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B. Dey

Publications and source records attributed to B. Dey.

At least 19 recordsLinked to original sources
arXiv2026

Linking neutral gas inflows and outflows to offsets in the star-forming main sequence and mass-metallicity relation

Gas inflows and outflows regulate galaxy growth, but direct observational links between measured gas flows and galaxy scaling relations remain limited. Using ~6,000 star-forming galaxies with down-the-barrel Na I D absorption from DESI DR2, we examine how systems with detected neutral-gas inflows and outflows populate the star-forming main sequence (SFMS) and mass-metallicity relation (MZR). Inflow and outflow hosts are compared with stellar-mass- and redshift-matched controls, and with SFMS and MZR fits derived from galaxies without detected gas flows. Outflow hosts (v_flow $\leq$ -50 km s$^{-1}$) show enhanced sSFRs by 0.25-0.40 dex and elevated central metallicities by 0.04-0.06 dex in the lower-redshift sample. Slow inflow hosts (0 $<$ v_flow $<$ 100 km s$^{-1}$) show similarly enhanced sSFRs of 0.20-0.30 dex, but no significant metallicity offset, while fast inflow hosts (v_flow $\geq$ 100 km s$^{-1}$) show weaker SFR enhancement and modestly lower metallicities. Together, these trends support a regulator picture in which neutral gas flows trace different phases of the baryon cycle. Slow inflow hosts lie above the SFMS, consistent with accretion sustaining enhanced star formation without strong central metallicity dilution. This may indicate that inflowing gas is already metal-enriched or has mixed or enriched over extended timescales. By contrast, outflow hosts lie near the upper 1{$\sigma$} SFMS envelope, consistent with feedback regulating subsequent growth. Gas-flow hosts also show small but systematic offsets in the narrow 4000 {\AA} break strength ($D_n$4000) relative to controls matched in redshift, stellar mass and SFR. Our results show that neutral gas flows are associated with population-level offsets from the SFMS and MZR, consistent with a baryon-cycle contribution to scaling-relation scatter.

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arXiv2026

Beyond traditional emission-line diagnostics: using autoencoders to uncover active galactic nuclei in DESI spectra

The growing volume of spectroscopic data in modern surveys motivates data-driven approaches that complement traditional emission-line diagnostics for active galactic nuclei (AGN) identification. We present a machine learning framework that exploits the full optical spectrum using unsupervised representation learning within a semi-supervised classification scheme. We use the SPENDER autoencoder to compress DESI galaxy spectra into a low-dimensional latent space and classify sources through a k-d tree nearest-neighbor search. The model is trained on 50,222 DESI Main Survey spectra from the Guadalupe dataset and released as part of Data Release 1 (DR1), restricted to z <= 0.5. We validate the performance using labels derived from FastSpecFit's emission line measurements defining seven galaxy classes: AGN, broad-line (BL), composite, star-forming, passive, retired, and Other. The method achieves high accuracies for AGN (0.952) and broad-line AGN (0.965), reliably identifying these sources even in low signal-to-noise spectra and recovering AGN missed by standard single-diagnostic methods. Our classification metrics are benchmarked against traditional diagnostics, and we show they represent lower limits of the model's true performance. We also find that the learned latent space correlates with key galaxy properties such as stellar mass and star-formation rate, demonstrating that it captures physically meaningful information. These results show that unsupervised spectral representation learning, implemented within a semi-supervised classification framework, provides a scalable and effective approach for constructing more complete AGN catalogues for current and future spectroscopic surveys.

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arXiv2026

Alcock-Paczynski Blinding Scheme for the Ly-$\alpha$ Forest Analysis

We present and validate a blinding method for the Lyman-$\alpha$ (Ly$\alpha$) forest analysis based on a modification of the Alcock-Paczynski test. In order to hide the background expansion history, the method employs a geometrical shift of each quasar (QSO) forest in wavelength space, once the quasar continuum has been fitted and the fluctuation field is extracted. The redshift positions for the QSO sample are also changed in a consistent manner. We show that the method remains effective when applied to real data, where contamination from metals and Lyman-$\beta$ is intrinsically mixed with the Lyman-$\alpha$ forest. This limitation is primarily visible in the 1D correlation function, where other blinding strategies can mitigate the effect. To assess its effectiveness, the prescription is tested against a series of datasets of increasing complexity: from idealized low-noise mocks, to realistic DESI year one synthetic datasets, and finally to data from DESI first data release (DR1), using both the auto (Ly$\alpha\times$Ly$\alpha$) and cross (Ly$\alpha\times$ QSO) correlations. We find that the method robustly shifts the BAO peak position from the 3D correlation functions to the expected value for cosmology changes of around 5\% in the matter content, without altering the shape of the posteriors in the model parameters. In conclusion, this catalog-level blinding strategy is a viable method for cosmological inference with the Lyman-$\alpha$ forest, particularly if a cross-analysis with other tracers using the same blinding strategy is pursued.

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arXiv2026

The largest sample of AGN outflows in dwarf galaxies using DESI DR1

In the last decade, the presence of active galactic nuclei (AGN) outflows and feedback in dwarf galaxies ($\mathrm{M_\ast}$<$10^{10}\mathrm{M}_\odot$) has gained ground over supernova (SN) feedback as the main mechanism regulating star formation. In this work, we perform the first systematic search for AGN outflows in dwarf galaxies using the Dark Energy Spectroscopic Instrument Data Release 1 (DESI DR1). From $\sim$ 7 million galaxies at z$<$0.45, we identify ionized outflows through the detection of broad components in the [OIII]$\lambda5007$\AA emission line. Galaxies are divided into dwarf and massive systems. Then, using emission-line diagnostic diagrams, we classify as star forming or AGN. We identify 1,502 AGN dwarf galaxies with outflow signatures. Comparing the distributions of star forming and AGN galaxies with outflows, we find that, among the 1,502 AGN dwarf galaxies with outflow signatures, AGN are the most likely drivers of the observed outflows in $\sim$83$\%$ of those with W$_{80}$ velocity $>250$ km s$^{-1}$. This constitutes the largest statistical sample of AGN outflows in dwarf galaxies to date. In massive galaxies, AGN dominance occurs above W$_{80}>350$ km s$^{-1}$. Therefore, two new velocity thresholds are proposed for identifying AGN-driven outflows in dwarf and massive galaxies. Besides, we find that outflows in dwarf galaxies are more likely to escape the dark matter halo than those in massive galaxies, allowing gas to be redistributed from the inner to the outer regions. This suggests that AGN outflows may have a major impact on dwarf galaxies.

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arXiv2026

Quality Assessment of Spectroscopic Data Reduction Pipelines Using Artificial Intelligence: Scrutinizing Data Release 2 from the DESI Survey

Large spectroscopic surveys now collect data at a scale that makes traditional visual inspection impractical. We present an unsupervised pipeline for spectroscopic quality assessment that requires no labeled training data. The method combines Uniform Manifold Approximation and Projection for dimensionality reduction with Friends-of-Friends clustering to isolate anomalous spectra for targeted review. We apply this pipeline to 58,291,334 spectra across 14,199 tiles from DESI Data Release 2, processing each tile independently to produce a tile-level outlier catalog. In each tile, the pipeline separates a dense core of typical spectra from small, isolated components and singletons, yielding a total of 1,095,816 outlier candidates. The mean tile-level outlier fraction is about 1.96 percent overall, with values of 0.76 percent and 2.36 percent for the dark and bright main-survey programs, respectively. From the visual inspection of 391 outlier candidates from the dark and bright programs of the main survey, we find that 66.8 percent exhibit identifiable spectral anomalies consistent with known reduction and calibration effects. By contrast, only 4.1 percent carry a non-zero quality flag from the standard reduction pipeline. This shows that the method provides a complementary quality-assessment layer to existing pipeline diagnostics and recovers a substantial population of problematic spectra that standard diagnostics miss. Extrapolating to the main-survey catalog, we estimate that approximately 218,000 candidate outliers are free of identifiable reduction artifacts and may correspond to genuine atypical spectra in the context of DESI. The pipeline is scalable, reproducible, and directly comparable across successive data releases, making it a practical quality-assurance monitor for DESI and future multi-object spectroscopic surveys.

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arXiv2026

DESI Data Release 2 ELGs: Property-dependent subsamples, imaging systematics, and clustering

Using emission-line galaxies (ELGs) from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2, we evaluate a property-dependent correction to imaging systematics. We derive systematic weights following the same linear regression method used for other DESI tracers, but do so separately on ELG subsamples to provide a physically-informed alternative to the fiducial, neural-network-based approach. In doing so, we show that the deeper imaging in the Dark Energy Survey (DES) footprint leads to a higher overall number density but a lack of targets with extreme $g-r$ and $r-z$ colors. ELGs in the DES region also show a distinct redshift distribution when subsampled by position in the $g-r$ vs. $r-z$ plane. To address these effects, we implement a separate treatment of the DES footprint within the DESI catalog production pipeline, which is generally well-motivated and, in some cases, imperative for accurate clustering measurements. With DES treated separately, we find that property-dependent systematic weights further mitigate spurious clustering signal in $\sim$10% of subsamples, while the fiducial scheme remains optimal for the full sample.

astro-ph.CO↗
arXiv2026

Precision Kinematic Sunyaev--Zel'dovich Measurements Across Halo Mass and Redshift with DESI DR2 and ACT DR6: Part I. Luminous Red Galaxies

We present the most precise measurements of the kinetic Sunyaev-Zel'dovich (kSZ) effect around luminous red galaxies to date, detecting the signal at $18\sigma$ significance in both harmonic and configuration space. Our analysis cross-correlates 2.4 million spectroscopic LRGs from the Dark Energy Spectroscopic Instrument (DESI) DR2 sample with Data Release 6 (DR6) of the Atacama Cosmology Telescope (ACT). We develop a novel harmonic-space cross-correlation approach using momentum-weighted kSZ templates, yielding nearly uncorrelated bandpowers within a framework consistent with other large-scale structure analyses. By incorporating the LRG halo occupation distribution (HOD) and its uncertainty, we convert measured galaxy gas profiles into halo gas profiles and provide generalized Navarro-Frenk-White (GNFW) fitting profiles, providing empirical targets for tuning feedback efficiency in hydrodynamical simulations and for baryonic modeling in large-scale structure analyses. We find strong evidence that gas profiles do not trace dark matter, providing direct evidence for gas redistribution beyond gravitational collapse. Comparing to hydrodynamical simulations, our measurements favor feedback efficiencies exceeding those in the Battaglia profile, suggesting more efficient gas ejection in group-scale halos than previously predicted. Splitting by redshift, we detect the kSZ signal at SNR $\approx 5$--$10$ in each of four bins and find amplitude evolution consistent with the expected decline in mean halo mass at fixed comoving number density. Splitting by stellar mass, we study the scaling of kSZ amplitude with galaxy properties. Together with BGS and ELG measurements in Paper II, these results span $0.1 \lesssim z \lesssim 1.6$ across three galaxy populations, demonstrating the potential of spectroscopic kSZ to map circumgalactic gas and constrain baryonic feedback.

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arXiv2026

FolpsD: combining EFT and phenomenological approaches for joint power spectrum and bispectrum analyses

We present a theoretical model for the power spectrum and bispectrum of galaxy clustering that exploits the complementarity between small-scale power spectrum information and large-scale bispectrum measurements. We extend the FOLPS code by combining its one-loop EFT galaxy power spectrum with a tree-level galaxy bispectrum projected onto the tripolar spherical harmonics (Sugiyama) basis. To access additional small-scale information, we also consider a line-of-sight damping factor in both statistics, mirroring approaches commonly used in studies of redshift-space distortions. We test the model using DESI DR2 galaxy mocks. Even without damping, the joint analysis of the EFT power spectrum and bispectrum significantly improves constraints and reduces parameter degeneracies relative to power spectrum analyses alone. For LRG-like samples, including the damping further extends the range beyond $k\sim 0.3 \,h \text{Mpc}^{-1}$ in the power spectrum and $k \sim 0.24 \,h \text{Mpc}^{-1}$ in the bispectrum without introducing statistically significant parameter biases. This leads to up to $\sim 30\%$ tighter constraints on $A_s$ and $\omega_{cdm}$. For low signal-to-noise tracers such as QSOs, however, the damping parameters are weakly constrained and can absorb noise fluctuations, leading to shifts in inferred parameters. Similar limitations may arise in models where cosmological information is encoded in power-spectrum shape features degenerate with the damping, such as scenarios with massive neutrinos. In contrast, for $w_0w_a$CDM we obtain $15\%$ and $21\%$ tighter constraints on $w_0$ and $w_a$, respectively, yielding a deviation from constant dark energy at slightly more than the $1\sigma$ level using full-shape information alone. The code is publicly available at https://github.com/cosmodesi/FolpsD

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arXiv2026

Measurement of the galaxy-velocity power spectrum of DESI tracers with the kinematic Sunyaev-Zeldovich effect using DESI DR2 and ACT DR6

Joint analyses of high-resolution CMB temperature maps with galaxy surveys provide a unique way to reconstruct the radial velocity field of the underlying matter distribution via the kinematic Sunyaev-Zeldovich (kSZ) effect. Using data from the Atacama Cosmology Telescope (ACT) DR6 and the Dark Energy Spectroscopic Instrument (DESI) DR2, we present radial velocity reconstructions for luminous red galaxies (LRGs), emission-line galaxies (ELGs), and quasars (QSOs). Leveraging the spectroscopic data, we are able to reliably model the foreground contamination and report a negligible impact on our main observables. We detect the velocity-galaxy cross-correlation at $17.0\sigma$ for LRGs, and for the first time, at $8.3\sigma$ for ELGs and $6.8\sigma$ for QSOs. We further report the first detection of the velocity-velocity correlation using LRGs at $3.1\sigma$, as well as the highest cumulative detection of the kSZ effect to date at $20.8 \sigma$. Similarly to previous results, we find a lower amplitude of the kSZ signal compared to our fiducial halo model prediction and electron profile assuming a Battaglia profile. Combining these new observables, we obtain constraints on local-type primordial non-Gaussianity (PNG): $f_{\rm NL}^{\rm loc} = 15.9_{-34.4}^{+34.6}$ at 68\% confidence, which represents the tightest constraint to date derived from the velocity field. The measurements presented here already exhibit lower noise on a per-mode basis than the galaxy auto-correlation on the largest scales, $k<0.004~\rm{Mpc^{-1}}$, highlighting the key role these observables will play in the context of future CMB experiments such as the Simons Observatory.

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arXiv2026

Local primordial non-Gaussianity using cross-correlations of DESI tracers

We constrain local primordial non-Gaussianity by a combined analysis of auto and cross-correlations of DESI DR1 tracers, leveraging LRGs and QSOs as well as ELGs between $0.8<z<3.1$. By cross-validating the signal across different clustering tracers within the same redshift range, we evaluate potential systematics in the $f^\mathrm{loc}_\mathrm{NL}$ measurements, capitalizing on the reduced susceptibility of cross-correlations to non-common systematics. We find that the cross-correlation between LRG and quasars can robustly improve the DESI DR1 $f^\mathrm{loc}_\mathrm{NL}$ constraints, by $\sim9\%$ to a measurement of $f^\mathrm{loc}_\mathrm{NL}=2.1_{-8.3}^{+8.8}$ at 68\% confidence. On the other hand, we do not find a clear improvement when including the DESI DR1 ELG sample. Mock tests predict an additional $\sim8\%$ gain with statistical scatter, and the lack of improvement in the data remains consistent with this expectation. This project serves as an exploratory analysis of DESI ELG clustering for $f^\mathrm{loc}_\mathrm{NL}$ through its cross-correlation in preparation for future DESI data analyses.

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arXiv2026

The Linear Point Standard Ruler with DESI DR1 and DR2 Data

The linear point, a purely geometric feature in the monopole of the two-point correlation function, has been proposed as an alternative standard ruler. Compared to the peak in the correlation function, it is more robust to late-time nonlinear effects at the percent level. In light of improved simulations and high quality data, we revisit the robustness of the linear point and use it as an alternative to template-based fitting approaches typically used in BAO analyses. We present the linear point measurements on galaxy samples from the first and second data releases (DR1 and DR2) of the DESI survey. We convert the linear point into a dimensionless parameter $\alpha_{iso,LP}$, defined as the ratio of the linear point in the fiducial cosmology and the observed value, analogous to the isotropic BAO scaling parameter $\alpha_{iso}$ used in previous BAO measurements. Using the 2nd generation of AbacusSummit mock catalogs, we find that linear point measurements are more precise when calculated in the post-reconstruction regime with 15-60% smaller uncertainties than those pre-reconstruction. We find a systematic shift in the linear point measurements compared against the isotropic BAO measurements in mocks; we attribute this to the isotropic damping parameter responsible for smearing the linear point in the nonlinear regime. We propose a sample-dependent correction that mitigates the impact of late-time nonlinear effects. While this introduces a cosmology dependence in an otherwise model-independent measurement, this is necessary given the sub-percent precision dictated by current cosmological surveys. Comparing $\alpha_{iso,LP}$ with isotropic BAO measurements made on the DESI DR1 and DR2 galaxy samples, we find excellent agreement after applying this correction, particularly post-reconstruction. We discuss future scope regarding cosmological inference with linear point measurements.

astro-ph.CO↗
arXiv2026

Electron temperature relations and the direct N, O, Ne, S and Ar abundances of 49959 star-forming galaxies in DESI Data Release 2

We present the largest direct-method abundance catalogue of galaxies to date, containing measurements of 49959 star-forming galaxies at z < 0.96 from DESI Data Release 2. By directly measuring electron temperatures across multiple ionisation zones, we provide constraints on a number of electron temperature relations. Using the temperature measurements, we derive reliable abundances for N, O, Ne, S and Ar and measure the evolution of abundances and abundance ratios of as a function of metallicity and other galaxy properties. Our measurements include direct oxygen abundances for 49507 galaxies, leading to the discovery of the two most metal-poor galaxies in the nearby Universe, with oxygen abundances of 12+log(O/H) = $\rm 12+\log(O/H) = 6.77_{-0.03}^{+0.03}~\rm dex $ (1.2\% $\rm Z_{\odot}$) and $\rm 12+\log(O/H) = 6.81_{-0.04}^{+0.04}~\rm dex$ (1.3\% $\rm Z_{\odot}$). We identify a rare outlier population of 24 galaxies with high N/O ratios at low metallicity, reminiscent of galaxy abundances observed in the early Universe. We find the Ne/O ratio is constant at low metallicity but increases gradually at $\rm 12+log(O/H) > 8.105\pm0.004$ dex. We show that the S/O and Ar/O abundance ratios are strongly correlated, consistent with the expected additional Type Ia enrichment channel for S and Ar. In this work we present an initial survey of the key properties of the sample, with this dataset serving as a foundation for extensive future work on galaxy abundances at low redshift.

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arXiv2025

Clustering redshift distribution calibration of weak lensing surveys using the DESI-DR1 spectroscopic dataset

We estimate the source redshift distribution of current weak lensing surveys by applying the clustering-based redshift calibration technique, using the galaxy redshift sample provided by the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1). We cross-correlate the Bright Galaxy Survey (BGS), Luminous Red Galaxies (LRGs) and Emission Line Galaxies (ELGs) from DESI, within the redshift range $0.1 < z < 1.6$, with overlapping tomographic source samples from the Dark Energy Survey (DES), Kilo-Degree Survey (KiDS), and Hyper Suprime-Cam (HSC) survey. Using realistic mock catalogues, we test the stability of the clustering-redshift signal to fitting scale, reference-sample choice, and the evolution of source galaxy bias, and we explicitly model and marginalise over magnification contributions, which become non-negligible at $z \gtrsim 1$ due to the depth of the DESI ELG sample. We then compare the resulting bias-weighted redshift distributions to those calibrated using self-organising map (SOM) techniques, finding agreement within uncertainties for all surveys and tomographic bins. Our results demonstrate that clustering redshifts enabled by DESI's unprecedented spectroscopic sample provides a robust, complementary, and independent constraint capable of reducing one of the dominant systematic uncertainties in weak lensing cosmology.

astro-ph.CO↗
arXiv2025

The DESI DR1 Peculiar Velocity Survey: Fundamental Plane Catalogue

Measurements of peculiar velocities in the local Universe are a powerful tool to study the nature of dark energy at low ($z < 0.1$) redshifts. Here we present the largest single set of $z<0.1$ peculiar velocity measurements to date, obtained using the Fundamental Plane (FP) of galaxies in the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). We describe the photometric and spectroscopic selection criteria used to define the sample, as well as extensive quality control checks on the photometry and velocity dispersion measurements. Additionally, we perform detailed systematics checks for the many analysis parameters in our pipeline. Our DESI DR1 catalogue contains FP-based distances and peculiar velocities for $98,292$ unique early-type galaxies, increasing the total number of $z < 0.1$ FP distances ever measured by a factor of $\sim2$. We achieve a precision of $26\%$ random error in our distance measurements which is comparable to previous surveys. A series of companion DESI papers use the distances and peculiar velocities presented in this paper to measure cosmological parameters.

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arXiv2025

Detection of supernova magnitude fluctuations induced by large-scale structure

The peculiar velocities of supernovae and their host galaxies are correlated with the large-scale structure of the Universe, and can be used to constrain the growth rate of structure and test the cosmological model. In this work, we measure the correlation statistics of the large-scale structure traced by the Dark Energy Spectroscopic Instrument Bright Galaxy Survey Data Release 1 sample, and magnitude fluctuations of type Ia supernova from the Pantheon+ compilation across redshifts $z < 0.1$. We find a detection of the cross-correlation signal between galaxies and type Ia supernova magnitudes. Fitting the normalised growth rate of structure $f \sigma_8$ to the auto- and cross-correlation function measurements we find $f \sigma_8 = 0.384^{+0.094}_{-0.157}$ at $z = 0.03$, which is consistent with the Planck $\Lambda$CDM model prediction, and indicates that the supernova magnitude fluctuations are induced by peculiar velocities. Using a large ensemble of N-body simulations, we validate our methodology, calibrate the covariance of the measurements, and demonstrate that our results are insensitive to supernova selection effects. We highlight the potential of this methodology for measuring the growth rate of structure, and forecast that the next generation of type Ia supernova surveys will improve $f \sigma_8$ constraints by a further order of magnitude.

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arXiv2025

Validation of the DESI-DR1 3x2-pt analysis: scale cut and shear ratio tests

Combined survey analyses of galaxy clustering and weak gravitational lensing (3x2-pt studies) will allow new and accurate tests of the standard cosmological model. However, careful validation is necessary to ensure that these cosmological constraints are not biased by uncertainties associated with the modelling of astrophysical or systematic effects. In this study we validate the combined 3x2-pt analysis of the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1) spectroscopic galaxy clustering and overlapping weak lensing datasets from the Kilo-Degree Survey (KiDS), the Dark Energy Survey (DES), and the Hyper-Suprime-Cam Survey (HSC). By propagating the modelling uncertainties associated with the non-linear matter power spectrum, non-linear galaxy bias and baryon feedback, we design scale cuts to ensure that measurements of the matter density and the amplitude of the matter power spectrum are biased by less than 30% of the statistical error. We also test the internal consistency of the data and weak lensing systematics by performing new measurements of the lensing shear ratio. We demonstrate that the DESI-DR1 shear ratios can be successfully fit by the same model used to describe cosmic shear correlations, and analyse the additional information that can be extracted about the source redshift distributions and intrinsic alignment parameters. This study serves as crucial preparation for the upcoming cosmological parameter analysis of these datasets.

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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: 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.

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