How to Measure Galaxy Star Formation Histories. II. Nonparametric Models
暂无分享,去创建一个
Benjamin D. Johnson | J. S. Dunlop | R. J. McLure | J. Dunlop | R. McLure | J. Speagle | C. Conroy | B. Johnson | J. Leja | A. Carnall | B. D. Johnson | A. C. Carnall | J. Leja | C. Conroy
[1] P. Hopkins,et al. MUFASA: Galaxy Formation Simulations With Meshless Hydrodynamics , 2016, 1604.01418.
[2] C. Conroy. Modeling the Panchromatic Spectral Energy Distributions of Galaxies , 2013, 1301.7095.
[3] M. Boquien,et al. Ultraviolet to infrared emission of z > 1 galaxies: Can we derive reliable star formation rates and stellar masses? , 2013, 1310.7712.
[4] R. Trotta. Bayes in the sky: Bayesian inference and model selection in cosmology , 2008, 0803.4089.
[5] A. Kinney,et al. The Dust Content and Opacity of Actively Star-forming Galaxies , 1999, astro-ph/9911459.
[6] P. Hopkins,et al. RECOVERING STELLAR POPULATION PROPERTIES AND REDSHIFTS FROM BROADBAND PHOTOMETRY OF SIMULATED GALAXIES: LESSONS FOR SED MODELING , 2009, 0901.4337.
[7] B. Draine,et al. Infrared Emission from Interstellar Dust. IV. The Silicate-Graphite-PAH Model in the Post-Spitzer Era , 2006, astro-ph/0608003.
[8] Eric Jones,et al. SciPy: Open Source Scientific Tools for Python , 2001 .
[9] V. Wild,et al. The VANDELS ESO public spectroscopic survey: Observations and first data release , 2018, Astronomy & Astrophysics.
[10] T. Yuan,et al. A massive, quiescent galaxy at a redshift of 3.717 , 2017, Nature.
[11] A. Dressler,et al. THE IMACS CLUSTER BUILDING SURVEY. IV. THE LOG-NORMAL STAR FORMATION HISTORY OF GALAXIES , 2013, 1303.3917.
[12] J. Silverman,et al. A HIGHLY CONSISTENT FRAMEWORK FOR THE EVOLUTION OF THE STAR-FORMING “MAIN SEQUENCE” FROM z ∼ 0–6 , 2014, 1405.2041.
[13] S. Bamford,et al. Galaxy And Mass Assembly: The G02 field, Herschel-ATLAS target selection and data release 3 , 2017, 1711.09139.
[14] A. Heavens,et al. Recovering galaxy star formation and metallicity histories from spectra using VESPA , 2007, 0704.0941.
[15] Jonathan R Goodman,et al. Ensemble samplers with affine invariance , 2010 .
[16] Daniel Foreman-Mackey,et al. emcee: The MCMC Hammer , 2012, 1202.3665.
[17] 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.
[18] H. Ferguson,et al. BREAKING THE CURVE WITH CANDELS: A BAYESIAN APPROACH TO REVEAL THE NON-UNIVERSALITY OF THE DUST-ATTENUATION LAW AT HIGH REDSHIFT , 2015, 1512.05396.
[19] M. Dickinson,et al. GALEX–SDSS–WISE LEGACY CATALOG (GSWLC): STAR FORMATION RATES, STELLAR MASSES, AND DUST ATTENUATIONS OF 700,000 LOW-REDSHIFT GALAXIES , 2016, 1610.00712.
[20] Heidelberg,et al. A census of metals and baryons in stars in the local universe , 2007, 0708.0533.
[21] M. Cappellari. Improving the full spectrum fitting method: accurate convolution with Gauss-Hermite functions , 2016, 1607.08538.
[22] D. Elbaz,et al. A simple model to interpret the ultraviolet, optical and infrared emission from galaxies , 2008, 0806.1020.
[23] C. Steidel,et al. THE CHARACTERISTIC STAR FORMATION HISTORIES OF GALAXIES AT REDSHIFTS z ∼ 2–7 , 2012, 1205.0555.
[24] G. Kauffmann,et al. First results from the IllustrisTNG simulations: the galaxy colour bimodality , 2017, 1707.03395.
[25] D. Foreman-Mackey,et al. python-fsps: Python bindings to FSPS (v0.1.1) , 2014 .
[26] T. Yuan,et al. Near infrared spectroscopy and star-formation histories of 3 ≤ z ≤ 4 quiescent galaxies , 2018, Astronomy & Astrophysics.
[27] S. Bamford,et al. GAMA: towards a physical understanding of galaxy formation , 2009, 0910.5123.
[28] A. Heavens,et al. The star formation histories of galaxies in the sloan digital sky survey , 2006, astro-ph/0608531.
[29] Samuel N. Leitner. ON THE LAST 10 BILLION YEARS OF STELLAR MASS GROWTH IN STAR-FORMING GALAXIES , 2011, 1108.0938.
[30] I. Paris,et al. STECMAP: STEllar Content from high-resolution galactic spectra via Maximum A Posteriori , 2005, astro-ph/0505209.
[31] R. Davé,et al. THE EVOLUTION OF STAR FORMATION HISTORIES OF QUIESCENT GALAXIES , 2016, 1609.03572.
[32] M. Dickinson,et al. Cosmic Star-Formation History , 1996, 1403.0007.
[33] 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.
[34] J. Skilling. Nested sampling for general Bayesian computation , 2006 .
[35] J. Cohn. Approximations to galaxy star formation rate histories: properties and uses of two examples , 2018, 1802.06197.
[36] S. Bamford,et al. Galaxy And Mass Assembly (GAMA): mass–size relations of z < 0.1 galaxies subdivided by Sérsic index, colour and morphology , 2014, 1411.6355.
[37] D. Elbaz,et al. Constraining the properties of AGN host galaxies with spectral energy distribution modelling , 2015, 1501.03672.
[38] P. Torrey,et al. Log-normal Star Formation Histories in Simulated and Observed Galaxies , 2017, 1701.02308.
[39] On the mass function of star clusters , 2002, astro-ph/0207514.
[40] A. Heavens,et al. Star formation and metallicity history of the SDSS galaxy survey: unlocking the fossil record , 2002, astro-ph/0211546.
[41] V. A. Bruce,et al. Characterizing the evolving K-band luminosity function using the UltraVISTA, CANDELS and HUDF surveys , 2016, 1610.06574.
[42] The Complete Star Formation History of the Universe , 2004, astro-ph/0403293.
[43] E. Gawiser,et al. SPECTRAL ENERGY DISTRIBUTION FITTING WITH MARKOV CHAIN MONTE CARLO: METHODOLOGY AND APPLICATION TO z = 3.1 Lyα-EMITTING GALAXIES , 2011, 1101.2215.
[44] A. Hopkins,et al. Galaxy And Mass Assembly: accurate panchromatic photometry from optical priors using lambdar , 2016 .
[45] N. Evans,et al. Star Formation in the Milky Way and Nearby Galaxies , 2012, 1204.3552.
[46] H. Rix,et al. On the importance of using appropriate spectral models to derive physical properties of galaxies at 0.7 < z < 2.8 , 2014, 1411.5689.
[47] H. Rix,et al. Simulating and interpreting deep observations in the Hubble Ultra Deep Field with theJWST/NIRSpec low-resolution ‘prism’ , 2017, Monthly Notices of the Royal Astronomical Society.
[48] Jordi Cepa,et al. ON STAR FORMATION RATES AND STAR FORMATION HISTORIES OF GALAXIES OUT TO z ∼ 3 , 2011, 1106.5502.
[49] V. Wild,et al. Stellar Populations of over 1000 z ∼ 0.8 Galaxies from LEGA-C: Ages and Star Formation Histories from Dn4000 and Hδ , 2018, 1802.06799.
[50] R. Wechsler,et al. THE RELATION BETWEEN STAR FORMATION RATE AND STELLAR MASS FOR GALAXIES AT 3.5 ⩽ z ⩽ 6.5 IN CANDELS , 2014, 1407.6012.
[51] Matthew Colless,et al. GAMA/G10-COSMOS/3D-HST: the 0 < z < 5 cosmic star formation history, stellar-mass, and dust-mass densities , 2017, 1710.06628.
[52] S. Bamford,et al. Galaxy And Mass Assembly: Stellar Mass Estimates , 2011, 1108.0635.
[53] V. Wild,et al. The VANDELS ESO public spectroscopic survey , 2018, 1803.07414.
[54] S. Charlot,et al. Modelling and interpreting spectral energy distributions of galaxies with BEAGLE , 2016, 1603.03037.
[55] J. A. Vázquez-Mata,et al. Galaxy And Mass Assembly (GAMA): Panchromatic Data Release (far-UV–far-IR) and the low-z energy budget , 2015, 1508.02076.
[56] P. Best,et al. Predicting dust extinction from the stellar mass of a galaxy , 2010, 1007.1145.
[57] E. Gawiser,et al. Reconstruction of Galaxy Star Formation Histories through SED Fitting:The Dense Basis Approach , 2017, 1702.04371.
[58] P. Dokkum,et al. RECONCILING THE OBSERVED STAR-FORMING SEQUENCE WITH THE OBSERVED STELLAR MASS FUNCTION , 2014, 1407.1842.
[59] Tucson,et al. Erratum: Recovering galaxy stellar population properties from broad-band spectral energy distribution fitting , 2012, 1203.3548.
[60] Iap,et al. The ages and metallicities of galaxies in the local universe , 2005, astro-ph/0506539.
[61] A. Fontana,et al. A CRITICAL ASSESSMENT OF STELLAR MASS MEASUREMENT METHODS , 2015, 1505.01501.
[62] J. Brinchmann,et al. Relative merits of different types of rest-frame optical observations to constrain galaxy physical parameters , 2012, 1201.0780.
[63] Paolo Coppi,et al. EAZY: A Fast, Public Photometric Redshift Code , 2008, 0807.1533.
[64] D. Elbaz,et al. Chasing passive galaxies in the early Universe: a critical analysis in CANDELS GOODS-South , 2017, 1709.00429.
[65] F. Feroz,et al. MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics , 2008, 0809.3437.
[66] H. Ferguson,et al. BIASES AND UNCERTAINTIES IN PHYSICAL PARAMETER ESTIMATES OF LYMAN BREAK GALAXIES FROM BROADBAND PHOTOMETRY , 2008, 0812.5111.
[67] J. Dunlop,et al. A robust sample of galaxies at redshifts 6.0 , 2011, 1102.4881.
[68] D. Elbaz,et al. The SFR-M ∗ main sequence archetypal star-formation history and analytical models , 2017, 1706.08531.
[69] Edinburgh,et al. The evolution of post-starburst galaxies from z=2 to 0.5 , 2016, 1608.00588.
[70] S. E. Persson,et al. GALAXY STELLAR MASS FUNCTIONS FROM ZFOURGE/CANDELS: AN EXCESS OF LOW-MASS GALAXIES SINCE z = 2 AND THE RAPID BUILDUP OF QUIESCENT GALAXIES , 2013, 1309.5972.
[71] H. Rix,et al. Star Formation Histories of z ∼ 1 Galaxies in LEGA-C , 2018, The Astrophysical Journal.
[72] A. Hopkins,et al. Galaxy And Mass Assembly (GAMA): The galaxy stellar mass function to $z=0.1$ from the r-band selected equatorial regions , 2017, 1705.04074.
[73] L. Sodré,et al. Semi‐empirical analysis of Sloan Digital Sky Survey galaxies – I. Spectral synthesis method , 2005 .
[74] P. McCarthy,et al. DUST EXTINCTION FROM BALMER DECREMENTS OF STAR-FORMING GALAXIES AT 0.75 ⩽ z ⩽ 1.5 WITH HUBBLE SPACE TELESCOPE/WIDE-FIELD-CAMERA 3 SPECTROSCOPY FROM THE WFC3 INFRARED SPECTROSCOPIC PARALLEL SURVEY , 2012, 1206.1867.
[75] F. Simpson,et al. Strong Bayesian evidence for the normal neutrino hierarchy , 2017, 1703.03425.
[76] R. Wechsler,et al. THE AVERAGE STAR FORMATION HISTORIES OF GALAXIES IN DARK MATTER HALOS FROM z = 0–8 , 2012, 1207.6105.
[77] B. Garilli,et al. The extended epoch of galaxy formation: age dating of ~3600 galaxies with 2 , 2016, 1602.01841.