Forward modeling of galaxy populations for cosmological redshift distribution inference
File(s)
Published version
Author(s)
Alsing, Justin
Peiris, Hiranya
Mortlock, Daniel
Leja, Joel
Leistedt, Boris
Type
Journal Article
Abstract
We present a forward-modeling framework for estimating galaxy redshift distributions from photometric surveys. Our forward model is composed of: a detailed population model describing the intrinsic distribution of the physical characteristics of galaxies, encoding galaxy evolution physics; a stellar population synthesis model connecting the physical properties of galaxies to their photometry; a data model characterizing the observation and calibration processes for a given survey; and explicit treatment of selection cuts, both into the main analysis sample and for the subsequent sorting into tomographic redshift bins. This approach has the appeal that it does not rely on spectroscopic calibration data, provides explicit control over modeling assumptions and builds a direct bridge between photo-z inference and galaxy evolution physics. In addition to redshift distributions, forward modeling provides a framework for drawing robust inferences about the statistical properties of the galaxy population more generally. We demonstrate the utility of forward modeling by estimating the redshift distributions for the Galaxy And Mass Assembly (GAMA) survey and the Vimos VLT Deep Survey (VVDS), validating against their spectroscopic redshifts. Our baseline model is able to predict tomographic redshift distributions for GAMA and VVDS with respective biases of Δz ≲ 0.003 and Δz ≃ 0.01 on the mean redshift—comfortably accurate enough for Stage III cosmological surveys—without any hyperparameter tuning (i.e., prior to doing any fitting to those data). We anticipate that with additional hyperparameter fitting and modeling improvements, forward modeling will provide a path to accurate redshift distribution inference for Stage IV surveys.
Date Issued
2023-02-01
Date Acceptance
2022-09-18
Citation
Astrophysical Journal Supplement Series, 2023, 264 (2)
ISSN
0067-0049
Publisher
IOP Publishing
Journal / Book Title
Astrophysical Journal Supplement Series
Volume
264
Issue
2
Copyright Statement
© 2023. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
License URL
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000916320100001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
Subjects
Astronomy & Astrophysics
DENSITY
DUST
MASS
METALLICITY
PARAMETER
PHOTOMETRIC REDSHIFTS
Physical Sciences
Science & Technology
SEQUENCE
STAR-FORMATION
Publication Status
Published
Article Number
29
Date Publish Online
2023-01-18