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We measure the growth of cosmic density fluctuations on large scales and across the redshift range $0.3

We present new Galactic reddening maps of the high Galactic latitude sky using DESI imaging and spectroscopy. We directly measure the reddening of 2.6 million stars by comparing the observed stellar colors in $g-r$ and $r-z$ from DESI imaging with the synthetic colors derived from DESI spectra from the first two years of the survey. The reddening in the two colors is on average consistent with the \cite{fitzpatrick_correcting_1999} extinction curve with $R_\mathrm{V}=3.1$. We find that our reddening maps differ significantly from the commonly used \cite{schlegel_maps_1998} (SFD) reddening map (by up to 80 mmag in $E(B-V)$), and we attribute most of this difference to systematic errors in the SFD map. To validate the reddening map, we select a galaxy sample with extinction correction based on our reddening map, and this yields significantly better uniformity than the SFD extinction correction. Finally, we discuss the potential systematic errors in the DESI reddening measurements, including the photometric calibration errors that are the limiting factor on our accuracy. The $E(g-r)$ and $E(g-r)$ maps presented in this work, and for convenience their corresponding $E(B-V)$ maps with SFD calibration, are publicly available., Comment: Submitted to the Open Journal of Astrophysics. Associated data files: https://data.desi.lbl.gov/public/papers/mws/desi_dust/y2/v1/maps/

We explore correlations between the orientations of small galaxy groups, or "multiplets", and the large-scale gravitational tidal field. Using data from the Dark Energy Spectroscopic Instrument (DESI) Y1 survey, we detect the intrinsic alignment (IA) of multiplets to the galaxy-traced matter field out to separations of 100 Mpc/h. Unlike traditional IA measurements of individual galaxies, this estimator is not limited by imaging of galaxy shapes and allows for direct IA detection beyond redshift z = 1. Multiplet alignment is a form of higher-order clustering, for which the scale-dependence traces the underlying tidal field and amplitude is a result of small-scale (< 1 Mpc/h) dynamics. Within samples of bright galaxies (BGS), luminous red galaxies (LRG) and emission-line galaxies (ELG), we find similar scale-dependence regardless of intrinsic luminosity or colour. This is promising for measuring tidal alignment in galaxy samples that typically display no intrinsic alignment. DESI's LRG mock galaxy catalogues created from the AbacusSummit N-body simulations produce a similar alignment signal, though with a 33% lower amplitude at all scales. An analytic model using a non-linear power spectrum (NLA) only matches the signal down to 20 Mpc/h. Our detection demonstrates that galaxy clustering in the non-linear regime of structure formation preserves an interpretable memory of the large-scale tidal field. Multiplet alignment complements traditional two-point measurements by retaining directional information imprinted by tidal forces, and contains additional line-of-sight information compared to weak lensing. This is a more effective estimator than the alignment of individual galaxies in dense, blue, or faint galaxy samples., Comment: For an accessible summary of this paper, see https://cmlamman.github.io/doc/multipletIA_summary.pdf

Post-starburst galaxies (PSBs) are young quiescent galaxies that have recently experienced a rapid decrease in star formation, allowing us to probe the fast-quenching period of galaxy evolution. In this work, we obtained HST WFC3/F110W imaging to measure the sizes of 171 massive ($\mathrm{log(M_{*}/M_{\odot})\sim\,11)}$ spectroscopically identified PSBs at $1

We present a high-significance cross-correlation of CMB lensing maps from the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) with spectroscopically calibrated luminous red galaxies (LRGs) from the Dark Energy Spectroscopic Instrument (DESI). We detect this cross-correlation at a significance of 38$\sigma$; combining our measurement with the Planck Public Release 4 (PR4) lensing map, we detect the cross-correlation at 50$\sigma$. Fitting this jointly with the galaxy auto-correlation power spectrum to break the galaxy bias degeneracy with $\sigma_8$, we perform a tomographic analysis in four LRG redshift bins spanning $0.4 \le z \le 1.0$ to constrain the amplitude of matter density fluctuations through the parameter combination $S_8^\times = \sigma_8 \left(\Omega_m / 0.3\right)^{0.4}$. Prior to unblinding, we confirm with extragalactic simulations that foreground biases are negligible and carry out a comprehensive suite of null and consistency tests. Using a hybrid effective field theory (HEFT) model that allows scales as small as $k_{\rm max}=0.6$ $h/{\rm Mpc}$, we obtain a 3.3% constraint on $S_8^\times = \sigma_8 \left(\Omega_m / 0.3\right)^{0.4} = 0.792^{+0.024}_{-0.028}$ from ACT data, as well as constraints on $S_8^\times(z)$ that probe structure formation over cosmic time. Our result is consistent with the early-universe extrapolation from primary CMB anisotropies measured by Planck PR4 within 1.2$\sigma$. Jointly fitting ACT and Planck lensing cross-correlations we obtain a 2.7% constraint of $S_8^\times = 0.776^{+0.019}_{-0.021}$, which is consistent with the Planck early-universe extrapolation within 2.1$\sigma$, with the lowest redshift bin showing the largest difference in mean. The latter may motivate further CMB lensing tomography analyses at $z<0.6$ to assess the impact of potential systematics or the consistency of the $\Lambda$CDM model over cosmic time., Comment: Prepared for submission to JCAP (47 pages, 13 figures)

We use the forward modeling pipeline, Obiwan, to study the imaging systematics of the Luminous Red Galaxies (LRGs) targeted by the Dark Energy Spectroscopic Instrument (DESI). We update the Obiwan pipeline, which had previously been developed to simulate the optical images used to target DESI data, to further simulate WISE images in the infrared. This addition makes it possible to simulate the DESI LRGs sample, which utilizes WISE data in the target selection. Deep DESI imaging data combined with a method to account for biases in their shapes is used to define a truth sample of potential LRG targets. We simulate a total of 15 million galaxies to obtain a simulated LRG sample (Obiwan LRGs) that predicts the variations in target density due to imaging properties. We find that the simulations predict the trends with depth observed in the data, including how they depend on the intrinsic brightness of the galaxies. We observe that faint LRGs are the main contributing power of the imaging systematics trend induced by depth. We also find significant trends in the data against Galactic extinction that are not predicted by Obiwan. These trends depend strongly on the particular map of Galactic extinction chosen to test against, implying Large-Scale Structure systematic contamination (e.g. Cosmic-Infrared Background) in the Galactic extinction maps is a likely root cause. We additionally observe that the DESI LRGs sample exhibits a complex dependency on a combination of seeing, depth, and intrinsic galaxy brightness, which is not replicated by Obiwan, suggesting discrepancies between the current simulation settings and the actual observations. The detailed findings we present should be used to guide any observational systematics mitigation treatment for the clustering of the DESI LRG sample., Comment: 46 pages, 26 figures

We present a simple, differentiable method for predicting emission line strengths from rest-frame optical continua using an empirically-determined mapping. Extensive work has been done to develop mock galaxy catalogues that include robust predictions for galaxy photometry, but reliably predicting the strengths of emission lines has remained challenging. Our new mapping is a simple neural network implemented using the JAX Python automatic differentiation library. It is trained on Dark Energy Spectroscopic Instrument Early Release data to predict the equivalent widths (EWs) of the eight brightest optical emission lines (including H$\alpha$, H$\beta$, [O II], and [O III]) from a galaxy's rest-frame optical continuum. The predicted EW distributions are consistent with the observed ones when noise is accounted for, and we find Spearman's rank correlation coefficient $\rho_s > 0.87$ between predictions and observations for most lines. Using a non-linear dimensionality reduction technique (UMAP), we show that this is true for galaxies across the full range of observed spectral energy distributions. In addition, we find that adding measurement uncertainties to the predicted line strengths is essential for reproducing the distribution of observed line-ratios in the BPT diagram. Our trained network can easily be incorporated into a differentiable stellar population synthesis pipeline without hindering differentiability or scalability with GPUs. A synthetic catalogue generated with such a pipeline can be used to characterise and account for biases in the spectroscopic training sets used for training and calibration of photo-$z$'s, improving the modelling of systematic incompleteness for the Rubin Observatory LSST and other surveys., Comment: 17 pages, 8 figures, 1 table. Published in MNRAS

Ultraviolet (UV; rest-frame $\sim1200-2000$ A) spectra provide a wealth of diagnostics to characterize fundamental galaxy properties, such as their chemical enrichment, the nature of their stellar populations, and their amount of Lyman-continuum (LyC) radiation. In this work, we leverage publicly released JWST data to construct the rest-frame UV-to-optical composite spectrum of a sample of 63 galaxies at $5.6

We estimate the redshift-dependent, anisotropic clustering signal in DESI's Year 1 Survey created by tidal alignments of Luminous Red Galaxies (LRGs) and a selection-induced galaxy orientation bias. To this end, we measured the correlation between LRG shapes and the tidal field with DESI's Year 1 redshifts, as traced by LRGs and Emission-Line Galaxies (ELGs). We also estimate the galaxy orientation bias of LRGs caused by DESI's aperture-based selection, and find it to increase by a factor of seven between redshifts 0.4 - 1.1 due to redder, fainter galaxies falling closer to DESI's imaging selection cuts. These effects combine to dampen measurements of the quadrupole of the correlation function caused by structure growth on scales of 10 - 80 Mpc/h by about 0.15% for low redshifts (0.4

We explore the galaxy-halo connection information that is available in low-redshift samples from the early data release of the Dark Energy Spectroscopic Instrument (DESI). We model the halo occupation distribution (HOD) from z=0.1-0.3 using Survey Validation 3 (SV3; a.k.a., the One-Percent Survey) data of the DESI Bright Galaxy Survey (BGS). In addition to more commonly used metrics, we incorporate counts-in-cylinders (CiC) measurements, which drastically tighten HOD constraints. Our analysis is aided by the Python package, galtab, which enables the rapid, precise prediction of CiC for any HOD model available in halotools. This methodology allows our Markov chains to converge with much fewer trial points, and enables even more drastic speedups due to its GPU portability. Our HOD fits constrain characteristic halo masses tightly and provide statistical evidence for assembly bias, especially at lower luminosity thresholds: the HOD of central galaxies in $z\sim0.15$ samples with limiting absolute magnitude $M_r < -20.0$ and $M_r < -20.5$ samples is positively correlated with halo concentration with a significance of 99.9% and 99.5%, respectively. Our models also favor positive central assembly bias for the brighter $M_r < -21.0$ sample at $z\sim0.25$ (94.8% significance), but there is no significant evidence for assembly bias with the same luminosity threshold at $z\sim0.15$. We provide our constraints for each threshold sample's characteristic halo masses, assembly bias, and other HOD parameters. These constraints are expected to be significantly tightened with future DESI data, which will span an area 100 times larger than that of SV3.

We present two galaxy samples, selected from DESI Legacy Imaging Surveys (LS) DR9, with approximately 20,000 square degrees of coverage and spectroscopic redshift distributions designed for cross-correlations such as with CMB lensing, galaxy lensing, and the Sunyaev-Zel'dovich effect. The first sample is identical to the DESI Luminous Red Galaxy (LRG) sample, and the second sample is an extended LRG sample with 2-3 times the DESI LRG density. We present the improved photometric redshifts, tomographic binning and their spectroscopic redshift distributions and imaging systematics weights, and magnification bias coefficients. The catalogs and related data products will be made publicly available. The cosmological constraints using this sample and Planck lensing maps are presented in a companion paper. We also make public the new set of general-purpose photometric redshifts trained using DESI spectroscopic redshifts, which are used in this work, for all galaxies in LS DR9., Comment: Matches the journal version. Associated data files: https://data.desi.lbl.gov/public/papers/c3/lrg_xcorr_2023/. General-purpose photo-z catalogs: https://www.legacysurvey.org/dr9/files/#photo-z-sweeps-9-1-photo-z-sweep-brickmin-brickmax-pz-fits

Galaxy clusters enable unique opportunities to study cosmology, dark matter, galaxy evolution, and strongly-lensed transients. We here present a new cluster-finding algorithm, CluMPR (Clusters from Masses and Photometric Redshifts), that exploits photometric redshifts (photo-z's) as well as photometric stellar mass measurements. CluMPR uses a 2-dimensional binary search tree to search for overdensities of massive galaxies with similar redshifts on the sky and then probabilistically assigns cluster membership by accounting for photo-z uncertainties. We leverage the deep DESI Legacy Survey grzW1W2 imaging over one-third of the sky to create a catalogue of ~ 300,000 galaxy cluster candidates out to z = 1, including tabulations of member galaxies and estimates of each cluster's total stellar mass. Compared to other methods, CluMPR is particularly effective at identifying clusters at the high end of the redshift range considered (z = 0.75-1), with minimal contamination from low-mass groups. These characteristics make it ideal for identifying strongly lensed high-redshift supernovae and quasars that are powerful probes of cosmology, dark matter, and stellar astrophysics. As an example application of this cluster catalogue, we present a catalogue of candidate wide-angle strongly-lensed quasars in Appendix C. The five best candidates identified from this sample include two known lensed quasar systems and a possible changing-look lensed QSO with SDSS spectroscopy. All code and catalogues produced in this work are publicly available (see Data Availability)., Comment: 19 pages, 27 figures, redshifts debiased with new methodology, published by MNRAS

We use angular clustering of luminous red galaxies from the Dark Energy Spectroscopic Instrument (DESI) imaging surveys to constrain the local primordial non-Gaussianity parameter $\fnl$. Our sample comprises over 12 million targets, covering 14,000 square degrees of the sky, with redshifts in the range $0.2< z < 1.35$. We identify Galactic extinction, survey depth, and astronomical seeing as the primary sources of systematic error, and employ linear regression and artificial neural networks to alleviate non-cosmological excess clustering on large scales. Our methods are tested against simulations with and without $\fnl$ and systematics, showing superior performance of the neural network treatment. The neural network with a set of nine imaging property maps passes our systematic null test criteria, and is chosen as the fiducial treatment. Assuming the universality relation, we find $\fnl = 34^{+24(+50)}_{-44(-73)}$ at 68\%(95\%) confidence. We apply a series of robustness tests (e.g., cuts on imaging, declination, or scales used) that show consistency in the obtained constraints. We study how the regression method biases the measured angular power-spectrum and degrades the $\fnl$ constraining power. The use of the nine maps more than doubles the uncertainty compared to using only the three primary maps in the regression. Our results thus motivate the development of more efficient methods that avoid over-correction, protect large-scale clustering information, and preserve constraining power. Additionally, our results encourage further studies of $\fnl$ with DESI spectroscopic samples, where the inclusion of 3D clustering modes should help separate imaging systematics and lessen the degradation in the $\fnl$ uncertainty., Comment: 21 pages, 17 figures, 7 tables (Appendix excluded). Published in MNRAS

The One-Percent survey of the Dark Energy Spectroscopic Instrument collected ~ 270k emission line galaxies (ELGs) at 0.8 < z < 1.6. The high completeness of the sample allowed the clustering to be measured down to scales never probed before, 0.04 Mpc/h in rp for the projected 2-point correlation function (2PCF) and 0.17 Mpc/h in galaxy pair separation s for the 2PCF monopole and quadrupole. The most striking feature of the measurements is a strong signal at the smallest scales, below 0.2 Mpc/h in rp and 1 Mpc/h in s. We analyze these data in the halo occupation distribution framework. We consider different distributions for central galaxies, a standard power law for satellites with no condition on the presence of a central galaxy and explore several extensions of these models. For all considered models, the mean halo mass of the sample is found to be log10 ~ 11.9. We obtain a satellite mean occupation function which agrees with physically motivated ELG models only if we introduce central-satellite conformity, meaning that the satellite occupation is conditioned by the presence of central galaxies of the same type. To achieve in addition a good modeling of the clustering between 0.1 and 1 Mpc/h in rp, we allow for ELG positioning outside of the halo virial radius and find 0.5% of ELGs residing in the outskirts of halos. Furthermore, the satellite velocity dispersion inside halos is found to be ~ 30% larger than that of the halo dark matter particles. These are the main findings of our work. We investigate assembly bias as a function of halo concentration, local density or local density anisotropies and observe no significant change in our results. We split the data sample in two redshift bins and report no significant evolution with redshift. Lastly, changing the cosmology in the modeling impacts only slightly our results.

In the current Dark Energy Spectroscopic Instrument (DESI) survey, emission line galaxies (ELGs) and luminous red galaxies (LRGs) are essential for mapping the dark matter distribution at $z \sim 1$. We measure the auto and cross correlation functions of ELGs and LRGs at $0.80.1$ $\mathrm{Mpc}\,h^{-1}$. We can also reproduce the auto correlations of ELGs at $r_{\mathrm{p}}>0.3$ $\mathrm{Mpc}\,h^{-1}$ ($s>1$ $\mathrm{Mpc}\,h^{-1}$) in real (redshift) space. Although our model has only seven parameters, we show that it can be extended to higher redshifts and reproduces the observed auto correlations of ELGs in the whole range of $0.8

We present the first comprehensive Halo Occupation Distribution (HOD) analysis of the DESI One-Percent survey Luminous Red Galaxy (LRG) and Quasi-Stellar Object (QSO) samples. We constrain the HOD of each sample and test possible HOD extensions by fitting the redshift-space galaxy 2-point correlation functions in 0.15 < r < 32 Mpc/h in a set of fiducial redshift bins. We use AbacusSummit cubic boxes at Planck 2018 cosmology as model templates and forward model galaxy clustering with the AbacusHOD package. We achieve good fits with a standard HOD model with velocity bias, and we find no evidence for galaxy assembly bias or satellite profile modulation at the current level of statistical uncertainty. For LRGs in 0.4 < z < 0.6, we infer a satellite fraction of fsat = 11+-1%, a mean halo mass of log10 Mh = 13.40+0.02-0.02, and a linear bias of blin = 1.93+0.06-0.04. For LRGs in 0.6 < z < 0.8, we find fsat = 14+-1%, log10 Mh = 13.24+0.02-0.02, and blin = 2.08+0.03-0.03. For QSOs, we infer fsat = 3+8-2%, log10 Mh = 12.65+0.09-0.04, and blin = 2.63+0.37-0.26 in redshift range 0.8 < z < 2.1. Using these fits, we generate a large suite of high-fidelity galaxy mocks. We also study the redshift-evolution of the DESI LRG sample from z = 0.4 up to z = 1.1, revealing significant and interesting trends in mean halo mass, linear bias, and satellite fraction., Comment: Submitted to MNRAS, comments welcome

The massive end of the gas-phase mass--metallicity relation (MZR) is a sensitive probe of active galactic nuclei (AGN) feedback that is a crucial but highly uncertain component of galaxy evolution models. In this paper, we extend the $z\sim0.7$ MZR by $\sim$0.5 dex up to log$(M_\star/\textrm{M}_\odot)\sim11.1$. We use extremely deep VLT VIMOS spectra from the Large Early Galaxy Astrophysics Census (LEGA-C) survey to measure metallicities for 145 galaxies. The LEGA-C MZR matches the normalization of the $z\sim0.8$ DEEP2 MZR where they overlap, so we combine the two to create an MZR spanning from 9.3 to 11.1 log$(M_\star/\textrm{M}_\odot)$. The LEGA-C+DEEP2 MZR at $z\sim0.7$ is offset to slightly lower metallicities (0.05-0.13 dex) than the $z\sim0$ MZR, but it otherwise mirrors the established power law rise at low/intermediate stellar masses and asymptotic flattening at high stellar masses. We compare the LEGA-C+DEEP2 MZR to the MZR from two cosmological simulations (IllustrisTNG and SIMBA), which predict qualitatively different metallicity trends for high-mass galaxies. This comparison highlights that our extended MZR provides a crucial observational constraint for galaxy evolution models in a mass regime where the MZR is very sensitive to choices about the implementation of AGN feedback., Comment: 10 pages, 4 figures, 1 table

Large imaging surveys, such as the Legacy Survey of Space and Time, rely on photometric redshifts and tomographic binning for 3x2pt analyses that combine galaxy clustering and weak lensing. In this paper, we propose a method for optimizing the tomographic binning choice for the lens sample of galaxies. We divide the CosmoDC2 and Buzzard simulated galaxy catalogs into a training set and an application set, where the training set is nonrepresentative in a realistic way, and then estimate photometric redshifts for the application sets. The galaxies are sorted into redshift bins covering equal intervals of redshift or comoving distance, or with an equal number of galaxies in each bin, and we consider a generalized extension of these approaches. We find that bins of equal comoving distance produce the highest dark energy figure of merit of the initial binning choices, but that the choice of bin edges can be further optimized. We then train a neural network classifier to identify galaxies that are either highly likely to have accurate photometric redshift estimates or highly likely to be sorted into the correct redshift bin. The neural network classifier is used to remove poor redshift estimates from the sample, and the results are compared to the case when none of the sample is removed. We find that the neural network classifiers are able to improve the figure of merit by ~13% and are able to recover ~25% of the loss in the figure of merit that occurs when a nonrepresentative training sample is used., Comment: 18 pages, 14 figures

We utilize $\sim17000$ bright Luminous Red Galaxies (LRGs) from the novel Dark Energy Spectroscopic Instrument Survey Validation spectroscopic sample, leveraging its deep ($\sim2.5$ hour/galaxy exposure time) spectra to characterize the contribution of recently quenched galaxies to the massive galaxy population at $0.41$) of our sample of recently quenched galaxies represents the largest spectroscopic sample of post-starburst galaxies at that epoch. At $0.411.2$) LRGs by measuring the fraction of stellar mass each galaxy formed in the Gyr before observation, $f_\mathrm{1 Gyr}$. Although galaxies with $f_\mathrm{1 Gyr}>0.1$ are rare at $z\sim0.4$ ($\lesssim 0.5\%$ of the population), by $z\sim0.8$ they constitute $\sim3\%$ of massive galaxies. Relaxing this threshold, we find that galaxies with $f_\mathrm{1 Gyr}>5\%$ constitute $\sim10\%$ of the massive galaxy population at $z\sim0.8$. We also identify a small but significant sample of galaxies at $z=1.1-1.3$ that formed with $f_\mathrm{1 Gyr}>50\%$, implying that they may be analogues to high-redshift quiescent galaxies that formed on similar timescales. Future analysis of this unprecedented sample promises to illuminate the physical mechanisms that drive the quenching of massive galaxies after cosmic noon., Comment: Re-uploaded after acceptance to the Astrophysical Journal Letters. 14 pages, 5 figures, comments welcome!

K-corrections, conversions between flux in observed bands to flux in rest-frame bands, are critical for comparing galaxies at various redshifts. These corrections often rely on fits to empirical or theoretical spectral energy distribution (SED) templates of galaxies. However, the templates limit reliable K-corrections to regimes where SED models are robust. For instance, the templates are not well-constrained in some bands (e.g., WISE W4), which results in ill-determined K-corrections for these bands. We address this shortcoming by developing an empirically-driven approach to K-corrections as a means to mitigate dependence on SED templates. We perform a polynomial fit for the K-correction as a function of a galaxy's rest-frame color determined in well-constrained bands (e.g., rest-frame (g-r)) and redshift, exploiting the fact that galaxy SEDs can be described as a one parameter family at low redshift (0.01 < z < 0.09). For bands well-constrained by SED templates, our empirically-driven K-corrections are comparable to the SED fitting method of Kcorrect and SED template fitting employed in the GSWLC-M2 catalogue (the updated medium-deep GALEX-SDSS-WISE Legacy Catalogue). However, our method dramatically outperforms the available SED fitting K-corrections for WISE W4. Our method also mitigates incorrect template assumptions and enforces the K-correction to be 0 at z = 0. Our K-corrected photometry and code are publicly available., Comment: 15 pages, 9 figures, submitted to MNRAS

The study of galaxy evolution hinges on our ability to interpret multi-wavelength galaxy observations in terms of their physical properties. To do this, we rely on spectral energy distribution (SED) models which allow us to infer physical parameters from spectrophotometric data. In recent years, thanks to the wide and deep multi-waveband galaxy surveys, the volume of high quality data have significantly increased. Alongside the increased data, algorithms performing SED fitting have improved, including better modeling prescriptions, newer templates, and more extensive sampling in wavelength space. We present a comprehensive analysis of different SED fitting codes including their methods and output with the aim of measuring the uncertainties caused by the modeling assumptions. We apply fourteen of the most commonly used SED fitting codes on samples from the CANDELS photometric catalogs at z~1 and z~3. We find agreement on the stellar mass, while we observe some discrepancies in the star formation rate (SFR) and dust attenuation results. To explore the differences and biases among the codes, we explore the impact of the various modeling assumptions as they are set in the codes (e.g., star formation histories, nebular, dust, and AGN models) on the derived stellar masses, SFRs, and A_V values. We then assess the difference among the codes on the SFR-stellar mass relation and we measure the contribution to the uncertainties by the modeling choices (i.e., the modeling uncertainties) in stellar mass (~0.1dex), SFR (~0.3dex), and dust attenuation (~0.3mag). Finally, we present some resources summarizing best practices in SED fitting., Comment: 25 pages, 11 figures. Accepted for publication in ApJ

This report summarizes the current status of Cosmic Frontier physics and the broad and exciting future prospects identified for the Cosmic Frontier as part of the 2021 Snowmass Process., Comment: 55 pages. Contribution to the 2021 Snowmass Summer Study

We present a comprehensive analysis of the evolution of the morphological and structural properties of a large sample of galaxies at z=3-9 using early JWST CEERS NIRCam observations. Our sample consists of 850 galaxies at z>3 detected in both CANDELS HST imaging and JWST CEERS NIRCam images to enable a comparison of HST and JWST morphologies. Our team conducted a set of visual classifications, with each galaxy in the sample classified by three different individuals. We also measure quantitative morphologies using the publicly available codes across all seven NIRCam filters. Using these measurements, we present the fraction of galaxies of each morphological type as a function of redshift. Overall, we find that galaxies at z>3 have a wide diversity of morphologies. Galaxies with disks make up a total of 60\% of galaxies at z=3 and this fraction drops to ~30% at z=6-9, while galaxies with spheroids make up ~30-40% across the whole redshift range and pure spheroids with no evidence for disks or irregular features make up ~20%. The fraction of galaxies with irregular features is roughly constant at all redshifts (~40-50%), while those that are purely irregular increases from ~12% to ~20% at z>4.5. We note that these are apparent fractions as many selection effects impact the visibility of morphological features at high redshift. The distributions of S\'ersic index, size, and axis ratios show significant differences between the morphological groups. Spheroid Only galaxies have a higher S\'ersic index, smaller size, and higher axis ratio than Disk/Irregular galaxies. Across all redshifts, smaller spheroid and disk galaxies tend to be rounder. Overall, these trends suggest that galaxies with established disks and spheroids exist across the full redshift range of this study and further work with large samples at higher redshift is needed to quantify when these features first formed., Comment: Accepted for publication to ApJL, 24 pages, 14 figures

We present the first comprehensive release of photometric redshifts (photo-z's) from the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS) team. We use statistics based upon the Quantile-Quantile (Q--Q) plot to identify biases and signatures of underestimated or overestimated errors in photo-z probability density functions (PDFs) produced by six groups in the collaboration; correcting for these effects makes the resulting PDFs better match the statistical definition of a PDF. After correcting each group's PDF, we explore three methods of combining the different groups' PDFs for a given object into a consensus curve. Two of these methods are based on identifying the minimum f-divergence curve, i.e., the PDF that is closest in aggregate to the other PDFs in a set (analogous to the median of an array of numbers). We demonstrate that these techniques yield improved results using sets of spectroscopic redshifts independent of those used to optimize PDF modifications. The best photo-z PDFs and point estimates are achieved with the minimum f-divergence using the best 4 PDFs for each object (mFDa4) and the Hierarchical Bayesian (HB4) methods, respectively. The HB4 photo-z point estimates produced $\sigma_{\rm NMAD} = 0.0227/0.0189$ and $|\Delta z/(1+z)| > 0.15$ outlier fraction = 0.067/0.019 for spectroscopic and 3D-HST redshifts, respectively. Finally, we describe the structure and provide guidance for the use of the CANDELS photo-z catalogs, which are available at https://archive.stsci.edu/hlsp/candels., Comment: 35 pages, 19 figures, published in ApJ, data available at https://archive.stsci.edu/hlsp/candels

We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4-m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the Universe with the Baryon Acoustic Oscillation technique and the growth rate of structure with Redshift Space Distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near UV to near infrared (3600 to 9800 Angstrom) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline's algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project's requirements for redshift performance, with high efficiency and a purity greater than 99 percent for all target classes., Comment: AJ, revised version, 55 pages, 55 figures, 4 tables

Cosmological observations in the new millennium have dramatically increased our understanding of the Universe, but several fundamental questions remain unanswered. This topical group report describes the best opportunities to address these questions over the coming decades by extending observations to the $z<6$ universe. The greatest opportunity to revolutionize our understanding of cosmic acceleration both in the modern universe and the inflationary epoch would be provided by a new Stage V Spectroscopic Facility (Spec-S5) which would combine a large telescope aperture, wide field of view, and high multiplexing. Such a facility could simultaneously provide a dense sample of galaxies at lower redshifts to provide robust measurements of the growth of structure at small scales, as well as a sample at redshifts $2

In this white paper, we present the MegaMapper concept. The MegaMapper is a proposed ground-based experiment to measure Inflation parameters and Dark Energy from galaxy redshifts at $2

In this white paper, we present an experimental road map for spectroscopic experiments beyond DESI. DESI will be a transformative cosmological survey in the 2020s, mapping 40 million galaxies and quasars and capturing a significant fraction of the available linear modes up to z=1.2. DESI-II will pilot observations of galaxies both at much higher densities and extending to higher redshifts. A Stage-5 experiment would build out those high-density and high-redshift observations, mapping hundreds of millions of stars and galaxies in three dimensions, to address the problems of inflation, dark energy, light relativistic species, and dark matter. These spectroscopic data will also complement the next generation of weak lensing, line intensity mapping and CMB experiments and allow them to reach their full potential., Comment: Contribution to Snowmass 2021

In 2021 May, the Dark Energy Spectroscopic Instrument (DESI) began a 5 yr survey of approximately 50 million total extragalactic and Galactic targets. The primary DESI dark-time targets are emission line galaxies (ELGs), luminous red galaxies (LRGs) and quasars (QSOs). In bright time, DESI will focus on two surveys known as the Bright Galaxy Survey (BGS) and the Milky Way Survey (MWS). DESI also observes a selection of "secondary" targets for bespoke science goals. This paper gives an overview of the publicly available pipeline (desitarget) used to process targets for DESI observations. Highlights include details of the different DESI survey targeting phases, the targeting ID (TARGETID) used to define unique targets, the bitmasks used to indicate a particular type of target, the data model and structure of DESI targeting files, and examples of how to access and use the desitarget code base. This paper will also describe "supporting" DESI target classes, such as standard stars, sky locations, and random catalogs that mimic the angular selection function of DESI targets. The DESI target selection pipeline is complex and sizable; this paper attempts to summarize the most salient information required to understand and work with DESI targeting data., Comment: AJ, accepted, 27 pages, 4 figures, 10 tables, one of a suite of 8 papers detailing targeting for DESI. Minor textual updates to better match the final, accepted version. Also added two missing co-authors

The Dark Energy Spectroscopic Instrument (DESI) Survey has obtained a set of spectroscopic measurements of galaxies to validate the final survey design and target selections. To assist in these tasks, we visually inspect (VI) DESI spectra of approximately 2,500 bright galaxies, 3,500 luminous red galaxies (LRGs), and 10,000 emission line galaxies (ELGs), to obtain robust redshift identifications. We then utilize the VI redshift information to characterize the performance of the DESI operation. Based on the VI catalogs, our results show that the final survey design yields samples of bright galaxies, LRGs, and ELGs with purity greater than $99\%$. Moreover, we demonstrate that the precision of the redshift measurements is approximately 10 km/s for bright galaxies and ELGs and approximately 40 km/s for LRGs. The average redshift accuracy is within 10 km/s for the three types of galaxies. The VI process also helps improve the quality of the DESI data by identifying spurious spectral features introduced by the pipeline. Finally, we show examples of unexpected real astronomical objects, such as Ly$\alpha$ emitters and strong lensing candidates, identified by VI. These results demonstrate the importance and utility of visually inspecting data from incoming and upcoming surveys, especially during their early operation phases., Comment: 22 pages, 14 figures, 3 tables, one of a suite of 8 papers detailing targeting for DESI. ApJ accepted version with minor textual updates

The Dark Energy Spectroscopic Instrument (DESI) is carrying out a 5-year survey that aims to measure the redshifts of tens of millions of galaxies and quasars, including 8 million luminous red galaxies (LRGs) in the redshift range of $0.4

The Dark Energy Spectroscopic Instrument (DESI) will precisely constrain cosmic expansion and the growth of structure by collecting $\sim$40 million extra-galactic redshifts across $\sim$80\% of cosmic history and one third of the sky. The Emission Line Galaxy (ELG) sample, which will comprise about one-third of all DESI tracers, will be used to probe the Universe over the $0.6 < z < 1.6$ range, which includes the $1.1

The Dark Energy Spectroscopic Instrument (DESI) survey will measure large-scale structures using quasars as direct tracers of dark matter in the redshift range 0.92.1. We present several methods to select candidate quasars for DESI, using input photometric imaging in three optical bands (g, r, z) from the DESI Legacy Imaging Surveys and two infrared bands (W1, W2) from the Wide-field Infrared Explorer (WISE). These methods were extensively tested during the Survey Validation of DESI. In this paper, we report on the results obtained with the different methods and present the selection we optimized for the DESI main survey. The final quasar target selection is based on a Random Forest algorithm and selects quasars in the magnitude range 16.599% purity for a nominal effective exposure time of ~1000s. With a 310 per sq. deg. target density, the main selection allows DESI to select more than 200 QSOs per sq. deg. (including 60 quasars with z>2.1), exceeding the project requirements by 20%. The redshift distribution of the selected quasars is in excellent agreement with quasar luminosity function predictions., Comment: 21 pages, 21 figures, typos corrected, references added

Lyman Break Galaxy (LBG) candidates at z>10 are rapidly being identified in JWST/NIRCam observations. Due to the (redshifted) break produced by neutral hydrogen absorption of rest-frame UV photons, these sources are expected to drop out in the bluer filters while being well detected in redder filters. However, here we show that dust-enshrouded star-forming galaxies at lower redshifts (z<7) may also mimic the near-infrared (near-IR) colors of z>10 LBGs, representing potential contaminants in LBG candidate samples. First, we analyze CEERS-DSFG-1, a NIRCam dropout undetected in the F115W and F150W filters but detected at longer wavelengths. Combining the JWST data with (sub)millimeter constraints, including deep NOEMA interferometric observations, we show that this source is a dusty star-forming galaxy (DSFG) at z~5.1. We also present a tentative 2.6sigma SCUBA-2 detection at 850um around a recently identified z~16 LBG candidate in the same field and show that, if the emission is real and associated with this candidate, the available photometry is consistent with a z~5 dusty galaxy with strong nebular emission lines despite its blue near-IR colors. Further observations on this candidate are imperative to mitigate the low confidence of this tentative submillimeter emission and its positional uncertainty. Our analysis shows that robust (sub)millimeter detections of NIRCam dropout galaxies likely imply z=4-6 redshift solutions, where the observed near-IR break would be the result of a strong rest-frame optical Balmer break combined with high dust attenuation and strong nebular line emission, rather than the rest-frame UV Lyman break. This provides evidence that DSFGs may contaminate searches for ultra high-redshift LBG candidates from JWST observations., Comment: Published in The Astrophysical Journal Letters (updated to match the published version)

We report the discovery of a candidate galaxy with a photo-z of z~12 in the first epoch of the JWST Cosmic Evolution Early Release Science (CEERS) Survey. Following conservative selection criteria we identify a source with a robust z_phot = 11.8^+0.3_-0.2 (1-sigma uncertainty) with m_F200W=27.3, and >7-sigma detections in five filters. The source is not detected at lambda < 1.4um in deep imaging from both HST and JWST, and has faint ~3-sigma detections in JWST F150W and HST F160W, which signal a Ly-alpha break near the red edge of both filters, implying z~12. This object (Maisie's Galaxy) exhibits F115W-F200W > 1.9 mag (2-sigma lower limit) with a blue continuum slope, resulting in 99.6% of the photo-z PDF favoring z > 11. All data quality images show no artifacts at the candidate's position, and independent analyses consistently find a strong preference for z > 11. Its colors are inconsistent with Galactic stars, and it is resolved (r_h = 340 +/- 14 pc). Maisie's Galaxy has log M*/Msol ~ 8.5 and is highly star-forming (log sSFR ~ -8.2 yr^-1), with a blue rest-UV color (beta ~ -2.5) indicating little dust though not extremely low metallicity. While the presence of this source is in tension with most predictions, it agrees with empirical extrapolations assuming UV luminosity functions which smoothly decline with increasing redshift. Should followup spectroscopy validate this redshift, our Universe was already aglow with galaxies less than 400 Myr after the Big Bang., Comment: 17 pages, 6 figures, 3 tables, ApJL in press. Summary of changes from original submission: Improvements in astrometry generated a weak detection in F150W that reduces the photo-z to 11.8 but does not increase the likelihood of lower-z solutions. A full discussion of changes from the original version is available at: https://web.corral.tacc.utexas.edu/ceersdata/papers/Maisie_update.pdf

Photometric redshifts are essential in studies of both galaxy evolution and cosmology, as they enable analyses of objects too numerous or faint for spectroscopy. The Rubin Observatory, Euclid, and Roman Space Telescope will soon provide a new generation of imaging surveys with unprecedented area coverage, wavelength range, and depth. To take full advantage of these datasets, further progress in photometric redshift methods is needed. In this review, we focus on the greatest common challenges and prospects for improvement in applications of photo-$z$'s to the next generation of surveys: - Gains in $performance$ -- i.e., the precision of redshift estimates for individual galaxies -- could greatly enhance studies of galaxy evolution and some probes of cosmology. - Improvements in $characterization$ -- i.e., the accurate recovery of redshift $distributions$ of galaxies in the presence of uncertainty on individual redshifts -- are urgently needed for cosmological measurements with next-generation surveys. - To achieve both of these goals, improvements in the scope and treatment of the samples of spectroscopic redshifts which make high-fidelity photo-$z$'s possible will also be needed. For the full potential of the next generation of surveys to be reached, the characterization of redshift distributions will need to improve by roughly an order of magnitude compared to the current state of the art, requiring progress on a wide variety of fronts. We conclude by presenting a speculative evaluation of how photometric redshift methods and the collection of the necessary spectroscopic samples may improve by the time near-future surveys are completed., Comment: Posted with permission from the Annual Review of Astronomy and Astrophysics, Volume 60, copyright 2022 Annual Reviews, http://www.annualreviews.org/

Uncertainty quantification is crucial for assessing the predictive ability of AI algorithms. Much research has been devoted to describing the predictive distribution (PD) $F(y|\mathbf{x})$ of a target variable $y \in \mathbb{R}$ given complex input features $\mathbf{x} \in \mathcal{X}$. However, off-the-shelf PDs (from, e.g., normalizing flows and Bayesian neural networks) often lack conditional calibration with the probability of occurrence of an event given input $\mathbf{x}$ being significantly different from the predicted probability. Current calibration methods do not fully assess and enforce conditionally calibrated PDs. Here we propose \texttt{Cal-PIT}, a method that addresses both PD diagnostics and recalibration by learning a single probability-probability map from calibration data. The key idea is to regress probability integral transform scores against $\mathbf{x}$. The estimated regression provides interpretable diagnostics of conditional coverage across the feature space. The same regression function morphs the misspecified PD to a re-calibrated PD for all $\mathbf{x}$. We benchmark our corrected prediction bands (a by-product of corrected PDs) against oracle bands and state-of-the-art predictive inference algorithms for synthetic data. We also provide results for two applications: (i) probabilistic nowcasting given sequences of satellite images, and (ii) conditional density estimation of galaxy distances given imaging data (so-called photometric redshift estimation). Our code is available as a Python package https://github.com/lee-group-cmu/Cal-PIT ., Comment: 21 pages, 11 figures. Under review. Code available as a Python package https://github.com/lee-group-cmu/Cal-PIT

The Dark Energy Spectroscopic Instrument (DESI) has embarked on an ambitious five-year survey to explore the nature of dark energy with spectroscopy of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the Baryon Acoustic Oscillation method to measure distances from the nearby universe to z > 3.5, as well as measure the growth of structure and probe potential modifications to general relativity. In this paper we describe the significant instrumentation we developed for the DESI survey. The new instrumentation includes a wide-field, 3.2-deg diameter prime-focus corrector that focuses the light onto 5020 robotic fiber positioners on the 0.812 m diameter, aspheric focal surface. The positioners and their fibers are divided among ten wedge-shaped petals. Each petal is connected to one of ten spectrographs via a contiguous, high-efficiency, nearly 50 m fiber cable bundle. The ten spectrographs each use a pair of dichroics to split the light into three channels that together record the light from 360 - 980 nm with a resolution of 2000 to 5000. We describe the science requirements, technical requirements on the instrumentation, and management of the project. DESI was installed at the 4-m Mayall telescope at Kitt Peak, and we also describe the facility upgrades to prepare for DESI and the installation and functional verification process. DESI has achieved all of its performance goals, and the DESI survey began in May 2021. Some performance highlights include RMS positioner accuracy better than 0.1", SNR per \sqrt{\AA} > 0.5 for a z > 2 quasar with flux 0.28e-17 erg/s/cm^2/A at 380 nm in 4000s, and median SNR = 7 of the [OII] doublet at 8e-17 erg/s/cm^2 in a 1000s exposure for emission line galaxies at z = 1.4 - 1.6. We conclude with highlights from the on-sky validation and commissioning of the instrument, key successes, and lessons learned. (abridged), Comment: 78 pages, 32 figures, submitted to AJ

Gas-phase metallicity gradients in galaxies provide important clues to those galaxies' formation histories. Using SDSS-IV MaNGA data, we previously demonstrated that gas metallicity gradients vary systematically and significantly across the galaxy mass--size plane: at stellar masses beyond approximately $10^{10}$ $\mathrm{M_\odot}$, more extended galaxies display steeper gradients (in units of $\mathrm{dex/R_e}$) at a given stellar mass. Here, we set out to develop a physical interpretation of these findings by examining the ability of local $\sim$kpc-scale relations to predict the gradient behaviour along the mass--size plane. We find that local stellar mass surface density, when combined with total stellar mass, is sufficient to reproduce the overall mass--size trend in a qualitative sense. We further find that we can improve the predictions by correcting for residual trends relating to the recent star formation histories of star-forming regions. However, we find as well that the most extended galaxies display steeper average gradients than predicted, even after correcting for residual metallicity trends with other local parameters. From these results, we argue that gas-phase metallicity gradients can largely be understood in terms of known local relations, but we also discuss some possible physical causes of discrepant gradients., Comment: 21 pages, 23 figures. Accepted by MNRAS; some minor corrections made following receipt of journal proofs