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The Dark Energy Spectroscopic Instrument (DESI) team has validated a new method for mapping the three-dimensional structure of the distant universe using the Lyman-alpha forest, which are absorption patterns in light from distant quasars. Using substantially larger and more realistic simulations than previous studies, they confirmed that their technique can reliably measure cosmic distances and the expansion history of the universe through baryon acoustic oscillations and Alcock-Paczynski measurements. However, validation tests revealed significant biases in measuring the cosmic growth rate parameter, leading them to exclude this measurement from their final analysis.
Why it matters
This validated methodology enables more precise measurements of dark energy and the universe's expansion history by utilizing light from some of the most distant observable objects. The improved techniques will help cosmologists better understand the fundamental properties driving the evolution of the universe over the past 11 billion years.
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⚠️ Preprint – Noch nicht peer-reviewed
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Abstract: We present the validation of the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) Lyman-$alpha$ (Ly$alpha$) forest full-shape analysis. This analysis combines three-dimensional Ly$alpha$ forest auto-correlations and cross-correlations with quasars to extract information from both the baryon acoustic oscillation (BAO) feature and the broadband clustering signal, with primary emphasis on the Alcock-Paczynski (AP) measurement. Compared to the DESI DR1 analysis, the DR2 validation uses substantially larger and more realistic mock datasets, including CoLoRe 2LPT and AbacusSummit Ly$alpha$ forest simulations. The modeling framework is also improved through analytic marginalization over small scales ($<10$ $h^{-1}$Mpc) and the impact of ultraviolet background fluctuations. The validation program was completed prior to unblinding and defines quantitative requirements for the cosmological parameters of interest, which are evaluated using hundreds of mock realizations. We further test the analysis through independent fits to the auto- and cross-correlations, multiple catalog splits, and a broad suite of analysis and modeling variations applied to both mocks and blinded observational data. We find that the BAO and AP parameters satisfy all validation requirements and remain stable across all tests. In contrast, mock studies reveal a significant bias in the inferred growth-rate parameter $fsigma_8$, leading us to exclude this measurement from the final analysis. The consistency across mocks, data splits, and robustness tests demonstrates that the DR2 Ly$alpha$ full-shape analysis provides a reliable and substantially improved broadband AP measurement over previous Ly$alpha$ forest studies.
Source: Validation of the DESI DR2 Ly$alpha$ forest full-shape analysis