 41.5 41.0 40.5 40.0 39.5 39.0 38.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2227−088 with one sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 168

2230+114 11 44 15

10

05

00

43 55

50

45

DECLINATION (J2000) 40

35

30

22 32 38.0 37.5 37.0 36.5 36.0 35.5 35.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2230+114 with two sided halo morphol- ogy and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 169

2243-123

-12 06 40

45

50

55 DECLINATION (J2000)

07 00

05 22 46 19.2 19.0 18.8 18.6 18.4 18.2 18.0 17.8 17.6 17.4 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2243−123 with one sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 170

2251+158

16 09 05

00

08 55

50 DECLINATION (J2000)

45

40

22 53 58.6 58.4 58.2 58.0 57.8 57.6 57.4 57.2 57.0 56.8 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2251+158 (3C 454.3) with one sided jet morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 171

2331+073

07 36 40

35

30

25 DECLINATION (J2000) 20

15

23 34 13.8 13.6 13.4 13.2 13.0 12.8 12.6 12.4 12.2 12.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2331+073 with one sided halo morphol- ogy and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 172

2345-167

-16 31 00

05

10

15 DECLINATION (J2000) 20

25

23 48 03.5 03.0 02.5 02.0 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2345−167 with one sided halo mor- phology and near orthogonal ∆PA, taken from Cooper, Lister & Kochancyzk [2007], continued. 173

2351+456

45 53 15

10

05

00 DECLINATION (J2000)

52 55

50 23 54 23.0 22.5 22.0 21.5 21.0 20.5 RIGHT ASCENSION (J2000)

Figure A.1. 1.4 GHz VLA−A image of FSRQ 2351+456 with core morphology and low angle ∆PA, taken from Cooper, Lister & Kochancyzk [2007]. 174

PLot file version 7 created 26-JUN-2008 12:06:41 CONT: J0733+50 IPOL 1425.000 MHZ J0733+5022.ICL001.1

50 22 25

20

15

10

05 DECLINATION (J2000)

00

21 55

07 33 54.0 53.5 53.0 52.5 52.0 51.5 51.0 RIGHT ASCENSION (J2000) Cont peak flux = 6.7220E-01 JY/BEAM Levs = 6.722E-03 * (-0.042, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.2. 1.4 GHz VLA−A image of FSRQ 0730+504 with two sided jet morphology and wide angle ∆PA, taken from Kharb, Lister & Cooper [2010], continued. 175

PLot file version 5 created 26-JUN-2008 11:46:11 CONT: J0808-07 IPOL 1425.000 MHZ J0808-0751.ICL001.26

-07 50 55

51 00

05

10 DECLINATION (J2000) 15

20

25 08 08 16.5 16.0 15.5 15.0 14.5 RIGHT ASCENSION (J2000) Cont peak flux = 1.4335E+00 JY/BEAM Levs = 1.433E-02 * (-0.010, 0.010, 0.021, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.2. 1.4 GHz VLA−A image of 0805−077 with two sided jet morphology and low angle ∆PA, taken from Kharb, Lister & Cooper [2010], continued. 176

PLot file version 8 created 26-JUN-2008 12:05:40 CONT: J1038+05 IPOL 1425.000 MHZ J1038+0512.ICL001.17

05 12 45

40

35

30

25 DECLINATION (J2000)

20

15

10 38 47.5 47.0 46.5 46.0 RIGHT ASCENSION (J2000) Cont peak flux = 8.9189E-01 JY/BEAM Levs = 8.919E-03 * (-0.021, 0.021, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.2. 1.4 GHz VLA−A image of FSRQ 1036+054 with two sided jet morphology and wide angle ∆PA, taken from Kharb, Lister & Cooper [2010], continued. 177

PLot file version 5 created 26-JUN-2008 11:52:01 CONT: J1048-19 IPOL 1425.000 MHZ J1048-1909.ICL001.19 -19 09 20

25

30

35

40 DECLINATION (J2000)

45

50

10 48 07.5 07.0 06.5 06.0 05.5 RIGHT ASCENSION (J2000) Cont peak flux = 7.2436E-01 JY/BEAM Levs = 7.244E-03 * (-0.021, 0.021, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.2. 1.4 GHz VLA−A image of FSRQ 1045−188 with two sided halo mor- phology and low angle ∆PA, taken from Kharb, Lister & Cooper [2010], continued. 178

PLot file version 4 created 26-JUN-2008 12:00:58 CONT: J1215-17 IPOL 1425.000 MHZ J1215-1731.ICL001.18

-17 31 30

35

40

45

DECLINATION (J2000) 50

55

32 00

12 15 47.5 47.0 46.5 46.0 RIGHT ASCENSION (J2000) Cont peak flux = 1.6580E+00 JY/BEAM Levs = 1.658E-02 * (-0.021, 0.021, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.2. 1.4 GHz VLA−A image of unclassified object 1213−172 with one sided halo morphology and wide angle ∆PA, taken from Kharb, Lister & Cooper [2010], continued. 179

PLot file version 6 created 26-JUN-2008 12:04:41 CONT: J1222+04 IPOL 1425.000 MHZ J1222+0413.ICL001.17

04 13 30

25

20

15 DECLINATION (J2000) 10

05

00

12 22 23.5 23.0 22.5 22.0 21.5 RIGHT ASCENSION (J2000) Cont peak flux = 5.4894E-01 JY/BEAM Levs = 5.489E-03 * (-0.042, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.2. 1.4 GHz VLA−A image of FSRQ 1219+044 with two sided jet morphology and wide angle ∆PA, taken from Kharb, Lister & Cooper [2010] 180

Figure A.3. 1.4 GHz VLA−A image of BL Lac 0048−097 with two sided halo mor- phology, hot spots and wide angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 181

PLot file version 1 created 23-JUN-2008 11:43:19 CONT: 0316+413 IPOL 1312.150 MHZ 0316+413.ICL001.10

41 31 00

30 55

50

45

40

DECLINATION (J2000) 35

30

25

20 03 19 50.0 49.5 49.0 48.5 48.0 47.5 47.0 46.5 RIGHT ASCENSION (J2000) Cont peak flux = 2.1238E+01 JY/BEAM Levs = 2.124E-01 * (-0.021, 0.021, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.3. 1.4 GHz VLA−A image of radio galaxy 0316+413 (3C 84) with two sided jet morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 182

Figure A.3. 1.4 GHz VLA−A image of radio galaxy 0415+379 (3C 111) with two sided jet morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 183

PLot file version 2 created 29-JUN-2008 17:28:27 0430+052 IPOL 1464.900 MHZ 0430+052.IMAP.1 05 15 30

15

00 DECLINATION (B1950)

14 45

30

04 30 33.5 33.0 32.5 32.0 31.5 31.0 30.5 30.0 29.5 RIGHT ASCENSION (B1950) Peak flux = 2.8158E+00 JY/BEAM Levs = 2.816E-02 * (-0.063, 0.063, 0.125, 0.250, 0.500, 1, 2, 4, 8, 16, 32, 64, 128, 256, 512)

Figure A.3. 1.4 GHz VLA−A image of radio galaxy 0430+052 (3C 120) with two sided jet morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 184

PLot file version 1 created 27-JUN-2008 20:00:30 0727-115 IPOL 1489.900 MHZ 0727-115.ICLN.1

-11 39 30

40 00

30

41 00

30 DECLINATION (J2000)

42 00

30

43 00

07 30 26 24 22 20 18 16 14 12 RIGHT ASCENSION (J2000) Peak flux = 2.1149E+00 JY/BEAM Levs = 2.115E-02 * (-0.040, 0.040, 0.080, 0.160, 0.320, 0.640, 1.280, 2.560, 5.120, 10.24, 20.48, 40.96, 81.92)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 0727−115 with core morphology and undefined ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 185

PLot file version 1 created 11-JUL-2008 17:05:36 0735+178 IPOL 1425.000 MHZ 0735+178.ICLN.1

17 49 30

15

DECLINATION (B1950) 00

48 45

07 35 16.0 15.5 15.0 14.5 14.0 13.5 13.0 12.5 12.0 RIGHT ASCENSION (B1950) Peak flux = 2.9451E+00 JY/BEAM Levs = 2.945E-02 * (-0.025, 0.025, 0.050, 0.100, 0.200, 0.400, 0.800, 1.600, 3.200, 6.400, 12.80, 25.60, 51.20)

Figure A.3. 1.4 GHz VLA−A image of BL Lac 0735+178 with one sided jet morphol- ogy a possible hot spot and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 186

PLot file version 1 created 23-JUN-2008 11:02:42 CONT: 0736+017 IPOL 1489.900 MHZ 0736+017.ICL001.13

01 44 15

10

05

00

43 55 DECLINATION (B1950)

50

45

07 36 43.5 43.0 42.5 42.0 41.5 RIGHT ASCENSION (B1950) Cont peak flux = 2.3293E+00 JY/BEAM Levs = 2.329E-02 * (-0.042, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 0736+017 with two sided jet morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 187

Figure A.3. 1.4 GHz VLA−A image of FSRQ 0738+313 with two sided halo mor- phology low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 188

PLot file version 1 created 11-JUL-2008 17:58:40 0742+103 IPOL 1425.000 MHZ 0742+103.ICLN.1

10 19 00

18 45

30 DECLINATION (B1950)

15

07 42 50.5 50.0 49.5 49.0 48.5 48.0 47.5 47.0 46.5 RIGHT ASCENSION (B1950) Peak flux = 3.5958E+00 JY/BEAM Levs = 3.596E-02 * (-0.025, 0.025, 0.050, 0.100, 0.200, 0.400, 0.800, 1.600, 3.200, 6.400, 12.80, 25.60, 51.20)

Figure A.3. 1.4 GHz VLA−A image of 0742+103 with FSRQ morphology and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 189

Figure A.3. 1.4 GHz VLA−A image of FSRQ 0748+126 with two sided halo mor- phology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 190

Figure A.3. 1.4 GHz VLA−A image of BL Lac 0754+100 with two sided halo mor- phology, FRI luminosity and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 191

Figure A.3. 1.4 GHz VLA−A image of FSRQ 0804+499 with one sided halo morphol- ogy and undefined ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 192

PLot file version 1 created 23-JUN-2008 10:59:46 CONT: 0808+019 IPOL 1489.900 MHZ 0808+019.ICL001.13

01 56 05

00

55 55

50 DECLINATION (B1950)

45

40

35 08 08 52.0 51.5 51.0 50.5 RIGHT ASCENSION (B1950) Cont peak flux = 4.5029E-01 JY/BEAM Levs = 4.503E-03 * (-0.042, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.3. 1.4 GHz VLA−A image of BL Lac 0808+019 with two sided halo mor- phology, FRII luminosity, hot spots and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 193

Figure A.3. 1.4 GHz VLA−A image of BL Lac 0814+425 with two sided halo mor- phology, FRI/FRII luminosity and wide angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 194

Figure A.3. 1.4 GHz VLA−A image of BL Lac 0823+033 with one sided halo mor- phology, FRI/FRII luminosity, hot spots and undefined ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 195

PLot file version 1 created 30-JUN-2008 16:11:12 0827+243 IPOL 1510.000 MHZ 0827+243.ICLN.1

24 21 30

15

00 DECLINATION (B1950)

20 45

08 27 56.5 56.0 55.5 55.0 54.5 54.0 53.5 53.0 52.5 RIGHT ASCENSION (B1950) Peak flux = 7.6663E-01 JY/BEAM Levs = 7.666E-03 * (-0.075, 0.075, 0.150, 0.300, 0.600, 1.200, 2.400, 4.800, 9.600, 19.20, 38.40, 76.80)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 0827+243 with one sided halo morphol- ogy and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 196

Figure A.3. 1.4 GHz VLA−A image of BL Lac 0829+046 with two sided morphology, FRI/FRII luminosity and and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 197

PLot file version 1 created 23-JUN-2008 11:36:15 CONT: 0838+133 IPOL 1425.000 MHZ 0838+133.ICL001.10

13 23 20

15

10

05 DECLINATION (B1950) 00

22 55

50 08 38 02.5 02.0 01.5 01.0 RIGHT ASCENSION (B1950) Cont peak flux = 2.8925E-01 JY/BEAM Levs = 2.892E-03 * (-0.085, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 0838+133 with two sided halo mor- phology low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 198

Figure A.3. 1.4 GHz VLA−A image of BL Lac 0851+202 (OJ 287) with one sided jet morphology, FRI/FRII luminosity and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 199

PLot file version 1 created 08-JUL-2008 17:38:20 0906+015 IPOL 1564.900 MHZ 0906+015.ICLN.1

01 34 15

00

33 45 DECLINATION (B1950)

30

09 06 37.0 36.5 36.0 35.5 35.0 34.5 34.0 33.5 RIGHT ASCENSION (B1950) Peak flux = 9.1907E-01 JY/BEAM Levs = 9.191E-03 * (0.085, 0.170, 0.340, 0.680, 1.360, 2.720, 5.440, 10.88, 21.76, 43.52, 87.04)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 0906+015 with one sided morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 200

PLot file version 1 created 08-JUL-2008 14:53:47 0921+622 IPOL 1400.000 MHZ 0917+624.ICLN.1

62 16 15

00

15 45 DECLINATION (J2000)

30

09 21 40 39 38 37 36 35 34 33 32 RIGHT ASCENSION (J2000) Peak flux = 1.1668E+00 JY/BEAM Levs = 1.167E-02 * (-0.026, 0.026, 0.052, 0.104, 0.208, 0.416, 0.832, 1.664, 3.328, 6.656, 13.31, 26.62)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 0917+624 with one sided halo morphol- ogy and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 201

PLot file version 1 created 07-JUL-2008 15:00:44 0923+392 IPOL 1514.900 MHZ 0923+392.ICL001.1

39 15 45

30

15 DECLINATION (B1950)

00

09 23 58 57 56 55 54 53 RIGHT ASCENSION (B1950) Peak flux = 2.3866E+00 JY/BEAM Levs = 2.387E-02 * (-0.120, 0.120, 0.240, 0.480, 0.960, 1.920, 3.840, 7.680, 15.36, 30.72, 61.44)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 0923+392 with one sided halo morphol- ogy and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 202

Figure A.3. 1.4 GHz VLA−A image of FSRQ 0945+408 with one sided jet morphology and undefined ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 203

PLot file version 1 created 25-JUN-2008 10:56:28 CONT: 0955+476 IPOL 1489.900 MHZ 0955+476.ICL001.13

47 39 40

35

30

25 DECLINATION (B1950)

20

15

09 55 09.5 09.0 08.5 08.0 07.5 07.0 RIGHT ASCENSION (B1950) Cont peak flux = 5.9238E-01 JY/BEAM Levs = 5.924E-03 * (-0.042, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 0955+476 with core morphology and undefined ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 204

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1038+064 with one sided jet morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 205

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1055+018 with two sided jet morphol- ogy, and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 206

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1124−186 with one sided lobe morphol- ogy and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 207

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1127−145 with one sided jet morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 208

PLot file version 1 created 23-JUN-2008 11:04:11 CONT: 1156+295 IPOL 1489.900 MHZ 1156+295.ICL001.12 29 31 40

35

30

25 DECLINATION (B1950)

20

15

11 56 58.5 58.0 57.5 57.0 RIGHT ASCENSION (B1950) Cont peak flux = 1.4262E+00 JY/BEAM Levs = 1.426E-02 * (-0.042, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1156+295 with two sided halo mor- phology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 209

PLot file version 1 created 01-JUL-2008 16:40:43 1229+020 IPOL 1452.400 MHZ 1226+023.ICLN.1

02 03 45

30

15

00 DECLINATION (J2000)

02 45

30

12 29 09 08 07 06 05 04 RIGHT ASCENSION (J2000) Peak flux = 3.2602E+01 JY/BEAM Levs = 3.260E-01 * (-0.027, 0.027, 0.054, 0.108, 0.216, 0.432, 0.864, 1.728, 3.456, 6.912, 13.82, 27.65, 55.30)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1226+023 with one sided jet morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 210

PLot file version 1 created 30-JUN-2008 08:57:01 UGC07654 IPOL 1425.000 MHZ 1228+126.IMAP.1

12 24 00

23 45

30 DECLINATION (J2000) 15

00

12 30 51.5 51.0 50.5 50.0 49.5 49.0 48.5 48.0 47.5 47.0 RIGHT ASCENSION (J2000) Peak flux = 3.5238E+00 JY/BEAM Levs = 3.524E-02 * (-5, 5, 10, 20, 30, 40, 50, 60, 70)

Figure A.3. 1.4 GHz VLA−A image of radio galaxy 1228+126 with two sided jet morphology and wide angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 211

PLot file version 1 created 06-JUL-2008 15:22:34 J1256-05 IPOL 1664.900 MHZ 1253-055.ICLN.1

-05 47 00

05

10

15

20

25 DECLINATION (J2000) 30

35

40

45

12 56 12.5 12.0 11.5 11.0 10.5 10.0 09.5 RIGHT ASCENSION (J2000) Peak flux = 1.0177E+01 JY/BEAM Levs = 1.018E-01 * (-0.030, 0.060, 0.120, 0.240, 0.480, 0.960, 1.920, 3.840, 7.680, 15.36, 30.72, 61.44)

Figure A.3. 1.6 GHz VLA−A image of FSRQ 1253−055 (3C 279) with two sided jet morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 212

PLot file version 1 created 11-OCT-2010 18:15:55 1334-127 IPOL 1489.900 MHZ 1334-127.25.ICL001.1 -12 41 55

42 00

05

10

DECLINATION (B1950) 15

20

25 13 35 00.5 00.0 34 59.5 59.0 RIGHT ASCENSION (B1950) Peak flux = 1.9443E+00 JY/BEAM Levs = 1.944E-02 * (-0.040, 0.040, 0.050, 0.100, 0.200, 0.400, 0.800, 1.600, 3.200, 6.400, 12.80, 25.60, 51.20)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1334−127 with one sided halo morphol- ogy and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 213

PLot file version 1 created 02-JUL-2008 12:07:04 1415+133 IPOL 1425.000 MHZ 1413+135.ICLN.1

13 20 35

30

25

20 DECLINATION (J2000)

15

10

14 15 59.5 59.0 58.5 58.0 RIGHT ASCENSION (J2000) Peak flux = 1.1660E+00 JY/BEAM Levs = 1.166E-02 * (-0.041, 0.041, 0.082, 0.164, 0.328, 0.656, 1.312, 2.624, 5.248, 10.50, 20.99, 41.98)

Figure A.3. 1.4 GHz VLA−A image of BL Lac 1413+135 with core−halo morphology, FRI luminosity and undefined ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 214

-16 40 54

56

58

41 00

02 DECLINATION (B1950) 04

06

08

15 04 16.8 16.6 16.4 16.2 16.0 RIGHT ASCENSION (B1950)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1504−166 with two sided halo mor- phology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 215

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1510−089 with two sided jet morphology and wide angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 216

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1546+027 with one sided lobe morphol- ogy with low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 217

05 36 25

20

15

10 DECLINATION (B1950)

05

00

15 48 07.8 07.6 07.4 07.2 07.0 06.8 06.6 06.4 06.2 06.0 RIGHT ASCENSION (B1950)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1548+056 with core−halo morphology and undefined ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 218

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1606+106 with one sided halo morphol- ogy and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 219

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1611+343 with two sided lobe mor- phology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 220

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1633+382 with one sided halo mor- phology with counter lobe and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 221

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1637+574 with one sided halo morphol- ogy and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 222

PLot file version 1 created 06-AUG-2008 19:37:01 1638+398 IPOL 1414.900 MHZ 1638+698.ICLN.1 39 53 00

52 45

30 DECLINATION (B1950)

15

00 16 38 50 49 48 47 46 RIGHT ASCENSION (B1950) Peak flux = 1.1599E+00 JY/BEAM Levs = 1.160E-02 * (-0.080, 0.080, 0.160, 0.320, 0.640, 1.280, 2.560, 10.24, 20.48, 40.96, 81.92)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1638+398 with one sided halo mor- phology with counter lobe and wide angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 223

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1641+399 with two sided halo mor- phology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 224

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1655+077 with two sided halo mor- phology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 225

45 33 14

12

10

08

06

04 DECLINATION (B1950) 02

00

32 58

56 17 26 02.0 01.8 01.6 01.4 01.2 01.0 00.8 00.6 00.4 RIGHT ASCENSION (B1950)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1726+455 with two sided halo mor- phology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 226

-13 04 35

40

45

50 DECLINATION (J2000) 55

05 00

17 33 04.0 03.5 03.0 02.5 02.0 01.5 RIGHT ASCENSION (J2000)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1730−130 with two sided jet morphology and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 227

PLot file version 1 created 23-JUN-2008 15:49:18 CONT: 1739+522 IPOL 1489.900 MHZ 1739+522.ICL001.9

52 13 20

15

10 DECLINATION (B1950)

05

00

17 39 30.0 29.5 29.0 28.5 28.0 RIGHT ASCENSION (B1950) Cont peak flux = 1.5420E+00 JY/BEAM Levs = 1.542E-02 * (-0.042, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1739+522 with two sided halo morphol- ogy and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 228

-03 49 56

58

50 00

02

04

06

DECLINATION (J2000) 08

10

12

14

17 43 59.6 59.4 59.2 59.0 58.8 58.6 58.4 RIGHT ASCENSION (J2000)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1741−038 with core morphology and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 229

PLot file version 1 created 23-JUN-2008 11:12:24 CONT: 1749+096 IPOL 1489.900 MHZ 1749+096.ICL001.11 09 39 55

50

45

DECLINATION (B1950) 40

35

17 49 11.0 10.8 10.6 10.4 10.2 10.0 09.8 09.6 RIGHT ASCENSION (B1950) Cont peak flux = 7.7312E-01 JY/BEAM Levs = 7.731E-03 * (-0.042, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.3. 1.4 GHz VLA−A image of BL Lac 1749+096 with core morphology, FRI luminosity and undefined ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 230

PLot file version 1 created 01-AUG-2008 18:44:34 1751+288 IPOL 1435.000 MHZ 1751+288.ICL001.1

28 49 00

48 45

30 DECLINATION (B1950)

15

17 51 47.5 47.0 46.5 46.0 45.5 45.0 44.5 44.0 43.5 43.0 RIGHT ASCENSION (B1950) Peak flux = 2.6350E-01 JY/BEAM Levs = 2.635E-03 * (-0.200, 0.200, 0.400, 0.800, 1.600, 3.200, 6.400, 12.80, 25.60, 51.20)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1751+288 with one sided halo morphol- ogy and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 231

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1758+388 with core morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 232

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1800+440 with one sided halo morphol- ogy with counter lobe and low angle ∆PA, taken from NRAO Archive and Publica- tions listed in Table 2.1, continued. 233

PLot file version 1 created 23-JUN-2008 11:38:26 CONT: 1807+698 IPOL 1514.900 MHZ 1807+698.ICL001.14

69 49 15

10

05

00

48 55

50 DECLINATION (B1950)

45

40

35

18 07 21 20 19 18 17 16 15 14 13 RIGHT ASCENSION (B1950) Cont peak flux = 1.1372E+00 JY/BEAM Levs = 1.137E-02 * (-0.042, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.3. 1.4 GHz VLA−A image of BL Lac 1807+698 (3C 371) with one sided jet morphology, hot spots, FRI Luminosity and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 234

Figure A.3. 1.4 GHz VLA−A image of BL Lac 1823+568 with one sided halo mor- phology, FRII Luminosity and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 235

Figure A.3. 1.4 GHz VLA−A image of CSS 1828+487 (3C 380) with one sided halo morphology wide angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 236

PLot file version 12 created 02-AUG-200812-FEB-2009 12:30:3709:40:59 1936-155 IPOL 1489.900 MHZ 1936-155.ICL001.1

-15 32 15

30

45 DECLINATION (B1950)

33 00

19 36 38.0 37.5 37.0 36.5 36.0 35.5 35.0 34.5 34.0 RIGHT ASCENSION (B1950) Peak flux = 1.0541E+00 JY/BEAM Levs = 1.054E-02 * (-0.055,(-0.050, 0.055,0.050, 0.100, 0.200, 0.400, 0.800, 1.600, 3.200, 6.400, 12.80, 25.60, 51.20)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1936−155 with core−halo morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 237

Figure A.3. 1.4 GHz VLA−A image of radio galaxy 1957+405 (Cygnus A) with two sided jet morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 238

PLot file version 1 created 23-JUN-2008 11:41:32 CONT: 1958-179 IPOL 1489.900 MHZ 1958-179.ICL001.12

-17 57 05

10

15

20 DECLINATION (B1950)

25

30 19 58 05.4 05.2 05.0 04.8 04.6 04.4 04.2 04.0 03.8 RIGHT ASCENSION (B1950) Cont peak flux = 1.7690E+00 JY/BEAM Levs = 1.769E-02 * (-0.085, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 1958−179 with core morphology and undefined ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 239

PLot file version 2 created 12-FEB-2009 12:46:33 2005+403 IPOL 1665.738 MHZ 2005+403.ICL001.1

40 21 15

10

05

00 DECLINATION (B1950)

20 55

50

20 06 00.5 00.0 05 59.5 59.0 58.5 RIGHT ASCENSION (B1950) Peak flux = 2.4283E+00 JY/BEAM Levs = 2.428E-02 * (-0.060, 0.060, 0.120, 0.240, 0.480, 0.960, 1.920, 3.840, 7.680, 15.36, 30.72, 61.44)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 2005+403 with core−halo morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 240

PLot file version 3 created 12-FEB-2009 12:52:54 2008-159 IPOL 1489.900 MHZ 2008-159.ICL001.1

-15 55 15

30

45 DECLINATION (B1950)

56 00

20 08 28.0 27.5 27.0 26.5 26.0 25.5 25.0 24.5 24.0 RIGHT ASCENSION (B1950) Peak flux = 5.4454E-01 JY/BEAM Levs = 5.445E-03 * (-0.060, 0.060, 0.120, 0.240, 0.480, 0.960, 1.920, 3.840, 7.680, 15.36, 30.72, 61.44)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 2008−159 with one sided halo morphol- ogy and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 241

31 43 28

26

24

22

20

18 DECLINATION (B1950) 16

14

12

10 20 21 19.2 19.0 18.8 18.6 18.4 18.2 18.0 RIGHT ASCENSION (B1950)

Figure A.3. 1.4 GHz VLA−A image of unclassified AGN 2021+317 with one sided halo morphology and undefined ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 242

61 27 28

26

24

22

20

18

DECLINATION (B1950) 16

14

12

10

20 21 14.5 14.0 13.5 13.0 12.5 RIGHT ASCENSION (B1950)

Figure A.3. 1.4 GHz VLA−A image of radio galaxy 2021+614 with core morphology and undefined ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 243

51 08 44

42

40

38

36

DECLINATION (B1950) 34

32

30

28 20 37 07.8 07.6 07.4 07.2 07.0 06.8 06.6 06.4 06.2 RIGHT ASCENSION (B1950)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 2037+511 with one sided halo morphol- ogy and near orthogonal ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 244

Figure A.3. 1.4 GHz VLA−A image of FSRQ 2121+053 with core morphology and undefined ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 245

PLot file version 1 created 06-AUG-2008 17:54:23 2128-12 IPOL 1489.900 MHZ 2128-123.ICL001.1

-12 20 00

15

DECLINATION (B1950) 30

45

21 28 54.5 54.0 53.5 53.0 52.5 52.0 51.5 51.0 RIGHT ASCENSION (B1950) Peak flux = 1.3670E+00 JY/BEAM Levs = 1.367E-02 * (-0.042, 0.042, 0.084, 0.168, 0.330, 0.660, 1.320, 2.640, 5.280, 10.56, 21.12, 42.24, 84.48)

Figure A.3. 1.4 GHz VLA−A image of FSRQ 2128−123 with one sided jet morphology and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 246

PLot file version 1 created 23-JUN-2008 11:39:58 CONT: 2131-021 IPOL 1514.900 MHZ 2131-021.ICL001.10

-02 06 25

30

35

40

45 DECLINATION (B1950)

50

55

21 31 36.0 35.5 35.0 34.5 RIGHT ASCENSION (B1950) Cont peak flux = 1.2925E+00 JY/BEAM Levs = 1.293E-02 * (-0.042, 0.042, 0.085, 0.170, 0.350, 0.700, 1.400, 2.800, 5.600, 11.25, 22.50, 45, 90)

Figure A.3. 1.4 GHz VLA−A image of BL Lac 2131−021 with one sided halo morphol- ogy, FRII luminosity and low angle ∆PA, taken from NRAO Archive and Publications listed in Table 2.1, continued. 247

Figure A.3. 1.4 GHz VLA−A image of FSRQ 2134+004 with one sided halo morphol- ogy with counter lobe and low angle ∆PA, taken from NRAO Archive and Publica- tions listed in Table 2.1, continued. 248

Figure A.3. 1.4 GHz VLA−A image of FSRQ 2136+141 with core morphology and undefined ∆PA, taken from NRAO Archive and Publications listed in Table 2.1. LIST OF REFERENCES 249

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VITA

Nathaniel Jonathan Cooper was born in Lafayette, Indiana, on October 26, 1976. He is the son of Mr. John and Mrs. Debra Cooper. He is married to Kaliroi Tsamboukos−Cooper and they have a son. Nathaniel Cooper received a Bachelor of Science in Physics Education with a minor in Philosophy at Purdue University, West Lafayette in 2003. He was rewarded the Charles C. Chappelle Fellowship for continuing his education at Purdue University, West Lafayette where he completed a Master of Science in Physics in 2005 and a PhD in 2010. While in the final stages of completing his dissertation, Nathaniel Cooper accepted a faculty position as an Assistant Professor of Physics at Bard High School Early College in New York, New York.