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Compressing the cosmological information in one-dimensional correlations of the Lyman-$\alpha$ forest
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abstract
Observations of the Lyman-$\alpha$ (Ly$\alpha$) forest from spectroscopic surveys such as BOSS/eBOSS, or the ongoing DESI, offer a unique window to study the growth of structure on megaparsec scales. Interpretation of these measurements is a complicated task, requiring hydrodynamical simulations to model and marginalise over the thermal and ionisation state of the intergalactic medium. This complexity has limited the use of Ly$\alpha$ clustering measurements in joint cosmological analyses. In this work we show that the cosmological information content of the 1D power spectrum ($P_\mathrm{1D}$) of the Ly$\alpha$ forest can be compressed into a simple two-parameter likelihood without any significant loss of constraining power. We simulate $P_\mathrm{1D}$ measurements from DESI using hydrodynamical simulations and show that the compressed likelihood is model independent and lossless, recovering unbiased results even in the presence of massive neutrinos or running of the primordial power spectrum.
Forward citations
Cited by 4 Pith papers
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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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A sliding-window CNN recovers Lyα absorber locations and Voigt parameters from spectra, reproducing CDDF and b–N relations on mocks and, more weakly, on UVES data.
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Dark Matter Constraints from Small-Scale Cosmic Structure
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