DESI DR1 Lyman-alpha data yields Δ²★=0.379±0.032 and n★=-2.309±0.019 at k★=0.009 km⁻¹s and z=3, sharpening N_eff, α_s, and β_s constraints by factors of 1.18-1.90 when combined with other probes.
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An EFT-based field-level forward model for the Lyman-alpha forest matches simulations at the percent level on quasi-linear scales and generates mocks for DESI and DESI-II analyses.
Lya2pcf is an efficient pipeline implementing standard algorithms for 2PCF and 3PCF of the Lyman-alpha forest, with GPU speedups over PICCA and the first large-sample anisotropic 3PCF measurement up to 80 Mpc/h.
Global cosmic strings from symmetry breaking produce Nambu-Goldstone bosons whose cosmological signatures can be constrained by current and upcoming CMB and large-scale structure observations.
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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Cosmological analysis of the DESI DR1 Lyman alpha 1D power spectrum
DESI DR1 Lyman-alpha data yields Δ²★=0.379±0.032 and n★=-2.309±0.019 at k★=0.009 km⁻¹s and z=3, sharpening N_eff, α_s, and β_s constraints by factors of 1.18-1.90 when combined with other probes.
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Lyman-Alpha Forest and its Cross-Correlation with High-Redshift Galaxies in Effective Field Theory at the Field Level
An EFT-based field-level forward model for the Lyman-alpha forest matches simulations at the percent level on quasi-linear scales and generates mocks for DESI and DESI-II analyses.
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Lya2pcf: an efficient pipeline to estimate two- and three-point correlation functions of the Lyman-$\alpha$ forest
Lya2pcf is an efficient pipeline implementing standard algorithms for 2PCF and 3PCF of the Lyman-alpha forest, with GPU speedups over PICCA and the first large-sample anisotropic 3PCF measurement up to 80 Mpc/h.
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Echoes of Global Cosmic Strings
Global cosmic strings from symmetry breaking produce Nambu-Goldstone bosons whose cosmological signatures can be constrained by current and upcoming CMB and large-scale structure observations.
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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.