DESI DR2 Baryon Acoustic Oscillations from the Lyman Alpha Forest Multipoles

Abstract

We present an alternative measurement of the Baryon Acoustic Oscillation (BAO) using Legendre multipole representation of the Ly$α$ forest correlation functions from the second data release (DR2) of the Dark Energy Spectroscopic Instrument survey. Compressing the auto- and cross-correlation functions into Legendre multipoles yields a positive-definite covariance matrix without any smoothing -- unlike the baseline DR2 analysis -- thanks to a significantly reduced data vector size. We introduce the statistical corrections required to debias the finite-sample covariance matrix estimate and demonstrate that monopole and quadrupole terms for both auto- and cross-correlations can be used even when the correlation functions are distorted by continuum errors and contaminated by metals. This formalism has slightly diminished the constraining power of the BAO scale, while considerably weakening constraints on nuisance parameters. We measure the isotropic BAO scale with $0.96\%$ precision at $z_\mathrm{eff}=2.35$, the Hubble parameter $H(z_\mathrm{eff})=(238.7\pm3.4)~(147.09~\mathrm{Mpc}/r_d) ~\mathrm{km~s}^{-1}~\text{Mpc}^{-1}$, and the transverse comoving distance $D_M(z_\mathrm{eff})=(5.79 \pm 0.10)~(r_d/147.09~\mathrm{Mpc})$~Gpc for a given value of the sound horizon ($r_d$). Our BAO results are entirely consistent with the baseline DR2 analysis.

Figures (7)

• Figure 1: The average correlation matrix of ten CoLoRe-QL mocks ( top) and the correlation matrix obtained from data ( bottom). This demonstrates that mocks reasonably capture the correlations in the data covariance matrix. However, the variance in the data is considerably larger than in the mocks. Both matrices are positive definite without any ad hoc smoothing.
• Figure 2: BAO constraining power for various analysis choices when modeling errors and noise in measured correlations are eliminated using a data vector at the fiducial model. The constraints weaken slightly when the B region is excluded ( gray shaded) from the DR2 baseline analysis ( black dashed lines). They are further weakened slightly in the Legendre multipole space ( blue and orange solid lines), which is only performed using the A region.
• Figure 3: Average of ten Ly$\alpha$ auto ( top) and Ly$\alpha$$\times\mathrm{QSO}$ cross ( bottom) correlation functions measured from the mocks. The quadrupoles are shifted to match the monopole scale. The $\ell_\mathrm{max}=2$ best-fit model ( solid lines) provides a good fit with PTE of $22\%$, whereas the $\ell_\mathrm{max}=4$ has a near-zero PTE.
• Figure 4: Average of ten Ly$\alpha$ auto ( top) and Ly$\alpha$$\times\mathrm{QSO}$ cross ( bottom) hexadecapoles measured from the mocks. The best-fit model ( solid lines) yields a reasonable $\chi^2_\nu=36.4 / 37$ for the auto, while a poor $\chi^2_\nu=72.0 / 37$ for the cross correlation function. Including both in the fit yields a PTE of zero. Including only the auto correlation function still performs considerably worse than the $\ell_\mathrm{max}=2$ case with a PTE of $4\%$.
• Figure 5: The best-fit BAO parameters to the average of ten correlation function measurements from the mocks. Both the $\ell_\mathrm{max}=2$ case ( blue) and $\ell_\mathrm{max}=4$ case ( orange) yield unbiased values, that is, one within one-third of the DR2 uncertainty using $\ell_\mathrm{max}=2$ ( black line).