Hierarchical Bayesian Inference of Photometric Redshifts with Stellar Population Synthesis Models
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H. Peiris | D. Mortlock | J. Alsing | B. Leistedt | J. Leja | Justin Alsing
[1] S. Charlot,et al. Star formation histories of UV-luminous galaxies at z ≃ 6.8: Implications for stellar mass assembly at early cosmic times , 2022, Monthly Notices of the Royal Astronomical Society.
[2] J. Newman,et al. Photometric Redshifts for Next-Generation Surveys , 2022, Annual Review of Astronomy and Astrophysics.
[3] Andrew P. Hearin,et al. Diffstar: A fully parametric physical model for galaxy assembly history , 2022, Monthly Notices of the Royal Astronomical Society.
[4] Peter Melchior,et al. Accelerated Bayesian SED Modeling Using Amortized Neural Posterior Estimation , 2022, The Astrophysical Journal.
[5] D. Foreman-Mackey,et al. A Bayesian Population Model for the Observed Dust Attenuation in Galaxies , 2022, The Astrophysical Journal.
[6] K. Heitmann,et al. Machine learning synthetic spectra for probabilistic redshift estimation: SYTH-Z , 2021, Monthly Notices of the Royal Astronomical Society.
[7] G. Zamorani,et al. COSMOS2020: A Panchromatic View of the Universe to z ∼ 10 from Two Complementary Catalogs , 2021, The Astrophysical Journal Supplement Series.
[8] Benjamin D. Johnson,et al. A New Census of the 0.2 < z < 3.0 Universe. II. The Star-forming Sequence , 2021, The Astrophysical Journal.
[9] R. Laureijs,et al. Euclid Preparation. XIV. The Complete Calibration of the Color–Redshift Relation (C3R2) Survey: Data Release 3 , 2021, The Astrophysical Journal Supplement Series.
[10] J. Frieman,et al. Dark Energy Survey Year 3 results: redshift calibration of the weak lensing source galaxies , 2020, Monthly Notices of the Royal Astronomical Society.
[11] J. Frieman,et al. Dark Energy Survey Year 3 Results: Clustering Redshifts -- Calibration of the Weak Lensing Source Redshift Distributions with redMaGiC and BOSS/eBOSS , 2020, 2012.08569.
[12] Benjamin D. Johnson,et al. Stellar Population Inference with Prospector , 2020, The Astrophysical Journal Supplement Series.
[13] H. Hoekstra,et al. The PAU Survey: an improved photo-z sample in the COSMOS field , 2020, Monthly Notices of the Royal Astronomical Society.
[14] G. Bernstein,et al. Propagating sample variance uncertainties in redshift calibration: simulations, theory, and application to the COSMOS2015 data , 2020, Monthly Notices of the Royal Astronomical Society.
[15] D. Gerdes,et al. The impact of spectroscopic incompleteness in direct calibration of redshift distributions for weak lensing surveys , 2020, Monthly Notices of the Royal Astronomical Society.
[16] Charlie Conroy,et al. SPECULATOR: Emulating Stellar Population Synthesis for Fast and Accurate Galaxy Spectra and Photometry , 2019, The Astrophysical Journal Supplement Series.
[17] G. Bernstein,et al. Redshift inference from the combination of galaxy colours and clustering in a hierarchical Bayesian model – Application to realistic N-body simulations , 2019, 1910.07127.
[18] Benjamin D. Johnson,et al. A New Census of the 0.2 < z < 3.0 Universe. I. The Stellar Mass Function , 2019, The Astrophysical Journal.
[19] M. Salvato,et al. MAGPHYS+photo-z: Constraining the Physical Properties of Galaxies with Unknown Redshifts , 2019, The Astrophysical Journal.
[20] Simon P. Wilson,et al. Estimating redshift distributions using hierarchical logistic Gaussian processes , 2019, Monthly Notices of the Royal Astronomical Society.
[21] Judith G. Cohen,et al. The Complete Calibration of the Color–Redshift Relation (C3R2) Survey: Analysis and Data Release 2 , 2019, The Astrophysical Journal.
[22] P. Schneider,et al. KiDS+VIKING-450: Cosmic shear tomography with optical and infrared data , 2018, Astronomy & Astrophysics.
[23] Benjamin D. Johnson,et al. An Older, More Quiescent Universe from Panchromatic SED Fitting of the 3D-HST Survey , 2018, Proceedings of the International Astronomical Union.
[24] David Alonso,et al. The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document , 2018, 1809.01669.
[25] A. Heavens,et al. Bayesian photometric redshifts of blended sources , 2018, Monthly Notices of the Royal Astronomical Society.
[26] G. Bernstein,et al. Redshift inference from the combination of galaxy colours and clustering in a hierarchical Bayesian model , 2018, Monthly Notices of the Royal Astronomical Society.
[27] D. Hogg,et al. Hierarchical Modeling and Statistical Calibration for Photometric Redshifts , 2018, The Astrophysical Journal.
[28] G. Lavaux,et al. Physical Bayesian modelling of the non-linear matter distribution: New insights into the nearby universe , 2018, Astronomy & Astrophysics.
[29] G. Hasinger,et al. The DEIMOS 10K Spectroscopic Survey Catalog of the COSMOS Field , 2018, 1803.09251.
[30] R. Davé,et al. Inferring the star formation histories of massive quiescent galaxies with bagpipes: evidence for multiple quenching mechanisms , 2017, Monthly Notices of the Royal Astronomical Society.
[31] B. Yanny,et al. Dark Energy Survey year 1 results: Cosmological constraints from galaxy clustering and weak lensing , 2017, Physical Review D.
[32] Andrew J. Connolly,et al. Photometric Redshifts with the LSST: Evaluating Survey Observing Strategies , 2017, 1706.09507.
[33] Daniel Masters,et al. The Complete Calibration of the Color–Redshift Relation (C3R2) Survey: Survey Overview and Data Release 1 , 2017, 1704.06665.
[34] Benjamin D. Johnson,et al. Nebular Continuum and Line Emission in Stellar Population Synthesis Models , 2016, 1611.08305.
[35] Ivan K. Baldry,et al. the-wizz: clustering redshift estimation for everyone , 2016, 1609.09085.
[36] Benjamin D. Johnson,et al. Deriving Physical Properties from Broadband Photometry with Prospector: Description of the Model and a Demonstration of its Accuracy Using 129 Galaxies in the Local Universe , 2016, 1609.09073.
[37] O. Fèvre,et al. THE COSMOS2015 CATALOG: EXPLORING THE 1 < z < 6 UNIVERSE WITH HALF A MILLION GALAXIES , 2016, 1604.02350.
[38] H. Peiris,et al. Hierarchical Bayesian inference of galaxy redshift distributions from photometric surveys , 2016, 1602.05960.
[39] C. A. Oxborrow,et al. Planck2015 results , 2015, Astronomy & Astrophysics.
[40] D. Foreman-Mackey,et al. python-fsps: Python bindings to FSPS (v0.1.1) , 2014 .
[41] R. J. Brunner,et al. TPZ: photometric redshift PDFs and ancillary information by using prediction trees and random forests , 2013, 1303.7269.
[42] T. Budavari,et al. Clustering-based redshift estimation: method and application to data , 2013, 1303.4722.
[43] Davis,et al. Recovering redshift distributions with cross-correlations: pushing the boundaries , 2013, 1303.0292.
[44] M. White,et al. On using angular cross-correlations to determine source redshift distributions , 2013, 1302.0857.
[45] Paolo Coppi,et al. EAZY: A Fast, Public Photometric Redshift Code , 2008, 0807.1533.
[46] Zeljko Ivezic,et al. AGN Dusty Tori. I. Handling of Clumpy Media , 2008, 0806.0511.
[47] Jeffrey A. Newman,et al. Calibrating Redshift Distributions beyond Spectroscopic Limits with Cross-Correlations , 2008, 0805.1409.
[48] S. Maddox,et al. zCOSMOS: A Large VLT/VIMOS Redshift Survey Covering 0 < z < 3 in the COSMOS Field , 2006, astro-ph/0612291.
[49] B. Draine,et al. Infrared Emission from Interstellar Dust. IV. The Silicate-Graphite-PAH Model in the Post-Spitzer Era , 2006, astro-ph/0608003.
[50] A. Connolly,et al. Using Galaxy Two-Point Correlation Functions to Determine the Redshift Distributions of Galaxies Binned by Photometric Redshift , 2006, astro-ph/0606098.
[51] B. Garilli,et al. Accurate photometric redshifts for the CFHT legacy survey calibrated using the VIMOS VLT deep survey , 2006, astro-ph/0603217.
[52] O. Lahav,et al. ANNz: Estimating Photometric Redshifts Using Artificial Neural Networks , 2003, astro-ph/0311058.
[53] G. Chabrier. Galactic Stellar and Substellar Initial Mass Function , 2003, astro-ph/0304382.
[54] S. M. Fall,et al. A Simple Model for the Absorption of Starlight by Dust in Galaxies , 2000, astro-ph/0003128.
[55] A. Kinney,et al. The Dust Content and Opacity of Actively Star-forming Galaxies , 1999, astro-ph/9911459.
[56] N. Benı́tez. Bayesian Photometric Redshift Estimation , 1998, astro-ph/9811189.
[57] Piero Madau,et al. Radiative transfer in a clumpy universe: The colors of high-redshift galaxies , 1995 .
[58] D. Alter. PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC , 2016 .