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DESI DR1 Lyα 1D power spectrum: The optimal estimator measurement
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DESI DR1 Lyα 1D power spectrum: The optimal estimator measurement
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The one-dimensional power spectrum $P_{\mathrm{1D}}$ of Ly$\alpha$ forest offers rich insights into cosmological and astrophysical parameters, including constraints on the sum of neutrino masses, warm dark matter models, and the thermal state of the intergalactic medium. We present the measurement of $P_{\mathrm{1D}}$ using the optimal quadratic maximum likelihood estimator applied to over 300,000 Ly$\alpha$ quasars from Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI) survey. This sample represents the largest to date for $P_{\mathrm{1D}}$ measurements and is larger than the Extended Baryon Oscillation Spectroscopic Survey (eBOSS) by a factor of 1.7. We conduct a meticulous investigation of instrumental and analysis systematics and quantify their impact on $P_{\mathrm{1D}}$. This includes the development of a cross-exposure estimator that eliminates the need to model the pipeline noise and has strong potential for future $P_{\mathrm{1D}}$ measurements. We also present new insights into metal contamination through the 1D correlation function. Using a fitting function we measure the evolution of the Ly$\alpha$ forest bias with high precision: $b_F(z) = (-0.218\pm0.002)\times((1 + z) / 4)^{2.96\pm0.06}$. In a companion validation paper, we substantially extend our previous suite of CCD image simulations to quantify the pipeline's exquisite performance accurately. In another companion paper, we present DR1 $P_{\mathrm{1D}}$ measurements using the Fast Fourier Transform (FFT) approach to power spectrum estimation. These two measurements produce a forest bias parameter that differs by 2.2 sigma. However, our model is simplistic, so this disagreement will be investigated in future work.
Forward citations
Cited by 10 Pith papers
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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...
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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 holography: 3D predictions from 1D measurements
One-dimensional Lyman-α forest power spectrum measurements, propagated through the ForestFlow emulator, predict three-dimensional clustering that matches DESI BAO and ACCEL-2 simulation results.
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DESI DR2 Results IV: Alcock-Paczy\'nski Measurements from the Lyman Alpha Forest and Cosmological Constraints
DESI DR2 Lyman-alpha forest full-shape correlations yield a 1% Alcock-Paczyński measurement at z=2.33 and 0.8% distance ratio constraints.
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DESI DR2 Results IV: Alcock-Paczy\'nski Measurements from the Lyman Alpha Forest and Cosmological Constraints
The full shape of DESI DR2 Lyman-alpha forest correlations constrains the distance ratio DM/DH at z=2.33 to 1.0%, twice as precise as BAO alone.
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Probing Confining Dark Sectors with Cosmological Perturbations
Composite dark matter from a keV–MeV confining phase transition sources an IR-enhanced curvature spectrum that competes with free-streaming suppression, yielding concrete CMB and Lyman-α bounds on transition strength ...
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Probing Confining Dark Sectors with Cosmological Perturbations
Composite dark matter from a keV-MeV confining phase transition generates curvature perturbations constrained by CMB anisotropies and Lyman-alpha forest data, offering a testable scenario even without visible sector c...
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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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Validation of the DESI DR2 Ly$\alpha$ forest full-shape analysis
The DESI DR2 Lyman-alpha full-shape analysis passes validation for BAO and Alcock-Paczynski parameters on 400 mocks and blinded data, while f-sigma-8 is rejected due to a roughly 10% mock bias.
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Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest
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