The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge

The PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ( M _* ), star formation rate (SFR), stellar metallicity ( Z ), and stellar age ( t _age ), for <10 million galaxies of the Dark Energy Spectroscopic Instrume...
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Autor*in:	ChangHoon Hahn [verfasserIn] K. J. Kwon [verfasserIn] Rita Tojeiro [verfasserIn] Malgorzata Siudek [verfasserIn] Rebecca E. A. Canning [verfasserIn] Mar Mezcua [verfasserIn] Jeremy L. Tinker [verfasserIn] David Brooks [verfasserIn] Peter Doel [verfasserIn] Kevin Fanning [verfasserIn] Enrique Gaztañaga [verfasserIn] Robert Kehoe [verfasserIn] Martin Landriau [verfasserIn] Aaron Meisner [verfasserIn] John Moustakas [verfasserIn] Claire Poppett [verfasserIn] Gregory Tarle [verfasserIn] Benjamin Weiner [verfasserIn] Hu Zou [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Galactic and extragalactic astronomy Galaxies Galaxy spectroscopy Redshift surveys Spectrophotometry Spectral energy distribution

Übergeordnetes Werk:	In: The Astrophysical Journal - IOP Publishing, 2022, 945(2023), 1, p 16
Übergeordnetes Werk:	volume:945 ; year:2023 ; number:1, p 16

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3847/1538-4357/ac8983

Katalog-ID:	DOAJ089160029

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allfields	10.3847/1538-4357/ac8983 doi (DE-627)DOAJ089160029 (DE-599)DOAJ031b60c5ad6a4c26bdc21f8431bf68e0 DE-627 ger DE-627 rakwb eng QB460-466 ChangHoon Hahn verfasserin aut The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ( M _* ), star formation rate (SFR), stellar metallicity ( Z ), and stellar age ( t _age ), for <10 million galaxies of the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, the neural emulator for the model, and the Bayesian inference framework of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-Galaxies semi-analytic model. We compare the inferred galaxy properties to the true values of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true M _* , SFR, Z , and t _age of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors, which we characterize in detail. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses. https://github.com/changhoonhahn/provabgs/ Galactic and extragalactic astronomy Galaxies Galaxy spectroscopy Redshift surveys Spectrophotometry Spectral energy distribution Astrophysics K. J. Kwon verfasserin aut Rita Tojeiro verfasserin aut Malgorzata Siudek verfasserin aut Rebecca E. A. Canning verfasserin aut Mar Mezcua verfasserin aut Jeremy L. Tinker verfasserin aut David Brooks verfasserin aut Peter Doel verfasserin aut Kevin Fanning verfasserin aut Enrique Gaztañaga verfasserin aut Robert Kehoe verfasserin aut Martin Landriau verfasserin aut Aaron Meisner verfasserin aut John Moustakas verfasserin aut Claire Poppett verfasserin aut Gregory Tarle verfasserin aut Benjamin Weiner verfasserin aut Hu Zou verfasserin aut In The Astrophysical Journal IOP Publishing, 2022 945(2023), 1, p 16 (DE-627)269019219 (DE-600)1473835-1 15384357 nnns volume:945 year:2023 number:1, p 16 https://doi.org/10.3847/1538-4357/ac8983 kostenfrei https://doaj.org/article/031b60c5ad6a4c26bdc21f8431bf68e0 kostenfrei https://doi.org/10.3847/1538-4357/ac8983 kostenfrei https://doaj.org/toc/1538-4357 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2088 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 945 2023 1, p 16
spelling	10.3847/1538-4357/ac8983 doi (DE-627)DOAJ089160029 (DE-599)DOAJ031b60c5ad6a4c26bdc21f8431bf68e0 DE-627 ger DE-627 rakwb eng QB460-466 ChangHoon Hahn verfasserin aut The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ( M _* ), star formation rate (SFR), stellar metallicity ( Z ), and stellar age ( t _age ), for <10 million galaxies of the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, the neural emulator for the model, and the Bayesian inference framework of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-Galaxies semi-analytic model. We compare the inferred galaxy properties to the true values of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true M _* , SFR, Z , and t _age of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors, which we characterize in detail. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses. https://github.com/changhoonhahn/provabgs/ Galactic and extragalactic astronomy Galaxies Galaxy spectroscopy Redshift surveys Spectrophotometry Spectral energy distribution Astrophysics K. J. Kwon verfasserin aut Rita Tojeiro verfasserin aut Malgorzata Siudek verfasserin aut Rebecca E. A. Canning verfasserin aut Mar Mezcua verfasserin aut Jeremy L. Tinker verfasserin aut David Brooks verfasserin aut Peter Doel verfasserin aut Kevin Fanning verfasserin aut Enrique Gaztañaga verfasserin aut Robert Kehoe verfasserin aut Martin Landriau verfasserin aut Aaron Meisner verfasserin aut John Moustakas verfasserin aut Claire Poppett verfasserin aut Gregory Tarle verfasserin aut Benjamin Weiner verfasserin aut Hu Zou verfasserin aut In The Astrophysical Journal IOP Publishing, 2022 945(2023), 1, p 16 (DE-627)269019219 (DE-600)1473835-1 15384357 nnns volume:945 year:2023 number:1, p 16 https://doi.org/10.3847/1538-4357/ac8983 kostenfrei https://doaj.org/article/031b60c5ad6a4c26bdc21f8431bf68e0 kostenfrei https://doi.org/10.3847/1538-4357/ac8983 kostenfrei https://doaj.org/toc/1538-4357 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2088 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 945 2023 1, p 16
allfields_unstemmed	10.3847/1538-4357/ac8983 doi (DE-627)DOAJ089160029 (DE-599)DOAJ031b60c5ad6a4c26bdc21f8431bf68e0 DE-627 ger DE-627 rakwb eng QB460-466 ChangHoon Hahn verfasserin aut The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ( M _* ), star formation rate (SFR), stellar metallicity ( Z ), and stellar age ( t _age ), for <10 million galaxies of the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, the neural emulator for the model, and the Bayesian inference framework of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-Galaxies semi-analytic model. We compare the inferred galaxy properties to the true values of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true M _* , SFR, Z , and t _age of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors, which we characterize in detail. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses. https://github.com/changhoonhahn/provabgs/ Galactic and extragalactic astronomy Galaxies Galaxy spectroscopy Redshift surveys Spectrophotometry Spectral energy distribution Astrophysics K. J. Kwon verfasserin aut Rita Tojeiro verfasserin aut Malgorzata Siudek verfasserin aut Rebecca E. A. Canning verfasserin aut Mar Mezcua verfasserin aut Jeremy L. Tinker verfasserin aut David Brooks verfasserin aut Peter Doel verfasserin aut Kevin Fanning verfasserin aut Enrique Gaztañaga verfasserin aut Robert Kehoe verfasserin aut Martin Landriau verfasserin aut Aaron Meisner verfasserin aut John Moustakas verfasserin aut Claire Poppett verfasserin aut Gregory Tarle verfasserin aut Benjamin Weiner verfasserin aut Hu Zou verfasserin aut In The Astrophysical Journal IOP Publishing, 2022 945(2023), 1, p 16 (DE-627)269019219 (DE-600)1473835-1 15384357 nnns volume:945 year:2023 number:1, p 16 https://doi.org/10.3847/1538-4357/ac8983 kostenfrei https://doaj.org/article/031b60c5ad6a4c26bdc21f8431bf68e0 kostenfrei https://doi.org/10.3847/1538-4357/ac8983 kostenfrei https://doaj.org/toc/1538-4357 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2088 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 945 2023 1, p 16
allfieldsGer	10.3847/1538-4357/ac8983 doi (DE-627)DOAJ089160029 (DE-599)DOAJ031b60c5ad6a4c26bdc21f8431bf68e0 DE-627 ger DE-627 rakwb eng QB460-466 ChangHoon Hahn verfasserin aut The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ( M _* ), star formation rate (SFR), stellar metallicity ( Z ), and stellar age ( t _age ), for <10 million galaxies of the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, the neural emulator for the model, and the Bayesian inference framework of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-Galaxies semi-analytic model. We compare the inferred galaxy properties to the true values of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true M _* , SFR, Z , and t _age of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors, which we characterize in detail. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses. https://github.com/changhoonhahn/provabgs/ Galactic and extragalactic astronomy Galaxies Galaxy spectroscopy Redshift surveys Spectrophotometry Spectral energy distribution Astrophysics K. J. Kwon verfasserin aut Rita Tojeiro verfasserin aut Malgorzata Siudek verfasserin aut Rebecca E. A. Canning verfasserin aut Mar Mezcua verfasserin aut Jeremy L. Tinker verfasserin aut David Brooks verfasserin aut Peter Doel verfasserin aut Kevin Fanning verfasserin aut Enrique Gaztañaga verfasserin aut Robert Kehoe verfasserin aut Martin Landriau verfasserin aut Aaron Meisner verfasserin aut John Moustakas verfasserin aut Claire Poppett verfasserin aut Gregory Tarle verfasserin aut Benjamin Weiner verfasserin aut Hu Zou verfasserin aut In The Astrophysical Journal IOP Publishing, 2022 945(2023), 1, p 16 (DE-627)269019219 (DE-600)1473835-1 15384357 nnns volume:945 year:2023 number:1, p 16 https://doi.org/10.3847/1538-4357/ac8983 kostenfrei https://doaj.org/article/031b60c5ad6a4c26bdc21f8431bf68e0 kostenfrei https://doi.org/10.3847/1538-4357/ac8983 kostenfrei https://doaj.org/toc/1538-4357 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2088 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 945 2023 1, p 16
allfieldsSound	10.3847/1538-4357/ac8983 doi (DE-627)DOAJ089160029 (DE-599)DOAJ031b60c5ad6a4c26bdc21f8431bf68e0 DE-627 ger DE-627 rakwb eng QB460-466 ChangHoon Hahn verfasserin aut The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ( M _* ), star formation rate (SFR), stellar metallicity ( Z ), and stellar age ( t _age ), for <10 million galaxies of the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, the neural emulator for the model, and the Bayesian inference framework of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-Galaxies semi-analytic model. We compare the inferred galaxy properties to the true values of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true M _* , SFR, Z , and t _age of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors, which we characterize in detail. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses. https://github.com/changhoonhahn/provabgs/ Galactic and extragalactic astronomy Galaxies Galaxy spectroscopy Redshift surveys Spectrophotometry Spectral energy distribution Astrophysics K. J. Kwon verfasserin aut Rita Tojeiro verfasserin aut Malgorzata Siudek verfasserin aut Rebecca E. A. Canning verfasserin aut Mar Mezcua verfasserin aut Jeremy L. Tinker verfasserin aut David Brooks verfasserin aut Peter Doel verfasserin aut Kevin Fanning verfasserin aut Enrique Gaztañaga verfasserin aut Robert Kehoe verfasserin aut Martin Landriau verfasserin aut Aaron Meisner verfasserin aut John Moustakas verfasserin aut Claire Poppett verfasserin aut Gregory Tarle verfasserin aut Benjamin Weiner verfasserin aut Hu Zou verfasserin aut In The Astrophysical Journal IOP Publishing, 2022 945(2023), 1, p 16 (DE-627)269019219 (DE-600)1473835-1 15384357 nnns volume:945 year:2023 number:1, p 16 https://doi.org/10.3847/1538-4357/ac8983 kostenfrei https://doaj.org/article/031b60c5ad6a4c26bdc21f8431bf68e0 kostenfrei https://doi.org/10.3847/1538-4357/ac8983 kostenfrei https://doaj.org/toc/1538-4357 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2088 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 945 2023 1, p 16
language	English
source	In The Astrophysical Journal 945(2023), 1, p 16 volume:945 year:2023 number:1, p 16
sourceStr	In The Astrophysical Journal 945(2023), 1, p 16 volume:945 year:2023 number:1, p 16
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Galactic and extragalactic astronomy Galaxies Galaxy spectroscopy Redshift surveys Spectrophotometry Spectral energy distribution Astrophysics
isfreeaccess_bool	true
container_title	The Astrophysical Journal
authorswithroles_txt_mv	ChangHoon Hahn @@aut@@ K. J. Kwon @@aut@@ Rita Tojeiro @@aut@@ Malgorzata Siudek @@aut@@ Rebecca E. A. Canning @@aut@@ Mar Mezcua @@aut@@ Jeremy L. Tinker @@aut@@ David Brooks @@aut@@ Peter Doel @@aut@@ Kevin Fanning @@aut@@ Enrique Gaztañaga @@aut@@ Robert Kehoe @@aut@@ Martin Landriau @@aut@@ Aaron Meisner @@aut@@ John Moustakas @@aut@@ Claire Poppett @@aut@@ Gregory Tarle @@aut@@ Benjamin Weiner @@aut@@ Hu Zou @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	269019219
id	DOAJ089160029
language_de	englisch
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callnumber-first	Q - Science
author	ChangHoon Hahn
spellingShingle	ChangHoon Hahn misc QB460-466 misc Galactic and extragalactic astronomy misc Galaxies misc Galaxy spectroscopy misc Redshift surveys misc Spectrophotometry misc Spectral energy distribution misc Astrophysics The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge
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topic_title	QB460-466 The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge Galactic and extragalactic astronomy Galaxies Galaxy spectroscopy Redshift surveys Spectrophotometry Spectral energy distribution
topic	misc QB460-466 misc Galactic and extragalactic astronomy misc Galaxies misc Galaxy spectroscopy misc Redshift surveys misc Spectrophotometry misc Spectral energy distribution misc Astrophysics
topic_unstemmed	misc QB460-466 misc Galactic and extragalactic astronomy misc Galaxies misc Galaxy spectroscopy misc Redshift surveys misc Spectrophotometry misc Spectral energy distribution misc Astrophysics
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title	The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge
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title_full	The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge
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author_browse	ChangHoon Hahn K. J. Kwon Rita Tojeiro Malgorzata Siudek Rebecca E. A. Canning Mar Mezcua Jeremy L. Tinker David Brooks Peter Doel Kevin Fanning Enrique Gaztañaga Robert Kehoe Martin Landriau Aaron Meisner John Moustakas Claire Poppett Gregory Tarle Benjamin Weiner Hu Zou
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title_sort	desi probabilistic value-added bright galaxy survey (provabgs) mock challenge
callnumber	QB460-466
title_auth	The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge
abstract	The PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ( M _* ), star formation rate (SFR), stellar metallicity ( Z ), and stellar age ( t _age ), for <10 million galaxies of the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, the neural emulator for the model, and the Bayesian inference framework of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-Galaxies semi-analytic model. We compare the inferred galaxy properties to the true values of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true M _* , SFR, Z , and t _age of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors, which we characterize in detail. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses. https://github.com/changhoonhahn/provabgs/
abstractGer	The PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ( M _* ), star formation rate (SFR), stellar metallicity ( Z ), and stellar age ( t _age ), for <10 million galaxies of the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, the neural emulator for the model, and the Bayesian inference framework of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-Galaxies semi-analytic model. We compare the inferred galaxy properties to the true values of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true M _* , SFR, Z , and t _age of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors, which we characterize in detail. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses. https://github.com/changhoonhahn/provabgs/
abstract_unstemmed	The PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ( M _* ), star formation rate (SFR), stellar metallicity ( Z ), and stellar age ( t _age ), for <10 million galaxies of the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, the neural emulator for the model, and the Bayesian inference framework of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-Galaxies semi-analytic model. We compare the inferred galaxy properties to the true values of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true M _* , SFR, Z , and t _age of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors, which we characterize in detail. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses. https://github.com/changhoonhahn/provabgs/
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title_short	The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge
url	https://doi.org/10.3847/1538-4357/ac8983 https://doaj.org/article/031b60c5ad6a4c26bdc21f8431bf68e0 https://doaj.org/toc/1538-4357
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