Emulating Simulations of Cosmic Dawn for 21 cm Power Spectrum Constraints on Cosmology, Reionization, and X-Ray Heating
Abstract
Current and upcoming radio interferometric experiments are aiming to make a statistical characterization of the high-redshift 21 cm fluctuation signal spanning the hydrogen reionization and X-ray heating epochs of the universe. However, connecting 21 cm statistics to the underlying physical parameters is complicated by the theoretical challenge of modeling the relevant physics at computational speeds quick enough to enable exploration of the high-dimensional and weakly constrained parameter space. In this study, we use machine learning algorithms to build a fast emulator that can accurately mimic an expensive simulation of the 21 cm signal across a wide parameter space. We embed our emulator within a Markov Chain Monte Carlo framework in order to perform Bayesian parameter constraints over a large number of model parameters, including those that govern the Epoch of Reionization, the Epoch of X-ray Heating, and cosmology. As a worked example, we use our emulator to present an updated parameter constraint forecast for the Hydrogen Epoch of Reionization Array experiment, showing that its characterization of a fiducial 21 cm power spectrum will considerably narrow the allowed parameter space of reionization and heating parameters, and could help strengthen Planck's constraints on $${\sigma }_{8}$$. We provide both our generalized emulator code and its implementation specifically for 21 cm parameter constraints as publicly available software.
- Authors:
-
[1];
[1];
- Univ. of California, Berkeley, CA (United States). Dept. of Astronomy and Radio Astronomy Lab.
- Scuola Normale Superiore (SNS), Pisa (Italy)
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1524233
- Grant/Contract Number:
- AC02-05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- The Astrophysical Journal (Online)
- Additional Journal Information:
- Journal Name: The Astrophysical Journal (Online); Journal Volume: 848; Journal Issue: 1; Journal ID: ISSN 1538-4357
- Publisher:
- Institute of Physics (IOP)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 79 ASTRONOMY AND ASTROPHYSICS; dark ages; reionization; first stars; methods: numerical; methods: statistical
Citation Formats
Kern, Nicholas S., Liu, Adrian, Parsons, Aaron R., Mesinger, Andrei, and Greig, Bradley. Emulating Simulations of Cosmic Dawn for 21 cm Power Spectrum Constraints on Cosmology, Reionization, and X-Ray Heating. United States: N. p., 2017.
Web. doi:10.3847/1538-4357/aa8bb4.
Kern, Nicholas S., Liu, Adrian, Parsons, Aaron R., Mesinger, Andrei, & Greig, Bradley. Emulating Simulations of Cosmic Dawn for 21 cm Power Spectrum Constraints on Cosmology, Reionization, and X-Ray Heating. United States. https://doi.org/10.3847/1538-4357/aa8bb4
Kern, Nicholas S., Liu, Adrian, Parsons, Aaron R., Mesinger, Andrei, and Greig, Bradley. Fri .
"Emulating Simulations of Cosmic Dawn for 21 cm Power Spectrum Constraints on Cosmology, Reionization, and X-Ray Heating". United States. https://doi.org/10.3847/1538-4357/aa8bb4. https://www.osti.gov/servlets/purl/1524233.
@article{osti_1524233,
title = {Emulating Simulations of Cosmic Dawn for 21 cm Power Spectrum Constraints on Cosmology, Reionization, and X-Ray Heating},
author = {Kern, Nicholas S. and Liu, Adrian and Parsons, Aaron R. and Mesinger, Andrei and Greig, Bradley},
abstractNote = {Current and upcoming radio interferometric experiments are aiming to make a statistical characterization of the high-redshift 21 cm fluctuation signal spanning the hydrogen reionization and X-ray heating epochs of the universe. However, connecting 21 cm statistics to the underlying physical parameters is complicated by the theoretical challenge of modeling the relevant physics at computational speeds quick enough to enable exploration of the high-dimensional and weakly constrained parameter space. In this study, we use machine learning algorithms to build a fast emulator that can accurately mimic an expensive simulation of the 21 cm signal across a wide parameter space. We embed our emulator within a Markov Chain Monte Carlo framework in order to perform Bayesian parameter constraints over a large number of model parameters, including those that govern the Epoch of Reionization, the Epoch of X-ray Heating, and cosmology. As a worked example, we use our emulator to present an updated parameter constraint forecast for the Hydrogen Epoch of Reionization Array experiment, showing that its characterization of a fiducial 21 cm power spectrum will considerably narrow the allowed parameter space of reionization and heating parameters, and could help strengthen Planck's constraints on ${\sigma }_{8}$. We provide both our generalized emulator code and its implementation specifically for 21 cm parameter constraints as publicly available software.},
doi = {10.3847/1538-4357/aa8bb4},
journal = {The Astrophysical Journal (Online)},
number = 1,
volume = 848,
place = {United States},
year = {Fri Oct 06 00:00:00 EDT 2017},
month = {Fri Oct 06 00:00:00 EDT 2017}
}
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Figure 1: Top: scree plot showing the eigenvalues of the 30 principal components formed from the training data of ln $Δ^{2}_{21}$ . Bottom: the first nine principal components of the power spectrum data at each unique $k$–$z$ combination. The color scale is artificially normalized to [−1, 1] for easier comparison.
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