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Title: A Novel Statistical Method for Measuring the Temperature–Density Relation in the IGM Using the b N Hi Distribution of Absorbers in the Ly α Forest

Abstract

We propose a new method for determining the thermal state of the intergalactic medium based on Voigt profile decomposition of the Lyα forest. The distribution of Doppler parameter and column density (b–N H i distribution) is sensitive to the temperature–density relation T = T 0(ρ/ρ 0) γ-1, and previous work has inferred T 0 and γ by fitting its low-b cutoff. This approach discards the majority of available data and is susceptible to systematics related to cutoff determination. We introduce an approach that exploits all information encoded in the b N H i distribution by modeling its entire shape. We apply kernel density estimation to discrete absorption lines to generate model probability density functions, and then we use principal component decomposition to create an emulator that can be evaluated anywhere in thermal parameter space. We introduce a Bayesian likelihood based on these models enabling parameter inference via Markov Chain Monte Carlo. The method's robustness is tested by applying it to a large grid of thermal history simulations. By conducting 160 mock measurements, we establish that our approach delivers unbiased estimates and valid uncertainties for a 2D ( T 0, γ) measurement. Furthermore, we conduct a pilot study applying this methodology to real observational data at z = 2. Using 200 absorbers, equivalent in path length to a single Lya forest spectrum, we measure $$\mathrm{log}{T}_{0}={4.092}_{-0.055}^{+0.050}$$ and $$\gamma ={1.49}_{-0.074}^{+0.073}$$ in excellent agreement with cutoff fitting determinations using the same data. Our method is far more sensitive than cutoff fitting, enabling measurements of log T 0 and γ with precision on $$\mathrm{log}{T}_{0}$$ (γ) nearly two (three) times higher for current data set sizes.

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [4]
  1. Max-Planck-Institut für Astronomie, Heidelberg (Germany); Heidelberg Univ. (Germany)
  2. Max-Planck-Institut für Astronomie, Heidelberg (Germany); Heidelberg Univ. (Germany); Univ. of California, Santa Barbara, CA (United States)
  3. Max-Planck-Institut für Astronomie, Heidelberg (Germany); Royal Observatories, Edinburgh (United Kingdom)
  4. Max-Planck-Institut für Astronomie, Heidelberg (Germany); Univ. of California, Santa Barbara, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Org.:
USDOE
OSTI Identifier:
1528862
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: 876; 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; cosmology: observations; dark ages; reionization; first stars; intergalactic medium; quasars: absorption lines

Citation Formats

Hiss, Hector, Walther, Michael, Oñorbe, Jose, and Hennawi, Joseph F. A Novel Statistical Method for Measuring the Temperature–Density Relation in the IGM Using the b–NHi Distribution of Absorbers in the Lyα Forest. United States: N. p., 2019. Web. doi:10.3847/1538-4357/ab1418.
Hiss, Hector, Walther, Michael, Oñorbe, Jose, & Hennawi, Joseph F. A Novel Statistical Method for Measuring the Temperature–Density Relation in the IGM Using the b–NHi Distribution of Absorbers in the Lyα Forest. United States. doi:10.3847/1538-4357/ab1418.
Hiss, Hector, Walther, Michael, Oñorbe, Jose, and Hennawi, Joseph F. Mon . "A Novel Statistical Method for Measuring the Temperature–Density Relation in the IGM Using the b–NHi Distribution of Absorbers in the Lyα Forest". United States. doi:10.3847/1538-4357/ab1418.
@article{osti_1528862,
title = {A Novel Statistical Method for Measuring the Temperature–Density Relation in the IGM Using the b–NHi Distribution of Absorbers in the Lyα Forest},
author = {Hiss, Hector and Walther, Michael and Oñorbe, Jose and Hennawi, Joseph F.},
abstractNote = {We propose a new method for determining the thermal state of the intergalactic medium based on Voigt profile decomposition of the Lyα forest. The distribution of Doppler parameter and column density (b–N H i distribution) is sensitive to the temperature–density relation T = T 0(ρ/ρ 0) γ-1, and previous work has inferred T 0 and γ by fitting its low-b cutoff. This approach discards the majority of available data and is susceptible to systematics related to cutoff determination. We introduce an approach that exploits all information encoded in the b– N H i distribution by modeling its entire shape. We apply kernel density estimation to discrete absorption lines to generate model probability density functions, and then we use principal component decomposition to create an emulator that can be evaluated anywhere in thermal parameter space. We introduce a Bayesian likelihood based on these models enabling parameter inference via Markov Chain Monte Carlo. The method's robustness is tested by applying it to a large grid of thermal history simulations. By conducting 160 mock measurements, we establish that our approach delivers unbiased estimates and valid uncertainties for a 2D (T 0, γ) measurement. Furthermore, we conduct a pilot study applying this methodology to real observational data at z = 2. Using 200 absorbers, equivalent in path length to a single Lya forest spectrum, we measure $\mathrm{log}{T}_{0}={4.092}_{-0.055}^{+0.050}$ and $\gamma ={1.49}_{-0.074}^{+0.073}$ in excellent agreement with cutoff fitting determinations using the same data. Our method is far more sensitive than cutoff fitting, enabling measurements of log T 0 and γ with precision on $\mathrm{log}{T}_{0}$ (γ) nearly two (three) times higher for current data set sizes.},
doi = {10.3847/1538-4357/ab1418},
journal = {The Astrophysical Journal (Online)},
number = 1,
volume = 876,
place = {United States},
year = {2019},
month = {5}
}

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