Galaxy Catalogs Research Articles

Reionization morphology and intrinsic velocity offsets allow transmission of Lyman-α emission from JADES-GS-z13-1-LA

ABSTRACT We investigate the detectability of Lyman-$\alpha$ (Ly $\alpha$) emission from galaxies at the onset of cosmic reionization, aiming to understand the conditions necessary for detecting high-redshift sources like JADES-GS-z13-1-LA at $z=13$. By integrating galaxy formation models with detailed intergalactic medium (IGM) reionization simulations, we construct high-redshift galaxy catalogues to model intrinsic Ly $\alpha$ profiles and assess their transmission through the IGM. For a galaxy with $M_{\rm UV}\sim -18.5$ like JADES-GS-z13-1-LA, our fiducial model predicts a Ly $\alpha$ transmission of ${\sim }13$ per cent and there is a probability of observing Ly $\alpha$ emission with an equivalent width $\gt 40$ Å of up to 10 per cent. We also explore how variations in the UV ionizing escape fraction, dependent on host halo mass or specific star formation rate, impact Ly $\alpha$ detectability. Our findings reveal that reionization morphology significantly influences detection chances – models where reionization is driven by low-mass galaxies can boost the detection probability to as much as 12 per cent, while those driven by massive galaxies tend to reduce ionized regions around faint emitters, limiting their detectability. Our findings remain robust when further accounting for stochastic star formation with the detection probability still spanning 3 per cent to 12 per cent. This study underscores the interplay between reionization morphology and intrinsic galaxy properties in interpreting high-redshift Ly $\alpha$ observations.

Dwarf Galaxies with Radio-excess Active Galactic Nuclei in the Very Large Array Sky Survey

We present a systematic search for radio active galactic nuclei (AGNs) in dwarf galaxies using recent observations taken by the Very Large Array Sky Survey (VLASS). To select these objects, we first establish a criterion to identify radio-excess AGNs using the infrared-radio correlation parameter, q, that describes the tight relation between radio and IR emission in star-forming galaxies. We find a 2σ threshold of q < 1.94 to select radio-excess AGNs, which is derived from a sample of ∼7000 galaxies across the full mass range in the NASA-Sloan Atlas that have radio and IR detections from VLASS and the Wide-Field Infrared Survey Explorer, respectively. We create catalogs of radio-excess AGNs and star-forming galaxies and make these available to the community. Applying our criterion to dwarf galaxies with stellar masses M ⋆ ≲ 3 × 109 M ⊙ and redshifts z ≤ 0.15, and carefully removing interlopers, we find 10 radio-excess AGNs with radio-optical positional offsets between ∼0″ and 2.′3 (0–2.7 kpc). Based on statistical arguments and emission line diagnostics, we expect the majority of these radio-excess AGNs to be associated with the dwarf host galaxies rather than background AGNs. Five of the objects have evidence for hosting AGNs at other wavelengths, and five objects are identified as AGNs in dwarf galaxies for the first time. We also identify eight variable radio sources in dwarf galaxies by comparing the VLASS epoch 1 and epoch 2 observations to Faint Images of the Radio Sky at Twenty-centimeters detections presented in A. E. Reines et al. (2020).

Gravitational-wave Dark Siren Cosmology Systematics from Galaxy Weighting

The detection of GW170817 and the measurement of its redshift from the associated electromagnetic counterpart provided the first gravitational-wave (GW) determination of the Hubble constant (H 0), demonstrating the potential power of standard siren cosmology. In contrast to this “bright siren” approach, the “dark siren” approach can be utilized for GW sources in the absence of an electromagnetic counterpart: One considers all galaxies contained within the localization volume as potential hosts. When statistically averaging over the potential host galaxies, weighting them by physically motivated properties (e.g., tracing star formation or stellar mass) could improve convergence. Using mock galaxy catalogs, we explore the impact of these weightings on the measurement of H 0. We find that incorrect weighting schemes can lead to significant biases due to two effects: the assumption of an incorrect galaxy redshift distribution, and preferentially weighting incorrect host galaxies during the inference. The magnitudes of these biases are influenced by the number of galaxies along each line of sight, the measurement uncertainty in the GW luminosity distance, and correlations in the parameter space of galaxies. We show that the bias may be overcome from improved localization constraints in future GW detectors, a strategic choice of priors or weighting prescription, and by restricting the analysis to a subset of high-signal-to-noise ratio events. We propose the use of hierarchical inference as a diagnostic of incorrectly weighted prescriptions. Such approaches can simultaneously infer the correct weighting scheme and the values of the cosmological parameters, thereby mitigating the bias in dark siren cosmology due to incorrect host-galaxy weighting.

Cosmic multipoles in galaxy surveys – I. How inferences depend on source counts and masks

ABSTRACT We present a new approach to constructing and fitting dipoles and higher-order multipoles in synthetic galaxy samples over the sky. Within our Bayesian paradigm, we illustrate that this technique is robust to masked skies, allowing us to make credible inferences about the relative contributions of each multipole. We also show that dipoles can be recovered in surveys with small footprints, determining the requisite source counts required for concrete estimation of the dipole parameters. This work is motivated by recent probes of the cosmic dipole in galaxy catalogues. Namely, the kinematic dipole of the cosmic microwave background, as arising from the motion of our heliocentric frame at $\approx 370\ \text{km}\, \text{s}^{-1}$, implies that an analogous dipole should be observed in the number counts of galaxies in flux-density-limited samples. Recent studies have reported a dipole aligning with the kinematic dipole but with an anomalously large amplitude. Accordingly, our new technique will be important as forthcoming galaxy surveys are made available and for revisiting previous data.

The first all-sky survey of star-forming galaxies with eROSITA. Scaling relations and a population of X-ray luminous starbursts

In this work, we present the results from a study of X-ray normal galaxies, that is, galaxies not harbouring active galactic nuclei (AGN), using data from the first complete all-sky scan of the X-ray survey (eRASS1) obtained with eROSITA on board the Spectrum-Roentgen-Gamma observatory. eRASS1 provides the first unbiased X-ray census of local normal galaxies, thus allowing us to study the X-ray emission (0.2-8.0 ) from X-ray binaries (XRBs) and the hot interstellar medium in the full range of stellar population parameters present in the local Universe. By combining the updated version of the Heraklion Extragalactic Catalogue (HECATE v2.0) value-added catalogue of nearby galaxies (Distance ; lesssim \,200$Mpc) with the X-ray data obtained from eRASS1, we studied the integrated X-ray emission from normal galaxies as a function of their star-formation rate ( ), stellar mass ( ), metallicity, and stellar population age. After applying stringent optical and mid-infrared activity classification criteria, we constructed a sample of 18790 bona fide star-forming galaxies (HEC-eR1 galaxy sample) with measurements of their integrated X-ray luminosity (using each galaxy's D$_ $) over the full range of stellar population parameters present in the local Universe. By stacking the X-ray data in bins, we studied the correlation between the average X-ray luminosity and the average stellar population parameters. We also present updated and -metallicity scaling relations based on a completely blind galaxy sample and accounting for the scatter dependence on the The average X-ray spectrum of star-forming galaxies is well described by a power law ($ $) and a thermal plasma component ($kT = 0.70^ $). We find that the integrated X-ray luminosity of the individual HEC-eR1 star-forming galaxies is significantly elevated (reaching $10^ $) with respect to what is expected from the current standard scaling relations. The observed scatter is also significantly larger. This excess persists even when we measured the average luminosity of galaxies in and metallicity bins, and it is stronger (up to $ sim 2$ dex) towards lower s. Our analysis shows that the excess is not the result of the contribution by hot gas, low-mass XRBs, background AGN, low-luminosity AGN (including tidal disruption events), or stochastic sampling of the XRB X-ray luminosity function. We find that while the excess is generally correlated with lower metallicity galaxies, its primary driver is the age of the stellar populations. Our analysis reveals a sub-population of very X-ray luminous starburst galaxies with higher specific SFRs (sSFRs), lower metallicities, and younger stellar populations. This population drives upwards the X-ray scaling relations for star-forming galaxies and has important implications for understanding the population of XRBs contributing in the most X-ray luminous galaxies in the local and high-redshift Universe. These results demonstrate the power of large blind surveys such eRASS1, which can provide a more complete picture of the X-ray emitting galaxy population and their diversity, revealing rare populations of objects and recovering unbiased underlying correlations.

Morphologies of galaxies within voids

Among the largest structures in which matter is distributed in the Universe, we find cosmic voids, which are large, under-dense regions almost devoid of galaxies. The study of these structures and the galaxies that inhabit them, the void galaxies, provides key information for understanding galaxy evolution. In this work we investigate the effects of the environment on the evolution of void galaxies. In particular, we study their morphology and explore its dependence on the location within the void where the galaxies reside, as well as on the properties of the void, such as its size and the galaxy number density. The sample of void galaxies that we use in this study is based on the catalogue of cosmic voids and void galaxies in the Sloan Digital Sky Survey Data Release 7 (SDSS-DR7). As we are interested in studying the morphology of void galaxies, we select galaxies in the redshift range of 0.005\,leq \,z\,leq \,0.080, and use the public galaxy morphologies of the SDSS sample together with deep learning algorithms to divide the sample into early- and late-type void galaxies. We analyse the fractions of galaxies of each morphological type as a function of the void-centric distance, the size of the voids, and the density of galaxies in each void. There is a higher abundance of late-type galaxies with respect to early-type galaxies within voids, which remains nearly constant from the inner to the outer part of the voids. We do not find any dependence of the fraction of early- and late-type galaxies on void size or on the number-density of galaxies in the voids. Galaxies in voids follow the morphology--density relation, in the sense that the majority of the galaxies in voids (the most under-dense large-scale environments) are late-type galaxies. However, we find no difference between voids with lower or higher volume number-density of galaxies: the fractions of early- and late-type galaxies do not depend on the density of the voids. The physical processes responsible for the evolution from late towards earlier types (such as external environmental quenching) are not sufficiently effective in voids or are so slow (internal secular quenching) that their contributions do not appear in the morphology--density relation.

Cosmic cartography: Bayesian reconstruction of the galaxy density informed by large-scale structure

The dark sirens method combines gravitational waves and catalogs of galaxies to constrain the cosmological expansion history, merger rates and mass distributions of compact objects, and the laws of gravity. However, the incompleteness of galaxy catalogs means faint potential host galaxies are unobserved, and must be modeled to avoid inducing a bias. The majority of dark sirens analyses to date assume that the missing galaxies are distributed uniformly across the sky, which is clearly unphysical. We introduce a new Bayesian approach to the reconstruction of galaxy catalogs, which makes full use of our knowledge of large-scale structure. Our method quantifies the uncertainties on the estimated true galaxy number count in each voxel, and is marginalized over cosmological parameters and bias parameters. Crucially, our method further assesses the (absolute) magnitude distribution of galaxies, which is not known from the galaxy catalog itself. We present the details of our method and validate our approach on a galaxy catalog associated to the Millennium Simulation. The tools developed here generate physically-informed and robust host galaxy reconstructions, enabling more informative dark sirens analyses. Stage IV galaxy surveys will display greater redshift overlap with GW observations, whilst remaining incomplete — emphasizing the importance of our work.

Confusion of extragalactic sources in the far-infrared: A baseline assessment of the performance of PRIMAger in intensity and polarization

Aims. Because of their limited angular resolution, far-infrared telescopes are usually affected by the confusion phenomenon. Since several galaxies can be located in the same instrumental beam, only the brightest objects emerge from the fluctuations caused by fainter sources. The PRobe far-Infrared Mission for Astrophysics imager (PRIMAger) will observe the mid- and far-infrared (25–235 μm) sky both in intensity and polarization. We aim to provide predictions of the confusion level and its consequences for future surveys. Methods. We produced simulated PRIMAger maps affected only by the confusion noise using the simulated infrared extragalactic sky (SIDES) semi-empirical simulation. We then estimated the confusion limit in these maps and extracted the sources using a basic blind extractor. By comparing the input galaxy catalog and the extracted source catalog, we derived various performance metrics as completeness, purity, and the accuracy of various measurements (e.g., the flux density in intensity and polarization or the polarization angle). Results. In intensity maps, we predict that the confusion limit increases rapidly with increasing wavelength (from 21 μJy at 25 μm to 46 mJy at 235 μm). The confusion limit in polarization maps is more than two orders of magnitude lower (from 0.03 mJy at 96 μm to 0.25 mJy at 235 μm). Both in intensity and polarization maps, the measured (polarized) flux density is dominated by the brightest galaxy in the beam, but other objects also contribute in intensity maps at longer wavelengths (∼30% at 235 μm). We also show that galaxy clustering has a mild impact on confusion in intensity maps (up to 25%), while it is negligible in polarization maps. In intensity maps, a basic blind extraction will be sufficient to detect galaxies at the knee of the luminosity function up to z ∼ 3 and 1011 M⊙ main-sequence galaxies up to z ∼ 5. In polarization for the most conservative sensitivity forecast (payload requirements), ∼200 galaxies can be detected up to z = 1.5 in two 1500 h surveys covering 1 deg2 and 10 deg2. For a conservative sensitivity estimate, we expect ∼8000 detections up to z = 2.5, opening a totally new window on the high-z dust polarization. Finally, we show that intensity surveys at short wavelengths and polarization surveys at long wavelengths tend to reach confusion at similar depth. There is thus a strong synergy between them.

Enhancing photometric redshift catalogs through color-space analysis: Application to KiDS-bright galaxies

Aims. We present a method for refining photometric redshift galaxy catalogs based on a comparison of their color-space matching with overlapping spectroscopic calibration data. We focus on cases where photometric redshifts (photo-z) are estimated empirically. Identifying galaxies that are poorly represented in spectroscopic data is crucial, as their photo-z may be unreliable due to extrapolation beyond the training sample. Methods. Our approach uses a self-organizing map (SOM) to project a multidimensional parameter space of magnitudes and colors onto a 2D manifold, allowing us to analyze the resulting patterns as a function of various galaxy properties. Using SOM, we compared the Kilo-Degree Survey’s bright galaxy sample (KiDS-Bright), limited to r &lt; 20 mag, with various spectroscopic samples, including the Galaxy And Mass Assembly (GAMA). Results. Our analysis reveals that GAMA tends to underrepresent KiDS-Bright at its faintest (r ≳ 19.5) and highest-redshift (z ≳ 0.4) ranges; however, no strong trends are seen in terms of color or stellar mass. By incorporating additional spectroscopic data from the SDSS, 2dF, and early DESI, we identified SOM cells where the photo-z values are estimated suboptimally. We derived a set of SOM-based criteria to refine the photometric sample and improve photo-z statistics. For the KiDS-Bright sample, this improvement is modest, namely, it excludes the least represented 20% of the sample reduces photo-z scatter by less than 10%. Conclusions. We conclude that GAMA, used for KiDS-Bright photo-z training, is sufficiently representative for reliable redshift estimation across most of the color space. Future spectroscopic data from surveys such as DESI should be better suited for exploiting the full improvement potential of our method.

A Photometric Redshift Catalogue of Galaxies from the DESI Legacy Imaging Surveys DR10

The large-scale measurement of galaxy redshifts holds significant importance for cosmological research, as well as for understanding the formation and evolution of galaxies. This study utilizes a known sample obtained by cross-correlating the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys DR10 galaxy catalog with various galaxy catalogs from different spectroscopic surveys. The methods Easy and Accurate Photometric Redshifts from Yale (EAZY) and CatBoost are employed to estimate redshifts. In the case of EAZY, the known sample is used solely for testing, while CatBoost utilizes it for both training and testing purposes. The known sample is categorized into different subsamples based on various classification methods. Several CatBoost regression models are trained and optimized using these subsamples. By comparing the performance of different methods and models, it is observed that the two-step and two-part models outperform the one-step model, with further enhancements achieved through the combination of the two-step and two-part models. Based on the findings from all experiments, we propose a photometric redshift estimation workflow designed to facilitate the photometric redshift measurement of all galaxies within the DESI Legacy Imaging Surveys DR10. Consequently, a photometric redshift catalog has been released, comprising a total of 1,533,107,988 galaxies. Among these, 312,960,837 galaxies have reliable redshift estimates, determined using the CatBoost algorithm, with magnitude limits set at g > 24.0, r > 23.4, and z > 22.5. For galaxies with g, r, and z magnitudes exceeding these thresholds, the photometric redshifts estimated by EAZY can be employed as a reference.

The SAGA Survey. III. A Census of 101 Satellite Systems around Milky Way–mass Galaxies

Abstract We present Data Release 3 (DR3) of the Satellites Around Galactic Analogs (SAGA) Survey, a spectroscopic survey characterizing satellite galaxies around Milky Way (MW)-mass galaxies. The SAGA Survey DR3 includes 378 satellites identified across 101 MW-mass systems in the distance range of 25–40.75 Mpc, and an accompanying redshift catalog of background galaxies (including about 46,000 taken by SAGA) in the SAGA footprint of 84.7 deg2. The number of confirmed satellites per system ranges from zero to 13, in the stellar mass range of 106−10 M ⊙. Based on a detailed completeness model, this sample accounts for 94% of the true satellite population down to M ⋆ = 107.5 M ⊙. We find that the mass of the most massive satellite in SAGA systems is the strongest predictor of satellite abundance; one-third of the SAGA systems contain LMC-mass satellites, and they tend to have more satellites than the MW. The SAGA satellite radial distribution is less concentrated than the MW's, and the SAGA quenched fraction below 108.5 M ⊙ is lower than the MW's, but in both cases, the MW is within 1σ of SAGA system-to-system scatter. SAGA satellites do not exhibit a clear corotating signal as has been suggested in the MW/M31 satellite systems. Although the MW differs in many respects from the typical SAGA system, these differences can be reconciled if the MW is an older, slightly less massive host with a recently accreted LMC/SMC system.

MAMBO: An empirical galaxy and AGN mock catalogue for the exploitation of future surveys

Context. Current and future large surveys will produce unprecedented amounts of data. Realistic simulations have become essential for the design and development of these surveys, as well as for the interpretation of the results. Aims. We present MAMBO, a flexible and efficient workflow to build empirical galaxy and active galactic nucleus (AGN) mock catalogues that reproduce the physical and observational properties of these sources. Methods. We started with simulated dark matter (DM) haloes, to preserve the link with the cosmic web, and we populated them with galaxies and AGN using abundance matching techniques. We followed an empirical methodology, using stellar mass functions, host galaxy AGN mass functions, and AGN accretion rate distribution functions studied at different redshifts to assign, among other properties, stellar masses, the fraction of quenched galaxies, or the AGN activity (demography, obscuration, multiwavelength emission, etc.). Results. As a proof test, we applied the method to a Millennium DM lightcone of 3.14 deg2 up to a redshift of z = 10 and down to stellar masses of ℳ ≳ 1075 M⊙. We show that the AGN population from the mock lightcone presented here reproduces with good accuracy various observables, such as state-of-the-art luminosity functions in the X-ray up to z~7 and in the ultraviolet up to z~5, optical/near-infrared colour-colour diagrams, and narrow emission line diagnostic diagrams. Finally, we demonstrate how this catalogue can be used to make useful predictions for large surveys. Using Euclid as a case example, we compute, among other forecasts, the expected surface densities of galaxies and AGN detectable in the Euclid HE band. We find that Euclid might observe (on HE only) about 107 and 8 × 107 type 1 and 2 AGN, respectively, and 2 × 109 galaxies at the end of its 14 679 deg2 Wide survey, in good agreement with other published forecasts.

Identifying the Host Galaxies of Supermassive Black Hole Binaries Found by Pulsar Timing Arrays

Supermassive black hole binaries (SMBHBs) are thought to form in galaxy mergers, possessing the potential to produce electromagnetic (EM) radiation as well as gravitational waves (GWs) detectable with pulsar timing arrays (PTAs). Once GWs from individually resolved SMBHBs are detected, the identification of the host galaxy will be a major challenge due to the ambiguity in possible EM signatures and the poor localization capability of PTAs. To aid EM observations in choosing follow-up sources, we use NANOGrav’s galaxy catalog to quantify the number of plausible hosts in both realistic and idealistic scenarios. We outline a host identification pipeline that injects a single-source GW signal into a simulated PTA data set, recovers the signal using production-level techniques, quantifies the localization region and number of galaxies contained therein, and finally imposes cuts on the galaxies using parameter estimates from the GW search. In an ideal case, the 90% credible areas span 29–241 deg2, containing about 14–341 galaxies. After cuts, the number of galaxies remaining ranges from 22 at worst to one true host at best. In a realistic case, these areas range from 287 to 530 deg2 and enclose about 285–1238 galaxies. After cuts, the number of galaxies is 397 at worst and 27 at best. While the signal-to-noise ratio is the primary determinant of the localization area of a given source, we find that the area is also influenced by the proximity to nearby pulsars on the sky and the binary chirp mass.

Topological Approach to Void Finding Applied to the SDSS Galaxy Map

The structure of the low redshift Universe is dominated by a multiscale void distribution delineated by filaments and walls of galaxies. The characteristics of voids, such as morphology, average density profile, and correlation function, can be used as cosmological probes. However, their physical properties are difficult to infer due to shot noise and the general lack of tracer particles used to define them. In this work, we construct a robust, topology-based void-finding algorithm that utilizes Persistent Homology to detect persistent features in the data. We apply this approach to a volume-limited subsample of galaxies in the SDSS I/II Main Galaxy catalog with the r-band absolute magnitude brighter than M r = −20.19, and a set of mock catalogs constructed using the Horizon Run 4 cosmological N-body simulation. We measure the size distribution of voids, their averaged radial profile, sphericity, and the centroid nearest neighbor separation, using conservative values for the threshold and persistence. We find 32 topologically robust voids in the SDSS data over the redshift range 0.02 ≤ z ≤ 0.116, with effective radii in the range 21−56 h −1 Mpc. The median nearest neighbor void separation is found to be ∼57 h −1 Mpc, and the median radial void profile is consistent with the expected shape from the mock data.

A dark standard siren measurement of the Hubble constant following LIGO/Virgo/KAGRA O4a and previous runs

ABSTRACT We present a new constraint on the Hubble constant ($H_0$) from the standard dark siren method using a sample of five well-covered gravitational wave (GW) alerts reported during the first part of the fourth observing run of the Laser Interferometer Gravitational-Wave Observatory (LIGO), the Virgo and Kamioka Gravitational Wave Detector (KAGRA) collaborations (LVK) and with three updated standard dark sirens from third observation run in combination with the previous constraints from the first three runs. Our methodology relies on the galaxy catalogue method alone. We use a deep learning method to derive the full probability density estimation of photometric redshifts using the Legacy Survey catalogues. We add the constraints from well localized binary black hole mergers to the sample of standard dark sirens analysed in our previous work. We combine the $H_0$ posterior for 5 new standard sirens with other 10 previous events (using the most recent available data for the five novel events and updated three previous posteriors from O3), finding $H_0 = 70.4^{+13.6}_{-11.7}~{\rm km~s^{-1}~Mpc^{-1}}$ (68 per cent confidence interval) with the catalogue method only. This result represents an improvement of $\sim 23~{{\ \rm per\ cent}}$ comparing the new 15 dark siren constraints with the previous 10 dark siren constraints and a reduction in uncertainty of $\sim 40~{{\ \rm per\ cent}}$ from the combination of 15 dark and bright sirens compared with the GW170817 bright siren alone. The combination of dark and bright siren GW170817 with recent jet constraints yields $H_0$ of $68.0^{+4.4}_{-3.8}~{\rm km~s^{-1}~Mpc^{-1}}$, a $\sim 6~{{\ \rm per\ cent}}$ precision from standard sirens, reducing the previous constraint uncertainty by $\sim 10~{{\ \rm per\ cent}}$.

Inferring Cosmological Parameters on SDSS via Domain-generalized Neural Networks and Light-cone Simulations

We present a proof-of-concept simulation-based inference on Ωm and σ 8 from the Sloan Digital Sky Survey (SDSS) Baryon Oscillation Spectroscopic Survey (BOSS) LOWZ Northern Galactic Cap (NGC) catalog using neural networks and domain generalization techniques without the need of summary statistics. Using rapid light-cone simulations L-picola, mock galaxy catalogs are produced that fully incorporate the observational effects. The collection of galaxies is fed as input to a point cloud-based network, Minkowski-PointNet . We also add relatively more accurate Gadget mocks to obtain robust and generalizable neural networks. By explicitly learning the representations that reduce the discrepancies between the two different data sets via the semantic alignment loss term, we show that the latent space configuration aligns into a single plane in which the two cosmological parameters form clear axes. Consequently, during inference, the SDSS BOSS LOWZ NGC catalog maps onto the plane, demonstrating effective generalization and improving prediction accuracy compared to non-generalized models. Results from the ensemble of 25 independently trained machines find Ωm = 0.339 ± 0.056 and σ 8 = 0.801 ± 0.061, inferred only from the distribution of galaxies in the light-cone slices without relying on any indirect summary statistics. A single machine that best adapts to the Gadget mocks yields a tighter prediction of Ωm = 0.282 ± 0.014 and σ 8 = 0.786 ± 0.036. We emphasize that adaptation across multiple domains can enhance the robustness of the neural networks in observational data.

Secondary halo bias through cosmic time II. Reconstructing halo properties using clustering information

When constructing mock galaxy catalogs based on suites of dark matter halo catalogs generated with approximated, calibrated, or machine-learning approaches, assigning intrinsic properties for these tracers is a step of paramount importance, given that they can shape the abundance and spatial distribution of mock galaxies and galaxy clusters. We explore the possibility of assigning properties of dark matter halos within the context of calibrated or learning approaches, explicitly using clustering information. The goal is to retrieve the correct signal of primary and secondary large-scale effective bias as a function of properties reconstructed solely based on phase-space properties of the halo distribution and dark matter density field. The algorithm reconstructs a set of halo properties (such as virial mass, maximum circular velocity, concentration, and spin) constrained to reproduce both primary and secondary (or assembly) bias. The key ingredients of the algorithm are the implementation of individually-assigned large-scale effective bias, a multi-scale approach to account for halo exclusion, and a hierarchical assignment of halo properties. The method facilitates the assignment of halo properties, aiming to replicate the large-scale effective bias, both primary and secondary. This constitutes an improvement over previous methods in the literature, especially for the high-mass end population. We have designed a strategy for reconstructing the main properties of dark matter halos obtained using calibrated or learning algorithms, such that the one- and two-point statistics (on large scales) replicate the signal from detailed $N$-body simulations. We encourage the application of this strategy (or the implementation of our algorithm) for the generation of mock catalogs of dark matter halos based on approximated methods.

Analysis of Ring Galaxies Detected Using Deep Learning with Real and Simulated Data

Understanding the formation and evolution of ring galaxies, which possess an atypical ring-like structure, is crucial for advancing knowledge of black holes and galaxy dynamics. However, current catalogs of ring galaxies are limited, as manual analysis takes months to accumulate an appreciable sample of rings. This paper presents a convolutional neural network (CNN) to identify ring galaxies from unclassified samples. A CNN was trained on 100,000 simulated galaxies, transfer learned onto a sample of real galaxies, and applied to a previously unclassified data set to generate a catalog of rings, which was then manually verified. Data augmentation with a generative adversarial network to simulate images of galaxies was also employed. The resulting catalog contains 1967 ring galaxies. The properties of these galaxies were then estimated from their photometry and compared to the Galaxy Zoo 2 catalog of rings. However, the model’s precision is currently limited due to a severe imbalance of rings in real data sets, leading to a significant false-positive rate of 41.1%, which poses challenges for large-scale applications in surveys imaging billions of galaxies. This study demonstrates the potential of optimizing machine learning pipelines for low training data in rare morphologies and underscores the need for further refinements to enhance precision for extensive surveys like the Vera Rubin Observatory Legacy Survey of Space and Time.

Detection of the large-scale tidal field with galaxy multiplet alignment in the DESI Y1 spectroscopic survey

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

Hydrodynamics and Nucleosynthesis of Jet-driven Supernovae. II. Comparisons with Abundances of Extremely Metal-poor Galaxies and Constraints on Supernova Progenitors

The spectra of several galaxies, including extremely metal-poor galaxies from EMPRESS, have shown that the abundances of some Si-group elements differ from “spherical” explosion models of massive stars. This leads to the speculation that these galaxies have experienced supernova explosions with high asphericity, where mixing and fallback of the inner ejecta with the outer material lead to the distinctive chemical compositions. In this paper, we consider the jet-driven supernova models by direct 2D hydrodynamics simulations using progenitors of about 20–25 M ⊙ at zero metallicity. We investigate how the abundance patterns depend on the progenitor mass, mass cut, and asphericity of the explosion. We compare the observable with available supernova and galaxy catalogs based on 56Ni, ejecta mass, and individual element ratios. The proximity of our results with the observational data signifies the importance of aspherical supernova explosions in chemical evolution of these galaxies. Our models will provide the theoretical counterpart for understanding the chemical abundances of high-z galaxies measured by the James Webb Space Telescope.