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A. Lambert

Publications and source records attributed to A. Lambert.

At least 19 recordsLinked to original sources

Combined tracer analysis for DESI 2024 BAO

This paper demonstrates how the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) and future baryon acoustic oscillations (BAO) analyses can optimally combine overlapping tracers (galaxies of distinct types) in the same redshift range. We make a unified catalog of Luminous Red Galaxies (LRGs) and Emission Line Galaxies (ELGs) in the redshift range 0.8 < z < 1.1 and investigate the impact on the BAO constraints. DESI DR1 contains ~30% of the final DESI LRG sample and less than 25% of the final ELG sample, and the combination of LRGs and ELGs increases the number density and reduces the shot noise. We developed a pipeline to merge the overlapping tracers using galaxy bias as an approximately optimal weight and tested the pipeline on a suite of Abacus simulations, calibrated on the final version of the DESI Early Data Release. When applying our pipeline to the DESI DR1 catalog, we find an improvement in the BAO constraints of 11% for $α_\mathrm{iso}$ and ~7.0% for $α_\mathrm{AP}$ consistent with our findings in mock catalogs. Our analysis was integrated into the DESI DR1 BAO analysis to produce the LRG+ELG result in the 0.8 < z < 1.1 redshift bin, which provided the most precise BAO measurement from DESI DR1 with a 0.86% constraint on the BAO distance scale and a $9.1σ$ detection of the isotropic BAO feature.

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Extending the Stellar-to-Halo Mass Relation to Dwarf Galaxies with DESI DR1

Constraining the dark matter halos of the smallest galaxies offers fundamental insights into the nature of dark matter and stellar feedback. Using the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, we infer the stellar-to-halo mass relation (SHMR) down to the dwarf scale ($M_\star < 10^9\,M_\odot$), without extrapolation from the higher mass range. Leveraging the unprecedented depth of the DESI Bright Galaxy Survey at $0.01 < z < 0.2$, we construct 12 samples spanning nearly four orders of magnitude in stellar mass, and measure their projected clustering $w_p$, galaxy-galaxy lensing $ΔΣ$, as well as a novel observable: satellite occupation number $N_{\rm sat}$. The addition of $N_{\rm sat}$ enables robust subtraction of satellite contributions to both $w_p$ and $ΔΣ$ across the 12 individual halo occupation distribution analyses, yielding an average halo-to-stellar mass relation (HSMR) of $\log \langle M_h(M_\star) \rangle = 12.06 + 0.58\log(M_\star/10^{11}) + (M_\star/10^{11})^{0.73}$. Combining this HSMR with an observed stellar mass function, we constrain the SHMR across five orders of magnitude in halo mass, with the power-law slope steepening from $0.32 \pm 0.06$ above the Milky Way mass to $2.08 \pm 0.21$ in the dwarf regime. Interestingly, the scatter about the SHMR grows from $0.17 \pm 0.02$ dex at Milky Way-like scales to $0.68_{-0.33}^{+0.21}$ dex for systems comparable to the Large Magellanic Cloud, suggesting that smaller galaxies follow increasingly diverse evolutionary paths. Our work highlights the power of DESI in probing the galaxy-halo connection within the dwarf regime, offering an exciting avenue to bridge the gap between large-scale and near-field cosmologies in the future.

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Spatially-Resolved Spectra of Diffuse Galactic Light using 10.8 M DESI Sky Fibers

Using 10.8 million ``blank'' sky spectra from the DESI Year 3 dataset, we measure the diffuse galactic light (DGL) spectrum in the optical at spectral resolution $R \sim 4000$ by correlating with far-infrared emission from IRAS. Subdividing the sky into 54 deg$^2$ pixels (HEALPix, NSIDE = 8), we map the variation of the DGL correlation spectrum and nebular emission lines across the DESI footprint in the high-Galactic-latitude sky. The increased data volume over previous SDSS-based analyses enables several new detections in the DGL, including scattering both onto and out of the line of sight from neutral interstellar sodium and potassium. We further detect direct emission from ro-vibrational transitions of molecular hydrogen in the near-infrared with an absolute radiance of $0.65\substack{+0.13 \\ -0.12}\times10^{-9}~{\rm erg\, cm^{-2}\,s^{-1}\,sr^{-1}}$, roughly consistent with theoretical expectations, but with an apparent ortho-to-para line ratio that is lower by a factor of $0.60\substack{+0.28 \\ -0.27}$. We confirm previous detections of extended red emission (ERE) in the DGL and map its spatial variation. Our spatially resolved DGL maps provide important observational constraints for the radiative transfer efforts that are now possible with recent 3D models of the Milky Way.

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Lyman Break Galaxy selection and redshift measurement with supervised contrastive learning

Some of the next steps for high-precision cosmology lie within the high-redshift, high-density universe. Spectroscopic survey experiments such as the Dark Energy Spectroscopic Instrument (DESI)'s second phase DESI Run 2 will shift towards probing Lyman Break Galaxy (LBG) populations from z$\sim$2 to z$\sim$4.5. For this faint sample, spectroscopic redshift measurement and sample decontamination remains a challenge, even after target selection. We propose an approach based on supervised weighted contrastive learning, in order to both learn a redshift representation for spectra and decontaminate the sample from quasars and low redshift emission line galaxies. This strategy generalizes the contrastive learning loss approach with continuous relationship weights, such that the network simultaneously learns redshift and classification tasks. The model shows stronger outlier classification and comparable redshift identification performances when compared to the previous network used for DESI (a modified version of QuasarNET) on the same dataset. In particular, contrastive learning is well suited to the small, visually-inspected sample used for training and testing, especially given the multi-task nature of this work.

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Lyman-$α$ forest holography: 3D predictions from 1D measurements

Cosmological analyses of Lyman-$α$ forest clustering rely on either one-dimensional correlations along individual sightlines or three-dimensional correlations between different sightlines. Because these observables probe the matter distribution on very different scales, they have traditionally been analyzed independently. In this work, we bridge this gap using ForestFlow, an emulator trained on a suite of cosmological hydrodynamical simulations that provides a unified description of Lyman-$α$ forest clustering from linear to nonlinear scales. This framework enables us to determine the range of three-dimensional clustering models compatible with the DESI one-dimensional flux power spectrum ($P_{\rm 1D}$). The resulting predictions successfully reproduce the large-scale clustering measured by the DESI BAO analysis and provide physically motivated priors on nonlinear clustering that are used in a companion paper presenting the full-shape analysis of the DESI DR2 Lyman-$α$ forest. We validate our methodology using the large-volume, high-resolution hydrodynamical simulation ACCEL-2, demonstrating excellent agreement across the full range of scales considered. Finally, we combine constraints from the $P_{\rm 1D}$ and BAO analyses on the parameter combinations $b_δσ_8$ and $b_ηf σ_8$, finding that the two probes provide comparable constraining power while exhibiting complementary parameter degeneracies. Our results establish a direct connection between one- and three-dimensional Lyman-$α$ forest measurements through ForestFlow, an approach we term Lyman-$α$ holography by analogy with the reconstruction of higher-dimensional structure from lower-dimensional information.

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Probing the matter-dominated expansion with multi-redshift Lyman-$α$ BAO from DESI DR2

We present a multi-redshift Baryon Acoustic Oscillations (BAO) analysis of the DESI Data Release 2 (DR2) Lyman-$α$ (Ly$α$) forest, splitting the forest auto-correlation and its cross-correlation with quasars into three redshift bins. We obtain BAO measurements at effective redshifts $z_{\rm eff} = 2.13$, $2.40$, and $2.81$ with $\sim2.0$--$2.5\%$ precision per bin in the radial and transverse directions, corresponding to $\sim1.1$--$1.2\%$ precision for the isotropic BAO measurement. Using the same data products and modeling framework as the DESI DR2 Ly$α$ BAO analysis, we validate the pipeline on $400$ synthetic datasets and find unbiased BAO recovery with well-calibrated uncertainties. The measurements show an increase in the isotropic dilation parameter $D_V/r_d$ from $30.26\pm0.39$ to $32.22\pm0.47$ and in the Alcock-Paczyński parameter $D_M/D_H$ from $3.96\pm0.15$ to $5.63^{+0.22}_{-0.24}$. The Hubble distance $D_H/r_d$ decreases from $9.40\pm0.20$ to $7.22\pm0.17$, providing a direct measurement of the expansion history consistent with $Λ$CDM and the expected matter-dominated scaling, with $H(z)\propto(1+z)^n$ giving $n=1.34\pm0.16$. The redshift split also provides a self-consistent measurement of clustering evolution: the Ly$α$ forest bias evolves as $(1+z)^γ$ with $γ_α=3.05\pm0.16$, the RSD parameter has a redshift evolution described by $γ_β=-0.97\pm0.26$, and the quasar bias evolves with $γ_Q=1.56\pm0.23$, consistent with independent quasar clustering measurements. Combining these three-bin BAO measurements with DESI DR2 galaxy and quasar BAO measurements yields cosmological constraints consistent with the single-bin Ly$α$ BAO analysis in flat $Λ$CDM and $w_0w_a$CDM and improves curvature constraints by $\sim12\%$ in $Λ$CDM$+Ω_\mathrm{K}$.

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Alcock-Paczynski Blinding Scheme for the Ly-$α$ Forest Analysis

We present and validate a blinding method for the Lyman-$α$ (Ly$α$) 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-$β$ is intrinsically mixed with the Lyman-$α$ 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$α\times$Ly$α$) and cross (Ly$α\times$ 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-$α$ forest, particularly if a cross-analysis with other tracers using the same blinding strategy is pursued.

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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$Åemission 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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Inference of matter power spectrum at z=0 using DESI DR1 Full-Shape data

Measurements of galaxy distributions at large cosmic distances capture clustering from the past. In this study, we use a cosmological model to translate these observations into the present-day galaxy distribution. Specifically, we reconstruct the 3D matter power spectrum at redshift $ z = 0 $ using Dark Energy Spectroscopic Instrument (DESI) Year 1 (DR1) galaxy clustering data and Cosmic Microwave Background (CMB) observations, assuming the $ Λ\text{CDM} $ model, and compare it to the result assuming the $ w_0w_a \text{CDM} $ model. Building on previous state-of-the-art methods, we apply Effective Field Theory (EFT) modelling of the galaxy power spectrum to account for small-scale effects in the 2-point statistics of galaxy data. The EFT approach offers a more robust methodology than traditional methods for modelling the galaxy power spectrum from galaxy clustering data, which can be used to test the consistency of the assumed cosmological model. By incorporating both CMB and galaxy clustering data across a range of redshifts, we can identify discrepancies between the datasets, which would indicate potential inaccuracies in the assumed expansion history. While previous studies have shown consistency with $ Λ\text{CDM} $, this work extends the analysis with higher-quality data to further test the expansion histories of both $ Λ\text{CDM} $ and $ w_0w_a \text{CDM} $. Our findings show that both $ Λ\text{CDM} $ and $ w_0w_a \text{CDM} $ provide consistent fits to the matter power spectrum recovered from DESI DR1 data.

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DESI Strong Lens Foundry III: Keck Spectroscopy for Strong Lenses Discovered Using Residual Neural Networks

We present spectroscopic data of strong lenses and their source galaxies using the Keck Near-Infrared Echellette Spectrometer (NIRES) and the Dark Energy Spectroscopic Instrument (DESI), providing redshifts necessary for nearly all strong-lensing applications with these systems, especially the extraction of physical parameters from lensing modeling. These strong lenses were found in the DESI Legacy Imaging Surveys using Residual Neural Networks (ResNet) and followed up by our Hubble Space Telescope program, with all systems displaying unambiguous lensed arcs. With NIRES, we target eight lensed sources at redshifts difficult to measure in the optical range and determine the source redshifts for six, between $z_s$ = 1.675 and 3.332. DESI observed one of the remaining source redshifts, as well as an additional source redshift within the six systems. The two systems with non-detections by NIRES were observed for a considerably shorter 600s at high airmass. Combining NIRES infrared spectroscopy with optical spectroscopy from our DESI Strong Lensing Secondary Target Program, these results provide the complete lens and source redshifts for six systems, a resource for refining automated strong lens searches in future deep- and wide-field imaging surveys and addressing a range of questions in astrophysics and cosmology.

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Identifying Anomalous DESI Galaxy Spectra with a Variational Autoencoder

The tens of millions of spectra being captured by the Dark Energy Spectroscopic Instrument (DESI) provide tremendous discovery potential. In this work we show how Machine Learning, in particular Variational Autoencoders (VAE), can detect anomalies in a sample of approximately 200,000 DESI spectra comprising galaxies, quasars and stars. We demonstrate that the VAE can compress the dimensionality of a spectrum by a factor of 100, while still retaining enough information to accurately reconstruct spectral features. We then detect anomalous spectra as those with high reconstruction error and those which are isolated in the VAE latent representation. The anomalies identified fall into two categories: spectra with artefacts and spectra with unique physical features. Awareness of the former can help to improve the DESI spectroscopic pipeline; whilst the latter can lead to the identification of new and unusual objects. To further curate the list of outliers, we use the Astronomaly package which employs Active Learning to provide personalised outlier recommendations for visual inspection. In this work we also explore the VAE latent space, finding that different object classes and subclasses are separated despite being unlabelled. We demonstrate the interpretability of this latent space by identifying tracks within it that correspond to various spectral characteristics. For example, we find tracks that correspond to increasing star formation and increase in broad emission lines along the Balmer series. In upcoming work we hope to apply the methods presented here to search for both systematics and astrophysically interesting objects in much larger datasets of DESI spectra.

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Clustering analysis of medium-band selected high-redshift galaxies

Next-generation large-scale structure spectroscopic surveys will probe cosmology at high redshifts $(2.3 < z < 3.5)$, relying on abundant galaxy tracers such as Ly$α$ emitters (LAEs) and Lyman break galaxies (LBGs). Medium-band photometry has emerged as a potential technique for efficiently selecting these high-redshift galaxies. In this work, we present clustering analysis of medium-band selected galaxies at high redshift, utilizing photometric data from the Intermediate Band Imaging Survey (IBIS) and spectroscopic data from the Dark Energy Spectroscopic Instrument (DESI). We interpret the clustering of such samples using both Halo Occupation Distribution (HOD) modeling and a perturbation theory description of large-scale structure. Our modeling indicates that the current target sample is composed from an overlapping mixture of LAEs and LBGs with emission lines. Despite differences in target selection, we find that the clustering properties are consistent with previous studies, with correlation lengths $r_0\simeq 3-4\,h^{-1}$Mpc and a linear bias of $b\sim1.8-2.5$. Finally, we discuss the simulation requirements implied by these measurements and demonstrate that the properties of the samples would make them excellent targets to enhance our understanding of the high-$z$ universe.

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DESI DR2 reference mocks: clustering results from Uchuu-BGS and LRG

The aim of this work is to construct mock galaxy catalogues that accurately reproduce the redshift evolution of galaxy number density, clustering statistics, and baryonic properties, such as stellar mass for luminous red galaxies (LRGs) and absolute magnitude in the $r$-band for the bright galaxy sample (BGS), based on the first three years of observations from the Dark Energy Spectroscopic Instrument (DESI). To achieve this, we applied the subhalo abundance matching (SHAM) technique to the Uchuu $N$-body simulation, which follows the evolution of 2.1 trillion particles within a volume of $8\,h^{-3}\,\mathrm{Gpc}^{3}$, assuming a Planck base-$Λ$CDM cosmology. Using SHAM, we populated Uchuu subhalos with LRGs and BGS-BRIGHT ($r<19.5$) galaxies up to redshift $z=1.1$, assigning stellar masses to LRGs and luminosities to BGS galaxies (up to $M_{\rm r}\leq 20$). Furthermore, we analyzed the clustering dependence on stellar mass and luminosity for each tracer. Our results show that the Uchuu BGS-BRIGHT and LRG mocks accurately reproduce the observed redshift evolution of clustering, with better than 5\% agreement for separations of $1<r<20\,h^{-1}\,\mathrm{Mpc}$ and below 10\% for $0.1<r<1\,h^{-1}\,\mathrm{Mpc}$. For the Uchuu-LRG mock, we successfully captured the stellar mass dependence of clustering, while for the Uchuu-BGS mock, we replicated the clustering for various volume-limited subsamples. We also find good agreement between the data and mocks in the dependence of large-scale bias on luminosity for BGS-BRIGHT galaxies and on stellar mass for LRGs. Altogether, these results equip DESI with robust tools for generating high-fidelity lightcones for the remainder of the survey, thereby enhancing our understanding of the galaxy--halo connection.

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The Lyman-$α$ Forest from LBGs: First 3D Correlation Measurement with DESI and Prospects for Cosmology

The Lyman-$α$ (Ly$α$) forest is a key tracer of large-scale structure at redshifts z > 2, traditionally studied using spectra of quasars. Here, we explore the viability Lyman Break Galaxies (LBGs) as alternative background sources for Ly$α$ forest studies. We analyze 4,151 Ly$α$ forest skewers extracted from LBG spectra obtained in the DESI pilot surveys in the COSMOS and XMM-LSS fields. We present the first measurement of the Ly$α$ forest auto-correlation function derived exclusively from LBG spectra, probing comoving separations up to 48 $h^{-1}$Mpc at an effective redshift of $z_\mathrm{eff}$ = 2.70. The measured signal is consistent with that from DESI DR2 quasar Ly$α$ forest spectra at a comparable redshift, validating LBGs as reliable background sources. We also measure the cross-correlation between the LBG Ly$α$ forest and 13,362 galaxy positions, showing that this observable serves as a sensitive diagnostic for galaxy redshift uncertainties and systematic offsets. Finally, using synthetic LBG spectra and Fisher forecasts, we show that a future wide-area survey over 5000 deg$^2$, targeting 1000 LBGs per deg$^2$ at similar signal-to-noise than our dataset, could enable Ly$α$ forest baryon acoustic oscillation (BAO) measurements with 0.4% precision on the isotropic BAO scale and 1.3% on the anisotropic (Alcock-Paczynski) scale. Combining BAO with a Ly$α$ forest full-shape analysis improves the AP constraint to 0.6%. These results open a new path for precision cosmology at high redshift using dense LBG samples.

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Probing the environment around GW170817 with DESI: insights on galaxy group peculiar velocities for standard siren measurements

We present a new measurement of the Hubble constant, $H_0$, following the gravitational wave event GW170817 and Dark Energy Spectroscopic Instrument (DESI) observations. A standard siren measurement with a nearby (luminosity distance $\sim 40 $ Mpc) event such as GW170817 is typically sensitive to the peculiar motion of the host galaxy due to local dynamics. Previous measurements from this event have taken advantage of peculiar velocity measurements of nearby galaxies, including a handful of objects in the galaxy group that the host of the event, NGC 4993, has been associated with. Still, the group's properties and NGC 4993's membership were debated. We present DESI observations of thousands of galaxies in the vicinity of NGC 4993, resulting in 39 group galaxies and a five-fold increase in galaxies compared to previous observations with many of these galaxies contributing to a peculiar velocity measurement. Examining the local dynamics, our observations support the presence of a galaxy group of which NGC 4993 is part with a halo mass of order $\sim$$10^{13}~M_\odot$. Using peculiar velocity measurements from our Fundamental Plane galaxies observations, we find $H_0 =70.9^{+6.4}_{-8.5}$ km s$^{-1}$ Mpc$^{-1}$. In addition, using a peculiar velocity measurement for NGC 4993 from Surface Brightness Fluctuations in Cosmicflows-4 we find $H_0 =73.4^{+3.3}_{-3.9}$ km s$^{-1}$ Mpc$^{-1}$. We study the impact of different galaxy selection criteria on the determination of the peculiar velocity and, in turn, on the $H_0$ measurement. Our results highlight the importance of multiplexed spectroscopic observations of the environments of gravitational wave events to probe local dynamics, which can ultimately affect standard siren measurements.

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Updated cosmological constraints on axion dark energy with DESI

We present updated constraints on the parameters of an axion dark energy model, for which we took into account the properties of its characteristic potential and its full cosmological evolution. We show that the values of the axion parameters appear sufficiently constrained by the data, including the latest DESI DR1, and are consistent with the theoretical expectations of a field mass $m_a$ in the ultralight regime $\log (m_a c^2/~\mathrm{eV}) \simeq -32.60~\pm~0.12$, and an effective energy scale $f_a$ close to the reduced Planck energy $\log (f_a/~ M_\mathrm{Pl}) \simeq -0.28~\pm~0.19$. Our results also support the idea of dynamical dark energy, although Bayesian evidence still favors the phenomenological dark energy model $w_0w_a$ over the axion dark energy, with the Bayes factor indicating moderate and weak strength of the evidence, respectively, when the models are compared to the cosmological constant $Λ$. However, the results suggest that axion dark energy remains a well-motivated model and its parameters may be better constrained if the upcoming DESI data show further evidence for dynamical dark energy.

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Clustering of DESI galaxies split by thermal Sunyaev-Zeldovich effect

The thermal Sunyaev-Zeldovich (tSZ) effect is associated with galaxy clusters - extremely large and dense structures tracing the dark matter with a higher bias than isolated galaxies. We propose to use the tSZ data to separate galaxies from redshift surveys into distinct subpopulations corresponding to different densities and biases independently of the redshift survey systematics. Leveraging the information from different environments, as in density-split and density-marked clustering, is known to tighten the constraints on cosmological parameters, like $Ω_m$, $σ_8$ and neutrino mass. We use data from the Dark Energy Spectroscopic Instrument (DESI) and the Atacama Cosmology Telescope (ACT) in their region of overlap to demonstrate informative tSZ splitting of Luminous Red Galaxies (LRGs). We discover a significant increase in the large-scale clustering of DESI LRGs corresponding to detections starting from 1-2 sigma in the ACT DR6 + Planck tSZ Compton-$y$ map, below the cluster candidate threshold (4 sigma). We also find that such galaxies have higher line-of-sight coordinate (and velocity) dispersions and a higher number of close neighbors than both the full sample and near-zero tSZ regions. We produce simple simulations of tSZ maps that are intrinsically consistent with galaxy catalogs and do not include systematic effects, and find a similar pattern of large-scale clustering enhancement with tSZ effect significance. Moreover, we observe that this relative bias pattern remains largely unchanged with variations in the galaxy-halo connection model in our simulations. This is promising for future cosmological inference from tSZ-split clustering with semi-analytical models. Thus, we demonstrate that valuable cosmological information is present in the lower signal-to-noise regions of the thermal Sunyaev-Zeldovich map, extending far beyond the individual cluster candidates.

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Value Added Catalog of physical properties of more than 1.3 million galaxies from the DESI Survey

Aims. We present an extensive catalog of the physical properties of more than a million galaxies within the Dark Energy Spectroscopic Instrument (DESI), one of the largest spectroscopic surveys to date. Spanning over a full variety of target types, including emission line galaxies and luminous red galaxies as well as quasars, our survey encompasses an unprecedented range of spectroscopic redshifts, stretching from 0 to 6. Methods. The physical properties, such as stellar masses and star formation rates, are derived via the CIGALE spectral energy distribution (SED) fitting code accounting for the contribution coming from active galactic nuclei (AGN). Based on the modeling of the optical-mid-infrared (grz complemented by WISE photometry) SEDs, we study galaxy properties with respect to their location on the main sequence. Results. We revise the dependence of stellar mass estimates on model choices and availability of the WISE photometry. The WISE information is mandatory to minimize the misclassification of star-forming galaxies as AGN. The lack of WISE bands in SED fits leads to elevated AGN fractions for 68% of star-forming galaxies identified using emission line diagnostic diagram but does not significantly affect their stellar mass nor star formation estimates.

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