Qinxun Li

Qinxun Li

Graduate student at Department of Physics and Astronomy in University of Utah

DESI DR2 results. II. Measurements of baryon acoustic oscillations and cosmological constraints

Published in Physical Review D, 2025

DESI Collaboration, M. Abdul Karim, J. Aguilar, S. Ahlen, S. Alam, L. Allen, et al. "DESI DR2 results. II. Measurements of baryon acoustic oscillations and cosmological constraints." Physical Review D, 2025.

Contribution: I performed the consistency tests of BAO measurements and wrote Section III.C. I also made Figure 6 and 13, which show the BAO and SN distance measurements in comparison to various cosmological models.

Abstract

We present baryon acoustic oscillation (BAO) measurements from more than 14 million galaxies and quasars drawn from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2), based on three years of operation. For cosmology inference, these galaxy measurements are combined with DESI Lyman-α forest BAO results presented in a companion paper (M. Abdul-Karim et al., companion paper, Phys. Rev. D 112, 083514 202510.1103/2wwn-xjm5.). The DR2 BAO results are consistent with DESI DR1 and the Sloan Digital Sky Survey, and their distance-redshift relationship matches those from recent compilations of supernovae (SNe) over the same redshift range. The results are well described by a flat Λ cold dark matter (ΛCDM) model, but the parameters preferred by BAO are in mild, 2.3σ tension with those determined from the cosmic microwave background (CMB), although the DESI results are consistent with the acoustic angular scale θ* that is well measured by Planck. This tension is alleviated by dark energy with a time-evolving equation of state parametrized by w0 and wa, which provides a better fit to the data, with a favored solution in the quadrant with w0>-1 and wa<0. This solution is preferred over ΛCDM at 3.1σ for the combination of DESI BAO and CMB data. When also including SNe, the preference for a dynamical dark energy model over ΛCDM ranges from 2.8-4.2σ depending on which SNe sample is used. We present evidence from other data combinations which also favor the same behavior at high significance. From the combination of DESI and CMB we derive 95% upper limits on the sum of neutrino masses, finding ∑mν<0.064 eV assuming ΛCDM and ∑mν<0.16 eV in the w0wa model. Unless there is an unknown systematic error associated with one or more datasets, it is clear that ΛCDM is being challenged by the combination of DESI BAO with other measurements and that dynamical dark energy offers a possible solution.

Figures

The BAO distance measurements from DESI DR2 in comparison to DR1 and the predictions from DESI best-fit $Lambda$CDM model and Planck 2018 $Lambda$CDM model. The four panels are for different BAO observables, including the isotropic BAO distance $D_V/r_d$, the angular diameter distance $D_M/r_d$, the Hubble distance $D_H/r_d$, and the combination of $D_M$ and $D_H$ in the anisotropic BAO measurement. We find a good agreement and a significant improvement in the precision of the BAO measurements from DR1 to DR2. The best-fit $Lambda$CDM model from DR2 is in a clear tension with the Planck 2018, yielding a $sim 2sigma$ discrepancy in the constrained $Omega_m$ and $H_0r_d$ parameters. I made this plot for the paper.
The BAO distance measurements from DESI DR2 in comparison to DR1 and the predictions from DESI best-fit $Lambda$CDM model and Planck 2018 $Lambda$CDM model. The four panels are for different BAO observables, including the isotropic BAO distance $D_V/r_d$, the angular diameter distance $D_M/r_d$, the Hubble distance $D_H/r_d$, and the combination of $D_M$ and $D_H$ in the anisotropic BAO measurement. We find a good agreement and a significant improvement in the precision of the BAO measurements from DR1 to DR2. The best-fit $Lambda$CDM model from DR2 is in a clear tension with the Planck 2018, yielding a $sim 2sigma$ discrepancy in the constrained $Omega_m$ and $H_0r_d$ parameters. I made this plot for the paper.
A synthetic Hubble diagram summarizing the distance measurements from both supernovae (SN) and BAO, in comparison to the predictions from various cosmological models. In the top row, BAO distances from DESI DR2 are shown in grey points, normalized by the Planck 2018 $Lambda$CDM model. In the bottom row, SN distances from the Pantheon+, Union3, and DES Y5 compilations are shown in grey points, in the unit of distance modulus, shifted to match the Planck 2018 $Lambda$CDM model at their average redshift. The $Lambda$CDM models constrained by CMB, BAO, and SN data are shown in black, blue, and orange solid lines, respectively. The $w_0w_a$CDM models constrained by CMB+BAO+SN data are shown in red dashed lines. From this figure, we can tell why $w$CDM and $Lambda$CDM models can not fit the BAO and SN data simultaneously, and how the $w_0w_a$CDM model can provide a better fit to both datasets. I made this plot for the paper.
A synthetic Hubble diagram summarizing the distance measurements from both supernovae (SN) and BAO, in comparison to the predictions from various cosmological models. In the top row, BAO distances from DESI DR2 are shown in grey points, normalized by the Planck 2018 $Lambda$CDM model. In the bottom row, SN distances from the Pantheon+, Union3, and DES Y5 compilations are shown in grey points, in the unit of distance modulus, shifted to match the Planck 2018 $Lambda$CDM model at their average redshift. The $Lambda$CDM models constrained by CMB, BAO, and SN data are shown in black, blue, and orange solid lines, respectively. The $w_0w_a$CDM models constrained by CMB+BAO+SN data are shown in red dashed lines. From this figure, we can tell why $w$CDM and $Lambda$CDM models can not fit the BAO and SN data simultaneously, and how the $w_0w_a$CDM model can provide a better fit to both datasets. I made this plot for the paper.
The dark energy equation of state parameters $w_0$ and $w_a$ constrained by different combinations of datasets. The $Lambda$CDM model corresponds to $w_0=-1$ and $w_a=0$, the cross of two dashed lines. The tension from the $Lambda$CDM model appears among all combinations of datasets. But the significance of the tension varies from $sim 3sigma$ to $sim 4sigma$ depending on the dataset combination.
The dark energy equation of state parameters $w_0$ and $w_a$ constrained by different combinations of datasets. The $Lambda$CDM model corresponds to $w_0=-1$ and $w_a=0$, the cross of two dashed lines. The tension from the $Lambda$CDM model appears among all combinations of datasets. But the significance of the tension varies from $sim 3sigma$ to $sim 4sigma$ depending on the dataset combination.

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