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Abstract:

The second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI), containing data from the first three years of observations, doubles the number of Lyman-α (Lyα) forest spectra in DR1 and it provides the largest dataset of its kind. To ensure a robust validation of the baryonic acoustic oscillation (BAO) analysis using Lyα forests, we have made significant updates compared to DR1 to both the mocks and the analysis framework used in the validation. In particular, we present CoLoRe-QL, a new set of Lyα mocks that use a quasilinear input power spectrum to incorporate the nonlinear broadening of the BAO peak. We have also increased the number of realizations used in the validation to 400, compared to the 150 realizations used in DR1. Finally, we present a detailed study of the impact of quasar redshift errors on the BAO measurement, and we compare different strategies to mask damped Lyman-α absorbers in our spectra. The BAO measurement from the Lyα dataset of DESI DR2 is presented in a companion publication.

Abstract:

We measure the angular power spectrum and bispectrum of the projected overdensity of photometric DESI luminous red galaxies, and its cross-correlation with maps of the Cosmic Microwave Background lensing convergence from Planck. This analysis is enabled by the use of the “filtered-squared bispectrum” approach, introduced in previous work, which we generalise here to the case of cross-correlations between multiple fields. The projected galaxy bispectrum is detected at very high significance (above <math display="inline"> <mrow> <mn>30</mn> <mi>σ</mi> </mrow> </math> in all redshift bins), and the galaxy-galaxy-convergence bispectrum is detected above <math display="inline"> <mrow> <mn>5</mn> <mi>σ</mi> </mrow> </math> in the three highest-redshift bins. We find that the bispectrum is reasonably well described over a broad range of scales by a tree-level prediction using the linear galaxy bias measured from the power spectrum. We carry out the first cosmological analysis combining projected power spectra and bispectra under a relatively simple model, and show that the galaxy bispectrum can be used in combination with the power spectrum to place a constraint on the amplitude of matter fluctuations, <math display="inline"> <msub> <mi>σ</mi> <mn>8</mn> </msub> </math> , an on the non-relativistic matter fraction <math display="inline"> <msub> <mi>Ω</mi> <mi>m</mi> </msub> </math> . We find that data combinations involving the galaxy bispectrum recover constraints on these parameters that are in good agreement with those found from the traditional “2 <math display="inline"> <mo>×</mo> </math> 2-point” combination of galaxy-galaxy and galaxy-convergence power spectra, across all redshift bins.

Abstract:

Despite growing efforts to find the sources of high-energy neutrinos measured by IceCube, the bulk of the neutrinos remain with unknown origins. In this work, we aim to constrain the emissivity of cosmic high-energy neutrinos from extragalactic sources through their correlation with the large-scale structure. We use cross-correlations between the IceCube 10-year data set and tomographic maps of the galaxy overdensity to place constraints on the bias-weighted high-energy neutrino emissivity out to redshift . We test two different models to describe the evolution of neutrino emissivity with redshift, a power-law model , and a model tracking the star formation history, assuming a simple power-law model for the energy injection spectrum. We also consider a non-parametric reconstruction of the astrophysical neutrino emissivity as a function of redshift. We do not find any significant correlation, with our strongest results corresponding to a deviation with respect to a model with zero signal. We use our measurements to place upper bounds on the bias-weighted astrophysical high-energy neutrino emission rate as a function of redshift for different source models. This analysis provides a new probe to test extragalactic neutrino source models. With future neutrino and galaxy data sets, we expect the constraining and detection power of this type of analysis to increase.