DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars

TL;DR

We present DESI DR1 BAO measurements from six tracers over $0.1<z<2.1$, achieving a combined BAO precision of $\sim$0.52% across six redshift bins. The analysis introduces a unified, physically motivated BAO modelling pipeline with RecSym reconstruction, spline-based broadband marginalization, and catalog-level blinding, validated by Abacus-2 and EZmock mocks. The results detect BAO in all bins (up to $9.1\sigma$) and provide isotropic and anisotropic dilation constraints ($\alpha_{\rm iso}$, $\alpha_{\rm AP}$) that map to $D_M/r_d$ and $D_H/r_d$, enabling robust cosmological inferences and Hubble diagram construction. A mild tension with Planck 2018 $\Lambda$CDM is observed at $z<0.8$, with DESI also noting a notable SDSS DESI discrepancy in the $0.6<z<0.8$ range; the study emphasizes the importance of blinded analyses and sets the stage for future DESI data (Y3, Y5) to refine the expansion history.

Abstract

We present the DESI 2024 galaxy and quasar baryon acoustic oscillations (BAO) measurements using over 5.7 million unique galaxy and quasar redshifts in the range 0.1<z<2.1. Divided by tracer type, we utilize 300,017 galaxies from the magnitude-limited Bright Galaxy Survey with 0.1<z<0.4, 2,138,600 Luminous Red Galaxies with 0.4<z<1.1, 2,432,022 Emission Line Galaxies with 0.8<z<1.6, and 856,652 quasars with 0.8<z<2.1, over a ~7,500 square degree footprint. The analysis was blinded at the catalog-level to avoid confirmation bias. All fiducial choices of the BAO fitting and reconstruction methodology, as well as the size of the systematic errors, were determined on the basis of the tests with mock catalogs and the blinded data catalogs. We present several improvements to the BAO analysis pipeline, including enhancing the BAO fitting and reconstruction methods in a more physically-motivated direction, and also present results using combinations of tracers. We present a re-analysis of SDSS BOSS and eBOSS results applying the improved DESI methodology and find scatter consistent with the level of the quoted SDSS theoretical systematic uncertainties. With the total effective survey volume of ~ 18 Gpc$^3$, the combined precision of the BAO measurements across the six different redshift bins is ~0.52%, marking a 1.2-fold improvement over the previous state-of-the-art results using only first-year data. We detect the BAO in all of these six redshift bins. The highest significance of BAO detection is $9.1σ$ at the effective redshift of 0.93, with a constraint of 0.86% placed on the BAO scale. We find our measurements are systematically larger than the prediction of Planck-2018 LCDM model at z<0.8. We translate the results into transverse comoving distance and radial Hubble distance measurements, which are used to constrain cosmological models in our companion paper [abridged].

Figures (15)

• Figure 1: The comoving number density as a function of redshift for the samples used for the DESI DR1 galaxy/quasar BAO measurements. Here, we show simply the observed number of redshifts, per comoving volume element. The vertical lines represent the boundaries of the redshift bins used in this analysis, except for the QSO sample which is analyzed as a single redshift bin.
• Figure 2: Comparison of fits using the RascalC semi-analytical and mock-based covariance matrices. The figure demonstrates the consistency of the inferred distance scales and errors using our two approaches for computing the covariance matrices. The panels on the left show the BAO distance scales $\alpha_{\rm iso}$ and $\alpha_{\rm AP}$, while the panels on the right show the errors on these parameters. The $x$-axis show results using the mock-based covariances in the fits, while the $y$-axis show results using the RascalC semi-analytical covariances. The RascalC matrices have been tuned to the ensemble of mocks. Further tests were performed using matrices tuned to a single mock which yield consistent results. The $\Delta$ values in the legends on the left show the fractional mean and standard deviation (in percent, relative to the analytic value) of the difference between the $\alpha$ values, while the values on the right correspond to the difference in the errors.
• Figure 3: The impact of imaging systematics on the BAO scales. In detail, we show the difference in the derived BAO scales when we use the mitigation method for imaging systematics and when we use the raw data ('No weight'). The two measurements for each tracer are slightly displaced horizontally for a better visualization. The BAO scales are very stable even when there was no mitigating and even after density field reconstruction using such raw data. Again, the BAO is robust against the imaging systematics.
• Figure 4: Contour plots of the differences of the (rescaled) alpha values measured with the different AbacusSummit cosmologies using DESI DR1 data. As an example, the LRG high redshift bin is shown. The quantities $\Delta \alpha^{c000}$ are defined as follows. For a given cosmology c00x, the derived alpha values are rescaled to c000 units and the values measured directly with c000 are subtracted.
• Figure 5: Two-point correlation functions of various tracers of the unblinded DESI DR1 (colored lines). We compare the overall clustering amplitude over the BAO fitting range ($48\ h^{-1}\text{Mpc}<r<152\ h^{-1}\text{Mpc}$) before (dotted lines) and after reconstruction (solid lines), compared to the corresponding mean of the 25 Abacus-2 DR1 mocks (black lines). Gray shading represents the error associated with post-reconstruction DESI DR1 based on RascalC covariance. As a reminder, the data points of $\xi$ are substantially correlated between different separation $r$. The upper set of the lines is for the monopole, and the lower set of the lines is for the quadrupole. The plots demonstrate excellent consistency in the overall clustering between the data and the mocks.