Search

Near-future facilities observing the high-redshift universe (2 < z < 5) will have an opportunity to take advantage of “multi-tracer” cosmology by observing multiple tracers of the matter density field: Lyman alpha emitters (LAE), Lyman break galaxies (LBG), and CMB lensing κ. In this work we use Fisher forecasts to investigate the effect of multi-tracers on next-generation facilities. In agreement with previous work, we show that multiple tracers improve constraints primarily from degeneracy breaking, instead of the traditional intuition of sample variance cancellation. Then, we forecast that for both BBN and CMB primary priors, the addition of lensing and LAEs onto a LBG-only sample will gain 25% or more in many parameters, with the largest gains being factor of ∼ 10 improvement for fEDE. We include a preliminary approach towards modelling the impact of radiative transfer (RT) on forecasts involving LAEs by introducing a simplified model at linear theory level. Our results, albeit preliminary, show that while RT influences LAE-only forecasts strongly, its effect on composite multi-tracer forecasts is limited.

Cosmic voids identified in the spatial distribution of galaxies provide complementary information to two-point statistics. In particular, constraints on the neutrino mass sum, ∑ m ν , promise to benefit from the inclusion of void statistics. We perform inference on the CMASS Northern Galactic Cap sample of the third-generation Sloan Digital Sky Survey/Baryon Oscillation Spectroscopic Survey (BOSS) with the aim of constraining ∑ m ν . We utilize the void size function, the void–galaxy cross power spectrum, and the galaxy auto power spectrum. To extract constraints from these summary statistics we use a simulation-based approach, specifically implicit likelihood inference. We populate approximate gravity-only, particle-neutrino cosmological simulations with an expressive halo occupation distribution model. With a conservative scale cut of k max = 0.15 h Mpc − 1 and a Planck-inspired Lambda cold dark matter prior, we find upper bounds on ∑ m ν of 0.43 and 0.35 eV from the galaxy auto power spectrum and the full data vector, respectively (95% credible interval). Relaxing the scale cut to k max = 0.2 h Mpc − 1 , we find 0.28 and 0.32 eV. Generally, void statistics appear to add modest but nonzero information beyond the auto power spectrum. We also substantiate the usual assumption that the void size function is Poisson distributed. [ABSTRACT FROM AUTHOR]

The growth of large-scale structure, as revealed in the anisotropic of clustering of galaxies in the low redshift Universe at z < 2, provides a stringent test of our cosmological model. The strongest current constraints come from the BOSS and eBOSS surveys, with uncertainties on σ 8, the amplitude of clustering on an 8 h -1Mpc scale, of less than 10 per cent. A number of different approaches have been taken to fitting this signal, leading to discrepancies of up to 1σ in the measurements of the amplitude of fluctuations at late times. We compare in some detail two of the leading approaches, one based on fitting a template cosmology whose amplitude and length scales are allowed to float with one based on varying the underlying parameters of a cosmological model directly, when fitting to the BOSS DR12 data. Holding the input data, scale cuts, window functions and modeling framework fixed we are able to isolate the cause of the differences and discuss the implications for future surveys.

Numerical simulations in cosmology require trade-offs between volume, resolution and run-time that limit the volume of the Universe that can be simulated, leading to sample variance in predictions of ensemble-average quantities such as the power spectrum or correlation function(s). Sample variance is particularly acute at large scales, which is also where analytic techniques can be highly reliable. This provides an opportunity to combine analytic and numerical techniques in a principled way to improve the dynamic range and reliability of predictions for clustering statistics. In this paper we extend the technique of Zel'dovich control variates, previously demonstrated for 2-point functions in real space, to reduce the sample variance in measurements of 2-point statistics of biased tracers in redshift space. We demonstrate that with this technique, we can reduce the sample variance of these statistics down to their shot-noise limit out to k ∼ 0.2 h Mpc-1. This allows a better matching with perturbative models and improved predictions for the clustering of e.g. quasars, galaxies and neutral Hydrogen measured in spectroscopic redshift surveys at very modest computational expense. We discuss the implementation of ZCV, give some examples and provide forecasts for the efficacy of the method under various conditions.

We present a formalism for jointly fitting pre- and post-reconstruction redshift-space clustering (RSD) and baryon acoustic oscillations (BAO) plus gravitational lensing (of the CMB) that works directly with the observed 2-point statistics. The formalism is based upon (effective) Lagrangian perturbation theory and a Lagrangian bias expansion, which models RSD, BAO and galaxy-lensing cross correlations within a consistent dynamical framework. As an example we present an analysis of clustering measured by the Baryon Oscillation Spectroscopic Survey in combination with CMB lensing measured by Planck. The post-reconstruction BAO strongly constrains the distance-redshift relation, the full-shape redshift-space clustering constrains the matter density and growth rate, and CMB lensing constrains the clustering amplitude. Using only the redshift space data we obtain Ωm = 0.303 ± 0.008, H 0 = 69.21 ± 0.78 and σ 8 = 0.743 ± 0.043. The addition of lensing information, even when restricted to the Northern Galactic Cap, improves constraints to Ωm = 0.303 ± 0.008, H 0 = 69.21 ± 0.77 and σ 8 = 0.707 ± 0.035, in tension with CMB and cosmic shear constraints. The combination of Ωm and H 0 are consistent with Planck, though their constraints derive mostly from redshift-space clustering. The low σ 8 value are driven by cross correlations with CMB lensing in the low redshift bin (z ≃ 0.38) and at large angular scales, which show a 20% deficit compared to expectations from galaxy clustering alone. We conduct several systematics tests on the data and find none that could fully explain these tensions.

We use luminous red galaxies selected from the imaging surveys that are being used for targeting by the Dark Energy Spectroscopic Instrument (DESI) in combination with CMB lensing maps from the Planck collaboration to probe the amplitude of large-scale structure over 0.4 ≤ z ≤ 1. Our galaxy sample, with an angular number density of approximately 500 deg-2 over 18,000 sq.deg., is divided into 4 tomographic bins by photometric redshift and the redshift distributions are calibrated using spectroscopy from DESI. We fit the galaxy autospectra and galaxy-convergence cross-spectra using models based on cosmological perturbation theory, restricting to large scales that are expected to be well described by such models. Within the context of ΛCDM, combining all 4 samples and using priors on the background cosmology from supernova and baryon acoustic oscillation measurements, we find S 8 = σ8(ωm/0.3)0.5 = 0.73 ± 0.03. This result is lower than the prediction of the ΛCDM model conditioned on the Planck data. Our data prefer a slower growth of structure at low redshift than the model predictions, though at only modest significance.

Abstract We present a new method for consistent, joint analysis of the pre- and post-reconstruction galaxy two-point functions of the BOSS survey. The post-reconstruction correlation function is used to accurately measure the distance-redshift relation and expansion history, while the pre-reconstruction power spectrum multipoles constrain the broad-band shape and the rate-of-growth of large-scale structure. Our technique uses Lagrangian perturbation theory to self-consistently work at the level of two-point functions, i.e. directly with the measured data, without approximating the constraints with summary statistics normalized by the drag scale. Combining galaxies across the full redshift range and both hemispheres we constrain Ωm = 0.303 ± 0.0082, H 0 = 69.23 ± 0.77 and σ8 = 0.733 ± 0.047 within the context of ΛCDM. These constraints are consistent both with the Planck primary CMB anisotropy data and recent cosmic shear surveys.

An observational program focused on the high redshift (2

Shortly after its discovery, General Relativity (GR) was applied to predict the behavior of our Universe on the largest scales, and later became the foundation of modern cosmology. Its validity has been verified on a range of scales and environments from the Solar system to merging black holes. However, experimental confirmations of GR on cosmological scales have so far lacked the accuracy one would hope for-its applications on those scales being largely based on extrapolation and its validity there sometimes questioned in the shadow of the discovery of the unexpected cosmic acceleration. Future astronomical instruments surveying the distribution and evolution of galaxies over substantial portions of the observable Universe, such as the Dark Energy Spectroscopic Instrument (DESI), will be able to measure the fingerprints of gravity and their statistical power will allow strong constraints on alternatives to GR. In this paper, based on a set of N-body simulations and mock galaxy catalogs, we study the predictions of a number of traditional and novel summary statistics beyond linear redshift distortions in two well-studied modified gravity models-chameleon f(R) gravity and a braneworld model-and the potential of testing these deviations from GR using DESI. These summary statistics employ a wide array of statistical properties of the galaxy and the underlying dark matter field, including two-point and higher-order statistics, environmental dependence, redshift space distortions and weak lensing. We find that they hold promising power for testing GR to unprecedented precision. The major future challenge is to make realistic, simulation-based mock galaxy catalogs for both GR and alternative models to fully exploit the statistic power of the DESI survey (by matching the volumes and galaxy number densities of the mocks to those in the real survey) and to better understand the impact of key systematic effects. Using these, we identify future simulation and analysis needs for gravity tests using DESI.

We update Halo Zeldovich Perturbation Theory (HZPT, [1]), an analytic model for the two-point statistics of dark matter, to describe halo and galaxy clustering, and galaxy-matter cross-correlation on nonlinear scales. The model correcting Zeldovich has an analytic Fourier transform, and therefore is valid in both configuration space and Fourier space. The model is accurate at the 2%-level or less for Pmm (k < 1 h/Mpc), Phm (k < 1 h/Mpc), Phh (k < 2 h/Mpc), Pgm (k < 1 h/Mpc), Pgg (k < 1 h/Mpc), ξmm (r > 1 Mpc/h), ξhm (r > 2 Mpc/h), ξhh (r > 2 Mpc/h), ξgm (r > 1 Mpc/h), ξgg (r > 2 Mpc/h), for LRG-like mock galaxies. We show that the HZPT model for matter correlators can account for the effects of a wide range of baryonic feedback models and provide two extended dark matter models which are of 1% (3%) accuracy for k < 10 (8) h/Mpc. We explicitly model the non-perturbative features of halo exclusion for the halo-halo and galaxy-galaxy correlators, as well as the presence of satellites for galaxy-matter and galaxy-galaxy correlation functions. We perform density estimation using N-body simulations and a wide range of HOD galaxy mocks to obtain correlations of model parameters with the cosmological parameters Ωm and σ8. HZPT can provide a fast, interpretable, and analytic model for combined-probe analyses of redshift surveys using scales well into the non-linear regime.

Line intensity mapping (LIM) proposes to efficiently observe distant faint galaxies and map the matter density field at high redshift. Building upon the formalism in a companion paper, we first highlight the degeneracies between cosmology and astrophysics in LIM. We discuss what can be constrained from measurements of the mean intensity and redshift-space power spectra. With a sufficient spectral resolution, the large-scale redshift-space distortions of the 2-halo term can be measured, helping to break the degeneracy between bias and mean intensity. With a higher spectral resolution, measuring the small-scale redshift-space distortions disentangles the 1-halo and shot noise terms. Cross-correlations with external galaxy catalogs or lensing surveys further break degeneracies. We derive requirements for experiments similar to SPHEREx, HETDEX, CDIM, COMAP and CONCERTO. We then revisit the question of the optimality of the LIM observables, compared to galaxy detection, for astrophysics and cosmology. We use a matched filter to compute the luminosity detection threshold for individual sources. We show that LIM contains information about galaxies too faint to detect, in the high-noise or high-confusion regimes. We quantify the sparsity and clustering bias of the detected sources and compare them to LIM, showing in which cases LIM is a better tracer of the matter density. We extend previous work by answering these questions as a function of Fourier scale, including for the first time the effect of cosmic variance, pixel-to-pixel correlations, luminosity-dependent clustering bias and redshift-space distortions.

Line intensity mapping (LIM) is a rapidly emerging technique for constraining cosmology and galaxy formation using multi-frequency, low angular resolution maps. Many LIM applications crucially rely on cross-correlations of two line intensity maps, or of intensity maps with galaxy surveys or galaxy/CMB lensing. We present a consistent halo model to predict all these cross-correlations and enable joint analyses, in 3D redshift-space and for 2D projected maps. We extend the conditional luminosity function formalism to the multi-line case, to consistently account for correlated scatter between multiple galaxy line luminosities. This allows us to model the scale-dependent decorrelation between two line intensity maps, a key input for foreground rejection and for approaches that estimate auto-spectra from cross-spectra. This also enables LIM cross-correlations to reveal astrophysical properties of the interstellar medium inacessible with LIM auto-spectra. We expose the different sources of luminosity scatter or "line noise"in LIM, and clarify their effects on the 1-halo and galaxy shot noise terms. In particular, we show that the effective number density of halos can in some cases exceed that of galaxies, counterintuitively. Using observational and simulation input, we implement this halo model for the Hα, [Oiii], Lyman-α, CO and [Cii] lines. We encourage observers and simulators to measure galaxy luminosity correlation coefficients for pairs of lines whenever possible. Our code is publicly available at https://github.com/EmmanuelSchaan/HaloGen/tree/LIM. In a companion paper, we use this halo model formalism and code to highlight the degeneracies between cosmology and astrophysics in LIM, and to compare the LIM observables to galaxy detection for a number of surveys.

We present the one-loop 2-point function of biased tracers in redshift space computed with Lagrangian perturbation theory, including a full resummation of both long-wavelength (infrared) displacements and associated velocities. The resulting model accurately predicts the power spectrum and correlation function of halos and mock galaxies from two different sets of N-body simulations at the percent level for quasi-linear scales, including the damping of the baryon acoustic oscillation signal due to the bulk motions of galaxies. We compare this full resummation with other, approximate, techniques including the moment expansion and Gaussian streaming model. We discuss infrared resummation in detail and compare our Lagrangian formulation with the Eulerian theory augmented by an infrared resummation based on splitting the input power spectrum into "wiggle"and "no-wiggle"components. We show that our model is able to recover unbiased cosmological parameters in mock data encompassing a volume much larger than what will be available to future galaxy surveys. We demonstrate how to efficiently compute the resulting expressions numerically, making available a fast Python code capable of rapidly computing these statistics in both configuration and Fourier space.

We study the ability of perturbative models with effective field theory contributions and infra-red resummation to model the redshift space clustering of biased tracers in models where the linear power spectrum has "features"- either imprinted during inflation or induced by non-standard expansion histories. We show that both Eulerian and Lagrangian perturbation theory are capable of reproducing the Fourier space two-point functions of halos up to the non-linear scale from a suite of 40963 particle N-body simulations. This is the first demonstration that perturbative models can accurately fit the redshift-space clustering of biased tracers in N-body simulations of such theories. By comparing different theoretical models and IR resummation schemes we assess the current theoretical uncertainty in predicting power spectra for models with features. Our results suggest that future surveys will be able to detect or tightly constrain features in the primordial spectrum below the one percent level across a wide range of scales.

This paper represents an effort to provide robust constraints on the galaxy–halo connection and simultaneously test the Planck ΛCDM cosmology using a fully numerical model of small-scale galaxy clustering. We explore two extensions to the standard Halo Occupation Distribution model: assembly bias, whereby halo occupation depends on both halo mass and the larger environment, and velocity bias, whereby galaxy velocities do not perfectly trace the velocity of the dark matter within the halo. Moreover, we incorporate halo mass corrections to account for the impact of baryonic physics on the halo population. We identify an optimal set of clustering measurements to constrain this "decorated" HOD model for both low- and high-luminosity galaxies in SDSS DR7. We find that, for low-luminosity galaxies, a model with both assembly bias and velocity bias provides the best fit to the clustering measurements, with no tension remaining in the fit. In this model, we find evidence for both central and satellite galaxy assembly bias at the 99% and 95% confidence levels, respectively. In addition, we find evidence for satellite galaxy velocity bias at the 99.9% confidence level. For high-luminosity galaxies, we find no evidence for either assembly bias or velocity bias, but our model exhibits significant tension with SDSS measurements. We find that all of these conclusions still stand when we include the effects of baryonic physics on the halo mass function, suggesting that the tension we find for high-luminosity galaxies may be due to a problem with our assumed cosmological model. [ABSTRACT FROM AUTHOR]

The peculiar velocities of biased tracers of the cosmic density field contain important information about the growth of large scale structure and generate anisotropy in the observed clustering of galaxies. Using N-body data, we show that velocity expansions for halo redshift-space power spectra are converged at the percent-level at perturbative scales for most line-of-sight angles μ when the first three pairwise velocity moments are included, and that the third moment is well-approximated by a counterterm-like contribution. We compute these pairwise-velocity statistics in Fourier space using both Eulerian and Lagrangian one-loop perturbation theory using a cubic bias scheme and a complete set of counterterms and stochastic contributions. We compare the models and show that our models fit both real-space velocity statistics and redshift-space power spectra for both halos and a mock sample of galaxies at sub-percent level on perturbative scales using consistent sets of parameters, making them appealing choices for the upcoming era of spectroscopic, peculiar-velocity and kSZ surveys.

We analyze the clustering of galaxies in the first public data release of the Hyper Suprime-Cam Subaru Strategic Program. Despite the relatively small footprints of the observed fields, the data are an excellent proxy for the very deep photometric datasets that will be acquired by the Large Synoptic Survey Telescope, and are therefore an ideal test bed for the analysis methods being implemented by the LSST Dark Energy Science Collaboration. We select a magnitude limited sample with i

Upcoming 21-cm intensity surveys will use the hyperfine transition in emission to map out neutral hydrogen in large volumes of the universe. Unfortunately, large spatial scales are completely contaminated with spectrally smooth astrophysical foregrounds which are orders of magnitude brighter than the signal. This contamination also leaks into smaller radial and angular modes to form a foreground wedge, further limiting the usefulness of 21-cm observations for different science cases, especially cross-correlations with tracers that have wide kernels in the radial direction. In this paper, we investigate reconstructing these modes within a forward modeling framework. Starting with an initial density field, a suitable bias parameterization and non-linear dynamics to model the observed 21-cm field, our reconstruction proceeds by {combining} the likelihood of a forward simulation to match the observations (under given modeling error and a data noise model) {with the Gaussian prior on initial conditions and maximizing the obtained posterior}. For redshifts z=2 and 4, we are able to reconstruct 21cm field with cross correlation, rc > 0.8 on all scales for both our optimistic and pessimistic assumptions about foreground contamination and for different levels of thermal noise. The performance deteriorates slightly at z=6. The large-scale line-of-sight modes are reconstructed almost perfectly. We demonstrate how our method also provides a technique for density field reconstruction for baryon acoustic oscillations, outperforming standard methods on all scales. We also describe how our reconstructed field can provide superb clustering redshift estimation at high redshifts, where it is otherwise extremely difficult to obtain dense spectroscopic samples, as well as open up a wealth of cross-correlation opportunities with projected fields (e.g. lensing) which are restricted to modes transverse to the line of sight.

HectoMAP is a dense redshift survey of 95,403 galaxies based primarily on MMT spectroscopy with a median redshift z = 0.345. The survey covers 54.64 deg2 in a 1.°5 wide strip across the northern sky centered at a decl. of 43.°25. We report the redshift, the spectral indicator D n 4000, and the stellar mass. The red-selected survey is 81% complete for 55,962 galaxies with (g − r) > 1 and r < 20.5; it is 72% complete for 32,908 galaxies with (g − r) > 1, (r − i) > 0.5 and 20.5 < r < 21.3. Comparison of the survey basis SDSS photometry with the HSC-SSP photometry demonstrates that HectoMAP provides complete magnitude-limited surveys based on either photometric system. We update the comparison between the HSC-SSP photometric redshifts with HectoMAP spectroscopic redshifts; the comparison demonstrates that the HSC-SSP photometric redshifts have improved between the second and third data releases. HectoMAP is a foundation for examining the quiescent galaxy population (63% of the survey), clusters of galaxies, and the cosmic web. HectoMAP is completely covered by the HSC-SSP survey, thus enabling a variety of strong- and weak-lensing investigations. [ABSTRACT FROM AUTHOR]

The PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass (M *), star formation rate (SFR), stellar metallicity (Z), and stellar age (t age), for >10 million galaxies of the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, the neural emulator for the model, and the Bayesian inference framework of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-Galaxies semi-analytic model. We compare the inferred galaxy properties to the true values of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true M *, SFR, Z, and t age of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors, which we characterize in detail. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses. https://github.com/changhoonhahn/provabgs/ [ABSTRACT FROM AUTHOR]

In this paper we describe the survey design for the Ultradeep NIRSpec and NIRCam Observations before the Epoch of Reionization (UNCOVER) Cycle 1 JWST Treasury program, which executed its early imaging component in 2022 November. The UNCOVER survey includes ultradeep (∼29–30AB) imaging of ∼45 arcmin ^2 on and around the well-studied A2744 galaxy cluster at z = 0.308 and will follow up ∼500 galaxies with extremely deep low-resolution spectroscopy with the NIRSpec/PRISM during the summer of 2023, with repeat visits in summer 2024. We describe the science goals, survey design, target selection, and planned data releases. We also present and characterize the depths of the first NIRCam imaging mosaic, highlighting previously unparalleled resolved and ultradeep 2–4 μ m imaging of known objects in the field. The UNCOVER primary NIRCam mosaic spans 28.8 arcmin ^2 in seven filters (F115W, F150W, F200W, F277W, F356W, F410M, and F444W) and 16.8 arcmin ^2 in our NIRISS parallel (F115W, F150W, F200W, F356W, and F444W). To maximize early community use of the Treasury data set, we publicly release the full reduced mosaics of public JWST imaging including 45 arcmin ^2 NIRCam and 17 arcmin ^2 NIRISS mosaics on and around the A2744 cluster, including the Hubble Frontier Field primary and parallel footprints.

The dispersion measure of fast radio bursts (FRBs), arising from the interactions with free electrons along the propagation path, constitutes a unique probe of the cosmic baryon distribution. Their constraining power is further enhanced in combination with observations of the foreground large-scale structure and intervening galaxies. In this work, we present the first constraints on the partition of the cosmic baryons between the intergalactic medium (IGM) and circumgalactic medium (CGM), inferred from the FLIMFLAM spectroscopic survey. In its first data release, the FLIMFLAM survey targeted galaxies in the foreground of eight localized FRBs. Using Bayesian techniques, we reconstruct the underlying ∼Mpc-scale matter density field that is traced by the IGM gas. Simultaneously, deeper spectroscopy of intervening foreground galaxies (at impact parameters b _⊥ ≲ r _200 ) and the FRB host galaxies constrains the contribution from the CGM. Applying Bayesian parameter inference to our data and assuming a fiducial set of priors, we infer the IGM cosmic baryon fraction to be ${f}_{\mathrm{igm}}={0.59}_{-0.10}^{+0.11}$ and a CGM gas fraction of ${f}_{\mathrm{gas}}={0.55}_{-0.29}^{+0.26}$ for 10 ^10 M _⊙ ≲ M _halo ≲ 10 ^13 M _⊙ halos. The mean FRB host dispersion measure (rest-frame) in our sample is $\langle {\mathrm{DM}}_{\mathrm{host}}\rangle ={90}_{-19}^{+29}\,\mathrm{pc}\ \ {\mathrm{cm}}^{-3}$ , of which $\langle {\mathrm{DM}}_{\mathrm{host}}^{\mathrm{unk}}\rangle ={69}_{-19}^{+28}\,\mathrm{pc}\ \ {\mathrm{cm}}^{-3}$ arises from the host galaxy interstellar medium (ISM) and/or the FRB progenitor environment. While our current f _igm and f _gas uncertainties are too broad to constrain most galactic feedback models, this result marks the first measurement of the IGM and CGM baryon fractions, as well as the first systematic separation of the FRB host dispersion measure into two components: arising from the halo and from the inner ISM/FRB engine.

We present pop-cosmos : a comprehensive model characterizing the galaxy population, calibrated to 140,938 ( r < 25 selected) galaxies from the Cosmic Evolution Survey (COSMOS) with photometry in 26 bands from the ultraviolet to the infrared. We construct a detailed forward model for the COSMOS data, comprising: a population model describing the joint distribution of galaxy characteristics and its evolution (parameterized by a flexible score-based diffusion model); a state-of-the-art stellar population synthesis model connecting galaxies’ intrinsic properties to their photometry; and a data model for the observation, calibration, and selection processes. By minimizing the optimal transport distance between synthetic and real data, we are able to jointly fit the population and data models, leading to robustly calibrated population-level inferences that account for parameter degeneracies, photometric noise and calibration, and selection. We present a number of key predictions from our model of interest for cosmology and galaxy evolution, including the mass function and redshift distribution; the mass–metallicity-redshift and fundamental metallicity relations; the star-forming sequence; the relation between dust attenuation and stellar mass, star formation rate, and attenuation-law index; and the relation between gas-ionization and star formation. Our model encodes a comprehensive picture of galaxy evolution that faithfully predicts galaxy colors across a broad redshift ( z < 4) and wavelength range.

We simulate galaxy properties and redshift estimation for SPHEREx, the next NASA Medium Class Explorer. To make robust models of the galaxy population and test the spectrophotometric redshift performance for SPHEREx, we develop a set of synthetic spectral energy distributions based on detailed fits to COSMOS2020 photometry spanning 0.1–8 μ m. Given that SPHEREx obtains low-resolution spectra, emission lines will be important for some fraction of galaxies. Here, we expand on previous work, using better photometry and photometric redshifts from COSMOS2020 and tight empirical relations to predict robust emission-line strengths and ratios. A second galaxy catalog derived from the GAMA survey is generated to ensure the bright ( m _AB < 18 in the i band) sample is representative over larger areas. Using template fitting to estimate photometric continuum redshifts, we forecast the recovery of 19 million galaxies over 30,000 deg ^2 with redshifts better than σ _z < 0.003(1 + z ), 445 million with σ _z < 0.1(1 + z ), and 810 million with σ _z < 0.2(1 + z ). We also find through idealized tests that emission-line information from spectrally dithered flux measurements can yield redshifts with accuracy beyond that implied by the naive SPHEREx channel resolution, motivating the development of a hybrid continuum–line redshift estimation approach.

We present a computationally efficient galaxy archetype-based redshift estimation and spectral classification method for the Dark Energy Survey Instrument (DESI) survey. The DESI survey currently relies on a redshift fitter and spectral classifier using a linear combination of principal component analysis–derived templates, which is very efficient in processing large volumes of DESI spectra within a short time frame. However, this method occasionally yields unphysical model fits for galaxies and fails to adequately absorb calibration errors that may still be occasionally visible in the reduced spectra. Our proposed approach improves upon this existing method by refitting the spectra with carefully generated physical galaxy archetypes combined with additional terms designed to absorb data reduction defects and provide more physical models to the DESI spectra. We test our method on an extensive data set derived from the survey validation (SV) and Year 1 (Y1) data of DESI. Our findings indicate that the new method delivers marginally better redshift success for SV tiles while reducing catastrophic redshift failure by 10%–30%. At the same time, results from millions of targets from the main survey show that our model has relatively higher redshift success and purity rates (0.5%–0.8% higher) for galaxy targets while having similar success for QSOs. These improvements also demonstrate that the main DESI redshift pipeline is generally robust. Additionally, it reduces the false-positive redshift estimation by 5%−40% for sky fibers. We also discuss the generic nature of our method and how it can be extended to other large spectroscopic surveys, along with possible future improvements.

Cosmic voids identified in the spatial distribution of galaxies provide complementary information to two-point statistics. In particular, constraints on the neutrino mass sum, ∑ m _ν , promise to benefit from the inclusion of void statistics. We perform inference on the CMASS Northern Galactic Cap sample of the third-generation Sloan Digital Sky Survey/Baryon Oscillation Spectroscopic Survey (BOSS) with the aim of constraining ∑ m _ν . We utilize the void size function, the void–galaxy cross power spectrum, and the galaxy auto power spectrum. To extract constraints from these summary statistics we use a simulation-based approach, specifically implicit likelihood inference. We populate approximate gravity-only, particle-neutrino cosmological simulations with an expressive halo occupation distribution model. With a conservative scale cut of ${k}_{\max }=0.15\,h\,{\mathrm{Mpc}}^{-1}$ and a Planck-inspired Lambda cold dark matter prior, we find upper bounds on ∑ m _ν of 0.43 and 0.35 eV from the galaxy auto power spectrum and the full data vector, respectively (95% credible interval). Relaxing the scale cut to ${k}_{\max }=0.2\,h\,{\mathrm{Mpc}}^{-1}$ , we find 0.28 and 0.32 eV. Generally, void statistics appear to add modest but nonzero information beyond the auto power spectrum. We also substantiate the usual assumption that the void size function is Poisson distributed.

We study the global kinematics of the Perseus galaxy cluster (A426) at redshift z = 0.017 using a large sample of galaxies from our new MMT/Hectospec spectroscopic observation for this cluster. The sample includes 1447 galaxies with measured redshifts within 60′ from the cluster center (1148 from this MMT/Hectospec program and 299 from the literature). The resulting spectroscopic completeness is 67% at r -band apparent magnitude r _Petro,0 ≤ 18.0 within 60′ from the cluster center. To identify cluster member galaxies in this sample, we develop a new open-source Python package, CausticSNUpy. This code implements the algorithm of the caustic technique and yields 418 member galaxies within 60′ of the cluster. We study the cluster using this sample of member galaxies. The cluster shows no significant signal of global rotation. A statistical test shows that the cluster does not have a noticeable substructure within 30′. We find two central regions where the X-ray-emitting intracluster medium and galaxies show significant velocity differences (>7 σ ). On a large scale, however, the overall morphology and kinematics between the intracluster medium and galaxies agree well. Our results suggest that the Perseus cluster is a relaxed system and has not experienced a recent merger.

We present the updated galaxy cluster catalog of the second Planck catalog of Sunyaev–Zel’dovich sources (PSZ2) through the compilation of the data for clusters and galaxies with spectroscopically measured redshifts in the literature. The original version of PSZ2 comprises 1653 Sunyaev–Zel’dovich (SZ) sources, of which 1203 have been validated as genuine galaxy clusters, while the remaining 450 sources are yet to be validated. To increase the number of genuine clusters in PSZ2, we first update the validations of the cluster candidates and their redshift information using the data compiled for the confirmed clusters and the member galaxies in the literature. We then use the galaxy redshift data in the fields of the remaining cluster candidates by searching for possible member galaxies with measured spectroscopic redshifts around the SZ centroids. In this search process, we classify clusters as strong candidates if they contain more than nine galaxies within a 4500 km s ^−1 velocity range and within 15′ around the SZ centroids. This process results in the validation of 139 new genuine clusters, the update of redshift information on 399 clusters, and the identification of 10 strong candidates, which increases the number of validated clusters up to 1334 among the 1653 SZ sources. Our updated galaxy cluster catalog will be very useful for studies of galaxy formation and cosmology through a combination with other all-sky surveys including the Wide-field Infrared Survey Explorer and SPHEREx.

The Hobby–Eberly Telescope (HET) VIRUS Parallel Survey (HETVIPS) is a blind spectroscopic program that sparsely covers approximately two-thirds of the celestial sphere and consists of roughly 252 million fiber spectra. The spectra were taken in parallel mode with the Visible Integral-field Replicable Unit Spectrograph (VIRUS) instrument when the HET was observing a primary target with other HET facility instruments. VIRUS can simultaneously obtain approximately 35,000 spectra covering 3470–5540 Å at a spectral resolution of ≈800. Although the vast majority of these spectra cover blank sky, we used the Pan-STARRS1 Data Release 2 Stacked Catalog to identify objects encompassed in the HETVIPS pointings and extract their spectra. This paper presents the first HETVIPS data release, containing 493,012 flux-calibrated spectra obtained through 2023 March 31, as well as a description of the data processing technique. Each of the object spectra were classified, resulting in a catalog of 74,196 galaxies, 4,087 quasars, 259,396 stars, and 154,543 unknown sources.

We investigate the group-scale environment of 15 luminous quasars (luminosity L _3000 > 10 ^46 erg s ^−1 ) from the Cosmic Ultraviolet Baryon Survey (CUBS) at redshift z ≈ 1. Using the Multi Unit Spectroscopic Explorer integral field spectrograph on the Very Large Telescope, we conduct a deep galaxy redshift survey in the CUBS quasar fields to identify group members and measure the physical properties of individual galaxies and galaxy groups. We find that the CUBS quasars reside in diverse environments. The majority (11 out of 15) of the CUBS quasars reside in overdense environments with typical halo masses exceeding 10 ^13 M _⊙ , while the remaining quasars reside in moderate-size galaxy groups. No correlation is observed between overdensity and redshift, black hole (BH) mass, or luminosity. Radio-loud quasars (5 out of 15 CUBS quasars) are more likely to be in overdense environments than their radio-quiet counterparts in the sample, consistent with the mean trends from previous statistical observations and clustering analyses. Nonetheless, we also observe radio-loud quasars in moderate groups and radio-quiet quasars in overdense environments, indicating a large scatter in the connection between radio properties and environment. We find that the most UV luminous quasars might be outliers in the stellar mass-to-halo mass relations or may represent departures from the standard single-epoch BH relations.

We report the discovery of 15 exceptionally luminous 10 ≲ z ≲ 14 candidate galaxies discovered in the first 0.28 deg ^2 of JWST/NIRCam imaging from the COSMOS-Web survey. These sources span rest-frame UV magnitudes of −20.5 > M _UV > −22, and thus constitute the most intrinsically luminous z ≳ 10 candidates identified by JWST to date. Selected via NIRCam imaging, deep ground-based observations corroborate their detection and help significantly constrain their photometric redshifts. We analyze their spectral energy distributions using multiple open-source codes and evaluate the probability of low-redshift solutions; we conclude that 12/15 (80%) are likely genuine z ≳ 10 sources and 3/15 (20%) likely low-redshift contaminants. Three of our z ∼ 12 candidates push the limits of early stellar mass assembly: they have estimated stellar masses ∼ 5 × 10 ^9 M _⊙ , implying an effective stellar baryon fraction of ϵ _⋆ ∼ 0.2−0.5, where ϵ _⋆ ≡ M _⋆ /( f _b M _halo ). The assembly of such stellar reservoirs is made possible due to rapid, burst-driven star formation on timescales < 100 Myr where the star formation rate may far outpace the growth of the underlying dark matter halos. This is supported by the similar volume densities inferred for M _⋆ ∼ 10 ^10 M _⊙ galaxies relative to M _⋆ ∼ 10 ^9 M _⊙ —both about 10 ^−6 Mpc ^−3 —implying they live in halos of comparable mass. At such high redshifts, the duty cycle for starbursts would be of order unity, which could cause the observed change in the shape of the UV luminosity function from a double power law to a Schechter function at z ≈ 8. Spectroscopic redshift confirmation and ensuing constraints of their masses will be critical to understand how, and if, such early massive galaxies push the limits of galaxy formation in the Lambda cold dark matter paradigm.

A complete and pure sample of quasars with accurate redshifts is crucial for quasar studies and cosmology. In this paper, we present CatNorth, an improved Gaia Data Release 3 (Gaia DR3) quasar candidate catalog with more than 1.5 million sources in the 3 π sky built with data from Gaia, Pan-STARRS1, and CatWISE2020. The XGBoost algorithm is used to reclassify the original Gaia DR3 quasar candidates as stars, galaxies, and quasars. To construct training/validation data sets for the classification, we carefully built two different master stellar samples in addition to the spectroscopic galaxy and quasar samples. An ensemble classification model is obtained by averaging two XGBoost classifiers trained with different master stellar samples. Using a probability threshold of p _QSO_mean > 0.95 in our ensemble classification model and an additional cut on the logarithmic probability density of zero proper motion, we retrieved 1,545,514 reliable quasar candidates from the parent Gaia DR3 quasar candidate catalog. We provide photometric redshifts for all candidates with an ensemble regression model. For a subset of 89,100 candidates, accurate spectroscopic redshifts are estimated with the convolutional neural network from the Gaia BP/RP spectra. The CatNorth catalog has a high purity of ∼90%, while maintaining high completeness, which is an ideal sample to understand the quasar population and its statistical properties. The CatNorth catalog is used as the main source of input catalog for the Large Sky Area Multi-Object Fiber Spectroscopic Telescope phase III quasar survey, which is expected to build a highly complete sample of bright quasars with i < 19.5.

The number density and correlation function of galaxies are two key quantities to characterize the distribution of the observed galaxy population. High- z spectroscopic surveys, which usually involve complex target selection and are incomplete in redshift sampling, present both opportunities and challenges to measure these quantities reliably in the high- z Universe. Using realistic mock catalogs, we show that target selection and redshift incompleteness can lead to significantly biased results, especially due to the flux-limit selection criteria. We develop a new method to correct the flux-limit effect, using information provided by the parent photometric data from which the spectroscopic sample is constructed. Our tests using realistic mock samples show that the method is able to reproduce the true stellar mass function and correlation function reliably. Mock catalogs are constructed for the existing zCOSMOS and VIPERS surveys, as well as for the forthcoming Prime Focus Spectrograph (PFS) galaxy evolution survey. The same set of mock samples are used to quantify the total variance expected for different sample sizes. We find that the total variance decreases very slowly when the survey area reaches about 4 deg ^2 for the abundance and about 8 deg ^2 for the clustering, indicating that the cosmic variance is no longer the dominant source of error for PFS-like surveys. We also quantify the improvements expected in the PFS-like galaxy survey relative to zCOSMOS and VIPERS surveys.

We present results exploring the role that probabilistic deep learning models can play in cosmology from large-scale astronomical surveys through photometric redshift (photo- z ) estimation. Photo- z uncertainty estimates are critical for the science goals of upcoming large-scale surveys such as the Legacy Survey of Space and Time (LSST); however, common machine learning methods typically provide only point estimates and lack uncertainties on predictions. We turn to Bayesian neural networks (BNNs) as a promising way to provide accurate predictions of redshift values with uncertainty estimates. We have compiled a galaxy data set from the Hyper Suprime-Cam Survey with grizy photometry, which is designed to be a smaller-scale version of large surveys like LSST. We use this data set to investigate the performance of a neural network and a probabilistic BNN for photo- z estimation and evaluate their performance with respect to LSST photo- z science requirements. We also examine the utility of photo- z uncertainties as a means to reduce catastrophic outlier estimates. The BNN outputs the estimate in the form of a Gaussian probability distribution. We use the mean and standard deviation as the redshift estimate and uncertainty. We find that the BNN can produce accurate uncertainties. Using a coverage test, we find excellent agreement with expectation—67.2% of galaxies between 0 < 2.5 have 1 σ uncertainties that cover the spectroscopic value. We also include a comparison to alternative machine learning models using the same data. We find the BNN meets two out of three of the LSST photo- z science requirements in the range 0 < z < 2.5.

We present a catalog of 717 candidate galaxies at z > 8 selected from 125 square arcmin of NIRCam imaging as part of the JWST Advanced Deep Extragalactic Survey (JADES). We combine the full JADES imaging data set with data from the JWST Extragalactic Medium Survey and First Reionization Epoch Spectroscopic COmplete Survey (FRESCO) along with extremely deep existing observations from Hubble Space Telescope (HST)/Advanced Camera for Surveys (ACS) for a final filter set that includes 15 JWST/NIRCam filters and five HST/ACS filters. The high-redshift galaxy candidates were selected from their estimated photometric redshifts calculated using a template-fitting approach, followed by visual inspection from seven independent reviewers. We explore these candidates in detail, highlighting interesting resolved or extended sources, sources with very red long-wavelength slopes, and our highest-redshift candidates, which extend to z _phot ∼ 18. Over 93% of the sources are newly identified from our deep JADES imaging, including 31 new galaxy candidates at z _phot > 12. We also investigate potential contamination by stellar objects, and do not find strong evidence from spectral energy distribution fitting that these faint high-redshift galaxy candidates are low-mass stars. Using 42 sources in our sample with measured spectroscopic redshifts from NIRSpec and FRESCO, we find excellent agreement to our photometric redshift estimates, with no catastrophic outliers and an average difference of 〈Δ z = z _phot − z _spec 〉 = 0.26. These sources comprise one of the most robust samples for probing the early buildup of galaxies within the first few hundred million years of the Universe’s history.

Gamma-ray bursts (GRBs), due to their high luminosities, are detected up to a redshift of 10, and thus have the potential to be vital cosmological probes of early processes in the Universe. Fulfilling this potential requires a large sample of GRBs with known redshifts, but due to observational limitations, only 11% have known redshifts ( z ). There have been numerous attempts to estimate redshifts via correlation studies, most of which have led to inaccurate predictions. To overcome this, we estimated GRB redshift via an ensemble-supervised machine-learning (ML) model that uses X-ray afterglows of long-duration GRBs observed by the Neil Gehrels Swift Observatory. The estimated redshifts are strongly correlated (a Pearson coefficient of 0.93) and have an rms error, namely, the square root of the average squared error 〈Δ z ^2 〉, of 0.46 with the observed redshifts showing the reliability of this method. The addition of GRB afterglow parameters improves the predictions considerably by 63% compared to previous results in peer-reviewed literature. Finally, we use our ML model to infer the redshifts of 154 GRBs, which increase the known redshifts of long GRBs with plateaus by 94%, a significant milestone for enhancing GRB population studies that require large samples with redshift.

Extremely metal-poor galaxies (XMPGs) at relatively low redshift are excellent laboratories for studying galaxy formation and evolution in the early universe. Much effort has been spent on identifying them from large-scale spectroscopic surveys or spectroscopic follow-up observations. Previous work has identified a few hundred XMPGs. In this work, we obtain a large sample of 223 XMPGs at z < 1 from the early data of the Dark Energy Spectroscopic Instrument (DESI). The oxygen abundance is determined using the direct T _e method based on the detection of the [O iii ] λ 4363 line. The sample includes 95 confirmed XMPGs based on the oxygen abundance uncertainty; the remaining 128 galaxies are regarded as XMPG candidates. These XMPGs are only 0.01% of the total DESI observed galaxies. Their coordinates and other properties are provided in the paper. The most XMPGs have an oxygen abundance of ∼1/34 Z _⊙ , a stellar mass of about 1.5 × 10 ^7 M _⊙, and a star formation rate of 0.22 M _⊙ yr ^−1 . The two most XMPGs present distinct morphologies suggesting different formation mechanisms. The local environmental investigation shows that XMPGs preferentially reside in relatively low-density regions. Many of them fall below the stellar mass–metallicity relations (MZRs) of normal star-forming galaxies. From a comparison of the MZR with theoretical simulations, it appears that XMPGs are good analogs to high-redshift star-forming galaxies. The nature of these XMPG populations will be further investigated in detail with larger and more complete samples from the ongoing DESI survey.

Galactic conformity is the phenomenon whereby a galaxy of a certain physical property is correlated with its neighbors of the same property, implying a possible causal relationship. The observed auto correlations of emission-line galaxies (ELGs) from the highly complete DESI One-Percent Survey exhibit a strong clustering signal on small scales, providing clear evidence for the conformity effect of ELGs. Building upon the original subhalo abundance-matching (SHAM) method developed by Gao et al., we propose a concise conformity model to improve the ELG–halo connection. In this model, the number of satellite ELGs is boosted by a factor of ∼5 in the halos whose central galaxies are ELGs. We show that the mean ELG satellite number in such central halos is still smaller than 1 and that the model does not significantly increase the overall satellite fraction. With this model, we can well recover the ELG auto correlations to the smallest scales explored with the current data (i.e., r _p > 0.03 Mpc h ^−1 in real space and at s > 0.3 Mpc h ^−1 in redshift space), while the cross correlations between luminous red galaxies and ELGs are nearly unchanged. Although our SHAM model has only eight parameters, we further verify that it can accurately describe the ELG clustering in the entire redshift range from z = 0.8 to 1.6. We therefore expect that this method can be used to generate high-quality ELG lightcone mocks for DESI.

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg ^2 over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI was evaluated during a 5 month survey validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar Milky Way Survey (MWS), Bright Galaxy Survey (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the 5 yr program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a One-Percent Survey conducted at the conclusion of SV covering 140 deg ^2 using the final target selection algorithms with exposures of a depth typical of the main survey. The SV indicates that DESI will be able to complete the full 14,000 deg ^2 program with spectroscopically confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval z < 1.1, 0.39% over the redshift interval 1.1 < z < 1.9, and 0.46% over the redshift interval 1.9 < z < 3.5.

We seek to prove the means, motive and opportunity of 'dropout' selected 2 ≤ z ≤ 5 galaxies for large-scale structure. Together with acquired low-z tracers, these samples would map practically every linear mode and facilitate a tomographic decomposition of the Cosmic Microwave Background (CMB) lensing kernel over an unprecedented volume. With this, one may infer (the time evolution of) matter density fluctuations and perform compelling tests of horizon-scale General Relativity, neutrino masses and Inflation - viz., curvature, running of the spectral index and a scale-dependent halo bias induced by (local) primordial non-Gaussianity. This is facilitated by the order-of-magnitude increase in sensitivity achieved by planned CMB, optical-to-near-infrared imaging and spectroscopy. Focusing on traditional color-color - rather than photometric redshift - selection, we estimate the expected completeness, contamination, and spectroscopic survey speed of tailored Lyman-break galaxy (LBG) samples. With these in hand, we forecast the potential of CMB lensing cross-correlation, 'clustering redshifts' and Redshift-Space Distortions (RSD) analyses. In particular, we estimate: the depth dependence of interlopers based on CFHTLS-Archive-Research Survey (CARS) data and propagate this to biases in cosmology; a simple relation for the dependence of the linear galaxy bias on redshift and depth; new inferences of non-linear halo bias at these redshifts using legacy data; detailed forecasts of LBG spectra as would be observed by the Dark Energy Spectroscopic Instrument, Prime Focus Spectrograph, and their successors. We further assess the relative competitiveness of these spectroscopic facilities based on an intuitive figure-of-merit and define modern equivalents to traditional color selection criteria for the Large Synoptic Survey Telescope, where necessary. We confirm these science cases to be compelling for achievable facilities in the next decade by defining a LBG sample of increasing Lyman-α equivalent width with redshift, which delivers both percent-level RSD constraints on the growth rate at high-z and measurements of CMB lensing cross-correlation at z=3 and 4 with a significance measured in the hundreds, given sufficient area overlap. Finally, we discuss the limitations of this initial exploration and provide avenues for future investigation.

This paper introduces the HiddenValley simulations, a set of trillion-particle N-body simulations in gigaparsec volumes aimed at intensity mapping science. We present details of the simulations and their convergence, then specialize to the study of 21-cm fluctuations between redshifts 2 and 6. Neutral hydrogen is assigned to halos using three prescriptions, and we investigate the clustering in real and redshift-space at the 2-point level. In common with earlier work we find the bias of HI increases from near 2 at z=2 to 4 at z=6, becoming more scale dependent at high z. The level of scale-dependence and decorrelation with the matter field are as predicted by perturbation theory. Due to the low mass of the hosting halos, the impact of fingers of god is small on the range relevant for proposed 21-cm instruments. We show that baryon acoustic oscillations and redshift-space distortions could be well measured by such instruments. Taking advantage of the large simulation volume, we assess the impact of fluctuations in the ultraviolet background, which change HI clustering primarily at large scales.

We study synergies between three promising methods to measure 22 and suffer from interloper problems even for spectroscopic surveys. Intensity mapping of the 21-cm signal can cover large volumes with exquisite fidelity, but is limited both by loss of information to foreground cleaning and by lack of knowledge of the mean signal. Cosmic microwave background (CMB) lensing is theoretically very clean, but ultimately measures just the projected variations in density. We find that cross-correlation between optical and radio can significantly improve the measurement of growth rate. Combining these with the CMB provides a promising avenue to detecting modified gravity at high redshifts, in particular by independently probing the Weyl and Newtonian potentials and by strengthening control of systematics. We find that cross-correlating a Stage ii 21-cm survey with DESI quasars with a reasonable brightness temperature prior could enable measurements of the growth rate fσ8 at sub 3% and sub 8% levels at z = 3, 4, representing a factor of 4 and 8 improvement over constraints obtainable from DESI quasars alone. Similarly, cross-correlating 21-cm data with a futuristic LBG survey to mUV

Line intensity mapping offers a new avenue for constraining cosmological parameters in the high redshift Universe. However measurements of the growth of structure, a sensitive probe of gravity, are affected by a well known degeneracy with astrophysical parameters, encoded in the mean brightness temperature of the specific line. In this work we show how to break this degeneracy, to a level that could allow constraints of the amplitude of cosmological fluctuations at the percent level, using information in the mildly non-linear regime of structure formation as described by Lagrangian Perturbation Theory. We focus on the 21-cm line with forecasts for HIRAX and the proposed Stage II experiment as illustrations.

We explore and compare different ways large-scale structure observables in redshift-space and real space can be connected. These include direct computation in Lagrangian space, moment expansions and two formulations of the streaming model. We derive for the first time a Fourier space version of the streaming model, which yields an algebraic relation between the real- and redshift-space power spectra which can be compared to earlier, phenomenological models. By considering the redshift-space 2-point function in both configuration and Fourier space, we show how to generalize the Gaussian streaming model to higher orders in a systematic and computationally tractable way. We present a closed-form solution to the Zeldovich power spectrum in redshift space and use this as a framework for exploring convergence properties of different expansion approaches. While we use the Zeldovich approximation to illustrate these results, much of the formalism and many of the relations we derive hold beyond perturbation theory, and could be used with ingredients measured from N-body simulations or in other areas requiring decomposition of Cartesian tensors times plane waves. We finish with a discussion of the redshift-space bispectrum, bias and stochasticity and terms in Lagrangian perturbation theory up to 1-loop order.

The repeating fast radio burst FRB 20190520B is an anomaly of the FRB population thanks to its high dispersion measure (DM = 1205 pc cm ^−3 ) despite its low redshift of z _frb = 0.241. This excess has been attributed to a large host contribution of DM _host ≈ 900 pc cm ^−3 , far larger than any other known FRB. In this paper, we describe spectroscopic observations of the FRB 20190520B field obtained as part of the FLIMFLAM survey, which yielded 701 galaxy redshifts in the field. We find multiple foreground galaxy groups and clusters, for which we then estimated halo masses by comparing their richness with numerical simulations. We discover two separate M _halo > 10 ^14 M _⊙ galaxy clusters at z = 0.1867 and 0.2170 that are directly intersected by the FRB sight line within their characteristic halo radius r _200 . Subtracting off their estimated DM contributions, as well that of the diffuse intergalactic medium, we estimate a host contribution of ${{\rm{D}}{\rm{M}}}_{{\rm{h}}{\rm{o}}{\rm{s}}{\rm{t}}}={430}_{-220}^{+140}$ or ${280}_{-170}^{+140}\,{\rm{p}}{\rm{c}}\,{{\rm{c}}{\rm{m}}}^{-3}$ (observed frame), depending on whether we assume that the halo gas extends to r _200 or 2 × r _200 . This significantly smaller DM _host —no longer the largest known value—is now consistent with H α emission measures of the host galaxy without invoking unusually high gas temperatures. Combined with the observed FRB scattering timescale, we estimate the turbulent fluctuation and geometric amplification factor of the scattering layer to be $\widetilde{F}G\approx 4.5\mbox{--}11{({\mathrm{pc}}^{2}\,\mathrm{km})}^{-1/3}$ , suggesting that most of the gas is close to the FRB host. This result illustrates the importance of incorporating foreground data for FRB analyses both for understanding the nature of FRBs and to realize their potential as a cosmological probe.

We explore an interacting dark matter (IDM) model that allows for a fraction of dark matter (DM) to undergo velocity-independent scattering with baryons. In this scenario, structure on small scales is suppressed relative to the cold DM scenario. Using the effective field theory of large-scale structure, we perform the first systematic analysis of BOSS full-shape galaxy clustering data for the IDM scenario, and we find that this model ameliorates the S _8 tension between large-scale structure and Planck data. Adding the S _8 prior from the Dark Energy Survey (DES) to our analysis further leads to a mild ∼3 σ preference for a nonvanishing DM–baryon scattering cross section, assuming ∼10% of DM is interacting and has a particle mass of 1 MeV. This result produces a modest ∼20% suppression of the linear power at k ≲ 1 h Mpc ^−1 , consistent with other small-scale structure observations. Similar scale-dependent power suppression was previously shown to have the potential to resolve S _8 tension between cosmological data sets. The validity of the specific IDM model explored here will be critically tested with upcoming galaxy surveys at the interaction level needed to alleviate the S _8 tension.

We present the first results from the JWST program A SPectroscopic survey of biased halos In the Reionization Era (ASPIRE). This program represents an imaging and spectroscopic survey of 25 reionization-era quasars and their environments by utilizing the unprecedented capabilities of NIRCam Wide Field Slitless Spectroscopy (WFSS) mode. ASPIRE will deliver the largest ( $\sim 280\,{\mathrm{arcmin}}^{2}$ ) galaxy redshift survey at 3–4 μ m among JWST Cycle 1 programs and provide extensive legacy values for studying the formation of the earliest supermassive black holes, the assembly of galaxies, early metal enrichment, and cosmic reionization. In this first ASPIRE paper, we report the discovery of a filamentary structure traced by the luminous quasar J0305–3150 and 10 [O iii ] emitters at z = 6.6. This structure has a 3D galaxy overdensity of δ _gal = 12.6 over 637 cMpc ^3 , one of the most overdense structures known in the early universe, and could eventually evolve into a massive galaxy cluster. Together with existing VLT/MUSE and ALMA observations of this field, our JWST observations reveal that J0305–3150 traces a complex environment where both UV-bright and dusty galaxies are present and indicate that the early evolution of galaxies around the quasar is not simultaneous. In addition, we discovered 31 [O iii ] emitters in this field at other redshifts, 5.3 < z < 6.7, with half of them situated at z ∼ 5.4 and 6.2. This indicates that star-forming galaxies, such as [O iii ] emitters, are generally clustered at high redshifts. These discoveries demonstrate the unparalleled redshift survey capabilities of NIRCam WFSS and the potential of the full ASPIRE survey data set.

We report the first constraints on the growth rate of the universe, f ( z ) σ _8 ( z ), with intrinsic alignments (IAs) of galaxies. We measure the galaxy density-intrinsic ellipticity cross-correlation and intrinsic ellipticity autocorrelation functions over 0.16 < z < 0.7 from luminous red galaxies (LRGs) and LOWZ and CMASS galaxy samples in the Sloan Digital Sky Survey (SDSS) and SDSS-III BOSS survey. We detect clear anisotropic signals of IA due to redshift-space distortions. By combining measured IA statistics with the conventional galaxy clustering statistics, we obtain tighter constraints on the growth rate. The improvement is particularly prominent for the LRG, which is the brightest galaxy sample and known to be strongly aligned with underlying dark matter distribution; using the measurements on scales above 10 h ^−1 Mpc, we obtain $f{\sigma }_{8}={0.5196}_{-0.0354}^{+0.0352}$ (68% confidence level) from the clustering-only analysis and $f{\sigma }_{8}={0.5322}_{-0.0291}^{+0.0293}$ with clustering and IA, meaning 19% improvement. The constraint is in good agreement with the prediction of general relativity, f σ _8 = 0.4937 at z = 0.34. For LOWZ and CMASS samples, the improvement of constraints on f σ _8 is found to be 10% and 3.5%, respectively. Our results indicate that the contribution from IA statistics for cosmological constraints can be further enhanced by carefully selecting galaxies for a shape sample.