Analytic compression of EFT parameters for Lyα forest P1D via Fisher matrix and linearization allows efficient marginalization, saturating constraints with linear bias plus five effective terms and forecasting 10% and 2% precision on Δ²_p and n_p at k_p=0.7 Mpc^{-1}.
Lyman-alpha Forest Constraints on Decaying Dark Matter
2 Pith papers cite this work. Polarity classification is still indexing.
abstract
We present an analysis of high-resolution N-body simulations of decaying dark matter cosmologies focusing on the statistical properties of the transmitted Lyman-alpha forest flux in the high-redshift intergalactic medium. In this type of model a dark matter particle decays into a slightly less massive stable dark matter daughter particle and a comparably light particle. The small mass splitting provides a non-relativistic kick velocity V_k to the daughter particle resulting in free-streaming and subsequent damping of small-scale density fluctuations. Current Lyman-alpha forest power spectrum measurements probe comoving scales up to ~ 2-3 h^-1 Mpc at redshifts z ~ 2-4, providing one of the most robust ways to probe cosmological density fluctuations on relatively small scales. The suppression of structure growth due to the free-streaming of dark matter daughter particles also has a significant impact on the neutral hydrogen cloud distribution, which traces the underlying dark matter distribution well at high redshift. We exploit Lyman-alpha forest power spectrum measurements to constrain the amount of free-streaming of dark matter in such models and thereby place limits on decaying dark matter based only on the dynamics of cosmological perturbations without any assumptions about the interactions of the decay products. We find that SDSS 1D Lyman-alpha forest power spectrum data place a lifetime-dependent upper limit V_k < 30-70 km/s for decay lifetimes < 10 Gyr. This is the most stringent model-independent bound on invisible dark matter decays with small mass splittings. For large mass splittings (large V_k), Lyman-alpha forest data restrict the dark matter lifetime to Gamma^-1 > 40 Gyr. Forthcoming BOSS data should be able to provide more stringent constraints on exotic dark matter, mainly because the larger BOSS quasar spectrum sample will significantly reduce statistical errors.
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Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.
citing papers explorer
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Analytic compression of the effective field theory of the Lyman-alpha forest
Analytic compression of EFT parameters for Lyα forest P1D via Fisher matrix and linearization allows efficient marginalization, saturating constraints with linear bias plus five effective terms and forecasting 10% and 2% precision on Δ²_p and n_p at k_p=0.7 Mpc^{-1}.
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Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest
Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.