arXiv subjects

M. Walther

Publications and source records attributed to M. Walther.

At least 19 recordsLinked to original sources

arXiv2026

Cosmological analysis of the DESI DR1 Lyman alpha 1D power spectrum

We present the cosmological analysis of the one-dimensional Lyman-$\alpha$ flux power spectrum from the first data release of the Dark Energy Spectroscopic Instrument (DESI). We capture the dependence of the signal on cosmology and intergalactic medium physics using an emulator trained on a cosmological suite of hydrodynamical simulations, and we correct its predictions for the impact of astrophysical contaminants and systematics, many of these not considered in previous analyses. We employ this framework to constrain the amplitude and logarithmic slope of the linear matter power spectrum at $k_\star=0.009\,\mathrm{km^{-1}s}$ and redshift $z=3$, obtaining $\Delta^2_\star=0.379\pm0.032$ and $n_\star=-2.309\pm0.019$. The robustness of these constraints is validated through the analysis of mocks and a large number of alternative data analysis variations, with cosmological parameters kept blinded throughout the validation process. We then combine our results with constraints from DESI BAO and temperature, polarization, and lensing measurements from Planck, ACT, and SPT-3G to set constraints on $\Lambda$CDM extensions. While our measurements do not significantly tighten the limits on the sum of neutrino masses from the combination of these probes, they sharpen the constraints on the effective number of relativistic species, $N_\mathrm{eff}=3.02\pm0.10$, the running of the spectral index, $\alpha_\mathrm{s}=0.0014\pm0.0041$, and the running of the running, $\beta_\mathrm{s}=-0.0006\pm0.0048$, by a factor of 1.18, 1.27, and 1.90, respectively. We conclude by outlining the improvements needed to fully reach the level of confidence implied by these uncertainties.

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arXiv2025

DESI DR1 Ly$\alpha$ forest: 3D full-shape analysis and cosmological constraints

We perform an analysis of the full shapes of Lyman-$\alpha$ (Ly$\alpha$) forest correlation functions measured from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). Our analysis focuses on measuring the Alcock-Paczynski (AP) effect and the cosmic growth rate times the amplitude of matter fluctuations in spheres of $8$ $h^{-1}\text{Mpc}$, $f\sigma_8$. We validate our measurements using two different sets of mocks, a series of data splits, and a large set of analysis variations, which were first performed blinded. Our analysis constrains the ratio $D_M/D_H(z_\mathrm{eff})=4.525\pm0.071$, where $D_H=c/H(z)$ is the Hubble distance, $D_M$ is the transverse comoving distance, and the effective redshift is $z_\mathrm{eff}=2.33$. This is a factor of $2.4$ tighter than the Baryon Acoustic Oscillation (BAO) constraint from the same data. When combining with Ly$\alpha$ BAO constraints from DESI DR2, we obtain the ratios $D_H(z_\mathrm{eff})/r_d=8.646\pm0.077$ and $D_M(z_\mathrm{eff})/r_d=38.90\pm0.38$, where $r_d$ is the sound horizon at the drag epoch. We also measure $f\sigma_8(z_\mathrm{eff}) = 0.37\; ^{+0.055}_{-0.065} \,(\mathrm{stat})\, \pm 0.033 \,(\mathrm{sys})$, but we do not use it for cosmological inference due to difficulties in its validation with mocks. In $\Lambda$CDM, our measurements are consistent with both cosmic microwave background (CMB) and galaxy clustering constraints. Using a nucleosynthesis prior but no CMB anisotropy information, we measure the Hubble constant to be $H_0 = 68.3\pm 1.6\;\,{\rm km\,s^{-1}\,Mpc^{-1}}$ within $\Lambda$CDM. Finally, we show that Ly$\alpha$ forest AP measurements can help improve constraints on the dark energy equation of state, and are expected to play an important role in upcoming DESI analyses.

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arXiv2025

Probing the limits of cosmological information from the Lyman-$\alpha$ forest 2-point correlation functions

The standard cosmological analysis with the Ly$\alpha$ forest relies on a continuum fitting procedure that suppresses information on large scales and distorts the three-dimensional correlation function on all scales. In this work, we present the first cosmological forecasts without continuum fitting distortion in the Ly$\alpha$ forest, focusing on the recovery of large-scale information. Using idealized synthetic data, we compare the constraining power of the full shape of the Ly$\alpha$ forest auto-correlation and its cross-correlation with quasars using the baseline continuum fitting analysis versus the true continuum. We find that knowledge of the true continuum enables a $\sim10\%$ reduction in uncertainties on the Alcock-Paczy\'nski (AP) parameter and the matter density, $\Omega_\mathrm{m}$. We also explore the impact of large-scale information by extending the analysis up to separations of $240\,h^{-1}\mathrm{Mpc}$ along and across the line of sight. The combination of these analysis choices can recover significant large-scale information, yielding up to a $\sim15\%$ improvement in AP constraints. This improvement is analogous to extending the Ly$\alpha$ forest survey area by $\sim40\%$.

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arXiv2025

DESI DR1 Ly$\alpha$ 1D power spectrum: Validation of estimators

The Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI) is the largest sample to date for small-scale Ly$\alpha$ forest cosmology, accessed through its one-dimensional power spectrum ($P_{\mathrm{1D}}$). The Ly$\alpha$ forest $P_{\mathrm{1D}}$ is extracted from quasar spectra that are highly inhomogeneous (both in wavelength and between quasars) in noise properties due to intrinsic properties of the quasar, atmospheric and astrophysical contamination, and also sensitive to low-level details of the spectral extraction pipeline. We employ two estimators in DR1 analysis to measure $P_{\mathrm{1D}}$: the optimal estimator and the fast Fourier transform (FFT) estimator. To ensure robustness of our DR1 measurements, we validate these two power spectrum and covariance matrix estimation methodologies against the challenging aspects of the data. First, using a set of 20 synthetic 1D realizations of DR1, we derive the masking bias corrections needed for the FFT estimator and the continuum fitting bias needed for both estimators. We demonstrate that both estimators, including their covariances, are unbiased with these corrections using the Kolmogorov-Smirnov test. Second, we substantially extend our previous suite of CCD image simulations to include 675,000 quasars, allowing us to accurately quantify the pipeline's performance. This set of simulations reveals biases at the highest $k$ values, corresponding to a resolution error of a few percent. We base the resolution systematics error budget of DR1 $P_{\mathrm{1D}}$ on these values, but do not derive corrections from them since the simulation fidelity is insufficient for precise corrections.

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arXiv2025

Human vs. machine -- 1:3. Joint analysis of classical and ML-based summary statistics of the Lyman-$\alpha$ forest

In order to compress and more easily interpret Lyman-$\alpha$ forest (Ly$\alpha$F) datasets, summary statistics, e.g. the power spectrum, are commonly used. However, such summaries unavoidably lose some information, weakening the constraining power on parameters of interest. Recently, machine learning (ML)-based summary approaches have been proposed as an alternative to human-defined statistical measures. This raises a question: can ML-based summaries contain the full information captured by traditional statistics, and vice versa? In this study, we apply three human-defined techniques and one ML-based approach to summarize mock Ly$\alpha$F data from hydrodynamical simulations and infer two thermal parameters of the intergalactic medium, assuming a power-law temperature-density relation. We introduce a metric for measuring the improvement in the figure of merit when combining two summaries. Consequently, we demonstrate that the ML-based summary approach not only contains almost all of the information from the human-defined statistics, but also that it provides significantly stronger constraints by a ratio of better than 1:3 in terms of the posterior volume on the temperature-density relation parameters.

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arXiv2025

Cosmological neutrino mass: a frequentist overview in light of DESI

We derive constraints on the neutrino mass using a variety of recent cosmological datasets, including DESI BAO, the full-shape analysis of the DESI matter power spectrum and the one-dimensional power spectrum of the Lyman-$\alpha$ forest (P1D) from eBOSS quasars as well as the cosmic microwave background (CMB). The constraints are obtained in the frequentist formalism by constructing profile likelihoods and applying the Feldman-Cousins prescription to compute confidence intervals. This method avoids potential prior and volume effects that may arise in a comparable Bayesian analysis. Parabolic fits to the profiles allow one to distinguish changes in the upper limits from variations in the constraining power $\sigma$ of the different data combinations. We find that all profiles in the $\Lambda$CDM model are cut off by the $\sum m_\nu \geq 0$ bound, meaning that the corresponding parabolas reach their minimum in the unphysical sector. The most stringent 95% C.L. upper limit is obtained by the combination of DESI DR2 BAO, Planck PR4 and CMB lensing at 53 meV, below the minimum of 59 meV set by the normal ordering. Extending $\Lambda$CDM to non-zero curvature and $w_0w_\mathrm{a}$CDM relaxes the constraints past 59 meV again, but only $w_0w_\mathrm{a}$CDM exhibits profiles with a minimum at a positive value. Using a combination of DESI DR1 full-shape, BBN and eBOSS Lyman-$\alpha$ P1D, we successfully constrain the neutrino mass independently of the CMB. This combination yields $\sum m_\nu \leq 285$ meV (95% C.L.). The addition of DESI full-shape or Lyman-$\alpha$ P1D to CMB and DESI BAO results in small but noticeable improvement of the constraining power of the data. Lyman-$\alpha$ free-streaming measurements especially improve the constraint. Since they are based on eBOSS data, this sets a promising precedent for upcoming DESI data.

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arXiv2025

Modeling of the High Column Density systems in The Lyman-Alpha Forest

The Lyman-$\alpha$ forests observed in the spectra of high-redshift quasars can be used as a tracer of the cosmological matter density to study baryon acoustic oscillations (BAO) and the Alcock-Paczynski effect. Extraction of cosmological information from these studies requires modeling of the forest correlations. While the models depend most importantly on the bias parameters of the intergalactic medium (IGM), they also depend on the numbers and characteristics of high-column-density systems (HCDs) ranging from Lyman-limit systems with column densities $\log_{10}\!\bigl(N_{\mathrm{HI}}/\mathrm{cm}^{-2}\bigr)>17$ to damped Lyman-$\alpha$ systems (DLAs) with $\log_{10}\!\bigl(N_{\mathrm{HI}}/\mathrm{cm}^{-2}\bigr)>20.2$. These HCDs introduce broad damped absorption characteristic of a Voigt profile. Consequently they imprint a component on the power spectrum whose modes in the radial direction are suppressed, leading to a scale-dependent bias. Using mock data sets of known HCD content, we test a model that describes this effect in terms of the distribution of column densities of HCDs, the Fourier transforms of their Voigt profiles and the bias of the halos containing the HCDs. Our results show that this physically well-motivated model describes the effects of HCDs with an accuracy comparable to that of the ad-hoc models used in published forest analyses. We also discuss the problems of applying the model to real data, where the HCD content and their bias is uncertain.

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arXiv2025

DESI DR1 Ly$\alpha$ 1D power spectrum: The optimal estimator measurement

The one-dimensional power spectrum $P_{\mathrm{1D}}$ of Ly$\alpha$ forest offers rich insights into cosmological and astrophysical parameters, including constraints on the sum of neutrino masses, warm dark matter models, and the thermal state of the intergalactic medium. We present the measurement of $P_{\mathrm{1D}}$ using the optimal quadratic maximum likelihood estimator applied to over 300,000 Ly$\alpha$ quasars from Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI) survey. This sample represents the largest to date for $P_{\mathrm{1D}}$ measurements and is larger than the Extended Baryon Oscillation Spectroscopic Survey (eBOSS) by a factor of 1.7. We conduct a meticulous investigation of instrumental and analysis systematics and quantify their impact on $P_{\mathrm{1D}}$. This includes the development of a cross-exposure estimator that eliminates the need to model the pipeline noise and has strong potential for future $P_{\mathrm{1D}}$ measurements. We also present new insights into metal contamination through the 1D correlation function. Using a fitting function we measure the evolution of the Ly$\alpha$ forest bias with high precision: $b_F(z) = (-0.218\pm0.002)\times((1 + z) / 4)^{2.96\pm0.06}$. In a companion validation paper, we substantially extend our previous suite of CCD image simulations to quantify the pipeline's exquisite performance accurately. In another companion paper, we present DR1 $P_{\mathrm{1D}}$ measurements using the Fast Fourier Transform (FFT) approach to power spectrum estimation. These two measurements produce a forest bias parameter that differs by 2.2 sigma. However, our model is simplistic, so this disagreement will be investigated in future work.

astro-ph.CO↗

arXiv2025

Positive neutrino masses with DESI DR2 via matter conversion to dark energy

The Dark Energy Spectroscopic Instrument (DESI) is a massively parallel spectroscopic survey on the Mayall telescope at Kitt Peak, which has released measurements of baryon acoustic oscillations determined from over 14 million extragalactic targets. We combine DESI Data Release 2 with CMB datasets to search for evidence of matter conversion to dark energy (DE), focusing on a scenario mediated by stellar collapse to cosmologically-coupled black holes (CCBH). In this physical model, which has the same number of free parameters as $\Lambda$CDM, DE production is determined by the cosmic star formation rate density (SFRD), allowing for distinct early- and late-time cosmologies. Using two SFRDs to bracket current observations, we find that the CCBH model: accurately recovers the cosmological expansion history, agrees with early-time baryon abundance measured by BBN, reduces tension with the local distance ladder, and relaxes constraints on the summed neutrino mass $\sum m_\nu$. For these SFRDs, we find a peaked positive $\sum m_\nu < 0.149\,\rm eV$ (95% confidence) and $\sum m_\nu = 0.106^{+0.050}_{-0.069}\,\rm eV$ respectively, in good agreement with lower limits from neutrino oscillation experiments. A peak in $\sum m_\nu > 0$ results from late-time baryon consumption in the CCBH scenario and is expected to be a general feature of any model that converts sufficient matter to dark energy during and after reionization.

astro-ph.CO↗

arXiv2025

Cosmological implications of DESI DR2 BAO measurements in light of the latest ACT DR6 CMB data

We report cosmological results from the Dark Energy Spectroscopic Instrument (DESI) measurements of baryon acoustic oscillations (BAO) when combined with recent data from the Atacama Cosmology Telescope (ACT). By jointly analyzing ACT and Planck data and applying conservative cuts to overlapping multipole ranges, we assess how different Planck+ACT dataset combinations affect consistency with DESI. While ACT alone exhibits a tension with DESI exceeding 3$\sigma$ within the $\Lambda$CDM model, this discrepancy is reduced when ACT is analyzed in combination with Planck. For our baseline DESI DR2 BAO+Planck PR4+ACT likelihood combination, the preference for evolving dark energy over a cosmological constant is about 3$\sigma$, increasing to over 4$\sigma$ with the inclusion of Type Ia supernova data. While the dark energy results remain quite consistent across various combinations of Planck and ACT likelihoods with those obtained by the DESI collaboration, the constraints on neutrino mass are more sensitive, ranging from $\sum m_\nu < 0.061$ eV in our baseline analysis, to $\sum m_\nu < 0.077$ eV (95\% confidence level) in the CMB likelihood combination chosen by ACT when imposing the physical prior $\sum m_\nu>0$ eV.

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arXiv2025

Early time solution as an alternative to the late time evolving dark energy with DESI DR2 BAO

Recently the Dark Energy Spectroscopic Instrument (DESI) provided constraints on the expansion history from their Data Release 2 (DR2). The DESI baryon acoustic oscillation (BAO) measurements are well described by a flat $\Lambda$CDM model, but the preferred parameters are in mild ($2.3\sigma$) tension with those determined from the cosmic microwave background (CMB). The DESI collaboration has already explored a variety of solutions to this tension relying on variations in the late-time evolution of dark energy. Here we test an alternative -- the introduction of an ``early dark energy'' (EDE) component. We find that EDE models can alleviate the tension, though they lead to differences in other cosmological parameters that have observational implications. Particularly the EDE models that fit the acoustic datasets prefer lower $\Omega_m$, higher $H_0$, $n_s$ and $\sigma_8$ in contrast to the late-time solutions. We discuss the current status and near-future prospects for distinguishing amongst these solutions.

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arXiv2025

Construction of the Damped Ly$\alpha$ Absorber Catalog for DESI DR2 Ly$\alpha$ BAO

We present the Damped Ly$\alpha$ Toolkit for automated detection and characterization of Damped Ly$\alpha$ absorbers (DLA) in quasar spectra. Our method uses quasar spectral templates with and without absorption from intervening DLAs to reconstruct observed quasar forest regions. The best-fitting model determines whether a DLA is present while estimating the redshift and \texttt{HI} column density. With an optimized quality cut on detection significance ($\Delta \chi_{r}^2>0.03$), the technique achieves an estimated 80\% purity and 79\% completeness when evaluated on simulated spectra with S/N~$>2$ that are free of broad absorption lines (BAL). We provide a catalog containing candidate DLAs from the DLA Toolkit detected in DESI DR1 quasar spectra, of which 21,719 were found in S/N~$>2$ spectra with predicted $\log_{10} (N_\texttt{HI}) > 20.3$ and detection significance $\Delta \chi_{r}^2 >0.03$. We compare the Damped Ly$\alpha$ Toolkit to two alternative DLA finders based on a convolutional neural network (CNN) and Gaussian process (GP) models. We present a strategy for combining these three techniques to produce a high-fidelity DLA catalog from DESI DR2 for the Ly$\alpha$ forest baryon acoustic oscillation measurement. The combined catalog contains 41,152 candidate DLAs with $\log_{10} (N_\texttt{HI}) > 20.3$ from quasar spectra with S/N~$>2$. We estimate this sample to be approximately 85\% pure and 79\% complete when BAL quasars are excluded.

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arXiv2025

Validation of the DESI DR2 Ly$\alpha$ BAO analysis using synthetic datasets

The second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI), containing data from the first three years of observations, doubles the number of Lyman-$\alpha$ (Ly$\alpha$) forest spectra in DR1 and it provides the largest dataset of its kind. To ensure a robust validation of the Baryonic Acoustic Oscillation (BAO) analysis using Ly$\alpha$ forests, we have made significant updates compared to DR1 to both the mocks and the analysis framework used in the validation. In particular, we present CoLoRe-QL, a new set of Ly$\alpha$ mocks that use a quasi-linear input power spectrum to incorporate the non-linear broadening of the BAO peak. We have also increased the number of realisations used in the validation to 400, compared to the 150 realisations used in DR1. Finally, we present a detailed study of the impact of quasar redshift errors on the BAO measurement, and we compare different strategies to mask Damped Lyman-$\alpha$ Absorbers (DLAs) in our spectra. The BAO measurement from the Ly$\alpha$ dataset of DESI DR2 is presented in a companion publication.

astro-ph.IM↗

arXiv2024

Validation of the DESI 2024 Lyman Alpha Forest BAL Masking Strategy

Broad absorption line quasars (BALs) exhibit blueshifted absorption relative to a number of their prominent broad emission features. These absorption features can contribute to quasar redshift errors and add absorption to the Lyman-alpha (LyA) forest that is unrelated to large-scale structure. We present a detailed analysis of the impact of BALs on the Baryon Acoustic Oscillation (BAO) results with the LyA forest from the first year of data from the Dark Energy Spectroscopic Instrument (DESI). The baseline strategy for the first year analysis is to mask all pixels associated with all BAL absorption features that fall within the wavelength region used to measure the forest. We explore a range of alternate masking strategies and demonstrate that these changes have minimal impact on the BAO measurements with both DESI data and synthetic data. This includes when we mask the BAL features associated with emission lines outside of the forest region to minimize their contribution to redshift errors. We identify differences in the properties of BALs in the synthetic datasets relative to the observational data, as well as use the synthetic observations to characterize the completeness of the BAL identification algorithm, and demonstrate that incompleteness and differences in the BALs between real and synthetic data also do not impact the BAO results for the LyA forest.

astro-ph.CO↗

arXiv2024

Characterization of contaminants in the Lyman-alpha forest auto-correlation with DESI

Baryon Acoustic Oscillations can be measured with sub-percent precision above redshift two with the Lyman-alpha forest auto-correlation and its cross-correlation with quasar positions. This is one of the key goals of the Dark Energy Spectroscopic Instrument (DESI) which started its main survey in May 2021. We present in this paper a study of the contaminants to the lyman-alpha forest which are mainly caused by correlated signals introduced by the spectroscopic data processing pipeline as well as astrophysical contaminants due to foreground absorption in the intergalactic medium. Notably, an excess signal caused by the sky background subtraction noise is present in the lyman-alpha auto-correlation in the first line-of-sight separation bin. We use synthetic data to isolate this contribution, we also characterize the effect of spectro-photometric calibration noise, and propose a simple model to account for both effects in the analysis of the lyman-alpha forest. We then measure the auto-correlation of the quasar flux transmission fraction of low redshift quasars, where there is no lyman-alpha forest absorption but only its contaminants. We demonstrate that we can interpret the data with a two-component model: data processing noise and triply ionized Silicon and Carbon auto-correlations. This result can be used to improve the modeling of the lyman-alpha auto-correlation function measured with DESI.

astro-ph.CO↗

arXiv2024

Validation of the DESI 2024 Ly$\alpha$ forest BAO analysis using synthetic datasets

The first year of data from the Dark Energy Spectroscopic Instrument (DESI) contains the largest set of Lyman-$\alpha$ (Ly$\alpha$) forest spectra ever observed. This data, collected in the DESI Data Release 1 (DR1) sample, has been used to measure the Baryon Acoustic Oscillation (BAO) feature at redshift $z=2.33$. In this work, we use a set of 150 synthetic realizations of DESI DR1 to validate the DESI 2024 Ly$\alpha$ forest BAO measurement. The synthetic data sets are based on Gaussian random fields using the log-normal approximation. We produce realistic synthetic DESI spectra that include all major contaminants affecting the Ly$\alpha$ forest. The synthetic data sets span a redshift range $1.8<z<3.8$, and are analysed using the same framework and pipeline used for the DESI 2024 Ly$\alpha$ forest BAO measurement. To measure BAO, we use both the Ly$\alpha$ auto-correlation and its cross-correlation with quasar positions. We use the mean of correlation functions from the set of DESI DR1 realizations to show that our model is able to recover unbiased measurements of the BAO position. We also fit each mock individually and study the population of BAO fits in order to validate BAO uncertainties and test our method for estimating the covariance matrix of the Ly$\alpha$ forest correlation functions. Finally, we discuss the implications of our results and identify the needs for the next generation of Ly$\alpha$ forest synthetic data sets, with the top priority being to simulate the effect of BAO broadening due to non-linear evolution.

astro-ph.CO↗

arXiv2024

Impact of Systematic Redshift Errors on the Cross-correlation of the Lyman-$\alpha$ Forest with Quasars at Small Scales Using DESI Early Data

The Dark Energy Spectroscopic Instrument (DESI) will measure millions of quasar spectra by the end of its 5 year survey. Quasar redshift errors impact the shape of the Lyman-$\alpha$ forest correlation functions, which can affect cosmological analyses and therefore cosmological interpretations. Using data from the DESI Early Data Release and the first two months of the main survey, we measure the systematic redshift error from an offset in the cross-correlation of the Lyman-$\alpha$ forest with quasars. We find evidence for a redshift dependent bias causing redshifts to be underestimated with increasing redshift, stemming from improper modeling of the Lyman-$\alpha$ optical depth in the templates used for redshift estimation. New templates were derived for the DESI Year 1 quasar sample at $z > 1.6$ and we found the redshift dependent bias, $\Delta r_\parallel$, increased from $-1.94 \pm 0.15$ $h^{-1}$ Mpc to $-0.08 \pm 0.04$ $h^{-1}$ Mpc ($-205 \pm 15~\text{km s}^{-1}$ to $-9.0 \pm 4.0~\text{km s}^{-1}$). These new templates will be used to provide redshifts for the DESI Year 1 quasar sample.

astro-ph.CO↗

arXiv2023

Synthetic spectra for Lyman-$\alpha$ forest analysis in the Dark Energy Spectroscopic Instrument

Synthetic data sets are used in cosmology to test analysis procedures, to verify that systematic errors are well understood and to demonstrate that measurements are unbiased. In this work we describe the methods used to generate synthetic datasets of Lyman-$\alpha$ quasar spectra aimed for studies with the Dark Energy Spectroscopic Instrument (DESI). In particular, we focus on demonstrating that our simulations reproduces important features of real samples, making them suitable to test the analysis methods to be used in DESI and to place limits on systematic effects on measurements of Baryon Acoustic Oscillations (BAO). We present a set of mocks that reproduce the statistical properties of the DESI early data set with good agreement. Additionally, we use full survey synthetic data to forecast the BAO scale constraining power with DESI.

astro-ph.CO↗