Galaxy Catalogs Research Articles

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.

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

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\,mu m) sky both in intensity and polarization. We aim to provide predictions of the confusion level and its consequences for future surveys. 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). In intensity maps, we predict that the confusion limit increases rapidly with increasing wavelength (from 21\,mu Jy at 25\,mu m to 46\,mJy at 235\,mu m). The confusion limit in polarization maps is more than two orders of magnitude lower (from 0.03\,mJy at 96\,mu m to 0.25\,mJy at 235\,mu m). 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 (sim 30\,<!PCT!> at 235\,mu m). We also show that galaxy clustering has a mild impact on confusion in intensity maps (up to 25\,<!PCT!>), 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 zsim 3 and 1011\,M$_ main-sequence galaxies up to zsim 5. In polarization for the most conservative sensitivity forecast (payload requirements), sim 200 galaxies can be detected up to z=1.5 in two 1\,500\,h surveys covering 1\,deg$^2$ and 10\,deg$^2$. For a conservative sensitivity estimate, we expect sim 8\,000 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.

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 (H0) from the standard dark siren method using a sample of 5 well-covered gravitational waves (GW) alerts reported during the first part of the fourth LIGO/Virgo/KAGRA observing run and with 3 updated standard dark sirens from third observation run in combination 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 H0 posterior for 5 new standard sirens with other 10 previous events (using the most recent available data for the 5 novel events and updated 3 previous posteriors from O3), finding $H_0 = 70.4^{+13.6}_{-11.7}~{\rm km~s^{-1}~Mpc^{-1}}$ (68% Confidence interval) with the catalogue method only. This result represents an improvement of $\sim 23~{{\%}}$ comparing the new 15 dark siren constrain with the previous 10 dark siren constraint and a reduction in uncertainty of $\sim 40~{{\%}}$ 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 H0 of $68.0^{+4.4}_{-3.8}~{\rm km~s^{-1}~Mpc^{-1}}$, a $\sim 6~{{\%}}$ precision from Standard Sirens, reducing the previous constraint uncertainty by $\sim 10~{{\%}}$ .

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.

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.

Axion-induced patchy screening of the Cosmic Microwave Background

Cosmic Microwave Background (CMB) photons can undergo resonant conversion into axions in the presence of magnetized plasma distributed inside non-linear large-scale structure (LSS). This process leads to axion-induced patchy screening: secondary temperature and polarization ani­sotropies with a characteristic non-blackbody frequency dependence that are strongly correlated with the distribution of LSS along our past light cone. We compute the axion-induced patchy screening contribution to two- and three- point correlation functions that include CMB anisotropies and tracers of LSS within the halo model. We use these results to forecast the sensitivity of existing and future surveys to photon-axion couplings for axion masses between 2 × 10-13 eV and 3 × 10-12 eV, using a combination of empirical estimates from Planck data of the contribution from instrumental noise and foregrounds as well as modeled contributions on angular scales only accessible with future datasets. We demonstrate that an analysis using Planck and the unWISE galaxy catalogue would be complementary to the most sensitive existing astrophysical axion searches, probing couplings as small as 3 × 10-12 GeV-1, while observations from a future survey such as CMB-S4 could extend this reach by almost an additional order of magnitude.

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

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. 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. 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.). As a proof test, we applied the method to a Millennium DM lightcone of 3.14 $ deg^2$ up to a redshift of $z=10$ and down to stellar masses of $ M \, 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 $H_ E $ band. We find that Euclid might observe (on $H_ E $ only) about $10^ $ and $8 $ type 1 and 2 AGN, respectively, and $2 $ galaxies at the end of its $ deg^2$ Wide survey, in good agreement with other published forecasts.

Bounds on galaxy stochasticity from halo occupation distribution modeling

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 probability distribution function (PDF). We investigate stochasticity in the conditional distribution of galaxy counts along lines of sight with fixed matter density, and we 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 a set of HODs that conserve the galaxies’ linear 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 for cells with mean matter density. Nearly all of the derived HODs show a positive relationship between local matter density and stochasticity. For galaxy catalogs with higher stochasticity, modeling galaxy bias to second order 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 nuisance model parameters and can be adapted to study other parametrizations of shot noise in galaxy counts, in particular to motivate prior ranges on stochasticity for cosmological analyses.

Tomographic redshift dipole: testing the cosmological principle

The cosmological principle posits that the universe is statistically homogeneous and isotropic on large scales, implying all matter shares the same rest frame. This principle suggests that velocity estimates of our motion from various sources should agree with the cosmic microwave background (CMB) dipole's inferred velocity of 370 km/s. Yet, for over two decades, analyses of radio galaxy and quasar catalogs have found velocities at odds with the CMB dipole, with tensions up to 5σ. In a blind analysis of BOSS and eBOSS spectroscopic data from galaxies and quasars across 0.2 < z < 2.2, we applied a novel dipole estimator for a tomographic approach, robustly correcting biases and quantifying uncertainties with realistic mock catalogs. Our findings with eBOSS data (0.6 < z < 2.2), indicating a velocity of 196+92 -79-79 km/s, demonstrate a 2σ agreement with the CMB dipole when considering the full 3D vector distribution and a 3-to-6σ tension with previous number count studies. This result supports the cosmological principle, emphasizing the consistency of our motion with the CMB across vast cosmic distances. On the other hand, the BOSS data revealed potential unmodeled systematics; the estimator could not be minimized using the LOWZ set (0.2 < z < 0.4), and the CMASS set (0.4 < z < 0.6) presented results that pointed towards the southern hemisphere, conflicting with the CMB dipole. Addressing the disparities with earlier number count analyses and understanding possible systematics in spectroscopic measurements will be essential to further validate the cosmological principle.

Dissecting a miniature universe: A multi-wavelength view of galaxy quenching in the Shapley supercluster

Multiple cluster systems, that is superclusters, contain large numbers of galaxies assembled in clusters interconnected by multi-scale filamentary networks. As such, superclusters are a smaller version of the cosmic web and can hence be considered as miniature universes. In addition to the galaxies, superclusters also contain gas, which is hot in the clusters and warmer in the filaments. Therefore, they are ideal laboratories to study the interplay between the galaxies and the gas. In this context, the Shapley supercluster (SSC) stands out since it hosts the highest number of galaxies in the local Universe with clusters interconnected by filaments. In addition, it is detected both in X-rays and via the thermal Sunyaev-Zel’dovich (tSZ) effect, making it ideal for a multi-wavelength study of the gas and galaxies. Applying for the first time a filament-finder based on graphs, T-REx, on a spectroscopic galaxy catalogue, we uncovered the 3D filamentary network in and around SSC. Simultaneously, we used a large sample of photometric galaxies with information on their star formation rates (SFRs) in order to investigate the quenching of star formation in the SSC environment which we define as a function of the gas distribution in the Planck tSZ map and the ROSAT X-ray map. With T-REx, we confirm filaments already observed in the distribution of galaxies of the SSC, and we detect new ones. We observe the quenching of star formation as a function of the gas contained in the SSC. We show a general trend of decreasing SFR where the tSZ and X-ray signals are the highest, within the high density environments of the SSC. Within these regions, we also observe a rapid decline in the number of star-forming galaxies, coinciding with an increasing number of transitioning and passive galaxies. Within the SSC filaments, the fraction of passive galaxies is larger than outside filaments, irrespective of the gas pressure. Our results suggest that the zone of influence of the SSC in which galaxies are pre-processed and quenched is well defined by the tSZ signal that combines the density and temperature of the environments.

Euclid preparation

Verifying the fully kinematic nature of the long-known cosmic microwave background (CMB) dipole is of fundamental importance in cosmology. In the standard cosmological model with the Friedman–Lemaitre–Robertson–Walker (FLRW) metric from the inflationary expansion, the CMB dipole should be entirely kinematic. Any non-kinematic CMB dipole component would thus reflect the preinflationary structure of space-time probing the extent of the FLRW applicability. Cosmic backgrounds from galaxies after the matter-radiation decoupling should have a kinematic dipole component identical in velocity to the CMB kinematic dipole. Comparing the two can lead to isolating the CMB non-kinematic dipole. It was recently proposed that such a measurement can be done using the near-infrared cosmic infrared background (CIB) measured with the currently operating Euclid telescope, and later with Roman. The proposed method reconstructs the resolved CIB, the integrated galaxy light (IGL), from Euclid’s Wide Survey and probes its dipole with a kinematic component amplified over that of the CMB by the Compton–Getting effect. The amplification coupled with the extensive galaxy samples forming the IGL would determine the CIB dipole with an overwhelming signal-to-noise ratio, isolating its direction to sub-degree accuracy. We developed details of the method for Euclid’s Wide Survey in four bands spanning from 0.6 to 2 μm. We isolated the systematic and other uncertainties and present methodologies to minimize them, after confining the sample to the magnitude range with a negligible IGL–CIB dipole from galaxy clustering. These include the required star–galaxy separation, accounting for the extinction correction dipole using the new method developed here achieving total separation, and accounting for the Earth’s orbital motion and other systematic effects. Finally, we applied the developed methodology to the simulated Euclid galaxy catalogs, successfully testing the upcoming applications. With the techniques presented, one would indeed measure the IGL–CIB dipole from Euclid’s Wide Survey with high precision, probing the non-kinematic CMB dipole.

The Universe SPHEREx Will See: Empirically Based Galaxy Simulations and Redshift Predictions

We simulate galaxy properties and redshift estimation for SPHEREx, the next NASA Medium Class Explorer. To make robust models of the galaxy population and test the spectrophotometric redshift performance for SPHEREx, we develop a set of synthetic spectral energy distributions based on detailed fits to COSMOS2020 photometry spanning 0.1–8 μm. Given that SPHEREx obtains low-resolution spectra, emission lines will be important for some fraction of galaxies. Here, we expand on previous work, using better photometry and photometric redshifts from COSMOS2020 and tight empirical relations to predict robust emission-line strengths and ratios. A second galaxy catalog derived from the GAMA survey is generated to ensure the bright (m AB < 18 in the i band) sample is representative over larger areas. Using template fitting to estimate photometric continuum redshifts, we forecast the recovery of 19 million galaxies over 30,000 deg2 with redshifts better than σ z < 0.003(1 + z), 445 million with σ z < 0.1(1 + z), and 810 million with σ z < 0.2(1 + z). We also find through idealized tests that emission-line information from spectrally dithered flux measurements can yield redshifts with accuracy beyond that implied by the naive SPHEREx channel resolution, motivating the development of a hybrid continuum–line redshift estimation approach.

Comparing Gaia, NED and SIMBAD source classifications in nearby galaxies

Abstract Gaia Data Release 3 (DR3) provides the first classifications for the sources in Gaia’s all-sky database. Most Gaia sources are stars in the Milky Way, but DR3 also contains many sources that belong to nearby galaxies, as well as background galaxies and quasars. In this work, we compare the Gaia classifications from the Discrete Source Classifier (CU8-DSC) module to the more detailed and heterogeneous classifications in NED and/or SIMBAD for sources with sky positions within twice the Holmberg radius of nearby galaxies. Matching these catalogues gives approximately 3.2 × 105 unique Gaia matches for 4 × 105 sources over 1040 galaxies (excluding some large Local Group galaxies) in the Local Volume Galaxy catalogue. Matched sources contain a lower fraction of Gaia-classified stars and higher fractions of galaxies and quasars (∼95, 2 and 2 per cent, respectively) than DR3 overall. Considering NED (SIMBAD) classifications as truth values, the balanced accuracy of Gaia classification is 0.80 (0.83): the most common disagreements are literature-classified galaxies Gaia-classified as stars and literature-classified stars Gaia-classified as quasars. Purity (P) and completeness (C) metrics show that agreement between Gaia classification and NED/SIMBAD classification is best for stars (P, C ∼ 0.9), and decreases for quasars (P &amp;lt; 0.3, 0.7 &amp;lt; C &amp;lt; 0.8), galaxies (0.7 &amp;lt; P &amp;lt; 0.8, 0.3 &amp;lt; C &amp;lt; 0.6), white dwarfs (0.04 &amp;lt; P &amp;lt; 0.6, C ∼ 0.6), and binary stars (P, C &amp;lt; 0.1). NED or SIMBAD sources classified only by detection wavelength are most often Gaia-classified as stars, while non-stellar components of galaxies appear in all Gaia classes.

A Candidate Dark Matter Deficient Dwarf Galaxy in the Fornax Cluster Identified through Overluminous Star Clusters

Two low surface brightness (LSB) dwarf galaxies were identified recently as having little or no dark matter (DM), provoking widespread interest in their formation histories. These galaxies also host populous systems of star clusters that are on average larger and more luminous than typical globular clusters (GCs). We report an initial attempt to identify new candidate DM-deficient dwarfs via their unusual GC systems. Using a large catalog of LSB galaxies from the Dark Energy Survey, we inspect their Dark Energy Camera Legacy Survey (DECaLS) imaging and identify FCC 224 as a candidate found on the outskirts of the Fornax cluster. We analyze the GC system using DECaLS and archival Hubble Space Telescope WFPC2 imaging, and find an apparent population of overluminous GCs. More detailed follow-up of FCC 224 is in progress.

Testing the transferability of Machine Learning techniques for determining photometric redshifts of galaxy catalogue populations

Abstract In this work the random forest algorithm GALPRO is implemented to generate photometric redshift posteriors, and its performance when trained and then applied to data from another survey is investigated. The algorithm is initially calibrated using a truth dataset compiled from the DESI Legacy survey. We find that the testing and training datasets must have very similar redshift distributions, with the range of their photometric data overlapping by at least 90% in the appropriate photometric bands in order for the training data to be applicable to the testing data. GALPRO is again trained using the DESI dataset and then applied to a sample drawn from the PanSTARRS survey, to explore whether GALPRO can be trained using a trusted dataset and applied to an entirely new survey, albeit one that uses a different magnitude system for its photometric bands, thus requiring careful conversion of the measured magnitudes. The results of this further test indicate that GALPRO does not produce accurate photometric redshift posteriors for the new survey, even where the distribution of redshifts for the two datasets overlaps by over 90%. We conclude that the photometric redshifts generated by GALPRO are not suitable for generating estimates of photometric redshifts and their posterior distribution functions when applied to an entirely new survey, particularly one that uses a different magnitude system. However, our results demonstrate that GALPRO is a useful tool for inferring photometric redshift estimates in the case where a spectroscopic galaxy survey is nearly complete, but missing some spectroscopic redshift values.