ON the INCLINATION DEPENDENCE of EXOPLANET PHASE SIGNATURES Stephen R
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Predicting Exoplanet Observability in Time, Contrast, Separation, and Polarization, in Scattered Light
A&A 578, A59 (2015) Astronomy DOI: 10.1051/0004-6361/201424202 & c ESO 2015 Astrophysics Predicting exoplanet observability in time, contrast, separation, and polarization, in scattered light Guillaume Schworer1;2 and Peter G. Tuthill2 1 LESIA, Observatoire de Paris, CNRS/UMR 8109, UPMC, Université Paris Diderot, 5 place J. Janssen, 92195 Meudon, France e-mail: [email protected] 2 Sydney Institute for Astronomy (SIfA), School of Physics, The University of Sydney, NSW 2006, Australia Received 14 May 2014 / Accepted 14 March 2015 ABSTRACT Context. Polarimetry is one of the keys to enhanced direct imaging of exoplanets. Not only does it deliver a differential observable pro- viding extra contrast, but when coupled with spectroscopy, it also reveals valuable information on the exoplanetary atmospheric com- position. Nevertheless, angular separation and contrast ratio to the host-star make for extremely challenging observation. Producing detailed predictions for exactly how the expected signals should appear is of critical importance for the designs and observational strategies of tomorrow’s telescopes. Aims. We aim at accurately determining the magnitudes and evolution of the main observational signatures for imaging an exoplanet: separation, contrast ratio to the host-star and polarization as a function of the orbital geometry and the reflectance parameters of the exoplanet. Methods. These parameters were used to construct a polarized-reflectance model based on the input of orbital parameters and two albedo values. The model is able to calculate a variety of observational predictions for exoplanets at any orbital time. Results. The inter-dependency of the three main observational criteria – angular separation, contrast ratio, polarization – result in a complex time-evolution of the system. -
University of California Santa Cruz
UNIVERSITY OF CALIFORNIA SANTA CRUZ BENEATH THE SURFACE OF GIANT PLANETS: EVOLUTION, STRUCTURE, AND COMPOSITION A dissertation submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in ASTRONOMY AND ASTROPHYSICS by Neil L Kelly Miller March 2013 The Dissertation of Neil L Kelly Miller is approved: Jonathan Fortney, Chair Professor D. Lin Professor P. Garaud Professor P. Bodenheimer Tyrus Miller Vice Provost and Dean of Graduate Studies Copyright c by Neil L Kelly Miller 2013 Table of Contents List of Figures v List of Tables xii Abstract xiii Dedication xv Acknowledgments xvi 1 Introduction 1 1.1 TheSolarSystemGiantPlanets . 3 1.2 FromIndividualSystemstoSamples . 4 1.3 Physical Processes in the Evolution of Giant Planets . ........ 8 2 Coupled Thermal and Tidal Evolution of Giant Expolanets 14 2.1 Abstract.................................... 14 2.2 Introduction.................................. 15 2.3 Model:Introduction ............................. 21 2.4 Model:Implementation ........................... 23 2.5 GeneralExamples .............................. 29 2.6 Results..................................... 37 2.6.1 SpecificSystems ........................... 37 2.6.2 SummaryforSuite .......................... 47 ′ 2.6.3 High Qs cases............................. 56 2.7 Discussion&Conclusions . 59 3 Applications of Giant Planet Thermal Evolution Model 74 3.1 Introduction.................................. 74 3.2 CoRoT-2b: Young Planet With Potentially Tidally Inflated Radius . 75 3.3 CoRoT-7b: Potential Evaporative Mass Loss Scenario . ....... 78 3.3.1 EvaporativeMassLossModel. 80 iii 3.3.2 PlanetEvolution ........................... 82 3.4 Kepler11 ................................... 82 3.4.1 Formation and Compositions of Kepler 11 Planets . 82 4 Measuring the Heavy Element Composition of Giant Exoplanets with Lower Irradiation 86 4.1 Abstract.................................... 86 4.2 Introduction.................................. 87 4.3 ModelandMethod............................. -
Exoplanet Characterization with Nirspec
Exoplanet Characterization with NIRSpec Jeff Valenti (STScI), Stephan Birkmann (ESA) Bernhard Dorner (MPIA) 1. Coupling optics 1 2. Fore optics 3. Filters 4. Focus 8 3 5. Apertures 6 4 6. Collimator 9 7. Gratings 7 5 2 8. Camera 9. Detectors 10. Lamps 10 1 NIRSpec Apertures Aperture Spectral Spatial S1600 1.6” 1.6” S400 0.4” 3.65” S200 0.2” 3.2” IFU 36 x 0.1” 3.6” MSA 2 x 95” 2 x 87” The S1600 aperture was designed for exoplanet observations 2 Noise Due to Jitter 1σ Jitter Jitter of 7 mas causes relative noise of 4 x 10-5 From PhD thesis Bernhard Dorner 3 NIRSpec Optical Configurations Grating Filter Wavelengths Resolution PRISM CLEAR 0.6 – 5.0 30 – 300 “100” F070LP 0.7 – 1.2 500 – 850 G140M F100LP 1.0 – 1.8 “1000” G235M F170LP 1.7 – 3.0 700 – 1300 G395M F290LP 2.9 – 5.0 F070LP 0.7 – 1.2 1300 – 2300 G140H F100LP 1.0 – 1.8 “2700” G235H F170LP 1.7 – 3.0 1900 – 3600 G395H F290LP 2.9 – 5.0 4 http://www.cosmos.esa.int/web/jwst/nirspec-performances 5 6 http://www.cosmos.esa.int/web/jwst/nirspec-performances Example of High-Resolution Model Spectra G395H Figure 4b of Burrows, Budaj, & Hubeny (2008) 7 Thermal Emission from a Hot Jupiter Adapted from Figure 4b of Burrows, Budaj, & Hubeny (2008) 8 Integrations and Exposures " An “exposure” is a sequence of integrations. " An “integration” is a sequence of groups, sampled up-the-ramp " One or more resets between integrations, but no other overheads " Currently using pixel-by-pixel resets, but row-by-row possible 9 Subarrays NX NY Frame time (s) Notes 2048 512 10.74 Full frame, 4 amps 2048 256 5.49 -
Transit Timing Analysis of the Hot Jupiters WASP-43B and WASP-46B and the Super Earth Gj1214b
Transit timing analysis of the hot Jupiters WASP-43b and WASP-46b and the super Earth GJ1214b Mathias Polfliet Promotors: Michaël Gillon, Maarten Baes 1 Abstract Transit timing analysis is proving to be a promising method to detect new planetary partners in systems which already have known transiting planets, particularly in the orbital resonances of the system. In these resonances we might be able to detect Earth-mass objects well below the current detection and even theoretical (due to stellar variability) thresholds of the radial velocity method. We present four new transits for WASP-46b, four new transits for WASP-43b and eight new transits for GJ1214b observed with the robotic telescope TRAPPIST located at ESO La Silla Observatory, Chile. Modelling the data was done using several Markov Chain Monte Carlo (MCMC) simulations of the new transits with old data and a collection of transit timings for GJ1214b from published papers. For the hot Jupiters this lead to a general increase in accuracy for the physical parameters of the system (for the mass and period we found: 2.034±0.052 MJup and 0.81347460±0.00000048 days and 2.03±0.13 MJup and 1.4303723±0.0000011 days for WASP-43b and WASP-46b respectively). For GJ1214b this was not the case given the limited photometric precision of TRAPPIST. The additional timings however allowed us to constrain the period to 1.580404695±0.000000084 days and the RMS of the TTVs to 16 seconds. We investigated given systems for Transit Timing Variations (TTVs) and variations in the other transit parameters and found no significant (3sv) deviations. -
THE MASS of KOI-94D and a RELATION for PLANET RADIUS, MASS, and INCIDENT FLUX∗
The Astrophysical Journal, 768:14 (19pp), 2013 May 1 doi:10.1088/0004-637X/768/1/14 C 2013. The American Astronomical Society. All rights reserved. Printed in the U.S.A. THE MASS OF KOI-94d AND A RELATION FOR PLANET RADIUS, MASS, AND INCIDENT FLUX∗ Lauren M. Weiss1,12, Geoffrey W. Marcy1, Jason F. Rowe2, Andrew W. Howard3, Howard Isaacson1, Jonathan J. Fortney4, Neil Miller4, Brice-Olivier Demory5, Debra A. Fischer6, Elisabeth R. Adams7, Andrea K. Dupree7, Steve B. Howell2, Rea Kolbl1, John Asher Johnson8, Elliott P. Horch9, Mark E. Everett10, Daniel C. Fabrycky11, and Sara Seager5 1 B-20 Hearst Field Annex, Astronomy Department, University of California, Berkeley, Berkeley, CA 94720, USA; [email protected] 2 NASA Ames Research Center, Moffett Field, CA 94035, USA 3 Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822, USA 4 Department of Astronomy & Astrophysics, University of California, Santa Cruz, 1156 High Street, 275 Interdisciplinary Sciences Building (ISB), Santa Cruz, CA 95064, USA 5 Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA 6 Department of Astronomy, Yale University, P.O. Box 208101, New Haven, CT 06510-8101, USA 7 Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138, USA 8 California Institute of Technology, 1216 E. California Blvd., Pasadena, CA 91106, USA 9 Southern Connecticut State University, Department of Physics, 501 Crescent St., New Haven, CT 06515, USA 10 National Optical Astronomy Observatory, 950 N. Cherry Ave, Tucson, AZ 85719, USA 11 The Department of Astronomy and Astrophysics, University of Chicago, 5640 S. -
Nested Sampling
Probabilistic Source Detection Farhan Feroz [email protected] Cavendish Astrophysics Source/Object Detection: Problem Definition • Aim: Detect and characterize discrete sources in a background • Each source described by a template f(p) with parameters p. • With source and noise contributions being additive and Ns source Ns d=++ bq() nr ()∑ f ( pk ) k =1 • Inference goal: Use data d to constrain source parameters Ns, pk (k = 1, 2, …, Ns). Margnialize over background and noise parameters (q and r). Probabilistic Source/Object Detection • Problems in Object Detection – Identification – Quantifying Detection – Characterization Textures in CMB Bayesian Parameter Estimation • Collect a set of N data points Di (i = 1, 2, …, N), denoted collectively as data vector D. • Propose some model (or hypothesis) H for the data, depending on a set of M parameter θi (i = 1, 2, …, N), denoted collectively as parameter vector θ. • Bayes’ Theorem: Likelihood Prior P(D | θ, H )P(θ | H ) L(θ)π(θ) P(θ | D, H ) = → P(θ) = P(D | H) Z Posterior Evidence • Parameter Estimation: P(θ) α L(θ)π(θ) posterior α likelihood x prior Bayesian Model Selection P(D | θ, H )P(θ | H ) P(D | H )P(H ) P(θ | D, H ) = → P(H | D) = P(D | H) P(D) Bayes Factor • Consider two models H0 and H1 Prior P(H | D) P(D | H )P(H ) Z P(H ) Odds R = 1 = 1 1 = 1 1 P(H 0 | D) P(D | H 0 )P(H 0 ) Z0 P(H 0 ) • Bayesian Evidence Z = P(D|H) = ∫ L ( θ ) π ( θ ) d θ plays the central role in Bayesian Model Selection. -
Naming the Extrasolar Planets
Naming the extrasolar planets W. Lyra Max Planck Institute for Astronomy, K¨onigstuhl 17, 69177, Heidelberg, Germany [email protected] Abstract and OGLE-TR-182 b, which does not help educators convey the message that these planets are quite similar to Jupiter. Extrasolar planets are not named and are referred to only In stark contrast, the sentence“planet Apollo is a gas giant by their assigned scientific designation. The reason given like Jupiter” is heavily - yet invisibly - coated with Coper- by the IAU to not name the planets is that it is consid- nicanism. ered impractical as planets are expected to be common. I One reason given by the IAU for not considering naming advance some reasons as to why this logic is flawed, and sug- the extrasolar planets is that it is a task deemed impractical. gest names for the 403 extrasolar planet candidates known One source is quoted as having said “if planets are found to as of Oct 2009. The names follow a scheme of association occur very frequently in the Universe, a system of individual with the constellation that the host star pertains to, and names for planets might well rapidly be found equally im- therefore are mostly drawn from Roman-Greek mythology. practicable as it is for stars, as planet discoveries progress.” Other mythologies may also be used given that a suitable 1. This leads to a second argument. It is indeed impractical association is established. to name all stars. But some stars are named nonetheless. In fact, all other classes of astronomical bodies are named. -
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A&A 562, A92 (2014) Astronomy DOI: 10.1051/0004-6361/201321493 & c ESO 2014 Astrophysics Li depletion in solar analogues with exoplanets Extending the sample, E. Delgado Mena1,G.Israelian2,3, J. I. González Hernández2,3,S.G.Sousa1,2,4, A. Mortier1,4,N.C.Santos1,4, V. Zh. Adibekyan1, J. Fernandes5, R. Rebolo2,3,6,S.Udry7, and M. Mayor7 1 Centro de Astrofísica, Universidade do Porto, Rua das Estrelas, 4150-762 Porto, Portugal e-mail: [email protected] 2 Instituto de Astrofísica de Canarias, C/ Via Lactea s/n, 38200 La Laguna, Tenerife, Spain 3 Departamento de Astrofísica, Universidad de La Laguna, 38205 La Laguna, Tenerife, Spain 4 Departamento de Física e Astronomia, Faculdade de Ciências, Universidade do Porto, 4169-007 Porto, Portugal 5 CGUC, Department of Mathematics and Astronomical Observatory, University of Coimbra, 3049 Coimbra, Portugal 6 Consejo Superior de Investigaciones Científicas, CSIC, Spain 7 Observatoire de Genève, Université de Genève, 51 ch. des Maillettes, 1290 Sauverny, Switzerland Received 18 March 2013 / Accepted 25 November 2013 ABSTRACT Aims. We want to study the effects of the formation of planets and planetary systems on the atmospheric Li abundance of planet host stars. Methods. In this work we present new determinations of lithium abundances for 326 main sequence stars with and without planets in the Teff range 5600–5900 K. The 277 stars come from the HARPS sample, the remaining targets were observed with a variety of high-resolution spectrographs. Results. We confirm significant differences in the Li distribution of solar twins (Teff = T ± 80 K, log g = log g ± 0.2and[Fe/H] = [Fe/H] ±0.2): the full sample of planet host stars (22) shows Li average values lower than “single” stars with no detected planets (60). -
Arxiv:2105.11583V2 [Astro-Ph.EP] 2 Jul 2021 Keck-HIRES, APF-Levy, and Lick-Hamilton Spectrographs
Draft version July 6, 2021 Typeset using LATEX twocolumn style in AASTeX63 The California Legacy Survey I. A Catalog of 178 Planets from Precision Radial Velocity Monitoring of 719 Nearby Stars over Three Decades Lee J. Rosenthal,1 Benjamin J. Fulton,1, 2 Lea A. Hirsch,3 Howard T. Isaacson,4 Andrew W. Howard,1 Cayla M. Dedrick,5, 6 Ilya A. Sherstyuk,1 Sarah C. Blunt,1, 7 Erik A. Petigura,8 Heather A. Knutson,9 Aida Behmard,9, 7 Ashley Chontos,10, 7 Justin R. Crepp,11 Ian J. M. Crossfield,12 Paul A. Dalba,13, 14 Debra A. Fischer,15 Gregory W. Henry,16 Stephen R. Kane,13 Molly Kosiarek,17, 7 Geoffrey W. Marcy,1, 7 Ryan A. Rubenzahl,1, 7 Lauren M. Weiss,10 and Jason T. Wright18, 19, 20 1Cahill Center for Astronomy & Astrophysics, California Institute of Technology, Pasadena, CA 91125, USA 2IPAC-NASA Exoplanet Science Institute, Pasadena, CA 91125, USA 3Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, CA 94305, USA 4Department of Astronomy, University of California Berkeley, Berkeley, CA 94720, USA 5Cahill Center for Astronomy & Astrophysics, California Institute of Technology, Pasadena, CA 91125, USA 6Department of Astronomy & Astrophysics, The Pennsylvania State University, 525 Davey Lab, University Park, PA 16802, USA 7NSF Graduate Research Fellow 8Department of Physics & Astronomy, University of California Los Angeles, Los Angeles, CA 90095, USA 9Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125, USA 10Institute for Astronomy, University of Hawai`i, -
Direct Measure of Radiative and Dynamical Properties of an Exoplanet Atmosphere
DIRECT MEASURE OF RADIATIVE AND DYNAMICAL PROPERTIES OF AN EXOPLANET ATMOSPHERE The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Wit, Julien de, et al. “DIRECT MEASURE OF RADIATIVE AND DYNAMICAL PROPERTIES OF AN EXOPLANET ATMOSPHERE.” The Astrophysical Journal, vol. 820, no. 2, Mar. 2016, p. L33. © 2016 The American Astronomical Society. As Published http://dx.doi.org/10.3847/2041-8205/820/2/L33 Publisher American Astronomical Society Version Final published version Citable link http://hdl.handle.net/1721.1/114269 Terms of Use Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. The Astrophysical Journal Letters, 820:L33 (6pp), 2016 April 1 doi:10.3847/2041-8205/820/2/L33 © 2016. The American Astronomical Society. All rights reserved. DIRECT MEASURE OF RADIATIVE AND DYNAMICAL PROPERTIES OF AN EXOPLANET ATMOSPHERE Julien de Wit1, Nikole K. Lewis2, Jonathan Langton3, Gregory Laughlin4, Drake Deming5, Konstantin Batygin6, and Jonathan J. Fortney4 1 Department of Earth, Atmospheric and Planetary Sciences, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA 2 Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA 3 Department of Physics, Principia College, Elsah, IL 62028, USA 4 Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064, USA 5 Department of Astronomy, University of Maryland at College Park, College Park, MD 20742, USA 6 Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125, USA Received 2016 January 28; accepted 2016 February 18; published 2016 March 28 ABSTRACT Two decades after the discovery of 51Pegb, the formation processes and atmospheres of short-period gas giants remain poorly understood. -
Arxiv:0809.1275V2
How eccentric orbital solutions can hide planetary systems in 2:1 resonant orbits Guillem Anglada-Escud´e1, Mercedes L´opez-Morales1,2, John E. Chambers1 [email protected], [email protected], [email protected] ABSTRACT The Doppler technique measures the reflex radial motion of a star induced by the presence of companions and is the most successful method to detect ex- oplanets. If several planets are present, their signals will appear combined in the radial motion of the star, leading to potential misinterpretations of the data. Specifically, two planets in 2:1 resonant orbits can mimic the signal of a sin- gle planet in an eccentric orbit. We quantify the implications of this statistical degeneracy for a representative sample of the reported single exoplanets with available datasets, finding that 1) around 35% percent of the published eccentric one-planet solutions are statistically indistinguishible from planetary systems in 2:1 orbital resonance, 2) another 40% cannot be statistically distinguished from a circular orbital solution and 3) planets with masses comparable to Earth could be hidden in known orbital solutions of eccentric super-Earths and Neptune mass planets. Subject headings: Exoplanets – Orbital dynamics – Planet detection – Doppler method arXiv:0809.1275v2 [astro-ph] 25 Nov 2009 Introduction Most of the +300 exoplanets found to date have been discovered using the Doppler tech- nique, which measures the reflex motion of the host star induced by the planets (Mayor & Queloz 1995; Marcy & Butler 1996). The diverse characteristics of these exoplanets are somewhat surprising. Many of them are similar in mass to Jupiter, but orbit much closer to their 1Carnegie Institution of Washington, Department of Terrestrial Magnetism, 5241 Broad Branch Rd. -
Exoplanet.Eu Catalog Page 1 # Name Mass Star Name
exoplanet.eu_catalog # name mass star_name star_distance star_mass OGLE-2016-BLG-1469L b 13.6 OGLE-2016-BLG-1469L 4500.0 0.048 11 Com b 19.4 11 Com 110.6 2.7 11 Oph b 21 11 Oph 145.0 0.0162 11 UMi b 10.5 11 UMi 119.5 1.8 14 And b 5.33 14 And 76.4 2.2 14 Her b 4.64 14 Her 18.1 0.9 16 Cyg B b 1.68 16 Cyg B 21.4 1.01 18 Del b 10.3 18 Del 73.1 2.3 1RXS 1609 b 14 1RXS1609 145.0 0.73 1SWASP J1407 b 20 1SWASP J1407 133.0 0.9 24 Sex b 1.99 24 Sex 74.8 1.54 24 Sex c 0.86 24 Sex 74.8 1.54 2M 0103-55 (AB) b 13 2M 0103-55 (AB) 47.2 0.4 2M 0122-24 b 20 2M 0122-24 36.0 0.4 2M 0219-39 b 13.9 2M 0219-39 39.4 0.11 2M 0441+23 b 7.5 2M 0441+23 140.0 0.02 2M 0746+20 b 30 2M 0746+20 12.2 0.12 2M 1207-39 24 2M 1207-39 52.4 0.025 2M 1207-39 b 4 2M 1207-39 52.4 0.025 2M 1938+46 b 1.9 2M 1938+46 0.6 2M 2140+16 b 20 2M 2140+16 25.0 0.08 2M 2206-20 b 30 2M 2206-20 26.7 0.13 2M 2236+4751 b 12.5 2M 2236+4751 63.0 0.6 2M J2126-81 b 13.3 TYC 9486-927-1 24.8 0.4 2MASS J11193254 AB 3.7 2MASS J11193254 AB 2MASS J1450-7841 A 40 2MASS J1450-7841 A 75.0 0.04 2MASS J1450-7841 B 40 2MASS J1450-7841 B 75.0 0.04 2MASS J2250+2325 b 30 2MASS J2250+2325 41.5 30 Ari B b 9.88 30 Ari B 39.4 1.22 38 Vir b 4.51 38 Vir 1.18 4 Uma b 7.1 4 Uma 78.5 1.234 42 Dra b 3.88 42 Dra 97.3 0.98 47 Uma b 2.53 47 Uma 14.0 1.03 47 Uma c 0.54 47 Uma 14.0 1.03 47 Uma d 1.64 47 Uma 14.0 1.03 51 Eri b 9.1 51 Eri 29.4 1.75 51 Peg b 0.47 51 Peg 14.7 1.11 55 Cnc b 0.84 55 Cnc 12.3 0.905 55 Cnc c 0.1784 55 Cnc 12.3 0.905 55 Cnc d 3.86 55 Cnc 12.3 0.905 55 Cnc e 0.02547 55 Cnc 12.3 0.905 55 Cnc f 0.1479 55