Inferring high redshift large-scale structure dynamics from the Lyman-alpha forest. (arXiv:1907.02973v1 [astro-ph.CO])
<a href="http://arxiv.org/find/astro-ph/1/au:+Porqueres_N/0/1/0/all/0/1">Natalia Porqueres</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Jasche_J/0/1/0/all/0/1">Jens Jasche</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Lavaux_G/0/1/0/all/0/1">Guilhem Lavaux</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Ensslin_T/0/1/0/all/0/1">Torsten Enßlin</a>
One of the major science goals over the coming decade is to test fundamental
physics with probes of the cosmic large-scale structure out to high redshift.
Here we present a fully Bayesian approach to infer the three-dimensional cosmic
matter distribution and its dynamics at $z>2$ from observations of the
Lyman-$alpha$ forest. We demonstrate that the method recovers the unbiased
mass distribution and the correct matter power spectrum at all scales. Our
method infers the three-dimensional density field from a set of one-dimensional
spectra, interpolating the information between the lines of sight. We show that
our algorithm provides unbiased mass profiles of clusters, becoming an
alternative to estimate cluster masses complementary to weak lensing or X-ray
observations. The algorithm employs a Hamiltonian Monte Carlo method to
generate realizations of initial and evolved density fields as well as the
three-dimensional large-scale flow, revealing the cosmic dynamics at
high-redshift. The method correctly handles multi-modal parameter
distributions, which allow to constrain the physics of the intergalactic medium
(IGM) with high accuracy. We performed several tests using realistic simulated
quasar spectra to test and validate our method. Our results show that detailed
and physically plausible inference of three-dimensional large-scale structures
at high redshift has become feasible.
One of the major science goals over the coming decade is to test fundamental
physics with probes of the cosmic large-scale structure out to high redshift.
Here we present a fully Bayesian approach to infer the three-dimensional cosmic
matter distribution and its dynamics at $z>2$ from observations of the
Lyman-$alpha$ forest. We demonstrate that the method recovers the unbiased
mass distribution and the correct matter power spectrum at all scales. Our
method infers the three-dimensional density field from a set of one-dimensional
spectra, interpolating the information between the lines of sight. We show that
our algorithm provides unbiased mass profiles of clusters, becoming an
alternative to estimate cluster masses complementary to weak lensing or X-ray
observations. The algorithm employs a Hamiltonian Monte Carlo method to
generate realizations of initial and evolved density fields as well as the
three-dimensional large-scale flow, revealing the cosmic dynamics at
high-redshift. The method correctly handles multi-modal parameter
distributions, which allow to constrain the physics of the intergalactic medium
(IGM) with high accuracy. We performed several tests using realistic simulated
quasar spectra to test and validate our method. Our results show that detailed
and physically plausible inference of three-dimensional large-scale structures
at high redshift has become feasible.
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