Extragalactic Radio Continuum Surveys and the Transformation of Radio Astronomy
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College of San Mateo Observatory Stellar Spectra Catalog ______
College of San Mateo Observatory Stellar Spectra Catalog SGS Spectrograph Spectra taken from CSM observatory using SBIG Self Guiding Spectrograph (SGS) ___________________________________________________ A work in progress compiled by faculty, staff, and students. Stellar Spectroscopy Stars are divided into different spectral types, which result from varying atomic-level activity on the star, due to its surface temperature. In spectroscopy, we measure this activity via a spectrograph/CCD combination, attached to a moderately sized telescope. The resultant data are converted to graphical format for further analysis. The main spectral types are characterized by the letters O,B,A,F,G,K, & M. Stars of O type are the hottest, as well as the rarest. Stars of M type are the coolest, and by far, the most abundant. Each spectral type is also divided into ten subtypes, ranging from 0 to 9, further delineating temperature differences. Type Temperature Color O 30,000 - 60,000 K Blue B 10,000 - 30,000 K Blue-white A 7,500 - 10,000 K White F 6,000 - 7,500 K Yellow-white G 5,000 - 6,000 K Yellow K 3,500 - 5,000 K Yellow-orange M >3,500 K Red Class Spectral Lines O -Weak neutral and ionized Helium, weak Hydrogen, a relatively smooth continuum with very few absorption lines B -Weak neutral Helium, stronger Hydrogen, an otherwise relatively smooth continuum A -No Helium, very strong Hydrogen, weak CaII, the continuum is less smooth because of weak ionized metal lines F -Strong Hydrogen, strong CaII, weak NaI, G-band, the continuum is rougher because of many ionized metal lines G -Weaker Hydrogen, strong CaII, stronger NaI, many ionized and neutral metals, G-band is present K -Very weak Hydrogen, strong CaII, strong NaI and many metals G- band is present M -Strong TiO molecular bands, strongest NaI, weak CaII very weak Hydrogen absorption. -
Introduction to Radio Astronomy
Introduction to Radio Astronomy Greg Hallenbeck 2016 UAT Workshop @ Green Bank Outline Sources of Radio Emission Continuum Sources versus Spectral Lines The HI Line Details of the HI Line What is our data like? What can we learn from each source? The Radio Telescope How do we actually detect this stuff? How do we get from the sky to the data? I. Radio Emission Sources The Electromagnetic Spectrum Radio ← Optical Light → A Galaxy Spectrum (Apologies to the radio astronomers) Continuum Emission Radiation at a wide range of wavelengths ❖ Thermal Emission ❖ Bremsstrahlung (aka free-free) ❖ Synchrotron ❖ Inverse Compton Scattering Spectral Line Radiation at a wide range of wavelengths ❖ The HI Line Categories of Emission Continuum Emission — “The Background” Radiation at a wide range of wavelengths ❖ Thermal Emission ❖ Synchrotron ❖ Bremsstrahlung (aka free-free) ❖ Inverse Compton Scattering Spectral Lines — “The Spikes” Radiation at specific wavelengths ❖ The HI Line ❖ Pretty much any element or molecule has lines. Thermal Emission Hot Things Glow Emit radiation at all wavelengths The peak of emission depends on T Higher T → shorter wavelength Regulus (12,000 K) The Sun (6,000 K) Jupiter (100 K) Peak is 250 nm Peak is 500 nm Peak is 30 µm Thermal Emission How cold corresponds to a radio peak? A 3 K source has peak at 1 mm. Not getting any colder than that. Synchrotron Radiation Magnetic Fields Make charged particles move in circles. Accelerating charges radiate. Synchrotron Ingredients Strong magnetic fields High energies, ionized particles. Found in jets: ❖ Active galactic nuclei ❖ Quasars ❖ Protoplanetary disks Synchrotron Radiation Jets from a Protostar At right: an optical image. -
The E-MERLIN Notebook
The e-MERLIN Notebook IRIS Collaboration F2F Meeting - 4 April 2019 Dr. Rachael Ainsworth Jodrell Bank Centre for Astrophysics University of Manchester @rachaelevelyn Overview ● Motivation ● Brief intro to e-MERLIN ● Pieces of the puzzle: ○ e-MERLIN CASA Pipeline ○ Data Archive ○ Open Notebooks ● Putting everything together: ○ e-MERLIN @ IRIS Motivation (Whitaker 2018, https://doi.org/10.6084/m9.figshare.7140050.v2 ) “Computational science has led to exciting new developments, but the nature of the work has exposed limitations in our ability to evaluate published findings. Reproducibility has the potential to serve as a minimum standard for judging scientific claims when full independent replication of a study is not possible.” (Peng 2011; https://doi.org/10.1126/science.1213847) e-MERLIN (e)MERLIN ● enhanced Multi Element Remotely Linked Interferometer Network ● An array of 7 radio telescopes spanning 217 km across the UK ● Connected by a superfast optical fibre network to its headquarters at Jodrell Bank Observatory. ● Has a unique position in the world with an angular resolution comparable to that of the Hubble Space Telescope and carrying out centimetre wavelength radio astronomy with micro-Jansky sensitivities. http://www.e-merlin.ac.uk/ (e)MERLIN ● Does not have a publicly accessible data archive. http://www.e-merlin.ac.uk/ Radio Astronomy Software: CASA ● The CASA infrastructure consists of a set of C++ tools bundled together under an iPython interface as data reduction tasks. ● This structure provides flexibility to process the data via task interface or as a python script. ● https://casa.nrao.edu/ Pieces of the puzzle e-MERLIN CASA Pipeline ● Developed openly on GitHub (Moldon, et al.) ● Python package composed of different modules that can be run together sequentially to produce calibration tables, calibrated data, assessment plots and a summary weblog. -
The Merlin - Phase 2
Radio Interferometry: Theory, Techniques and Applications, 381 IAU Coll. 131, ASP Conference Series, Vol. 19, 1991, T.J. Comwell and R.A. Perley (eds.) THE MERLIN - PHASE 2 P.N. WILKINSON University of Manchester, Nuffield Radio Astronomy Laboratories, Jodrell Bank, Macclesfield, Cheshire, SKll 9DL, United Kingdom ABSTRACT The Jodrell Bank MERLIN is currently being upgraded to produce higher sensitivity and higher resolving power. The major capital item has been a new 32m telescope located at MRAO Cambridge which will operate to at least 50 GHz. A brief outline of the upgraded MERLIN and its performance is given. INTRODUCTION The MERLIN (Multi-Element Radio-Linked Interferometer Network), based at Jodrell Bank, was conceived in the mid-1970s and first became operational in 1980. It was a bold concept; no one had made a real-time long-baseline interferometer array with phase-stable local oscillator links before. Six remotely operated telescopes, controlled via telephone lines, are linked to a control computer at Jodrell Bank. The rf signals are transmitted to Jodrell via commercial multi-hop microwave links operating at 7.5 GHz. The local oscillators are coherently slaved to a master oscillator via go-and- return links operating at L-band, the change in the link path-length being taken out in software. This single-frequency L-band link can transfer phase to the equivalent of < 1 picosec (< 0.3 mm of path length) on timescales longer than a few seconds. A detailed description of the MERLIN system has been given by Thomasson (1986). The MERLIN has provided the UK with a unique astronomical facility, one which has made important contributions to extragalactic radio source and OH maser studies. -
Binary Star Modeling: a Computational Approach
TCNJ JOURNAL OF STUDENT SCHOLARSHIP VOLUME XIV APRIL 2012 BINARY STAR MODELING: A COMPUTATIONAL APPROACH Author: Daniel Silano Faculty Sponsor: R. J. Pfeiffer, Department of Physics ABSTRACT This paper illustrates the equations and computational logic involved in writing BinaryFactory, a program I developed in Spring 2011 in collaboration with Dr. R. J. Pfeiffer, professor of physics at The College of New Jersey. This paper outlines computational methods required to design a computer model which can show an animation and generate an accurate light curve of an eclipsing binary star system. The final result is a light curve fit to any star system using BinaryFactory. An example is given for the eclipsing binary star system TU Muscae. Good agreement with observational data was obtained using parameters obtained from literature published by others. INTRODUCTION This project started as a proposal for a simple animation of two stars orbiting one another in C++. I found that although there was software that generated simple animations of binary star orbits and generated light curves, the commercial software was prohibitively expensive or not very user friendly. As I progressed from solving the orbits to generating the Roche surface to generating a light curve, I learned much about computational physics. There were many trials along the way; this paper aims to explain to the reader how a computational model of binary stars is made, as well as how to avoid pitfalls I encountered while writing BinaryFactory. Binary Factory was written in C++ using the free C++ libraries, OpenGL, GLUT, and GLUI. A basis for writing a model similar to BinaryFactory in any language will be presented, with a light curve fit for the eclipsing binary star system TU Muscae in the final secion. -
De-Coding Starlight (Grades 5-8)
Teacher's Guide to Chandra X-ray Observatory From Pixels to Images: De-Coding Starlight (Grades 5-8) Background and Purpose In an effort to learn more about black holes, pulsars, supernovas, and other high-energy astronomical events, NASA launched the Chandra X-ray Observatory in 1999. Chandra is the largest space telescope ever launched and detects "invisible" X-ray radiation, which is often the only way that scientists can pinpoint and understand high-energy events in our universe. Computer aided data collection and processing is an essential facet to astronomical research using space- and ground-based telescopes. Every 8 hours, Chandra downloads millions of pieces of information to Earth. To control, process, and analyze this flood of numbers, scientists rely on computers, not only to do calculations, but also to change numbers into pictures. The final results of these analyses are wonderful and exciting images that expand understanding of the universe for not only scientists, but also decision-makers and the general public. Although computers are used extensively, scientists and programmers go through painstaking calibration and validation processes to ensure that computers produce technically correct images. As Dr. Neil Comins so eloquently states1, “These images create an impression of the glamour of science in the public mind that is not entirely realistic. The process of transforming [i.e., by using computers] most telescope data into accurate and meaningful images is long, involved, unglamorous, and exacting. Make a mistake in one of dozens of parameters or steps in the analysis and you will get inaccurate results.” The process of making the computer-generated images from X-ray data collected by Chandra involves the use of "false color." X-rays cannot be seen by human eyes, and therefore, have no "color." Visual representation of X-ray data, as well as radio, infrared, ultraviolet, and gamma, involves the use of "false color" techniques, where colors in the image represent intensity, energy, temperature, or another property of the radiation. -
Radio Galaxy Zoo: Compact and Extended Radio Source Classification with Deep Learning
MNRAS 476, 246–260 (2018) doi:10.1093/mnras/sty163 Advance Access publication 2018 January 26 Radio Galaxy Zoo: compact and extended radio source classification with deep learning V. Lukic,1‹ M. Bruggen,¨ 1‹ J. K. Banfield,2,3 O. I. Wong,3,4 L. Rudnick,5 R. P. Norris6,7 and B. Simmons8,9 1Hamburger Sternwarte, University of Hamburg, Gojenbergsweg 112, D-21029 Hamburg, Germany 2Research School of Astronomy and Astrophysics, Australian National University, Canberra, ACT 2611, Australia 3ARC Centre of Excellence for All-Sky Astrophysics (CAASTRO), Building A28, School of Physics, The University of Sydney, NSW 2006, Australia 4International Centre for Radio Astronomy Research-M468, The University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009, Australia Downloaded from https://academic.oup.com/mnras/article/476/1/246/4826039 by guest on 23 September 2021 5University of Minnesota, 116 Church St SE, Minneapolis, MN 55455, USA 6Western Sydney University, Locked Bag 1797, Penrith South, NSW 1797, Australia 7CSIRO Astronomy and Space Science, Australia Telescope National Facility, PO Box 76, Epping, NSW 1710, Australia 8Oxford Astrophysics, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH, UK 9Center for Astrophysics and Space Sciences, Department of Physics, University of California, San Diego, CA 92093, USA Accepted 2018 January 15. Received 2018 January 9; in original form 2017 September 24 ABSTRACT Machine learning techniques have been increasingly useful in astronomical applications over the last few years, for example in the morphological classification of galaxies. Convolutional neural networks have proven to be highly effective in classifying objects in image data. In the context of radio-interferometric imaging in astronomy, we looked for ways to identify multiple components of individual sources. -
GCSE Astronomy Scheme of Work
Scheme of Work GCSE (9-1) Astronomy Pearson Edexcel Level 1/Level 2 GCSE (9-1) in Astronomy (1AS0) GCSE Astronomy Scheme of Work Topic 1 Planet Earth Week 1 1.1 The Earth’s structure Specification Maths Related practical Exemplar activities Exemplar resources points skills activities 1.1 Starter: Teacher shows images of the Earth showing its Find useful information in chapter 1 2a 1.2 many diverse surface features and asks the class to of GCSE Astronomy – A Guide for 2b 1.3 a-d share what they know about its shape, size and internal Pupils and Teachers (5th ed.) by structure. Marshall, N. (Mickledore). Pupils study the shape and mean diameter of the Earth (13 000 km). Further useful information in chapter Pupils study the Earth’s interior, its main divisions and 3 of The Planets by Aderin-Pocock, their properties (approximate size, state of matter, M. et al (DK). temperature etc.): o crust o mantle o outer core o inner core. © Pearson Education Ltd 2016 1 GCSE Astronomy Scheme of Work Topic 1 Planet Earth Week 2 1.2 Latitude and longitude Specification Maths Related practical Exemplar activities Exemplar resources points skills activities 1.4 Teacher demonstrates latitude and longitude on a globe Find useful information in chapter 1 5a 1.5 a-h of the Earth. of GCSE Astronomy – A Guide for 5d Pupils and Teachers (5th ed.) by Pupils use globes, maps and/or an atlas to study Marshall, N. (Mickledore). latitude and longitude. Model globes and atlases are Pupils learn that in addition to being simply lines on a available from many retail outlets or map, latitude and longitude are actually angles. -
A Study of Giant Radio Galaxies at Ratan-600 173
Bull. Spec. Astrophys. Obs., 2011, 66, 171–182 c Special Astrophysical Observatory of the Russian AS, 2018 A Study of Giant Radio Galaxies at RATAN-600 M.L. Khabibullinaa, O.V. Verkhodanova, M. Singhb, A. Piryab, S. Nandib, N.V. Verkhodanovaa a Special Astrophysical Observatory of the Russian AS, Nizhnij Arkhyz 369167, Russia; b Aryabhatta Research Institute of Observational Sciences, Manora Park, Nainital 263 129, India Received July 28, 2010; accepted September 15, 2010. We report the results of flux density measurements in the extended components of thirteen giant radio galaxies, made with the RATAN-600 in the centimeter range. Supplementing them with the WENSS, NVSS and GB6 survey data we constructed the spectra of the studied galaxy components. We computed the spectral indices in the studied frequency range and demonstrate the need for a detailed account of the integral contribution of such objects into the background radiation. Key words: Radio lines: galaxies—techniques: radar astronomy 1. INTRODUCTION than the one, expected from the evolutional models. As noted in [8], such radio galaxies may affect the According to the generally accepted definition, gi- processes of galaxy formation, since the pressure of ant radio galaxies (GRGs) are the radio sources with gas, outflowing from the radio source, may compress linear sizes greater than 1 Mpc, i.e. the largest ra- the cold gas clouds thus initiating the development dio sources in the Universe. They mostly belong to of stars on the one hand, and stop the formation of the morphological type FR II [1] and are identified galaxies on the other hand. -
Machine Learning in Large Radio Astronomy Surveys (How to Do Science with Petabytes)
Machine Learning in Large Radio Astronomy Surveys (How to do Science with Petabytes) Ray Norris, Western Sydney University & CSIRO Astronomy & Space Science, ASKAP: Australian Square Kilometre Array Pathfinder ▪ $185m telescope built by CSIRO, approaching completion ▪ Mission: to solve fundamental problems in astrophysics ▪ “EMU” = Evolutionary Map of the Universe PAFs -> Big Data Data Rate to correlator = 100 Tbit/s = 3000 Blu-ray disks/second = 62km tall stack of disks per day = world internet bandwidth in June 2012 Processed data volume = 70 PB/yr (only store 4 PB/yr) EMU: Evolutionary Map of the Universe ▪ PI Ray Norris ▪ Will survey the whole sky for radio continuum ▪ Will discover ~ 70 million galaxies, ▪ compared to 2.5 million currently known ▪ Will revolutionize our view of the Universe ▪ Will revolutionize the way we do astronomy ▪ “large-n astronomy” ASKAP Radio Continuum survey: EMU = 70 million NVSS=1.8 million current total=2.5 million From Norris, 2017, Nature Astronomy, 1,671 1940 1980 2020 EMU Team: ~300 scientists in 21 countries Key Title Project Leader project KP1. EMU Value-Added Catalogue Nick Seymour (Curtin) KP2. Characterising the Radio Sky Ian Heywood (Oxford) KP3. EMU Cosmology David Parkinson (KASA, Korea) KP4. Cosmic Web Shea Brown (Iowa) KP5. Clusters of Galaxies Melanie Johnston-Hollitt (NZ) KP6. cosmic star formation history Andrew Hopkins (AAO) KP7. Evolution of radio-loud AGN Anna Kapinska (UWA) KP8. Radio AGN in the EoR Jose Afonso (Lisbon) KP9. Radio-quiet AGN Isabella Prandoni (Bologna) KP10. Binary super-massive black holes Roger Deane (Cape Town) KP11. Local Universe Josh Marvil (NRAO) KP12. The Galactic Plane Roland Kothes (Canada) KP13. -
Essential Radio Astronomy
February 2, 2016 Time: 09:25am chapter1.tex © Copyright, Princeton University Press. No part of this book may be distributed, posted, or reproduced in any form by digital or mechanical means without prior written permission of the publisher. 1 Introduction 1.1 AN INTRODUCTION TO RADIO ASTRONOMY 1.1.1 What Is Radio Astronomy? Radio astronomy is the study of natural radio emission from celestial sources. The range of radio frequencies or wavelengths is loosely defined by atmospheric opacity and by quantum noise in coherent amplifiers. Together they place the boundary be- tween radio and far-infrared astronomy at frequency ν ∼ 1 THz (1 THz ≡ 1012 Hz) or wavelength λ = c/ν ∼ 0.3 mm, where c ≈ 3 × 1010 cm s−1 is the vacuum speed of light. The Earth’s ionosphere sets a low-frequency limit to ground-based radio astronomy by reflecting extraterrestrial radio waves with frequencies below ν ∼ 10 MHz (λ ∼ 30 m), and the ionized interstellar medium of our own Galaxy absorbs extragalactic radio signals below ν ∼ 2 MHz. The radio band is very broad logarithmically: it spans the five decades between 10 MHz and 1 THz at the low-frequency end of the electromagnetic spectrum. Nearly everything emits radio waves at some level, via a wide variety of emission mechanisms. Few astronomical radio sources are obscured because radio waves can penetrate interstellar dust clouds and Compton-thick layers of neutral gas. Because only optical and radio observations can be made from the ground, pioneering radio astronomers had the first opportunity to explore a “parallel universe” containing unexpected new objects such as radio galaxies, quasars, and pulsars, plus very cold sources such as interstellar molecular clouds and the cosmic microwave background radiation from the big bang itself. -
The Jansky Very Large Array
The Jansky Very Large Array To ny B e a s l e y National Radio Astronomy Observatory Atacama Large Millimeter/submillimeter Array Expanded Very Large Array Robert C. Byrd Green Bank Telescope Very Long Baseline Array EVLA EVLA Project Overview • The EVLA Project is a major upgrade of the Very Large Array. Upgraded array JanskyVLA • The fundamental goal is to improve all the observational capabilities of the VLA (except spatial resolution) by at least an order of magnitude • The project will be completed by early 2013, on budget and schedule. • Key aspect: This is a leveraged project – building upon existing infrastructure of the VLA. Key EVLA Project Goals EVLA • Full frequency coverage from 1 to 50 GHz. – Provided by 8 frequency bands with cryogenic receivers. • Up to 8 GHz instantaneous bandwidth – All digital design to maximize instrumental stability and repeatability. • New correlator with 8 GHz/polarization capability – Designed, funded, and constructed by HIA/DRAO – Unprecedented flexibility in matching resources to attain science goals. • <3 Jy/beam (1-, 1-Hr) continuum sensitivity at most bands. • <1 mJy/beam (1-, 1-Hr, 1-km/sec) line sensitivity at most bands. • Noise-limited, full-field imaging in all Stokes parameters for most observational fields. Jansky VLA-VLA Comparison EVLA Parameter VLA EVLA Factor Current Point Source Cont. Sensitivity (1,12hr.) 10 Jy 1 Jy 10 2 Jy Maximum BW in each polarization 0.1 GHz 8 GHz 80 2 GHz # of frequency channels at max. BW 16 16,384 1024 4096 Maximum number of freq. channels 512 4,194,304 8192 12,288 Coarsest frequency resolution 50 MHz 2 MHz 25 2 MHz Finest frequency resolution 381 Hz 0.12 Hz 3180 .12 Hz # of full-polarization spectral windows 2 64 32 16 (Log) Frequency Coverage (1 – 50 GHz) 22% 100% 5 100% EVLA Project Status EVLA • Installation of new wideband receivers now complete at: – 4 – 8 GHz (C-Band) – 18 – 27 GHz (K-Band) – 27 – 40 GHz (Ka-Band) – 40 – 50 GHz (Q-Band) • Installation of remaining four bands completed late-2012: – 1 – 2 GHz (L-Band) 19 now, completed end of 2012.