Forward Modeling of Large-scale Structure: An Open-source Approach with Halotools
Abstract
Here, we present the first stable release of Halotools (v0.2), a community-driven Python package designed to build and test models of the galaxy-halo connection. Halotools provides a modular platform for creating mock universes of galaxies starting from a catalog of dark matter halos obtained from a cosmological simulation. The package supports many of the common forms used to describe galaxy-halo models: the halo occupation distribution (HOD), the conditional luminosity function (CLF), abundance matching, and alternatives to these models that include effects such as environmental quenching or variable galaxy assembly bias. Satellite galaxies can be modeled to live in subhalos, or to follow custom number density profiles within their halos, including spatial and/or velocity bias with respect to the dark matter profile. Here, the package has an optimized toolkit to make mock observations on a synthetic galaxy population, including galaxy clustering, galaxy-galaxy lensing, galaxy group identification, RSD multipoles, void statistics, pairwise velocities and others, allowing direct comparison to observations. Halotools is object-oriented, enabling complex models to be built from a set of simple, interchangeable components, including those of your own creation.
- Authors:
-
- Yale Univ., New Haven, CT (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
- Yale Univ., New Haven, CT (United States)
- Yale Univ., New Haven, CT (United States); Space Telescope Science Institute, Baltimore, MD (United States)
- Univ. of California, Berkeley, CA (United States)
- Harvard-Smithsonian Center for Astrophysics, Cambridge, MA (United States)
- Univ. of Illinois at Urbana-Champaign, Urbana, IL (United States)
- Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Univ. of Chicago, Chicago, IL (United States)
- The Univ. of Tokyo, Chiba (Japan)
- Stanford Univ., Stanford, CA (United States); Univ. of Pittsburgh, Pittsburgh, PA (United States)
- Univ. of Washington, Seattle, WA (United States)
- Vanderbilt Univ., Nashville, TN (United States); Swinburne Univ. of Technology, Hawthorn, VIC (Australia)
- Univ. of Hertfordshire, Hatfield (United Kingdom); Univ. of Cambridge, Cambridge (United Kingdom)
- Univ. of Pittsburgh, Pittsburgh, PA (United States)
- Publication Date:
- Research Org.:
- Argonne National Laboratory (ANL), Argonne, IL (United States); Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), High Energy Physics (HEP)
- OSTI Identifier:
- 1406243
- Report Number(s):
- FERMILAB-PUB-16-723-A; arXiv:1606.04106
Journal ID: ISSN 1538-3881; 1469199; TRN: US1702907
- Grant/Contract Number:
- AC02-07CH11359
- Resource Type:
- Accepted Manuscript
- Journal Name:
- The Astronomical Journal (Online)
- Additional Journal Information:
- Journal Name: The Astronomical Journal (Online); Journal Volume: 154; Journal Issue: 5; Journal ID: ISSN 1538-3881
- Publisher:
- IOP Publishing - AAAS
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 79 ASTRONOMY AND ASTROPHYSICS; 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; cosmology: theory; galaxies: halos; galaxies: statistics; large-scale structure of universe
Citation Formats
Hearin, Andrew P., Campbell, Duncan, Tollerud, Erik, Behroozi, Peter, Diemer, Benedikt, Goldbaum, Nathan J., Jennings, Elise, Leauthaud, Alexie, Mao, Yao -Yuan, More, Surhud, Parejko, John, Sinha, Manodeep, Sipocz, Brigitta, and Zentner, Andrew. Forward Modeling of Large-scale Structure: An Open-source Approach with Halotools. United States: N. p., 2017.
Web. doi:10.3847/1538-3881/aa859f.
Hearin, Andrew P., Campbell, Duncan, Tollerud, Erik, Behroozi, Peter, Diemer, Benedikt, Goldbaum, Nathan J., Jennings, Elise, Leauthaud, Alexie, Mao, Yao -Yuan, More, Surhud, Parejko, John, Sinha, Manodeep, Sipocz, Brigitta, & Zentner, Andrew. Forward Modeling of Large-scale Structure: An Open-source Approach with Halotools. United States. https://doi.org/10.3847/1538-3881/aa859f
Hearin, Andrew P., Campbell, Duncan, Tollerud, Erik, Behroozi, Peter, Diemer, Benedikt, Goldbaum, Nathan J., Jennings, Elise, Leauthaud, Alexie, Mao, Yao -Yuan, More, Surhud, Parejko, John, Sinha, Manodeep, Sipocz, Brigitta, and Zentner, Andrew. Fri .
"Forward Modeling of Large-scale Structure: An Open-source Approach with Halotools". United States. https://doi.org/10.3847/1538-3881/aa859f. https://www.osti.gov/servlets/purl/1406243.
@article{osti_1406243,
title = {Forward Modeling of Large-scale Structure: An Open-source Approach with Halotools},
author = {Hearin, Andrew P. and Campbell, Duncan and Tollerud, Erik and Behroozi, Peter and Diemer, Benedikt and Goldbaum, Nathan J. and Jennings, Elise and Leauthaud, Alexie and Mao, Yao -Yuan and More, Surhud and Parejko, John and Sinha, Manodeep and Sipocz, Brigitta and Zentner, Andrew},
abstractNote = {Here, we present the first stable release of Halotools (v0.2), a community-driven Python package designed to build and test models of the galaxy-halo connection. Halotools provides a modular platform for creating mock universes of galaxies starting from a catalog of dark matter halos obtained from a cosmological simulation. The package supports many of the common forms used to describe galaxy-halo models: the halo occupation distribution (HOD), the conditional luminosity function (CLF), abundance matching, and alternatives to these models that include effects such as environmental quenching or variable galaxy assembly bias. Satellite galaxies can be modeled to live in subhalos, or to follow custom number density profiles within their halos, including spatial and/or velocity bias with respect to the dark matter profile. Here, the package has an optimized toolkit to make mock observations on a synthetic galaxy population, including galaxy clustering, galaxy-galaxy lensing, galaxy group identification, RSD multipoles, void statistics, pairwise velocities and others, allowing direct comparison to observations. Halotools is object-oriented, enabling complex models to be built from a set of simple, interchangeable components, including those of your own creation.},
doi = {10.3847/1538-3881/aa859f},
journal = {The Astronomical Journal (Online)},
number = 5,
volume = 154,
place = {United States},
year = {Fri Oct 20 00:00:00 EDT 2017},
month = {Fri Oct 20 00:00:00 EDT 2017}
}
Web of Science
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