Optimal 1D Ly$\alpha$ Forest Power Spectrum Estimation -- III. DESI early data

TL;DR

This paper presents the first measurement of the 1D Lyα forest power spectrum using DESI early data, demonstrating the pipeline's accuracy and systematic error control, with implications for cosmology.

Contribution

It introduces the first quadratic maximum likelihood estimation of the Lyα forest power spectrum from DESI early data, including systematic error analysis and pipeline validation.

Findings

Successful measurement of $P_{\mathrm{1D}}$ with QMLE from DESI data

Validation of spectroscopic pipeline noise and resolution accuracy

Comparison with FFT-based methods for future analysis

Abstract

The one-dimensional power spectrum $P_{\mathrm{1D}}$ of the Ly$\alpha$ forest provides important information about cosmological and astrophysical parameters, including constraints on warm dark matter models, the sum of the masses of the three neutrino species, and the thermal state of the intergalactic medium. We present the first measurement of $P_{\mathrm{1D}}$ with the quadratic maximum likelihood estimator (QMLE) from the Dark Energy Spectroscopic Instrument (DESI) survey early data sample. This early sample of $54~600$ quasars is already comparable in size to the largest previous studies, and we conduct a thorough investigation of numerous instrumental and analysis systematic errors to evaluate their impact on DESI data with QMLE. We demonstrate the excellent performance of the spectroscopic pipeline noise estimation and the impressive accuracy of the spectrograph resolution matrix with two-dimensional image simulations of raw DESI images that we processed with the DESI spectroscopic pipeline. We also study metal line contamination and noise calibration systematics with quasar spectra on the red side of the Ly$\alpha$ emission line. In a companion paper, we present a similar analysis based on the Fast Fourier Transform estimate of the power spectrum. We conclude with a comparison of these two approaches and implications for the upcoming DESI Year 1 analysis.