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}.
Cosmological analysis of the DESI DR1 Lyman alpha 1D power spectrum
4 Pith papers cite this work. Polarity classification is still indexing.
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abstract
We present the cosmological analysis of the one-dimensional Lyman-$\alpha$ flux power spectrum from the first data release of the Dark Energy Spectroscopic Instrument (DESI). We capture the dependence of the signal on cosmology and intergalactic medium physics using an emulator trained on a cosmological suite of hydrodynamical simulations, and we correct its predictions for the impact of astrophysical contaminants and systematics, many of these not considered in previous analyses. We employ this framework to constrain the amplitude and logarithmic slope of the linear matter power spectrum at $k_\star=0.009\,\mathrm{km^{-1}s}$ and redshift $z=3$, obtaining $\Delta^2_\star=0.379\pm0.032$ and $n_\star=-2.309\pm0.019$. The robustness of these constraints is validated through the analysis of mocks and a large number of alternative data analysis variations, with cosmological parameters kept blinded throughout the validation process. We then combine our results with constraints from DESI BAO and temperature, polarization, and lensing measurements from Planck, ACT, and SPT-3G to set constraints on $\Lambda$CDM extensions. While our measurements do not significantly tighten the limits on the sum of neutrino masses from the combination of these probes, they sharpen the constraints on the effective number of relativistic species, $N_\mathrm{eff}=3.02\pm0.10$, the running of the spectral index, $\alpha_\mathrm{s}=0.0014\pm0.0041$, and the running of the running, $\beta_\mathrm{s}=-0.0006\pm0.0048$, by a factor of 1.18, 1.27, and 1.90, respectively. We conclude by outlining the improvements needed to fully reach the level of confidence implied by these uncertainties.
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background 3representative citing papers
Wave-mechanical dynamics in mixed FDM-CDM models imprint distinct kinematic signatures on Lyman-alpha flux statistics that cannot be captured by the matter power spectrum alone.
Including spectral running α_s, β_s and self-interacting dark radiation relaxes the ACT DR6 bound on ΔN_eff to <0.58 and lowers the Hubble tension to 2.2σ with three extra parameters.
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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Lyman-$\alpha$ Forest Signatures of Mixed Fuzzy and Cold Dark Matter
Wave-mechanical dynamics in mixed FDM-CDM models imprint distinct kinematic signatures on Lyman-alpha flux statistics that cannot be captured by the matter power spectrum alone.
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The End of the First Act: Spectral Running, Interacting Dark Radiation, and the Hubble Tension in Light of ACT DR6 Data
Including spectral running α_s, β_s and self-interacting dark radiation relaxes the ACT DR6 bound on ΔN_eff to <0.58 and lowers the Hubble tension to 2.2σ with three extra parameters.
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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.