A typical Bayesian inference on the values of some parameters of interest q from some data D involves running a Markov Chain (MC) to sample from the posterior p(q,n divided by D)proportional to L(D divided by q,n)p(q)p(n), where n are some nuisance parameters with a separable prior. In some cases, the nuisance parameters are high-dimensional, and their prior p(n) is itself defined only by a set of samples that have been drawn from some other MC. The MC for the posterior will typically require evaluation of p(n) at arbitrary values of n, i.e., one needs to provide a density estimator over the full n space from the provided samples. But the high dimensionality of n hinders both the density estimation and the efficiency of the MC for the posterior. We describe a solution to this problem: a linear compression of the n space into a much lower-dimensional space u, which projects away directions in n space that cannot appreciably alter L. The algorithm for doing so is a slight modification to principal components analysis, and is less restrictive on p(n) than other proposed solutions to this issue. We demonstrate this "mode projection" technique using the analysis of 2-point correlation functions of weak lensing fields and galaxy density in the Dark Energy Survey, where n is a binned representation of the redshift distribution n(z) of the galaxies.

We present a new approach to measuring cosmic shear: the one-component Kinematic Lensing (KL) method. This technique provides a simplified implementation of KL that reduces shape noise in weak lensing (WL) by combining kinematic information with imaging data, while requiring less observational effort than the full two-component KL. We perform simulated likelihood analyses to assess the performance of the one-component KL and demonstrate its applicability to future radio surveys. Our forecasts indicate that, for radio surveys, the one-component KL is not yet competitive with traditional WL due to the shallow redshift distribution of HI-selected galaxies. However, when applying this method to deeper spectroscopic surveys with stronger emission lines, the one-component KL approach could surpass WL in constraining power, offering a promising and efficient pathway for future shear analyses.

Characterization of the redshift distribution of ensembles of galaxies is pivotal for large scale structure cosmological studies. In this work, we focus on improving the Self-Organizing Map (SOM) methodology for photometric redshift estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year 6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the underlying redshift distribution. We investigate three strategies for enhancing the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM algorithm with one tailored for redshift estimation challenges; 2) Incorporating $\textit{g}$-band flux information to refine redshift estimates (i.e. using $\textit{griz}$ fluxes as opposed to only $\textit{riz}$); 3) Augmenting redshift data for galaxies where available. These methods are applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our analysis indicates significant improvements with the first two strategies, notably reducing the overlap between redshift bins. By combining strategies 1 and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by up to 66$\%$. Conversely, the third strategy, involving the addition of redshift data for selected galaxies as an additional feature in the method, yields inferior results and is abandoned. Our findings contribute to the advancement of weak lensing redshift characterization and lay the groundwork for better redshift characterization in DES Year 6 and future stage IV surveys, like the Rubin Observatory.

The orientation of triaxial galaxy clusters with respect to the line-of-sight is expected to be one of the prime sources of scatter and potential bias in optical observables (e.g., richness and weak-lensing signal) of galaxy clusters. In this work, we use the observed shape of the central Brightest Cluster Galaxy (BCG) as proxy for the orientation along the line-of-sight for clusters selected via the Sunyaev-Zel'dovich (SZ) effect from the South Pole Telescope (SPT) and Atacama Cosmology Telescope (ACT) surveys, matched to optically selected clusters from the Dark Energy Survey Year 3 (DES). We construct two samples of clusters that are designed to be identical in SZ mass estimate and redshift but with the roundest vs. the most elliptical BCGs, which we expect to correspond to BCGs (and clusters) with major axes aligned along the line-of-sight vs. in the plane of the sky, respectively. We find that the optical richness of round-BCG clusters is ∼ 10% larger than that of elliptical-BCG clusters, in agreement with the expectation from projection effects and presenting the first such detection in data. The density profiles, however, are not in agreement with the expectation from projection effects: the 1-halo term (below 6 h^-1Mpc) of both the weak-lensing and galaxy density profiles are the same for the subsamples, contrary to previous studies based on X-ray selected clusters. In the 2-halo regime (above 6 h^-1Mpc), we find a significant excess of the elliptical-BCG cluster profiles compared to the round-BCG cluster profiles, which is the opposite of the expectation from numerical simulations. We hypothesize that the intrinsic shape of the BCG reflects not just the orientation angle, but also intrinsic properties of the cluster which can affect both the SZ signal and the amplitude of the 2-halo term.

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.

Using published simulations of the 10 yr Legacy Survey of Space and Time (LSST), we forecast its ability to determine the masses of individual main-belt asteroids (MBAs) through precise astrometry of any pairs of the ≈1.2 million known MBAs undergoing close gravitational encounters during the survey. The uncertainty σ _I on the impulse applied to a tracer asteroid by its deflector is derived from the Fisher matrix of the tracer’s astrometric data, including an azimuthal acceleration from the Yarkovsky effect as a free parameter for each tracer. If only LSST observations are available, the mean forecasted σ _I is 7 × 10 ^−6 m s ^−1 for MBAs at apparent magnitude m _V < 19.5, degrading ≈10× for m _V = 23. The forecasted median uncertainty on the mass of a deflector MBA is ≈3 × 10 ^−14 M _⊙ , with a wide range of variation depending on the (random) configurations of the closest encounters. All of these figures improve ≈ fivefold if strong pre-LSST astrometry is available. Use of LSST data will increase the number of MBAs with masses measured to 20% accuracy or better from the present ≈70 to between 200 and 550, depending on quality of pre-LSST data, if all MBAs have mass-to-reflected-light ratios (M/Ls) at the low end of the currently measured bodies. If high-end M/Ls are more common, 580–1100 bodies will attain a signal-to-noise ratio > 5, including nearly all bodies with absolute magnitude H < 10 and some as faint as H = 13. We forecast that ≈20 new Jupiter Trojans could also have masses measured at <20% accuracy. Tables of the measurable deflector MBAs and their tracers are provided.

Cosmic shear, galaxy clustering, and the abundance of massive halos each probe the large-scale structure of the Universe in complementary ways. We present cosmological constraints from the joint analysis of the three probes, building on the latest analyses of the lensing-informed abundance of clusters identified by the South Pole Telescope (SPT) and of the auto- and cross-correlation of galaxy position and weak lensing measurements (3 x 2pt) in the Dark Energy Survey (DES). We consider the cosmological correlation between the different tracers and we account for the systematic uncertainties that are shared between the large-scale lensing correlation functions and the small-scale lensing-based cluster mass calibration. Marginalized over the remaining Lambda cold dark matter (Lambda CDM) parameters (including the sum of neutrino masses) and 52 astrophysical modeling parameters, we measure Omega(m) = 0.300 +/- 0.017 and sigma(8) = 0.797 +/- 0.026. Compared to constraints from Planck primary cosmic microwave background (CMB) anisotropies, our constraints are only 15% wider with a probability to exceed of 0.22 (1.2 sigma) for the two-parameter difference. We further obtain S-8 equivalent to sigma(8)(Omega(m)/0.3)(0.5) = 0.796 +/- 0.013 which is lower than the Planck measurement at the 1.6 sigma level. The combined SPT cluster, DES 3 x 2pt, and Planck datasets mildly prefer a nonzero positive neutrino mass, with a 95% upper limit Sigma m(nu) < 0.25 eV on the sum of neutrino masses. Assuming a wCDM model, we constrain the dark energy equation of state parameter w = -1.15(-0.17)(+0.23) and when combining with Planck primary CMB anisotropies, we recover w = -1.20(-0.09)(+0.15), a 1.7 sigma difference with a cosmological constant. The precision of our results highlights the benefits of multiwavelength multiprobe cosmology and our analysis paves the way for upcoming joint analyses of next-generation datasets.

The explosion of high-precision astrometric data on main-belt asteroids (MBAs) enables new inferences on gravitational and non-gravitational forces present in this region. We estimate the size of MBA motions caused by mutual gravitational encounters with other MBAs that are either omitted from ephemeris models or have uncertain mass estimates. In other words, what is the typical Brownian motion among MBAs that cannot be predicted from the ephemeris, and therefore serves as noise on inferences from the MBAs? We estimate the RMS azimuthal shift σ_ϕ of this “Brownian noise” by numerical estimation of the distribution of impulse sizes and directions among known MBAs, combined with analytical propagation into future positional uncertainties. At current levels of asteroid-mass knowledge, σ_ϕ rises to ≈2 km or ≈1 mas over T=10 yr, increasing as T^3/2, large enough to degrade many inferences from Gaia and LSST MBA data. LSST data will, however, improve MBA mass knowledge enough to lower this Brownian uncertainty by ≥4×. Radial and vertical Brownian noise at T=10 yr are factors ≈7 and ≈45, respectively, lower than the azimuthal noise, and grow as T^3/2 and T^1/2. For full exploitation of Gaia and LSST MBA data, ephemeris models should include the ≈1000 largest asteroids as active bodies with free masses, even if not all are well constrained. This will correctly propagate the uncertainties from these 1000 sources' deflections into desired inferences. The RMS value of deflections from less-massive MBAs is then just σ_ϕ≈60 m or 30 μas, small enough to ignore until occultation-based position data become ubiquitously available for MBAs.

A proposed Vera C. Rubin Observatory deep-drilling microsurvey of the Kuiper Belt will investigate key properties of the distant solar system. Utilizing 30 hr of Rubin time across six 5 hr visits over 1 yr starting in summer 2026, the survey aims to discover and determine orbits for up to 730 Kuiper Belt objects (KBOs) to an r -magnitude of 27.5. These discoveries will enable precise characterization of the KBO size distribution, critical for understanding planetesimal formation. By aligning the survey field with NASA’s New Horizons spacecraft trajectory, the microsurvey will facilitate discoveries for the mission operating in the Kuiper Belt. Modeling based on the Outer Solar System Origin Survey predicts at least 12 distant KBOs observable with the New Horizons LOng Range Reconnaissance Imager (LORRI) and approximately three objects within 1 au of the spacecraft, allowing higher-resolution observations than Earth-based facilities. LORRI’s high-solar-phase-angle monitoring will reveal these objects’ surface properties and shapes, potentially identifying contact binaries and orbit-class surface correlations. The survey could identify a KBO suitable for a future spacecraft flyby. The survey’s size, depth, and cadence design will deliver transformative measurements of the Kuiper Belt’s size distribution and rotational properties across distance, size, and orbital class. The high stellar density in the survey field also offers synergies with transiting exoplanet studies.

We present a code that removes ∼90% of the variance in astrometric measurements caused by atmospheric turbulence, by using Gaussian process regression (GPR) to interpolate the turbulence field from the positions of stars measured by Gaia to the positions of arbitrary targets. This enables robust and routine accuracy of 1–3 milliarcsec on bright sources in single exposures of the Dark Energy Survey (DES) and the upcoming Legacy Survey of Space and Time (LSST). For the kernel of the GPR, we use the anisotropic correlation function of the turbulent displacement field, as measured directly from the Gaia reference stars, which should yield optimal accuracy if the displacement field is Gaussian. We test the code on 26 simulated LSST exposures and 604 real DES exposures in varying conditions. The average correlation function of the astrometric errors for separations < 1 ′ is used to estimate the variance of turbulence distortions. On average, for DES, the post-GPR variance is ∼12× smaller than the pre-GPR variance. Application of the GPR to LSST is hence equivalent, for brighter stars and asteroids, to having 12 Rubin observatories running simultaneously. The expected improvement in the root mean square (rms) of turbulence displacement errors is the square root of this value, ∼3.5. The post-GPR rms displacement decreases with the density of reference stars as ∼ n ⋆ − 0.5 for noiseless LSST simulations, and ∼ n ⋆ − 0.3 for DES data.

We explore the potential of an array of O(100) small fixed telescopes, aligned along a meridian and automated to measure millions of occultations of Gaia stars by minor planets, to constrain gravitational signatures from a "Planet X" mass in the outer solar system. The accuracy of center-of-mass tracking of occulters is limited by photon noise, uncertainties in asteroid shapes, and Gaia's astrometry of the occulted stars. Using both parametric calculations and survey simulations, we assess the total information obtainable from occultation measurements of main-belt asteroids (MBAs), Jovian Trojans, and trans-Neptunian objects (TNOs). We find that MBAs are the optimal target population due to their higher occultation rates and abundance of objects above Legacy Survey of Space and Time detection thresholds. A 10 yr survey of occultations by MBAs and Trojans using an array of 200 40 cm telescopes at 5 km separation would achieve 5 sigma sensitivity to the gravitational tidal field of a 5M(circle plus) Planet X at 800 au for >90% of potential sky locations. This configuration corresponds to an initial cost of approximate to$15 million. While the survey's sensitivity to tidal forces improves rapidly with increasing number of telescopes, sensitivity to a Planet X becomes limited by degeneracy with the uncertain masses of large moonless TNOs. The 200-telescope survey would additionally detect approximate to 1800 TNO occultations, providing detailed shape, size, and albedo information. It would also measure the Yarkovsky effect on many individual MBAs, measure masses of many asteroids involved in mutual gravitational deflections, and enable better searches for primordial black holes and departures from general relativity.

High-precision astrometric data on main-belt asteroids (MBAs) enable new inferences on the gravitational and nongravitational forces present in this region. We estimate the typical Brownian motion due to mutual encounters among MBAs that cannot be predicted from the ephemeris of larger bodies and therefore serves as noise on inferences from the MBAs. The rms azimuthal shift σ _ϕ of this “Brownian noise” is predicted using the distribution of known MBA orbits, combined with analytical propagation into future positional uncertainties—radial and vertical perturbations are much smaller. At current levels of asteroid-mass knowledge, we estimate that σ _ϕ accumulates to 2–9 km, or 1–5 mas over T = 10 yr, increasing as T ^3/2 . This must be taken into consideration for proper inferences from Gaia astrometry. Legacy Survey of Space and Time (LSST) data will, however, improve MBA mass knowledge enough to lower this Brownian uncertainty to 260–400 m, or 140–210 μ as, which in many but not all cases could be small enough to ignore in inferences using Gaia or LSST astrometry of MBAs. For full exploitation of Gaia and LSST MBA data, ephemeris models should include the ≈10,000 largest asteroids as active bodies with free masses, even if not all are well constrained. This will correctly propagate the uncertainties in these bodies’ gravity into desired inferences. The rms value of deflections from less massive MBAs is then just σ _ϕ ≈ 17–60 m, or 9–40 μ as, depending on the mean mass of the MBAs at fixed absolute magnitude small enough to ignore until occultation-based position data become ubiquitously available for MBAs.

Nonlinear cosmological fields like galaxy density and lensing convergence can be approximately related to Gaussian fields via analytic point transforms. The LogNormal (LN) transform has been widely used and is a simple example of a function that relates nonlinear fields to Gaussian fields. We consider more accurate general point-transformed Gaussian (GPTG) functions for such a mapping and apply them to convergence maps. We show that we can create maps that preserve the LN's ability to exactly match any desired power spectrum but go beyond LN by significantly improving the accuracy of the probability distribution function (PDF). With the aid of symbolic regression, we find a remarkably accurate GPTG function for convergence maps: its higher-order moments, scattering wavelet transform, Minkowski functionals, and peak counts match those of N-body simulations to the statistical uncertainty expected from tomographic lensing maps of the Rubin LSST 10 years survey. Our five-parameter function performs 2 to 5x better than the LogNormal in terms of accuracy of tested non-Gaussian summary statistics. Since baryonic feedback has a strong influence on very small scales, we restrict our study to scales larger than 7 arcmin. We demonstrate that the GPTG can robustly emulate variations in cosmological parameters due to the simplicity of the analytic transform. This opens up several possible applications, such as field-level inference, rapid covariance estimation, and other uses based on the generation of arbitrarily many maps with laptop-level computation capability.

For the 696 trans-Neptunian objects (TNOs) with absolute magnitudes 5.5 < H _r < 8.2 detected in the Dark Energy Survey, we characterize the relationships between their dynamical state and physical properties—namely H _r , indicating size; colors, indicating surface composition; and flux variation semiamplitude A , indicating asphericity and surface inhomogeneity. We seek “birth” physical distributions that can recreate these parameters in every dynamical class. We show that the observed colors of these TNOs are consistent with two Gaussian distributions in griz space, “near-infrared bright” (NIRB) and “near-infrared faint” (NIRF), presumably an inner and outer birth population, respectively. We find a model in which both the NIRB and NIRF H _r and A distributions are independent of current dynamical states, supporting their assignment as birth populations. All objects are consistent with a common rolling p ( H _r ), but NIRF objects are significantly more variable. Cold classicals (CCs) are purely NIRF, while hot classical (HC), scattered, and detached TNOs are consistent with ≈ 70% NIRB and the resonance NIRB fractions show significant variation. The NIRB components of the HCs and of some resonances have broader inclination distributions than the NIRFs, i.e. their current dynamics retains information about birth location. We find evidence for radial stratification within the birth NIRB population, in that HC NIRBs are on average redder than detached or scattered NIRBs; a similar effect distinguishes CCs from other NIRFs. We estimate total object counts and masses of each class within our H _r range. These results will strongly constrain models of the outer solar system.

We present simulation-based cosmological wcold dark matter (wCDM) inference using dark energy survey year 3 weak-lensing maps, via neural data compression of weak-lensing map summary statistics: power spectra, peak counts, and direct map-level compression/inference with convolutional neural networks (CNN). Using simulation-based inference, also known as likelihood-free or implicit inference, we use forward-modelled mock data to estimate posterior probability distributions of unknown parameters. This approach allows all statistical assumptions and uncertainties to be propagated through the forward-modelled mock data; these include sky masks, non-Gaussian shape noise, shape measurement bias, source galaxy clustering, photometric redshift uncertainty, intrinsic galaxy alignments, non-Gaussian density fields, neutrinos, and non-linear summary statistics. We include a series of tests to validate our inference results. This paper also describes the Gower Street simulation suite: 791 full-sky pkdgrav3 dark matter simulations, with cosmological model parameters sampled with a mixed active-learning strategy, from which we construct over 3000 mock dark energy survey lensing data sets. For wCDM inference, for which we allow -1<w<-(1)(3), our most constraining result uses power spectra combined with map-level (CNN) inference. Using gravitational lensing data only, this map-level combination gives Omega(m)=0.283(-0.027)(+0.020), S-8=0.804(-0.017)(+0.025), and w<-0.80 (with a 68 per cent credible interval); compared to the power spectrum inference, this is more than a factor of two improvement in dark energy parameter (Omega(DE),w) precision.

ABSTRACT We measure the impact of source galaxy clustering on higher order summary statistics of weak gravitational lensing data. By comparing simulated data with galaxies that either trace or do not trace the underlying density field, we show that this effect can exceed measurement uncertainties for common higher order statistics for certain analysis choices. We evaluate the impact on different weak lensing observables, finding that third moments and wavelet phase harmonics are more affected than peak count statistics. Using Dark Energy Survey (DES) Year 3 (Y3) data, we construct null tests for the source-clustering-free case, finding a p-value of p = 4 × 10−3 (2.6σ) using third-order map moments and p = 3 × 10−11 (6.5σ) using wavelet phase harmonics. The impact of source clustering on cosmological inference can be either included in the model or minimized through ad hoc procedures (e.g. scale cuts). We verify that the procedures adopted in existing DES Y3 cosmological analyses were sufficient to render this effect negligible. Failing to account for source clustering can significantly impact cosmological inference from higher order gravitational lensing statistics, e.g. higher order N-point functions, wavelet-moment observables, and deep learning or field-level summary statistics of weak lensing maps.

We present cosmological constraints from the sample of Type Ia supernovae (SN Ia) discovered during the full five years of the Dark Energy Survey (DES) Supernova Program. In contrast to most previous cosmological samples, in which SN are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being a SN Ia, we find 1635 DES SNe in the redshift range $0.100.5$ SNe compared to the previous leading compilation of Pantheon+, and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints we combine the DES supernova data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning $0.025

We present galaxy-galaxy lensing measurements using a sample of low surface brightness galaxies (LSBGs) drawn from the Dark Energy Survey Year 3 (Y3) data as lenses. LSBGs are diffuse galaxies with a surface brightness dimmer than the ambient night sky. These dark-matter-dominated objects are intriguing due to potentially unusual formation channels that lead to their diffuse stellar component. Given the faintness of LSBGs, using standard observational techniques to characterize their total masses proves challenging. Weak gravitational lensing, which is less sensitive to the stellar component of galaxies, could be a promising avenue to estimate the masses of LSBGs. Our LSBG sample consists of 23,790 galaxies separated into red and blue color types at $g-i\ge 0.60$ and $g-i< 0.60$, respectively. Combined with the DES Y3 shear catalog, we measure the tangential shear around these LSBGs and find signal-to-noise ratios of 6.67 for the red sample, 2.17 for the blue sample, and 5.30 for the full sample. We use the clustering redshifts method to obtain redshift distributions for the red and blue LSBG samples. Assuming all red LSBGs are satellites, we fit a simple model to the measurements and estimate the host halo mass of these LSBGs to be $\log(M_{\rm host}/M_{\odot}) = 12.98 ^{+0.10}_{-0.11}$. We place a 95% upper bound on the subhalo mass at $\log(M_{\rm sub}/M_{\odot})<11.51$. By contrast, we assume the blue LSBGs are centrals, and place a 95% upper bound on the halo mass at $\log(M_\mathrm{host}/M_\odot) < 11.84$. We find that the stellar-to-halo mass ratio of the LSBG samples is consistent with that of the general galaxy population. This work illustrates the viability of using weak gravitational lensing to constrain the halo masses of LSBGs.

Cross-correlation between weak lensing of the Cosmic Microwave Background (CMB) and weak lensing of galaxies offers a way to place robust constraints on cosmological and astrophysical parameters with reduced sensitivity to certain systematic effects affecting individual surveys. We measure the angular cross-power spectrum between the Atacama Cosmology Telescope (ACT) DR4 CMB lensing and the galaxy weak lensing measured by the Dark Energy Survey (DES) Y3 data. Our baseline analysis uses the CMB convergence map derived from ACT-DR4 and $\textit{Planck}$ data, where most of the contamination due to the thermal Sunyaev Zel'dovich effect is removed, thus avoiding important systematics in the cross-correlation. In our modelling, we consider the nuisance parameters of the photometric uncertainty, multiplicative shear bias and intrinsic alignment of galaxies. The resulting cross-power spectrum has a signal-to-noise ratio $= 7.1$ and passes a set of null tests. We use it to infer the amplitude of the fluctuations in the matter distribution ($S_8 \equiv \sigma_8 (\Omega_{\rm m}/0.3)^{0.5} = 0.782\pm 0.059$) with informative but well-motivated priors on the nuisance parameters. We also investigate the validity of these priors by significantly relaxing them and checking the consistency of the resulting posteriors, finding them consistent, albeit only with relatively weak constraints. This cross-correlation measurement will improve significantly with the new ACT-DR6 lensing map and form a key component of the joint 6x2pt analysis between DES and ACT.

We present the angular diameter distance measurement obtained with the Baryonic Acoustic Oscillation feature from galaxy clustering in the completed Dark Energy Survey, consisting of six years (Y6) of observations. We use the Y6 BAO galaxy sample, optimized for BAO science in the redshift range 0.6<z<1.2, with an effective redshift at z_ eff=0.85 and split into six tomographic bins. The sample has nearly 16 million galaxies over 4,273 square degrees. Our consensus measurement constrains the ratio of the angular distance to sound horizon scale to D_M(z_ eff)/r_d = 19.51±0.41 (at 68.3