Stellar Population Inference with Prospector

By Benjamin D. Johnson, J. Leja, C. Conroy, Joshua S. Speagle. Astrophysical Journal Supplement Series, 2020

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Inference of the physical properties of stellar populations from observed photometry and spectroscopy is a key goal in the study of galaxy evolution. In recent years, the quality and quantity of the available data have increased, and there have been corresponding efforts to increase the realism of the stellar population models used to interpret these observations. Describing the observed galaxy spectral energy distributions in detail now requires physical models with a large number of highly correlated parameters. These models do not fit easily on grids and necessitate a full exploration of the available parameter space. We present Prospector, a flexible code for inferring stellar population parameters from photometry and spectroscopy spanning UV through IR wavelengths. This code is based on forward modeling the data and Monte Carlo sampling the posterior parameter distribution, enabling complex models and exploration of moderate dimensional parameter spaces. We describe the key ingredients of the code and discuss the general philosophy driving the design of these ingredients. We demonstrate some capabilities of the code on several data sets, including mock and real data.

Subfields: Astronomy and Astrophysics, Atomic and Molecular Physics, and Optics, Instrumentation

View Paper: https://www.semanticscholar.org/paper/722bb44e803f24796017a5c5b56f6eaee9b42080

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Citations in the corpus

A JWST/NIRSpec First Census of Broad-line AGNs at z = 4–7: Detection of 10 Faint AGNs with M BH ∼ 106–108 M ⊙ and Their Host Galaxy Properties (2023, methodology): “To estimate the stellar mass, we conduct SED fittings for host galaxy components using prospector (Johnson et al. 2021).”
A Comprehensive Study of Galaxies at z ∼ 9–16 Found in the Early JWST Data: Ultraviolet Luminosity Functions and Cosmic Star Formation History at the Pre-reionization Epoch (2022, methodology): “Their estimates of the photometric redshifts ( = - +z 10.35 0.51 0.38 and = - +z 12.38 0.27 0.13 for GL-z10-1 and GL-z12-1, respectively, with PROSPECTOR, from the ApJL published version) are consistent with our estimates ( = - +z 10.49 0.72 0.53 and = - +z 12.28 0.07 0.08).”
JWST Census for the Mass–Metallicity Star Formation Relations at z = 4–10 with Self-consistent Flux Calibration and Proper Metallicity Calibrators (2023, methodology): “Using the total magnitudes and the errors of NIRCam, we perform the Bayesian SED ﬁ tting with Prospector ( Johnson et al. 2021 ) to derive the stellar population properties.”
Two Remarkably Luminous Galaxy Candidates at z ≈ 10–12 Revealed by JWST (2022, methodology): “Two Luminous z > 10 Galaxy Candidates We confirm the photometric redshifts for the two GLASS candidates and derive stellar population properties using the Prospector SED fitting code (Leja et al. 2017, 2019; Johnson et al. 2021).”
The Final Season Reimagined: 30 Tidal Disruption Events from the ZTF-I Survey (2022, methodology): “We use the Prospector software (Johnson et al. 2021) to run a Markov Chain Monte Carlo sampler (Foreman-Mackey et al. 2013), with 100 walkers and 1000 steps, to obtain the posterior distributions of the Flexible Stellar Population Synthesis models (Conroy et al. 2009).”
A Long Time Ago in a Galaxy Far, Far Away: A Candidate z ∼ 12 Galaxy in Early JWST CEERS Imaging (2022, methodology): “Our fiducial stellar population modeling is done with the PROSPECTOR Bayesian SED-fitting code (Johnson et al. 2021).”