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Scientists across disciplines often use data from the internet to conduct research, generating valuable insights about human behavior. However, as generative AI relying on massive text corpora becomes increasingly valuable, platforms have greatly restricted access to data through official channels. As a result, researchers will likely engage in more web scraping to collect data, introducing new challenges and concerns for researchers. This paper proposes a comprehensive framework for web scraping in social science research for U.S.-based researchers, examining the legal, ethical, institutional, and scientific factors that researchers should consider when scraping the web. We present an overview of the current regulatory environment impacting when and how researchers can access, collect, store, and share data via scraping. We then provide researchers with recommendations to conduct scraping in a scientifically legitimate and ethical manner. We aim to equip researchers with the relevant information to mitigate risks and maximize the impact of their research amidst this evolving data access landscape.

Modeling the intrinsic alignment (IA) of galaxies poses a challenge to weak lensing analyses. The Dark Energy Survey is expected to be less impacted by IA when limited 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 cosmic microwave background. Mitigating IA with sample selection, instead of flexible model choices, can reduce uncertainty in $S_8$ by a factor of 1.5., Comment: Data access available at https://jamiemccullough.github.io/data/blueshear/

The number density and redshift evolution of optically selected galaxy clusters offer an independent measurement of the amplitude of matter fluctuations, $S_8$. However, recent results have shown that clusters chosen by the redMaPPer algorithm show richness-dependent biases that affect the weak lensing signals and number densities of clusters, increasing uncertainty in the cluster mass calibration and reducing their constraining power. In this work, we evaluate an alternative cluster proxy, outskirt stellar mass, $M_{\textrm{out}}$, defined as the total stellar mass within a $[50,100]$ kpc envelope centered on a massive galaxy. This proxy exhibits scatter comparable to redMaPPer richness, $\lambda$, but is less likely to be subject to projection effects. We compare the Dark Energy Survey Year 3 redMaPPer cluster catalog with a $M_{\textrm{out}}$ selected cluster sample from the Hyper-Suprime Camera survey. We use weak lensing measurements to quantify and compare the scatter of $M_{\textrm{out}}$ and $\lambda$ with halo mass. Our results show $M_{\textrm{out}}$ has a scatter consistent with $\lambda$, with a similar halo mass dependence, and that both proxies contain unique information about the underlying halo mass. We find $\lambda$-selected samples introduce features into the measured $\Delta \Sigma$ signal that are not well fit by a log-normal scatter only model, absent in $M_{\textrm{out}}$ selected samples. Our findings suggest that $M_{\textrm{out}}$ offers an alternative for cluster selection with more easily calibrated selection biases, at least at the generally lower richnesses probed here. Combining both proxies may yield a mass proxy with a lower scatter and more tractable selection biases, enabling the use of lower mass clusters in cosmology. Finally, we find the scatter and slope in the $\lambda-M_{\textrm{out}}$ scaling relation to be $0.49 \pm 0.02$ and $0.38 \pm 0.09$., Comment: 22 pages, 8 figures, 4 tables, submitted to PRD

The world is evolving and so is the vocabulary used to discuss topics in speech. Analysing political speech data from more than 30 years requires the use of flexible topic models to uncover the latent topics and their change in prevalence over time as well as the change in the vocabulary of the topics. We propose the temporal Poisson factorisation (TPF) model as an extension to the Poisson factorisation model to model sparse count data matrices obtained based on the bag-of-words assumption from text documents with time stamps. We discuss and empirically compare different model specifications for the time-varying latent variables consisting either of a flexible auto-regressive structure of order one or a random walk. Estimation is based on variational inference where we consider a combination of coordinate ascent updates with automatic differentiation using batching of documents. Suitable variational families are proposed to ease inference. We compare results obtained using independent univariate variational distributions for the time-varying latent variables to those obtained with a multivariate variant. We discuss in detail the results of the TPF model when analysing speeches from 18 sessions in the U.S. Senate (1981-2016)., Comment: main paper: 19 pages (2 single figures, 3 double figures, 3 tables) appendix: 9 pages (3 quadruple figures, 1 table) references: 3 pages

Scaling political actors based on their individual characteristics and behavior helps profiling and grouping them as well as understanding changes in the political landscape. In this paper we introduce the Structural Text-Based Scaling (STBS) model to infer ideological positions of speakers for latent topics from text data. We expand the usual Poisson factorization specification for topic modeling of text data and use flexible shrinkage priors to induce sparsity and enhance interpretability. We also incorporate speaker-specific covariates to assess their association with ideological positions. Applying STBS to U.S. Senate speeches from Congress session 114, we identify immigration and gun violence as the most polarizing topics between the two major parties in Congress. Additionally, we find that, in discussions about abortion, the gender of the speaker significantly influences their position, with female speakers focusing more on women's health. We also see that a speaker's region of origin influences their ideological position more than their religious affiliation., Comment: 22 pages including 2.5 pages of references, 7 figures 20 additional pages of appendix (supplement), 5 figures, 2 tables

Beyond testing the current cosmological paradigm, cluster number counts can also be utilized to investigate the discrepancies currently affecting current cosmological measurements. In particular, cosmological studies based on cosmic shear and other large-scale structure probes routinely find a value of the amplitude of the fluctuations in the universe S8 smaller than the one inferred from the primary cosmic microwave background. In this work, we investigate this tension by measuring structure evolution across cosmic time as probed by the number counts of the massive halos with the first SRG/eROSITA All-Sky Survey cluster catalog in the Western Galactic Hemisphere complemented with the overlapping Dark Energy Survey Year-3, KiloDegree Survey, and Hyper Suprime-Cam data for weak lensing mass calibration, by implementing two different parameterizations and a model-agnostic method. In the first model, we measure the cosmic linear growth index as {\gamma} = 1.19 \pm 0.21, in tension with the standard value of {\gamma} = 0.55, but in good statistical agreement with other large-scale structures probes. The second model is a phenomenological scenario in which we rescale the linear matter power spectrum at low redshift to investigate a potential reduction of structure formation, providing similar results. Finally, in a third strategy, we consider a standard {\Lambda}CDM cosmology, but we separate the cluster catalog into five redshift bins, measuring the cosmological parameters in each and inferring the evolution of the structure formation, finding hints of a reduction. Interestingly, the S8 value inferred from eRASS1 cluster number counts, when we add a degree of freedom to the matter power spectrum, recovers the value inferred by cosmic shear studies.

Gravitational lensing magnification of Type Ia supernovae (SNe Ia) allows information to be obtained about the distribution of matter on small scales. In this paper, we derive limits on the fraction $\alpha$ of the total matter density in compact objects (which comprise stars, stellar remnants, small stellar groupings and primordial black holes) of mass $M > 0.03 M_{\odot}$ over cosmological distances. Using 1,532 SNe Ia from the Dark Energy Survey Year 5 sample (DES-SN5YR) combined with a Bayesian prior for the absolute magnitude $M$, we obtain $\alpha < 0.12$ at the 95\% confidence level after marginalisation over cosmological parameters, lensing due to large-scale structure, and intrinsic non-Gaussianity. Similar results are obtained using priors from the cosmic microwave background, baryon acoustic oscillations and galaxy weak lensing, indicating our results do not depend on the background cosmology. We argue our constraints are likely to be conservative (in the sense of the values we quote being higher than the truth), but discuss scenarios in which they could be weakened by systematics of the order of $\Delta \alpha \sim 0.04$, Comment: Submitted to MNRAS

We present constraints on the $f(R)$ gravity model using a sample of 1,005 galaxy clusters in the redshift range $0.25 - 1.78$ that have been selected through the thermal Sunyaev-Zel'dovich effect (tSZE) from South Pole Telescope (SPT) data and subjected to optical and near-infrared confirmation with the Multi-component Matched Filter (MCMF) algorithm. We employ weak gravitational lensing mass calibration from the Dark Energy Survey (DES) Year 3 data for 688 clusters at $z < 0.95$ and from the Hubble Space Telescope (HST) for 39 clusters with $0.6 < z < 1.7$. Our cluster sample is a powerful probe of $f(R)$ gravity, because this model predicts a scale-dependent enhancement in the growth of structure, which impacts the halo mass function (HMF) at cluster mass scales. To account for these modified gravity effects on the HMF, our analysis employs a semi-analytical approach calibrated with numerical simulations. Combining calibrated cluster counts with primary cosmic microwave background (CMB) temperature and polarization anisotropy measurements from the Planck2018 release, we derive robust constraints on the $f(R)$ parameter $f_{R0}$. Our results, $\log_{10} |f_{R0}| < -5.32$ at the 95 % credible level, are the tightest current constraints on $f(R)$ gravity from cosmological scales. This upper limit rules out $f(R)$-like deviations from general relativity that result in more than a $\sim$20 % enhancement of the cluster population on mass scales $M_\mathrm{200c}>3\times10^{14}M_\odot$., Comment: 21 pages, 6 figures, submitted to Phys. Rev. D

We present the detection and analysis of GRB 231115A, a candidate extragalactic magnetar giant flare (MGF) observed by Fermi/GBM and localized by INTEGRAL to the starburst galaxy M82. This burst exhibits distinctive temporal and spectral characteristics that align with known MGFs, including a short duration and a high peak energy. Gamma-ray analyses reveal significant insights into this burst, supporting conclusions already established in the literature: our time-resolved spectral studies provide further evidence that GRB 231115A is indeed a MGF. Significance calculations also suggest a robust association with M82, further supported by a high Bayes factor that minimizes the probability of chance alignment with a neutron star merger. Despite extensive follow-up efforts, no contemporaneous gravitational wave or radio emissions were detected. The lack of radio emission sets stringent upper limits on possible radio luminosity. Constraints from our analysis show no fast radio bursts (FRBs) associated with two MGFs. X-ray observations conducted post-burst by Swift/XRT and XMM/Newton provided additional data, though no persistent counterparts were identified. Our study underscores the importance of coordinated multi-wavelength follow-up and highlights the potential of MGFs to enhance our understanding of short GRBs and magnetar activities in the cosmos. Current MGF identification and follow-up implementation are insufficient for detecting expected counterparts; however, improvements in these areas may allow for the recovery of follow-up signals with existing instruments. Future advancements in observational technologies and methodologies will be crucial in furthering these studies.

Statistics that capture the directional dependence of the baryon distribution in the cosmic web enable unique tests of cosmology and astrophysical feedback. We use constrained oriented stacking of thermal Sunyaev-Zel'dovich (tSZ) maps to measure the anisotropic distribution of hot gas $2.5-40$ Mpc away from galaxy clusters embedded in massive filaments and superclusters. The cluster selection and orientation (at a scale of $\sim15$ Mpc) use Dark Energy Survey (DES) Year 3 data, while expanded tSZ maps from the Atacama Cosmology Telescope Data Release 6 enable a $\sim3\times$ more significant measurement of the extended gas compared to the technique's proof-of-concept. Decomposing stacks into cosine multipoles of order $m$, we detect a dipole ($m=1$) and quadrupole ($m=2$) at $8-10\sigma$, as well as evidence for $m=4$ signal at up to $6\sigma$, indicating sensitivity to late-time non-Gaussianity. We compare to the Cardinal simulations with spherical gas models pasted onto dark matter halos. The fiducial tSZ data can discriminate between two models that deplete pressure differently in low-mass halos (mimicking astrophysical feedback), preferring higher average pressure in extended structures. However, uncertainty in the amount of cosmic infrared background contamination reduces the constraining power. Additionally, we apply the technique to DES galaxy density and weak lensing to study for the first time their oriented relationships with tSZ. In the tSZ-to-lensing relation, averaged on 7.5 Mpc (transverse) scales, we observe dependence on redshift but not shape or radial distance. Thus, on large scales, the superclustering of gas pressure, galaxies, and total matter is coherent in shape and extent., Comment: 45 pages, 18 figures, submitted to ApJ

Using a sample of 2800 galaxy clusters identified in the Dark Energy Survey across the redshift range $0.20 < z < 0.60$, we characterize the hierarchical assembly of Bright Central Galaxies (BCGs) and the surrounding intracluster light (ICL). To quantify hierarchical formation we use the stellar mass - halo mass (SMHM) relation for the BCG+ICL system and incorporate the magnitude gap (M14), the difference in brightness between the BCG (measured within 30kpc) and 4th brightest cluster member galaxy within 0.5 $R_{200,c}$. The inclusion of M14, which traces BCG hierarchical growth, increases the slope and decreases the intrinsic scatter in the SMHM relation, highlighting that it is a latent variable within the BCG+ICL SMHM relation. Moreover, the correlation with M14 decreases at large radii from the BCG's centre. However, the stellar light within the BCG+ICL transition region (30kpc - 80kpc) most strongly correlates with the dark matter halo mass and has a statistically significant correlation with M14. As the light in the transition region and M14 are independent measurements, the transition region may grow as a result of the BCG's hierarchical two-phase formation. Additionally, as M14 and ICL result from hierarchical growth, we use a stacked sample and find that clusters with large M14 values are characterized by larger ICL and BCG+ICL fractions, which illustrates that the merger processes that build the BCG stellar mass also grow the ICL. Furthermore, this may suggest that M14 combined with the ICL fraction can be used as a method to identify dynamically relaxed clusters., Comment: 16 pages, 5 Figures, submitted to MNRAS on 8/30/2024

Using a long-standing conjecture from combinatorial group theory, we explore, from multiple angles, the challenges of finding rare instances carrying disproportionately high rewards. Based on lessons learned in the mathematical context defined by the Andrews-Curtis conjecture, we propose algorithmic improvements that can be relevant in other domains with ultra-sparse reward problems. Although our case study can be formulated as a game, its shortest winning sequences are potentially $10^6$ or $10^9$ times longer than those encountered in chess. In the process of our study, we demonstrate that one of the potential counterexamples due to Akbulut and Kirby, whose status escaped direct mathematical methods for 39 years, is stably AC-trivial., Comment: 39 pages, 18 figures, 1 table

It is well known that for analytic cost functions, gradient flow trajectories have finite length and converge to a single critical point. The gradient conjecture of R. Thom states that, again for analytic cost functions, whenever the gradient flow trajectory converges, the limit of its unit secants exists. One might think that already the convergence of the gradient flow trajectory to a critical point is enough to ensure that the unit secants have a limit, but this does not hold in general - the gradient conjecture is to a certain extend sharp. We provide a counterexample in case of the missing analyticity assumption, that is a smooth (non-analytic) cost function $f$, where the limit of unit secants does not exist. In addition, $f$ satisfies even a strong geometric length-distance convergence property., Comment: 6 pages, 1 figure

We prove new boundary regularity results for minimizers to the one-phase Alt-Caffarelli functional (also known as Bernoulli free boundary problem) in the case of continuous and H\"older-continuous boundary data. As an application, we use them to extend recent generic uniqueness and regularity results to families of continuous functions., Comment: 16 pages, 1 figure

The present state of cosmology is facing a crisis where there is a fundamental disagreement in measurements of the Hubble constant ($H_{0}$), with significant tension between the early and late universe methods. Type Ia supernovae (SNe Ia) are important to measuring $H_{0}$ through the astronomical distance ladder. However, there remains potential to better standardise SN Ia light curves by using known dependencies on host galaxy properties after the standard light curve width and colour corrections have been applied to the peak SN Ia luminosities. To explore this, we use the 5-year photometrically identified SNe Ia sample obtained by the Dark Energy Survey, along with host galaxy spectra obtained by the Australian Dark Energy Survey. Using host galaxy spectroscopy, we find a significant trend with the equivalent width (EW) of the [OII] $\lambda\lambda$ 3727, 29 doublet, a proxy for specific star formation rate, and Hubble residuals. We find that the correlation with [OII] EW is a powerful alternative to the commonly used mass step after initial light curve corrections. We applied our [OII] EW correction to a sample of 20 SN Ia hosted by calibrator galaxies observed using WiFeS, and examined the impact on both the SN Ia absolute magnitude and $H_{0}$. We then explored different [OII] EW corrections and found $H_{0}$ values ranging between $72.80$ to $73.28~\mathrm{km} \mathrm{s}^{-1} \mathrm{Mpc}^{-1}$. Notably, even after using an additional [OII] EW correction, the impact of host galaxy properties in standardising SNe Ia appears limited in reducing the current tension ($\sim$5$\sigma$) with the Cosmic Microwave Background result for $H_{0}$., Comment: 16 pages, 13 figures. Submitting to MNRAS

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.

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., Comment: 20 pages, 14 figures

Cosmological analyses with Type Ia Supernovae (SNe Ia) have traditionally been reliant on spectroscopy for both classifying the type of supernova and obtaining reliable redshifts to measure the distance-redshift relation. While obtaining a host-galaxy spectroscopic redshift for most SNe is feasible for small-area transient surveys, it will be too resource intensive for upcoming large-area surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time, which will observe on the order of millions of SNe. Here we use data from the Dark Energy Survey (DES) to address this problem with photometric redshifts (photo-z) inferred directly from the SN light-curve in combination with Gaussian and full p(z) priors from host-galaxy photo-z estimates. Using the DES 5-year photometrically-classified SN sample, we consider several photo-z algorithms as host-galaxy photo-z priors, including the Self-Organizing Map redshifts (SOMPZ), Bayesian Photometric Redshifts (BPZ), and Directional-Neighbourhood Fitting (DNF) redshift estimates employed in the DES 3x2 point analyses. With detailed catalog-level simulations of the DES 5-year sample, we find that the simulated w can be recovered within $\pm$0.02 when using SN+SOMPZ or DNF prior photo-z, smaller than the average statistical uncertainty for these samples of 0.03. With data, we obtain biases in w consistent with simulations within ~1$\sigma$ for three of the five photo-z variants. We further evaluate how photo-z systematics interplay with photometric classification and find classification introduces a subdominant systematic component. This work lays the foundation for next-generation fully photometric SNe Ia cosmological analyses., Comment: 19 pages, 9 figures. Submitting to MNRAS, comments welcome

We carried out long-term monitoring of the LIGO/Virgo/KAGRA binary black hole (BBH) merger candidate S230922g in search of electromagnetic emission from the interaction of the merger remnant with an embedding active galactic nuclei (AGN) accretion disk. Using a dataset primarily composed of wide-field imaging from the Dark Energy Camera (DECam) and supplemented by additional photometric and spectroscopic resources, we searched ~ 70% of the sky area probability for transient phenomena, and discovered 6 counterpart candidates. One especially promising candidate - AT 2023aagj - exhibited temporally varying asymmetric components in spectral broad line regions, a feature potentially indicative of an off-center event such as a BBH merger. This represents the first live search and multiwavelength, photometric, and spectroscopic monitoring of a GW BBH optical counterpart candidate in the disk of an AGN., Comment: 25 pages, 9 figures. Comments welcome

Finite mixture models are a useful statistical model class for clustering and density approximation. In the Bayesian framework finite mixture models require the specification of suitable priors in addition to the data model. These priors allow to avoid spurious results and provide a principled way to define cluster shapes and a preference for specific cluster solutions. A generic model estimation scheme for finite mixtures with a fixed number of components is available using Markov chain Monte Carlo (MCMC) sampling with data augmentation. The posterior allows to assess uncertainty in a comprehensive way, but component-specific posterior inference requires resolving the label switching issue. In this paper we focus on the application of Bayesian finite mixture models for clustering. We start with discussing suitable specification, estimation and inference of the model if the number of components is assumed to be known. We then continue to explain suitable strategies for fitting Bayesian finite mixture models when the number of components is not known. In addition, all steps required to perform Bayesian finite mixture modeling are illustrated on a data example where a finite mixture model of multivariate Gaussian distributions is fitted. Suitable prior specification, estimation using MCMC and posterior inference are discussed for this example assuming the number of components to be known as well as unknown.

We propose a Bayesian approach for model-based clustering of multivariate categorical data where variables are allowed to be associated within clusters and the number of clusters is unknown. The approach uses a two-layer mixture of finite mixtures model where the cluster distributions are approximated using latent class analysis models. A careful specification of priors with suitable hyperparameter values is crucial to identify the two-layer structure and obtain a parsimonious cluster solution. We outline the Bayesian estimation based on Markov chain Monte Carlo sampling with the telescoping sampler and describe how to obtain an identified clustering model by resolving the label switching issue. Empirical demonstrations in a simulation study using artificial data as well as a data set on low back pain indicate the good clustering performance of the proposed approach, provided hyperparameters are selected which induce sufficient shrinkage.

We present the first successful trapping of single erbium atoms in an array of optical tweezers. Using a single narrow-line optical transition, we achieve deep cooling for direct tweezer loading, pairwise ejection, and continous imaging without additional recoil suppression techniques. Our tweezer wavelength choice enables us to reach the magic trapping condition by tuning the ellipticity of the trapping light. Additionally, we implement an ultrafast high-fidelity fluorescence imaging scheme using a broad transition, allowing time-resolved study of the tweezer population dynamics from many to single atoms during light-assisted collisions. In particular, we extract a pair-ejection rate that qualitatively agrees with the semiclassical predictions by the Gallagher-Pritchard model. This work represents a promising starting point for the exploration of erbium as a powerful resource for quantum simulation in optical tweezers.

We present the joint tomographic analysis of galaxy-galaxy lensing and galaxy clustering in harmonic space, using galaxy catalogues from the first three years of observations by the Dark Energy Survey (DES Y3). We utilise the redMaGiC and MagLim catalogues as lens galaxies and the METACALIBRATION catalogue as source galaxies. The measurements of angular power spectra are performed using the pseudo-$C_\ell$ method, and our theoretical modelling follows the fiducial analyses performed by DES Y3 in configuration space, accounting for galaxy bias, intrinsic alignments, magnification bias, shear magnification bias and photometric redshift uncertainties. We explore different approaches for scale cuts based on non-linear galaxy bias and baryonic effects contamination. Our fiducial covariance matrix is computed analytically, accounting for mask geometry in the Gaussian term, and including non-Gaussian contributions and super-sample covariance terms. To validate our harmonic space pipelines and covariance matrix, we used a suite of 1800 log-normal simulations. We also perform a series of stress tests to gauge the robustness of our harmonic space analysis. In the $\Lambda$CDM model, the clustering amplitude $S_8 =\sigma_8(\Omega_m/0.3)^{0.5}$ is constrained to $S_8 = 0.704\pm 0.029$ and $S_8 = 0.753\pm 0.024$ ($68\%$ C.L.) for the redMaGiC and MagLim catalogues, respectively. For the $w$CDM, the dark energy equation of state is constrained to $w = -1.28 \pm 0.29$ and $w = -1.26^{+0.34}_{-0.27}$, for redMaGiC and MagLim catalogues, respectively. These results are compatible with the corresponding DES Y3 results in configuration space and pave the way for harmonic space analyses using the DES Y6 data., Comment: To be submitted to MNRAS

Star-galaxy separation is a crucial step in creating target catalogues for extragalactic spectroscopic surveys. A classifier biased towards inclusivity risks including spurious stars, wasting fibre hours, while a more conservative classifier might overlook galaxies, compromising completeness and hence survey objectives. To avoid bias introduced by a training set in supervised methods, we employ an unsupervised machine learning approach. Using photometry from the Wide Area VISTA Extragalactic Survey (WAVES)-Wide catalogue comprising 9-band $u-K_s$ data, we create a feature space with colours, fluxes, and apparent size information extracted by ${\rm P{\scriptsize RO} F{\scriptsize OUND}}$. We apply the non-linear dimensionality reduction method UMAP (Uniform Manifold Approximation and Projection) combined with the classifier ${\rm{\scriptsize HDBSCAN}}$ to classify stars and galaxies. Our method is verified against a baseline colour and morphological method using a truth catalogue from Gaia, SDSS, GAMA, and DESI. We correctly identify 99.72% of galaxies within the AB magnitude limit of $Z = 21.2$, with an F1 score of 0.9970 across the entire ground truth sample, compared to 0.9871 from the baseline method. Our method's higher purity (0.9966) compared to the baseline (0.9780) increases efficiency, identifying 11% fewer galaxy or ambiguous sources, saving approximately 70,000 fibre hours on the 4MOST instrument. We achieve reliable classification statistics for challenging sources including quasars, compact galaxies, and low surface brightness galaxies, retrieving 95.1%, 84.6%, and 99.5% of them respectively. Angular clustering analysis validates our classifications, showing consistency with expected galaxy clustering, regardless of the baseline classification., Comment: Submitted to MNRAS; 17 pages, 11 figures

For mobility exponents $n \in (2,3)$, we prove existence of strictly positive solutions to stochastic thin-film equations with singular effective interface potential and Stratonovich-type lower-order terms. With the perspective of using these solutions in Part II to construct surface-tension-energy dissipating solutions to stochastic thin-film equations with compactly supported initial data, for which finite speed of propagation is shown in future work, we establish decay estimates on the sum of surface-tension energy and effective interface potential -- without relying on further functionals involving initial data. Besides an extension of earlier techniques used in the case $n=2$ and a refinement of oscillation estimates for discrete solutions, the main analytical novelty of this paper is a discretization method which shows nonnegativity for a finite-element counterpart of the integral $\int_{\mathcal O} (u^{n-2}u_{x})_x u_{xx} dx$ under periodic boundary conditions in the parameter regime $n \in (2,3)$. This nonnegativity property serves to control It\^o-correction terms in the estimate for the decay of the surface-tension energy. This way, it is the key to obtain the desired decay estimates for the sum of surface-tension energy and effective interface potential which permit to establish the singular limit of vanishing effective interface potential in Part II., Comment: 57 pages

We prove existence of martingale solutions to a class of stochastic thin-film equations for mobility exponents $n \in (2,3)$ and compactly supported initial data. With the perspective to study free-boundary problems related to stochastic thin-film equations in future work, we start from the surface-tension driven stochastic thin-film equation with Stratonovich noise and exploit the regime of coefficients in front of the Stratonovich correction term (which is of porous-media-type) for which energy dissipation can be established. By Bernis inequalities, third order spatial derivatives of appropriate powers of the solution are controlled. Analytically, we rely on approximation with $\mathbb{P}$-almost surely strictly positive solutions and compactness methods based on energy-entropy estimates as well as martingale identification techniques., Comment: 38 pages

The residuals of the distance moduli of Type Ia supernovae (SN Ia) relative to a Hubble diagram fit contain information about the inhomogeneity of the universe, due to weak lensing magnification by foreground matter. By correlating the residuals of the Dark Energy Survey Year 5 SN Ia sample (DES-SN5YR) with extra-galactic foregrounds from the DES Y3 Gold catalog, we detect the presence of lensing at $6.0 \sigma$ significance. This is the first detection with a significance level above $5\sigma$. Constraints on the effective mass-to-light ratios and radial profiles of dark-matter haloes surrounding individual galaxies are also obtained. We show that the scatter of SNe Ia around the Hubble diagram is reduced by modifying the standardisation of the distance moduli to include an easily calculable de-lensing (i.e., environmental) term. We use the de-lensed distance moduli to recompute cosmological parameters derived from SN Ia, finding in Flat $w$CDM a difference of $\Delta \Omega_{\rm M} = +0.036$ and $\Delta w = -0.056$ compared to the unmodified distance moduli, a change of $\sim 0.3\sigma$. We argue that our modelling of SN Ia lensing will lower systematics on future surveys with higher statistical power. We use the observed dispersion of lensing in DES-SN5YR to constrain $\sigma_8$, but caution that the fit is sensitive to uncertainties at small scales. Nevertheless, our detection of SN Ia lensing opens a new pathway to study matter inhomogeneity that complements galaxy-galaxy lensing surveys and has unrelated systematics., Comment: Submitted to MNRAS

We report constraints on a variety of non-standard cosmological models using the full 5-year photometrically-classified type Ia supernova sample from the Dark Energy Survey (DES-SN5YR). Both Akaike Information Criterion (AIC) and Suspiciousness calculations find no strong evidence for or against any of the non-standard models we explore. When combined with external probes, the AIC and Suspiciousness agree that 11 of the 15 models are moderately preferred over Flat-$\Lambda$CDM suggesting additional flexibility in our cosmological models may be required beyond the cosmological constant. We also provide a detailed discussion of all cosmological assumptions that appear in the DES supernova cosmology analyses, evaluate their impact, and provide guidance on using the DES Hubble diagram to test non-standard models. An approximate cosmological model, used to perform bias corrections to the data holds the biggest potential for harbouring cosmological assumptions. We show that even if the approximate cosmological model is constructed with a matter density shifted by $\Delta\Omega_m\sim0.2$ from the true matter density of a simulated data set the bias that arises is sub-dominant to statistical uncertainties. Nevertheless, we present and validate a methodology to reduce this bias., Comment: Published to MNRAS on 20 August 2024; v2 updates to the accepted version

Narrowband galaxy surveys have recently gained interest as a promising method to achieve the necessary accuracy on the photometric redshift estimate of individual galaxies for stage-IV cosmological surveys. One key advantage is the ability to provide higher spectral resolution information about galaxies that should allow a more accurate and precise estimation of galaxy stellar population properties. However, the impact of adding narrow-band photometry on the stellar population properties estimate is largely unexplored. The scope of this work is two-fold: on one side, leveraging the predictive power of broad-band and narrow-band data to infer galaxy physical properties such as stellar masses, ages, star formation rates and metallicities. On the other hand, evaluating the improvement of performance in estimating galaxy properties when we use narrow-band data instead of broad-band. In this work we measure the stellar population properties of a sample of galaxies in the COSMOS field for which both narrowband and broadband data are available. In particular, we employ narrowband data from PAUS and broad-band data from CFHTLS. We use two different spectral energy distribution fitting codes to measure galaxy properties, namely CIGALE and Prospector. We find that the increased spectral resolution of narrow-band photometry does not yield a substantial improvement on constraining galaxy properties using spectral energy distribution fitting. Still we find that we obtain a more diverse distribution of metallicities and dust optical depths with cigale when employing the narrowband data. The effect is not as prominent as expected, which we relate this to the low narrowband SNR of a majority of the galaxies, the respective drawbacks of both codes as well as the coverage only in the optical regime. The measured properties are afterwards compared to the COSMOS2020 catalogue, showing good agreement., Comment: Published in A&A. 18 pages, 16 figures, 2 tables

We present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years (Y3) of the Dark Energy Survey (DES). We implement: 1) second and third moments; 2) wavelet phase harmonics; 3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven $\nu w$CDM cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the Figure of Merit $\textrm{FoM}(S_8, \Omega_{\textrm{m}})$ is improved by 70 percent ($\Lambda$CDM) and 90 percent ($w$CDM). When all the summary statistics are combined, we achieve a 2 percent constraint on the amplitude of fluctuations parameter $S_8 \equiv \sigma_8 (\Omega_{\textrm{m}}/0.3)^{0.5}$, obtaining $S_8 = 0.794 \pm 0.017$ ($\Lambda$CDM) and $S_8 = 0.817 \pm 0.021$ ($w$CDM). The constraints from different statistics are shown to be internally consistent (with a $p$-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the DES Y3 data, finding good consistency; we also compare with results from external datasets, such as \planck{} constraints from the Cosmic Microwave Background, finding statistical agreement, with discrepancies no greater than $<2.2\sigma$., Comment: 24 pages, 13 figures, to be submitted to PRD. Comments welcome!

Reverberation mapping is the leading technique used to measure direct black hole masses outside of the local Universe. Additionally, reverberation measurements calibrate secondary mass-scaling relations used to estimate single-epoch virial black hole masses. The Australian Dark Energy Survey (OzDES) conducted one of the first multi-object reverberation mapping surveys, monitoring 735 AGN up to $z\sim4$, over 6 years. The limited temporal coverage of the OzDES data has hindered recovery of individual measurements for some classes of sources, particularly those with shorter reverberation lags or lags that fall within campaign season gaps. To alleviate this limitation, we perform a stacking analysis of the cross-correlation functions of sources with similar intrinsic properties to recover average composite reverberation lags. This analysis leads to the recovery of average lags in each redshift-luminosity bin across our sample. We present the average lags recovered for the H$\beta$, Mg II and C IV samples, as well as multi-line measurements for redshift bins where two lines are accessible. The stacking analysis is consistent with the Radius-Luminosity relations for each line. Our results for the H$\beta$ sample demonstrate that stacking has the potential to improve upon constraints on the $R-L$ relation, which have been derived only from individual source measurements until now., Comment: 20 pages, 15 figures. Accepted by MNRAS

The forward modelling of galaxy surveys has recently gathered interest as one of the primary methods to achieve the required precision on the estimate of the redshift distributions for stage IV surveys. One of the key aspects of forward modelling a galaxy survey is the connection between the physical properties drawn from a galaxy population model and the intrinsic SEDs, achieved through SPS codes (e.g. FSPS). However, SPS requires a large number of detailed assumptions on the constituents of galaxies, for which the model choice or parameter values are currently uncertain. In this work, we perform a sensitivity study of the impact that the variations of the SED modelling choices have on the mean and scatter of the tomographic galaxy redshift distributions. We assumed the Prospector beta model as the fiducial input galaxy population model and used its SPS parameters to build 9 bands magnitudes of a fiducial sample of galaxies. We then built samples of galaxy magnitudes by varying one SED modelling choice at a time. We modelled the colour redshift relation of these galaxy samples using the SOM approach. We placed galaxies in the SOM cells according to their observed frame colours and used their cell assignment to build colour selected tomographic bins. Finally, we compared each variant's binned redshift distributions against the estimates obtained for the fiducial model. We find that the SED components related to the IMF, AGNs, gas physics, and the attenuation law substantially bias the mean and the scatter of the tomographic redshift distributions with respect to those estimated with the fiducial model. Regardless of the applied stellar mass function based re-weighting strategy, the bias in the mean and the scatter of the tomographic redshift distributions are greater than the precision requirements set by next-generation Stage IV galaxy surveys, such as LSST and Euclid., Comment: Accepted for publication in A&A. 29 pages, 12 figures

The foundational role of datasets in defining the capabilities of deep learning models has led to their rapid proliferation. At the same time, published research focusing on the process of dataset development for environment perception in automated driving has been scarce, thereby reducing the applicability of openly available datasets and impeding the development of effective environment perception systems. Sensor-based, mapless automated driving is one of the contexts where this limitation is evident. While leveraging real-time sensor data, instead of pre-defined HD maps promises enhanced adaptability and safety by effectively navigating unexpected environmental changes, it also increases the demands on the scope and complexity of the information provided by the perception system. To address these challenges, we propose a scenario- and capability-based approach to dataset development. Grounded in the principles of ISO 21448 (safety of the intended functionality, SOTIF), extended by ISO/TR 4804, our approach facilitates the structured derivation of dataset requirements. This not only aids in the development of meaningful new datasets but also enables the effective comparison of existing ones. Applying this methodology to a broad range of existing lane detection datasets, we identify significant limitations in current datasets, particularly in terms of real-world applicability, a lack of labeling of critical features, and an absence of comprehensive information for complex driving maneuvers., Comment: Accepted to be published at the 2024 35th IEEE Intelligent Vehicles Symposium (IV), Jeju Island, Korea, June 2 - 5, 2024

While Bayesian inference techniques are standard in cosmological analyses, it is common to interpret resulting parameter constraints with a frequentist intuition. This intuition can fail, e.g. when marginalizing high-dimensional parameter spaces onto subsets of parameters, because of what has come to be known as projection effects or prior volume effects. We present the method of Informed Total-Error-Minimizing (ITEM) priors to address this. An ITEM prior is a prior distribution on a set of nuisance parameters, e.g. ones describing astrophysical or calibration systematics, intended to enforce the validity of a frequentist interpretation of the posterior constraints derived for a set of target parameters, e.g. cosmological parameters. Our method works as follows: For a set of plausible nuisance realizations, we generate target parameter posteriors using several different candidate priors for the nuisance parameters. We reject candidate priors that do not accomplish the minimum requirements of bias (of point estimates) and coverage (of confidence regions among a set of noisy realizations of the data) for the target parameters on one or more of the plausible nuisance realizations. Of the priors that survive this cut we select the ITEM prior as the one that minimizes the total error of the marginalized posteriors of the target parameters. As a proof of concept, we apply our method to the Density Split Statistics (DSS) measured in Dark Energy Survey Year 1 data. We demonstrate that the ITEM priors substantially reduce prior volume effects that otherwise arise and allow sharpened yet robust constraints on the parameters of interest., Comment: 14 pages + appendix Submitted to A&A Comments are welcome!

Extracting precise cosmology from weak lensing surveys requires modelling the non-linear matter power spectrum, which is suppressed at small scales due to baryonic feedback processes. However, hydrodynamical galaxy formation simulations make widely varying predictions for the amplitude and extent of this effect. We use measurements of Dark Energy Survey Year 3 weak lensing (WL) and Atacama Cosmology Telescope DR5 kinematic Sunyaev-Zel'dovich (kSZ) to jointly constrain cosmological and astrophysical baryonic feedback parameters using a flexible analytical model, `baryonification'. First, using WL only, we compare the $S_8$ constraints using baryonification to a simulation-calibrated halo model, a simulation-based emulator model and the approach of discarding WL measurements on small angular scales. We find that model flexibility can shift the value of $S_8$ and degrade the uncertainty. The kSZ provides additional constraints on the astrophysical parameters and shifts $S_8$ to $S_8=0.823^{+0.019}_{-0.020}$, a higher value than attained using the WL-only analysis. We measure the suppression of the non-linear matter power spectrum using WL + kSZ and constrain a mean feedback scenario that is more extreme than the predictions from most hydrodynamical simulations. We constrain the baryon fractions and the gas mass fractions and find them to be generally lower than inferred from X-ray observations and simulation predictions. We conclude that the WL + kSZ measurements provide a new and complementary benchmark for building a coherent picture of the impact of gas around galaxies across observations.

The joint probability distribution of matter overdensity and galaxy counts in cells is a powerful probe of cosmology, and the extent to which variance in galaxy counts at fixed matter density deviates from Poisson shot noise is not fully understood. The lack of informed bounds on this stochasticity is currently the limiting factor in constraining cosmology with the galaxy-matter PDF. We investigate stochasticity in the conditional distribution of galaxy counts at fixed matter density and present a halo occupation distribution (HOD)-based approach for obtaining plausible ranges for stochasticity parameters. To probe the high-dimensional space of possible galaxy-matter connections, we derive HODs which conserve linear galaxy bias and number density to produce redMaGiC-like galaxy catalogs within the AbacusSummit suite of N-body simulations. We study the impact of individual HOD parameters and cosmology on stochasticity and perform a Monte Carlo search in HOD parameter space, subject to the constraints on bias and density. In mock catalogs generated by the selected HODs, shot noise in galaxy counts spans both sub-Poisson and super-Poisson values, ranging from 80% to 133% of Poisson variance at mean matter density. Nearly all derived HODs show a positive relationship between local matter density and stochasticity. For galaxy catalogs with higher stochasticity, quadratic galaxy bias is required for an accurate description of the conditional PDF of galaxy counts at fixed matter density. The presence of galaxy assembly bias also substantially extends the range of stochasticity in the super-Poisson direction. This HOD-based approach leverages degrees of freedom in the galaxy-halo connection to obtain informed bounds on model nuisance parameters and can be adapted to other parametrizations of stochasticity, in particular to motivate prior ranges for cosmological analyses., Comment: Submitted to Astronomy and Astrophysics

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

We present cosmological results from the measurement of baryon acoustic oscillations (BAO) in galaxy, quasar and Lyman-$\alpha$ forest tracers from the first year of observations from the Dark Energy Spectroscopic Instrument (DESI), to be released in the DESI Data Release 1. DESI BAO provide robust measurements of the transverse comoving distance and Hubble rate, or their combination, relative to the sound horizon, in seven redshift bins from over 6 million extragalactic objects in the redshift range $0.1-1$ and $w_a<0$. This preference is 2.6$\sigma$ for the DESI+CMB combination, and persists or grows when SN~Ia are added in, giving results discrepant with the $\Lambda$CDM model at the $2.5\sigma$, $3.5\sigma$ or $3.9\sigma$ levels for the addition of Pantheon+, Union3, or DES-SN5YR datasets respectively. For the flat $\Lambda$CDM model with the sum of neutrino mass $\sum m_\nu$ free, combining the DESI and CMB data yields an upper limit $\sum m_\nu < 0.072$ $(0.113)$ eV at 95% confidence for a $\sum m_\nu>0$ $(\sum m_\nu>0.059)$ eV prior. These neutrino-mass constraints are substantially relaxed in models beyond $\Lambda$CDM. [Abridged.], Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers). Typos corrected and a new figure and discussion added to Appendix A

We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman-$\alpha$ (Ly$\alpha$) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectroscopic Instrument (DESI). Our analysis uses over $420\,000$ Ly$\alpha$ forest spectra and their correlation with the spatial distribution of more than $700\,000$ quasars. An essential facet of this work is the development of a new analysis methodology on a blinded dataset. We conducted rigorous tests using synthetic data to ensure the reliability of our methodology and findings before unblinding. Additionally, we conducted multiple data splits to assess the consistency of the results and scrutinized various analysis approaches to confirm their robustness. For a given value of the sound horizon ($r_d$), we measure the expansion at $z_{\rm eff}=2.33$ with 2\% precision, $H(z_{\rm eff}) = (239.2 \pm 4.8) (147.09~{\rm Mpc} /r_d)$ km/s/Mpc. Similarly, we present a 2.4\% measurement of the transverse comoving distance to the same redshift, $D_M(z_{\rm eff}) = (5.84 \pm 0.14) (r_d/147.09~{\rm Mpc})$ Gpc. Together with other DESI BAO measurements at lower redshifts, these results are used in a companion paper to constrain cosmological parameters., Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers). Minor changes in v4, version accepted for publication in JCAP

We present the DESI 2024 galaxy and quasar baryon acoustic oscillations (BAO) measurements using over 5.7 million unique galaxy and quasar redshifts in the range 0.1

Assessing the similarity of matrices is valuable for analyzing the extent to which data sets exhibit common features in tasks such as data clustering, dimensionality reduction, pattern recognition, group comparison, and graph analysis. Methods proposed for comparing vectors, such as cosine similarity, can be readily generalized to matrices. However, this approach usually neglects the inherent two-dimensional structure of matrices. Here, we propose singular angle similarity (SAS), a measure for evaluating the structural similarity between two arbitrary, real matrices of the same shape based on singular value decomposition. After introducing the measure, we compare SAS with standard measures for matrix comparison and show that only SAS captures the two-dimensional structure of matrices. Further, we characterize the behavior of SAS in the presence of noise and as a function of matrix dimensionality. Finally, we apply SAS to two use cases: square non-symmetric matrices of probabilistic network connectivity, and non-square matrices representing neural brain activity. For synthetic data of network connectivity, SAS matches intuitive expectations and allows for a robust assessment of similarities and differences. For experimental data of brain activity, SAS captures differences in the structure of high-dimensional responses to different stimuli. We conclude that SAS is a suitable measure for quantifying the shared structure of matrices with arbitrary shape., Comment: 12 pages, 6 figures

We present simulation-based cosmological $w$CDM 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 PKDGRAV dark matter simulations, with cosmological model parameters sampled with a mixed active-learning strategy, from which we construct over 3000 mock DES lensing data sets. For $w$CDM inference, for which we allow $-1

The evolution of the cluster mass function traces the growth of the linear density perturbations and can be utilized for constraining the parameters of cosmological and alternative gravity models. In this context, we present new constraints on potential deviations from general relativity by investigating the Hu-Sawicki parametrization of the f(R) gravity with the first SRG-eROSITA All-Sky Survey (eRASS1) cluster catalog in the Western Galactic Hemisphere in combination with the overlapping Dark Energy Survey Year 3, KiloDegree Survey and Hyper Supreme Camera data for weak lensing mass calibration. For the first time, we present constraints obtained from cluster abundances only. When we consider massless neutrinos, we find a strict upper limit of log |fR0| < -4.31 at 95% confidence level. Massive neutrinos suppress structure growth at small scales, and thus have the opposite effect of f(R) gravity. We consequently investigate the joint fit of the mass of the neutrinos with the modified gravity parameter. We obtain log |fR0| < -4.12 jointly with \sum m_\nu < 0.44 e.V. at 95% confidence level, tighter than the limits in the literature utilizing cluster counts only. At log |fR0|= - 6, the number of clusters is not significantly changed by the theory. Consequently, we do not find any statistical deviation from general relativity from the study of eRASS1 cluster abundance. Deeper surveys with eROSITA, increasing the number of detected clusters, will further improve constraints on log |fR0| and investigate alternative gravity theories., Comment: 13 pages, 6 figures, submitted to A&A

Number counts of galaxy clusters across redshift are a powerful cosmological probe, if a precise and accurate reconstruction of the underlying mass distribution is performed -- a challenge called mass calibration. With the advent of wide and deep photometric surveys, weak gravitational lensing by clusters has become the method of choice to perform this measurement. We measure and validate the weak gravitational lensing (WL) signature in the shape of galaxies observed in the first 3 years of the DES Y3 caused by galaxy clusters selected in the first all-sky survey performed by SRG/eROSITA. These data are then used to determine the scaling between X-ray photon count rate of the clusters and their halo mass and redshift. We empirically determine the degree of cluster member contamination in our background source sample. The individual cluster shear profiles are then analysed with a Bayesian population model that self-consistently accounts for the lens sample selection and contamination, and includes marginalization over a host of instrumental and astrophysical systematics. To quantify the accuracy of the mass extraction of that model, we perform mass measurements on mock cluster catalogs with realistic synthetic shear profiles. This allows us to establish that hydro-dynamical modelling uncertainties at low lens redshifts ($z<0.6$) are the dominant systematic limitation. At high lens redshift the uncertainties of the sources' photometric redshift calibration dominate. With regard to the X-ray count rate to halo mass relation, we constrain all its parameters. This work sets the stage for a joint analysis with the number counts of eRASS1 clusters to constrain a host of cosmological parameters. We demonstrate that WL mass calibration of galaxy clusters can be performed successfully with source galaxies whose calibration was performed primarily for cosmic shear experiments., Comment: 27 pages, 18 figures, 2 appendices, submitted to A\&A

The cluster mass function traces the growth of linear density perturbations and provides valuable insights into the growth of structures, the nature of dark matter, and the cosmological parameters governing the Universe. The primary science goal of eROSITA, on board the {\it Spectrum Roentgen Gamma (SRG)} mission, launched in 2019, is to constrain cosmology through the evolution of cluster mass function. In this paper, we present the cosmological constraints obtained from 5259 clusters of galaxies detected over an area of 12791~deg$^2$ in the Western Galactic Hemisphere of the eROSITA's first All-Sky Survey (eRASS1). The common footprint region between the eROSITA Survey and DES, KiDS, and HSC surveys is used for calibration of the scaling between X-ray count rate and their total mass through measurements of their weak gravitational lensing signal. eRASS1 cluster abundances constrain the $\Lambda$CDM parameters, which are the energy density of the total matter to $\Omega_{\mathrm{m}}=0.29^{+0.01}_{-0.02}$, and the normalization of the density fluctuations to $\sigma_8=0.88\pm0.02$ and their combination yields $S_8=\sigma_8 (\Omega_\mathrm{m} / 0.3)^{0.5}=0.86\pm0.01$, consistent and at a similar precision with the state-of-the-art CMB measurements. eRASS1 cosmological experiment places a most stringent upper limit on the summed masses of left-handed light neutrinos to $\sum m_\nu< 0.22\mathrm{~eV}$ (95\% confidence interval). Combining eRASS1 cluster abundance measurements with CMB and ground-based neutrino oscillation experiments, we measure the summed neutrino masses to be $\sum m_\nu=0.08_{-0.02}^{+0.03}\mathrm{~eV}$ or $\sum m_\nu=0.12_{-0.01}^{+0.03}\mathrm{~eV}$ depending on the mass hierarchy scenario for neutrino eigenstates. eRASS1 cluster abundances significantly improve the constraints on the dark energy equation of state parameter to $w=-1.12\pm0.12$. (ABRIDGED), Comment: 41 pages, 22 figures, Accepted for publication by A&A

We aim to participate in the calibration of the X-ray photon count rate to halo mass scaling relation of galaxy clusters selected in the first eROSITA All-Sky Survey on the Western Galactic Hemisphere (eRASS1) using KiDS-1000 weak-lensing (WL) data. We measure the radial shear profiles around eRASS1 galaxy clusters using background galaxies in KiDS-1000, as well as the cluster member contamination. Furthermore we provide consistency checks with the other stage-III WL surveys who take part in the eRASS1 mass calibration, DES Y3 and HSC-Y3. We determine the cluster member contamination of eRASS1 clusters present in KiDS-1000 based on source number density profiles, where we account for the obscuration caused by cluster galaxies. The extracted shear profiles, together with the contamination model and the lens sample selection, are then analysed through a Bayesian population model. We calibrate the WL mass bias parameter by analysing realistic synthetic shear profiles from mock cluster catalogues. Our consistency checks between KiDS-1000 and DES Y3 & HSC-Y3 include the comparison of contamination-corrected density contrast profiles employing the union of background sources around common clusters, as well as the individual scaling relation results. We present a global contamination model for eRASS1 clusters in KiDS-1000 and the calibration results of the X-ray photon count rate to halo mass relation. The results of the WL mass bias parameter show that the uncertainty of the multiplicative shear bias dominates the systematic error budget at low clusters redshifts while the uncertainty of our contamination model does at high ones. The cross-checks between the three WL surveys show that they are statistically consistent with each other. This enables for the first time cosmological constraints from clusters calibrated by three state-of-the-art WL surveys. (abridged), Comment: 22 pages, 23 figures

Clusters of galaxies can be used as powerful probes to study astrophysical processes on large scales, test theories of the growth of structure, and constrain cosmological models. The driving science goal of the SRG/eROSITA All-Sky Survey (eRASS) is to assemble a large sample of X-ray-selected clusters with a well-defined selection function to determine the evolution of the mass function and, hence, the cosmological parameters. We present here a catalog of 12247 optically confirmed galaxy groups and clusters detected in the 0.2-2.3 keV as extended X-ray sources in a 13,116deg$^2$ region in the western Galactic hemisphere of the sky, which eROSITA surveyed in its first six months of operation. The clusters in the sample span the redshift range $0.003

The eROSITA telescope array aboard the Spektrum Roentgen Gamma (SRG) satellite began surveying the sky in December 2019, with the aim of producing all-sky X-ray source lists and sky maps of an unprecedented depth. Here we present catalogues of both point-like and extended sources using the data acquired in the first six months of survey operations (eRASS1; completed June 2020) over the half sky whose proprietary data rights lie with the German eROSITA Consortium. We describe the observation process, the data analysis pipelines, and the characteristics of the X-ray sources. With nearly 930000 entries detected in the most sensitive 0.2-2.3 keV energy range, the eRASS1 main catalogue presented here increases the number of known X-ray sources in the published literature by more than 60%, and provides a comprehensive inventory of all classes of X-ray celestial objects, covering a wide range of physical processes. A smaller catalogue of 5466 sources detected in the less sensitive but harder 2.3-5 keV band is the result of the first true imaging survey of the entire sky above 2 keV. We show that the number counts of X-ray sources in eRASS1 are consistent with those derived over narrower fields by past X-ray surveys of a similar depth, and we explore the number counts variation as a function of the location in the sky. Adopting a uniform all-sky flux limit (at 50% completeness) of F_{0.5-2 keV} > 5 \times 10^{-14}$ erg\,s$^{-1}$\,cm$^{-2}$, we estimate that the eROSITA all-sky survey resolves into individual sources about 20% of the cosmic X-ray background in the 1-2 keV range. The catalogues presented here form part of the first data release (DR1) of the SRG/eROSITA all-sky survey. Beyond the X-ray catalogues, DR1 contains all detected and calibrated event files, source products (light curves and spectra), and all-sky maps. Illustrative examples of these are provided., Comment: 39 pages, 23 figures. Accepted for publication in A&A. Accompanying eROSITA-DE Data Release 1