We conduct a search for strong gravitational lenses in the Dark Energy Survey (DES) Year 6 imaging data. We implement a pre-trained Vision Transformer (ViT) for our machine learning (ML) architecture and adopt interactive machine learning to construct a training sample with multiple classes to address common types of false positives. Our ML model reduces similar to 236 million DES cutout images to 22,564 targets of interest, including similar to 85% of previously reported galaxy-galaxy lens candidates discovered in DES. These targets were visually inspected by citizen scientists, who ruled out similar to 90% as false positives. Of the remaining 2618 candidates, 149 were expert-classified as "definite" lenses and 516 as "probable" lenses, for a total of 665 systems, with 147 of these candidates being newly identified. Additionally, we trained a second ViT to find double-source plane lens systems, finding at least one double-source system. Our main ViT excels at identifying galaxy-galaxy lenses, consistently assigning high scores to candidates with high expert assessments. The top 800 ViT-scored images include similar to 100 of our "definite" lens candidates. This selection is an order of magnitude higher in purity than previous convolutional neural-network-based lens searches and demonstrates the feasibility of applying our methodology for discovering large samples of lenses in future surveys.

We perform a frequentist analysis using the standard profile likelihood method for clustering measurements from Data Release 1 of the Dark Energy Spectroscopic Instrument (DESI). While Bayesian inferences for Effective Field Theory models of galaxy clustering can be highly sensitive to the choice of priors for extended cosmological models, frequentist inferences are not susceptible to such effects. We compare Bayesian and frequentist constraints for the parameter set {σ_8, H_0, Ω_m, w_0, w_a} when fitting to the full-shape of the power spectrum multipoles, the post-reconstruction Baryon Acoustic Oscillation (BAO) measurements, as well as external datasets from the CMB and type Ia supernovae measurements. Bayesian prior effects are very significant for the w_0w_aCDM model; while the 1 σ frequentist confidence intervals encompass the maximum a posteriori (MAP), the Bayesian credible intervals almost always exclude the maximum likelihood estimate (MLE) and the MAP - indicating strong prior volume projection effects - unless supernovae data are included. We observe limited prior effects for the ΛCDM model, due to the reduced number of parameters. When DESI full-shape and BAO data are jointly fit, we obtain the following 1σ frequentist confidence intervals for ΛCDM (w_0w_aCDM): σ_8 = 0.867^+0.048_-0.041 , H_0 = 68.91^+0.80_-0.79 km s^-1Mpc^-1 , Ω_m = 0.3038±0.0110 (σ_8 = 0.793^+0.069_-0.048 , H_0 = 64.9^+4.8_-2.8 km s^-1Mpc^-1 , Ω_m = 0.369^+0.029_-0.059 , w_0 = -0.24^+0.17_-0.64 , w_a = -2.5^+1.9_), corresponding to 0.7σ, 0.3σ, 0.7σ (1.9σ, 3.4σ, 5.6σ, 5.5σ, 5.6σ) shifts between the MLE relative to the Bayesian posterior mean for ΛCDM (w_0w_aCDM) respectively.

The effective redshift distribution n(z) of galaxies is a critical component in the study of weak gravitational lensing. Here, we introduce a new method for determining n(z) for weak lensing surveys based on high-quality redshifts and neural-network-based importance weights. Additionally, we present the first unified photometric redshift calibration of the three leading stage-III weak lensing surveys, the Dark Energy Survey (DES), the Hyper Suprime-Cam (HSC) survey, and the Kilo-Degree Survey (KiDS), with state-of-the-art spectroscopic data from the Dark Energy Spectroscopic Instrument (DESI). We verify our method using a new, data-driven approach and obtain n(z) constraints with statistical uncertainties of the order of sigma z & strns;similar to 0.01 and smaller. Our analysis is largely independent of previous photometric redshift calibrations and, thus, provides an important cross-check in light of recent cosmological tensions. Overall, we find excellent agreement with previously published results on the DES Y3 and HSC Y1 data sets, while there are some differences on the mean redshift with respect to the previously published KiDS-1000 results. We attribute the latter to mismatches in photometric noise properties in the COSMOS field compared to the wider KiDS self-organizing map-gold catalog. At the same time, the new n(z) estimates for KiDS do not significantly change estimates of cosmic structure growth from cosmic shear. Finally, we discuss how our method can be applied to future weak lensing calibrations with DESI data.

We present the discovery of SN 2025mkn, a gravitationally lensed Type II supernova. First detected as a blue transient in Zwicky Transient Facility (ZTF), 0 .'' 83 from a z = 0.42 elliptical galaxy, the follow-up SNIFS/UH2.2 m and LRIS/Keck spectra revealed absorption lines at z = 1.371. Later JWST NIRCam imaging shows that the bright transient is a close pair of point sources separated by similar to 0.'' 07 , and a 30 times fainter counterimage opposite the lens, for which NIRSpec reveals strong H alpha emission also at z = 1.371. The lightcurves and spectra are consistent with the Type II supernova source being magnified greater than or similar to 100 times, with similar to 250 required to reconcile its luminosity with that of nearby events such as SN 2023ixf. Lens models are consistent with such high magnifications, and always show that the faint image arrived first (undetected in earlier ZTF imaging), consistent with the later spectral phase of this fainter image. A fourth image is also predicted and possibly detected in the NIRSpec data. Lightcurve-based time-delay measurements are not possible due to the first image being the faintest; however, the resolved NIRSpec spectra offer a future opportunity for time-delay cosmography through supernova phase measurements.

We present a science case to perform high-redshift cosmic shear surveys for cosmology with next-generation spectroscopic instruments, such as the proposed MegaMapper and Wide-field Spectroscopic Telescope. We argue that by using the novel technique called 'kinematic lensing' (KL) it will be possible to obtain shear catalogues at redshifts between 2 and 5. We show that the signal-to-noise ratio of KL at such high redshifts is on average twice as much that expected from current weak lensing (WL) surveys such as Euclid or LSST, and several times that of the previous generation of WL surveys like DES and KiDS, even with very conservative assumptions about the fraction of spectroscopically-detected sources for which KL shear estimates will be available. This will allow cosmologists to perform joint galaxy clustering-cosmic shear analyses over unprecedented cosmic volumes and to probe the growth of structures deep in the matter-dominated era and across the onset of dark-energy domination, offering a unique opportunity to unveil the mystery of cosmic acceleration.

Quasars acting as strong gravitational lenses offer a rare opportunity to probe the redshift evolution of scaling relations between supermassive black holes and their host galaxies, particularly the M _BH – M _host relation. Using these powerful probes, the mass of the host galaxy can be precisely inferred from the Einstein radius θ _E . Using 812,118 quasars from DESI DR1 (0.03 ≤ z ≤ 1.8), we searched for quasars lensing higher-redshift galaxies by identifying background emission-line features in their spectra. To detect these rare systems, we trained a convolutional neural network (CNN) on mock lenses constructed from real DESI spectra of quasars and emission-line galaxies (ELGs), achieving a high classification performance (AUC = 0.99). We also trained a regression network to estimate the redshift of the background ELG. Applying this pipeline, we identified seven high-quality (Grade A) lens candidates, each exhibiting a strong [O II ] doublet at a higher redshift than the foreground quasar; four candidates additionally show H β , [O III ] λ 4959, and [O III ] λ 5007 emission. These results significantly expand the sample of quasar lens candidates beyond the 12 identified and 3 confirmed in previous work and demonstrate the potential for scalable, data-driven discovery of quasars as strong lenses in upcoming spectroscopic surveys.

Understanding the Universe's origins and evolution remains one of the most fundamental challenges in modern cosmology. This white paper explores three key science priorities in this field: unravelling the physics of cosmic inflation, investigating the accelerating expansion of the Universe, and precisely measuring the sum of the neutrino masses. Achieving these goals requires a dedicated survey to map the large-scale structure at high redshift in unprecedented detail. We describe how this can be achieved through a mission concept called SIRMOS, providing a high-throughput, highly multiplexed spectroscopic capability to obtain accurate redshifts for over 100 million galaxies over a wide sky area. Such a survey would leverage the deepest existing wide-area photometric catalogues for targeting, with spectra offering continuous 1.25-2.5 μm wavelength coverage at moderate resolution, allowing precise redshift measurements in the 1<z<4 range with minimal bias. We outline the scientific opportunities this presents. Recent years have seen significant advances in instrumentation, including digital micromirror devices, complex telescope mirrors, large detector arrays, and data processing pipelines. While these technologies have been demonstrated in terrestrial applications, such a survey is a unique opportunity to apply these proven capabilities in space to address fundamental questions in cosmology. Participation in such a mission will simultaneously deliver a compelling science case, help align UK Space Agency and STFC strategies, demonstrate the UK's growing capability in end-to-end space missions, and strengthen the national space economy through high-value industrial participation.

We present the first measurement of local-type primordial non-Gaussianity from the cross-correlation between 1.2 million spectroscopically confirmed quasars from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI) and the Planck PR4 CMB lensing reconstructions. The analysis is performed in three tomographic redshift bins covering 0.8 < z < 3.5, covering a sky fraction of similar to 20%. We adopt a catalog-based pseudo-C-l estimator and apply linear imaging weights validated on noiseless mocks. Compared to previous analyses using photometric quasar samples, our results benefit from the high purity of the DESI spectroscopic sample, the reduced noise of PR4 lensing, and the absence of excess large-scale power in the spectroscopic quasar auto-correlation. Fitting simultaneously for the non-Gaussianity parameter f(NL) and the linear bias amplitude in each redshift bin, we obtain f(NL) = 2(-34)(+28) for a response parameter p = 1.6, and f(NL) = 6(-24)(+20) for p = 1.0. These results improve the constraints on f(NL) by similar to 35% compared to the previous analysis based on the Legacy Imaging Survey DR9. Additionally, we derive an optimal weighting scheme to maximize the constraining power. In this case, and assuming p = 1.6, we obtain f(NL) = 19(-31)(+25). Our results demonstrate the statistical power of DESI quasars for probing inflationary physics, and highlight the promise of future DESI data releases.

This is a review article for The Review of Particle Physics 2026 (aka the Particle Data Book), appearing as Chapter 25. It forms a compact review of knowledge of the cosmological parameters near the end of 2025. Topics included are Parametrizing the Universe; Extensions to the standard model; Probes; Bringing observations together; Outlook for the future.

Astrophysics is a social enterprise exemplified here by the Dark Energy Survey (DES) which completed its fieldwork in 2019 after 16 years of preparation and observation, while data analysis continues. Society funds astrophysics on a grand scale. For human capital and for governance the discipline draws on a self-governing "republic of science", while the funds were provided by philanthropists in the past, and by governments today. The benefits accrue initially to scientists themselves, in the form of a rewarding vocation. For the social benefit it is tempting to apply formal cost benefit analysis, but that approach ignores the option value of science and imposes questionable assumptions from welfare economics. Astrophysics generates some useful spinoffs, offers attractive careers, appeals to the popular imagination, speaks to metaphysical cravings and constitutes a good in itself. The rise of AI also suggests a role in exploring future habitats for intelligence and cognition.

We present an efficient estimator for higher order galaxy clustering using small groups of nearby galaxies, or multiplets. Using the Luminous Red Galaxy sample from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2, we identify galaxy multiplets as discrete objects and measure their cross-correlations with the general galaxy field. Our results show that the multiplets exhibit stronger clustering bias as they trace more massive dark matter haloes than individual galaxies. When comparing the observed clustering statistics with the mock catalogues generated from the N-body simulation AbacusSummit, we find that the mocks underpredict multiplet clustering despite reproducing the galaxy two-point autocorrelation reasonably well. This discrepancy indicates that the standard Halo Occupation Distribution (HOD) model is insufficient to describe the properties of galaxy multiplets, revealing the greater constraining power of this higher order statistic on galaxy-halo connection and the possibility that multiplets are specific to additional assembly bias. We demonstrate that incorporating secondary biases into the HOD model improves agreement with the observed multiplet statistics, specifically by allowing galaxies to preferentially occupy haloes in denser environments. Our results highlight the potential of utilizing multiplet clustering, beyond traditional two-point correlation measurements, to break degeneracies in models describing the galaxy-dark matter connection.

We describe the photometric dataset assembled from the full 6 yr of observations by the Dark Energy Survey (DES) in support of static-sky cosmology analyses. DES Y6 Gold is a curated dataset derived from DES Data Release 2 (DR2) that incorporates improved measurement, photometric calibration, object classification and value-added information. Y6 Gold comprises nearly 5000 deg ^2 of grizY imaging in the south Galactic cap and includes 669 million objects with a depth of i _AB ∼ 23.4 mag at a signal-to-noise ratio ∼ 10 for extended objects and a top-of-the-atmosphere photometric uniformity <2 mmag. Y6 Gold augments DES DR2 with simultaneous fits to multiepoch photometry for more robust galaxy shapes, colors, and photometric redshift estimates. Y6 Gold features improved morphological star–galaxy classification with an efficiency of 98.6% and a contamination of 0.8% for galaxies with 17.5 < i _AB < 22.5. Additionally, it includes per-object quality information, and accompanying maps of the footprint coverage, masked regions, imaging depth, survey conditions, and astrophysical foregrounds that are used for cosmology analyses. After quality selections, benchmark samples contain 448 million galaxies and 120 million stars. This publication is complemented by data access and documentation.

General relativity is exquisitely tested in strong-field regimes, yet its validity on cosmological scales remains largely unexplored. Upcoming wide and deep large-scale structure surveys will access the ultra-large, linear scales where relativistic effects - Doppler terms, gravitational redshift, lensing magnification, and potential evolution - leave significant imprints in the clustering of galaxies. These signatures represent unique probes of spacetime that are inaccessible to standard Newtonian analyses but increasingly important as survey volumes grow. We outline the scientific potential of next-generation facilities, such as those envisioned within ESO's Expanding Horizons programme, to deliver the first robust measurements of relativistic effects in large-scale structure through multi-tracer power spectra and the single-tracer bispectrum of high-redshift Lyman-break galaxies. Detecting these contributions would open a new window on gravity, enabling precision tests of general relativity and its alternatives on cosmological scales in the 2040s.

Protoclusters represent sites of accelerated galaxy formation and extreme astrophysical activity characteristic of dense environments. Identifying massive protoclusters and mapping their spatial structures are therefore crucial first steps in understanding how the large-scale environment influences galaxy evolution. We combine wide-field Lyα imaging from the ODIN survey with extensive DESI and ancillary spectroscopy across the extended COSMOS and XMM-LSS fields (≈14 deg^2) to search for massive protoclusters. We confirm six systems at z≈ 2.4 and z≈ 3.1, reconstruct their three-dimensional structures, estimate descendant halo masses, and, for one structure at z≈ 3.12, demonstrate that overlapping narrowband filters (NB497 and N501) provide accurate redshift tomography for emission-line galaxies. One protocluster at z≈ 2.45 overlaps with one of the LATIS tomographic fields, enabling direct comparison between galaxy and H i overdensities traced by Lyα forest absorption. Another at z≈ 3.12 hosts a massive quiescent galaxy (M_∗≈ 1.2 × 10^11M_⊙), indicating early quenching in a dense environment. By comparing Lyα emission properties across environments, we find that protocluster galaxies exhibit higher median line fluxes and a deficit of faint emitters relative to the field. The effect is strongest when both 2D and 3D density information are combined, indicating that galaxies in the densest protocluster cores are most affected by environmental processes. This effect is stronger at z≈3.1 than at z≈2.4, suggesting possible redshift evolution.

We present a novel graph-based machine learning classifier for identifying the dark matter cosmic web environments of galaxies. Large galaxy surveys offer comprehensive statistical views of how galaxy properties are shaped by largescale structure, but this requires robust classifications of galaxies' cosmic web environments. Using stellar mass-selected IllustrisTNG-300 galaxies, we apply a three-stage, simulation-based framework to link galaxies to the total (mainly dark) underlying matter distribution. Here, we apply the following three steps: First, we assign the positions of simulated galaxies to a void, wall, filament, or cluster environment using the T-web classification of the underlying matter distribution. Secondly, we construct a Delaunay triangulation of the galaxy distribution to summarize the local geometric structure with ten graph metrics for each galaxy. Thirdly, we train a graph attention network (GAT) on each galaxy's graph metrics to predict its cosmic web environment. For galaxies with stellar mass > 10(9)M(circle dot), our GAT+ model achieves an accuracy of 85 per cent, outperforming graph-agnostic multilayer perceptrons and graph convolutional networks. Our results demonstrate that graph-based representations of galaxy positions provide a powerful and physically meaningful way to infer dark matter environments. We plan to apply thissimulation-based graph modelling to investigate how the properties of observed galaxies from the Dark Energy Spectroscopic Instrument (DESI) survey are influenced by their dark matter environments

On 2025 August 18, the LIGO-Virgo-KAGRA collaboration reported a subthreshold gravitational-wave candidate detection consistent with a subsolar-mass neutron star merger, denoted S250818k. An optical transient, AT2025ulz, was discovered within the localization region. AT2025ulz initially appeared to meet the expected behavior of kilonova emission, the telltale signature of a binary neutron star merger. The transient subsequently rebrightened after similar to 5 days and was classified as a Type IIb supernova. In this work, we analyze the observations of its host galaxy obtained by the Dark Energy Spectroscopic Instrument (DESI). From the DESI spectrum, we obtain a secure redshift of z = 0.084840 +/- 0.000006. If S250818k has an astrophysical origin, this places the transient within 2 sigma of the gravitational-wave distance and results in an integral overlap between the gravitational-wave alert and the transient location of log10I approximate to 3.9-4.2 . Our analysis of the host galaxy's spectral energy distribution reveals a star-forming, dusty galaxy with stellar mass similar to 1010 M circle dot, broadly consistent with the population of both short gamma-ray bursts and core-collapse supernova host galaxies. We also present our follow-up of DESI-selected candidate host galaxies using the Fraunhofer Telescope at the Wendelstein Observatory, and show the promise of DESI for associating or rejecting candidate electromagnetic counterparts to gravitational-wave alerts. These results emphasize the value of DESI's extensive spectroscopic dataset in rapidly characterizing host galaxies, enabling spectroscopic host subtraction, and guiding targeted follow-up.

Modeling the intrinsic alignment (IA) of galaxies poses a challenge to weak lensing analyses. Using the Dark Energy Survey Year 3 shape catalog, we expect less impact from IA when we limit the sample to blue, star-forming galaxies. The cosmological parameter constraints from this BLUE cosmic shear sample are stable to IA model choice, unlike passive galaxies in the full DES Y3 sample, the goodness-of-fit is improved and the Omega(m) and S-8 better agree with the observations from Planck on the cosmic microwave background. Mitigating IA with sample selection in DES, rather than flexible model choices, can reduce uncertainty in S-8 by a factor of 1.5.

We present the first systematic spectroscopic observations of extragalactic transients from the Dark Energy Spectroscopic Instrument (DESI), as part of the DESI Transients Survey program. With 5000 fibers and an similar to 8 deg2 field of view, we exploit DESI as a machine for the discovery and classification of transients. We present transient classifications from archival DESI data in Data Releases 1 and 2, relying on a combination of a secondary target program and serendipitous observations. We also present observations from the first 6 months of the DESI spare fiber program dedicated to transients. The program is run in coordination with a dedicated DECam time-domain survey, serving as a pathfinder for what we will be able to achieve in conjunction with the Rubin Observatory Legacy Survey of Space and Time (LSST). We classify over 250 transients, of which the majority were previously unclassified. The sample comprises thermonuclear and core-collapse supernovae and tidal disruption events (TDEs), including a TDE observed before its discovery in imaging. We demonstrate DESI's ability to classify a population of faint transients down to r similar to 22.5 mag during main survey operations, with negligible impacts on DESI's main observations. With the start of Rubin LSST operations, we expect to classify O(1000) transients per year.

Galaxy clustering constrains the baryon fraction Omega_b/Omega_m through the amplitude of baryon acoustic oscillations and the suppression of perturbations entering the horizon before recombination. This produces a different pre-recombination distribution of baryons and dark matter. After recombination, the gravitational potential responds to both components in proportion to their mass, allowing robust measurement of the baryon fraction. This is independent of new-physics scenarios altering the recombination background (e.g. Early Dark Energy). The accuracy of such measurements does, however, depend on how baryons and CDM are modeled in the power spectrum. Previous template-based splitting relied on approximate transfer functions that neglected part of information. We present a new method that embeds an extra parameter controlling the balance between baryons and dark matter in the growth terms of the perturbation equations in the CAMB Boltzmann solver. This approach captures the baryonic suppression of CDM prior to recombination, avoids inconsistencies, and yields a clean parametrization of the baryon fraction in the linear power spectrum, separating out the simple physics of growth due to the combined matter potential. We implement this framework in an analysis pipeline using Effective Field Theory of Large-Scale Structure with HOD-informed priors and validate it against noiseless LCDM and EDE cosmologies with DESI-like errors. The new scheme achieves comparable precision to previous splitting while reducing systematic biases, providing a more robust way to baryon-fraction measurements. In combination with BBN constraints on the baryon density and Alcock-Paczynski estimates of the matter density, these results strengthen the use of baryon fraction measurements to derive a Hubble constant from energy densities, with future DESI and Euclid data expected to deliver competitive constraints.

Using 1533 type Ia supernovae (SNe Ia) from the five-year sample of the Dark Energy Survey (DES), we investigate the relationship between the projected galactocentric separation of the SNe and their host galaxies and their light curves and standardization. We show, for the first time, that the difference in SN Ia post-standardization brightnesses between high and low-mass hosts reduces from 0.078±0.011 mag in the full sample to 0.036 ± 0.018 mag for SNe Ia located in the outer regions of their host galaxies, while increasing to 0.100 ± 0.014 mag for SNe in the inner regions. The difference in the size of the mass step between inner and outer regions is 0.064±0.023 mag. In these inner regions, the step can be reduced (but not removed) using a model where the R_V of dust along the line-of-sight to the SN changes as a function of galaxy properties. We investigate the remaining difference using the distributions of the SN Ia stretch parameter to test the inferred age of SN progenitors. Comparing red (older) environments only, outer regions have a higher proportion of high-stretch SNe and a more homogeneous stretch distribution. However, this effect cannot explain the reduction in significance of any Hubble residual step in outer regions. We conclude that the standardized distances of SNe Ia located in the outer regions of galaxies are less affected by their global host galaxy properties than those in the inner regions.