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Marie Lynn Abdul-Karim

Publications and source records attributed to Marie Lynn Abdul-Karim.

4 recordsLinked to original sources

Measurement of the small-scale 3D Lyman-$α$ forest power spectrum

Small-scale correlations measured in the Lyman-$α$ (Ly$α$) forest encode information about the intergalactic medium and the primordial matter power spectrum. In this article, we present and implement a simple method to measure the 3-dimensional power spectrum, $P_{\rm 3D}$, of the Ly$α$ forest at wavenumbers $k$ corresponding to small, $\sim$ Mpc scales. In order to estimate $P_{\rm 3D}$ from sparsely and unevenly distributed data samples, we rely on averaging 1-dimensional Fourier Transforms, as previously carried out to estimate the 1-dimensional power spectrum of the Ly$α$ forest, $P_{\rm 1D}$. This methodology exhibits a very low computational cost. We confirm the validity of this approach through its application to Nyx cosmological hydrodynamical simulations. Subsequently, we apply our method to the eBOSS DR16 Ly$α$ forest sample, providing as a proof of principle, a first $P_{\rm 3D}$ measurement averaged over two redshift bins $z=2.2$ and $z=2.4$. This work highlights the potential for forthcoming $P_{\rm 3D}$ measurements, from upcoming large spectroscopic surveys, to untangle degeneracies in the cosmological interpretation of $P_{\rm 1D}$.

astro-ph.CO↗

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

The one-dimensional power spectrum $P_{\mathrm{1D}}$ of the Ly$α$ 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$α$ 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.

astro-ph.CO↗

The Lyman-$α$ forest catalog from the Dark Energy Spectroscopic Instrument Early Data Release

We present and validate the catalog of Lyman-$α$ forest fluctuations for 3D analyses using the Early Data Release (EDR) from the Dark Energy Spectroscopic Instrument (DESI) survey. We used 88,511 quasars collected from DESI Survey Validation (SV) data and the first two months of the main survey (M2). We present several improvements to the method used to extract the Lyman-$α$ absorption fluctuations performed in previous analyses from the Sloan Digital Sky Survey (SDSS). In particular, we modify the weighting scheme and show that it can improve the precision of the correlation function measurement by more than 20%. This catalog can be downloaded from https://data.desi.lbl.gov/public/edr/vac/edr/lya/fuji/v0.3 and it will be used in the near future for the first DESI measurements of the 3D correlations in the Lyman-$α$ forest.

astro-ph.CO↗

The Dark Energy Spectroscopic Instrument: One-dimensional power spectrum from first Lyman-$α$ forest samples with Fast Fourier Transform

We present the one-dimensional Lyman-$α$ forest power spectrum measurement using the first data provided by the Dark Energy Spectroscopic Instrument (DESI). The data sample comprises $26,330$ quasar spectra, at redshift $z > 2.1$, contained in the DESI Early Data Release and the first two months of the main survey. We employ a Fast Fourier Transform (FFT) estimator and compare the resulting power spectrum to an alternative likelihood-based method in a companion paper. We investigate methodological and instrumental contaminants associated to the new DESI instrument, applying techniques similar to previous Sloan Digital Sky Survey (SDSS) measurements. We use synthetic data based on log-normal approximation to validate and correct our measurement. We compare our resulting power spectrum with previous SDSS and high-resolution measurements. With relatively small number statistics, we successfully perform the FFT measurement, which is already competitive in terms of the scale range. At the end of the DESI survey, we expect a five times larger Lyman-$α$ forest sample than SDSS, providing an unprecedented precise one-dimensional power spectrum measurement.

astro-ph.CO↗