Compressing the cosmological information in one-dimensional correlations of the Lyman- forest
arXiv:2209.09895 · doi:10.3847/1538-4357/acb433
Abstract
Observations of the Lyman- (Ly) 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 clustering measurements in joint cosmological analyses. In this work we show that the cosmological information content of the 1D power spectrum () of the Ly forest can be compressed into a simple two-parameter likelihood without any significant loss of constraining power. We simulate 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.
Published in ApJ. 17 pages, 7 figures
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- The Dark Energy Spectroscopic Instrument: One-dimensional power spectrum from first Lyman- forest samples with Fast Fourier Transform
- Observational constraints on early dark energy
- tension between Planck cosmic microwave background and eBOSS Lyman-alpha forest and constraints on physics beyond CDM
- The weak, the strong and the ugly -- A comparative analysis of interacting stepped dark radiation
- PRIYA: A New Suite of Lyman-alpha Forest Simulations for Cosmology
- Cosmological Constraints from the eBOSS Lyman- Forest using the PRIYA Simulations
- A neural network emulator for the Lyman- 1D flux power spectrum
- Measurement of the small-scale 3D Lyman- forest power spectrum
- Fresh Look at Neutrino Self-Interactions With the Lyman- Forest: Constraints from EFT and PRIYA Simulations
- Signatures of Very Early Dark Energy in the Matter Power Spectrum
- ForestFlow: predicting the Lyman- forest clustering from linear to nonlinear scales