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At least 1,045 records · Page 58
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DOE OSTI2023

Long-slit spectral study of the unusual post-interacting galaxy Arp 263

ABSTRACT Arp 263 is a single irregularly shaped galaxy with intense star formation. Its short tidal features of low brightness visible in both optics and the H i line, as well as the strong non-circular motion of atomic gas in the outskirts, give pieces of evidence of a recent merging with some intruder, non-observed directly. We carried out spectral observations of this galaxy at the 6 m telescope of the Special Astrophysical Observatory. The spectra for three positions of the spectral slit were obtained: two of them cross the central region of the galaxy and the third one runs along the nearly straight narrow chain of clumps of emission gas with a length of 4–5 kpc. We derived the profiles of velocity, fluxes, and oxygen abundances (O/H) along the slits. We confirm that within the radius of several kpc the galaxy rotates regularly. The maximal value of the rotational velocity allows us to conclude that the dark mass of the galaxy prevails over the mass of its visible components. The observed velocity profile along the peripheral star-forming chain gives pieces of evidence that it is located outside of the plane of the disc, and the gas that formed the chain is probably falling back on to the disc after being ejected from the galaxy. We discuss that the observed chain of clumps is the result of gravitational instability of the gaseous filament.

Astronomy & Astrophysics↗
DOE OSTI2024

Stellar populations and merger rates of brightest cluster galaxies a billion years ago: SDSS MaNGA IFU spectroscopy

ABSTRACT We investigate the spectroscopic properties of 85 brightest cluster galaxies (BCGs) and their companions observed with the SDSS MaNGA integral field unit. Galaxy redshifts are between 0.08 < z < 0.15, allowing for a field-of-view up to 80 × 80 kpc. For the main galaxies: the average age of the BCG cores is 7.66$\, \pm \,$1.36 Gyr with no significant gradient out to $2\, R_ {e}$; the average metallicity of the BCG cores is $[Z/H]=0.23\, \pm \, 0.03$ with a negative gradient of Δ[Z/H]/Δ(R/Re) = –0.14$\, \pm \, 0.09$ which flattens beyond $1.2\, R_ {e}$. Velocity dispersion gradients are mostly flat, but a few positive slopes are seen in the most massive galaxies. Emission lines are present in 12 of the BCGs, most often confined to the central $\sim 2\,$ kpc with emission line ratios well-described by a LINER or AGN excitation source. There are 78 companion galaxies identified and 9 have nebular emission lines that indicate recent star formation. The companions with flux ratios of 4:1 and 20:1 within 30 kpc of their BCG’s core are studied. The companion galaxies have a median age of 7.65$\, \pm \,$1.55 Gyr and are high-metallicity systems, with a median [Z/H] = 0.17 ± 0.07. Close spectroscopic companions with higher merging probabilities have an average merging time of 0.5 ± 0.2 Gyr. The average merger rate is 0.08$\, \pm \, 0.12 \,$ Gyr−1 for 4:1 companions and 0.26$\, \pm \, 0.22 \,$ Gyr−1 for 20:1 companions, allowing for an increase in mass of 2.3$\, \pm \,$3.4 per cent Gyr−1 and 3.5$\, \pm \,$3.2 per cent Gyr−1, respectively.

Edwards, Louise O. V. (ORCID:000000029135997X)↗
DOE OSTI2024

AstroCLIP: a cross-modal foundation model for galaxies

ABSTRACT We present AstroCLIP, a single, versatile model that can embed both galaxy images and spectra into a shared, physically meaningful latent space. These embeddings can then be used – without any model fine-tuning – for a variety of downstream tasks including (1) accurate in-modality and cross-modality semantic similarity search, (2) photometric redshift estimation, (3) galaxy property estimation from both images and spectra, and (4) morphology classification. Our approach to implementing AstroCLIP consists of two parts. First, we embed galaxy images and spectra separately by pre-training separate transformer-based image and spectrum encoders in self-supervised settings. We then align the encoders using a contrastive loss. We apply our method to spectra from the Dark Energy Spectroscopic Instrument and images from its corresponding Legacy Imaging Survey. Overall, we find remarkable performance on all downstream tasks, even relative to supervised baselines. For example, for a task like photometric redshift prediction, we find similar performance to a specifically trained ResNet18, and for additional tasks like physical property estimation (stellar mass, age, metallicity, and specific-star-formation rate), we beat this supervised baseline by 19 per cent in terms of R2. We also compare our results with a state-of-the-art self-supervised single-modal model for galaxy images, and find that our approach outperforms this benchmark by roughly a factor of two on photometric redshift estimation and physical property prediction in terms of R2, while remaining roughly in-line in terms of morphology classification. Ultimately, our approach represents the first cross-modal self-supervised model for galaxies, and the first self-supervised transformer-based architectures for galaxy images and spectra.

Parker, Liam (ORCID:0009000749521674)↗
DOE OSTI2024

A post-merger enhancement only in star-forming Type 2 Seyfert galaxies: the deep learning view

ABSTRACT Supermassive black holes require a reservoir of cold gas at the centre of their host galaxy in order to accrete and shine as active galactic nuclei (AGN). Major mergers have the ability to drive gas rapidly inwards, but observations trying to link mergers with AGN have found mixed results due to the difficulty of consistently identifying galaxy mergers in surveys. This study applies deep learning to this problem, using convolutional neural networks trained to identify simulated post-merger galaxies from survey-realistic imaging. This provides a fast and repeatable alternative to human visual inspection. Using this tool, we examine a sample of ∼8500 Seyfert 2 galaxies ($L[\mathrm{O\, {\small III}}] \sim 10^{38.5 - 42}$ erg s−1) at z < 0.3 in the Sloan Digital Sky Survey and find a merger fraction of $2.19_{-0.17}^{+0.21}$ per cent compared with inactive control galaxies, in which we find a merger fraction of $2.96_{-0.20}^{+0.26}$ per cent, indicating an overall lack of mergers among AGN hosts compared with controls. However, matching the controls to the AGN hosts in stellar mass and star formation rate reveals that AGN hosts in the star-forming blue cloud exhibit a ∼2 × merger enhancement over controls, while those in the quiescent red sequence have significantly lower relative merger fractions, leading to the observed overall deficit due to the differing M*–SFR distributions. We conclude that while mergers are not the dominant trigger of all low-luminosity, obscured AGN activity in the nearby Universe, they are more important to AGN fuelling in galaxies with higher cold gas mass fractions as traced through star formation.

Avirett-Mackenzie, M. S.↗
DOE OSTI2020

A method for classification of red, blue, and green galaxies using fuzzy set theory

ABSTRACT Red and blue galaxies are traditionally classified using some specific cuts in colour or other galaxy properties, which are supported by empirical arguments. The vagueness associated with such cuts are likely to introduce a significant contamination in these samples. Fuzzy sets are vague boundary sets that can efficiently capture the classification uncertainty in the absence of any precise boundary. We propose a method for classification of galaxies according to their colours using fuzzy set theory. We use data from the Sloan Digital Sky Survey (SDSS) to construct a fuzzy set for red galaxies with its members having different degrees of ‘redness’. We show that the fuzzy sets for the blue and green galaxies can be obtained from it using different fuzzy operations. We also explore the possibility of using fuzzy relation to study the relationship between different galaxy properties and discuss its strengths and limitations.

Pandey, Biswajit (ORCID:000000017876595X)↗
DOE OSTI2022

LOFAR discovery of rare large FR I jets in the low-luminosity radio galaxy NGC 5322

ABSTRACT The discovery of faint Fanaroff–Riley type I (FR I) radio jets in the elliptical galaxy NGC 5322 is reported here using the 144-MHz image from Data Release 2 of the Low-Frequency Array (LOFAR) Two-metre Sky Survey (LoTSS). The jets have an angular extent of ∼40 arcmin or a projected physical extent of ∼360 kpc. The faint jets remain well collimated and disappear in the intergalactic medium, without any detected hotspots or radio lobes. The relatively brighter jets, previously detected only up to the ∼21 kpc extent at higher frequencies, are within the optical extent of the galaxy. The jets become faint abruptly outside, where detection is made only in the LOFAR image. The total radio luminosity of the galaxy at 144 MHz is estimated to be (3.7 ± 0.4) × 1022 W Hz−1. The 144-MHz radio luminosity of the faint jets outside the optical extent is estimated to be (7.1 ± 2.0) × 1021 W Hz−1. The size of the jets is exceptionally large for the galaxy’s low radio luminosity, when compared with other radio galaxies. It makes NGC 5322 a rare radio galaxy, previously not detected in other radio surveys. A combined effect of stellar core depletion and low-density environment around the jets, which results in a weak entrainment of the material surrounding the jets, could be responsible for its large size despite a low radio luminosity.

Astronomy & Astrophysics↗
DOE OSTI2022

Passive spiral galaxies deeply captured by Subaru Hyper Suprime-Cam

Abstract This paper presents a thousand passive spiral galaxy samples at z = 0.01–0.3 based on a combined analysis of the Third Public Data Release of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP PDR3) and the GALEX–SDSS–WISE Legacy Catalog (GSWLC-2). Among 54871 gri galaxy cutouts taken from the HSC-SSP PDR3 over 1072 deg2, we conducted a search with deep-learning morphological classification for candidates of passive spirals below the star-forming main sequence derived by ultraviolet to mid-infrared spectral energy distribution fitting in the GSWLC-2. We then classified the candidates into 1100 passive spirals and 1141 secondary samples based on visual inspections. Most of the latter cases are considered to be passive ringed S0 or pseudo-ringed galaxies. The remaining secondary samples have ambiguous morphologies, including two peculiar objects with diamond-shaped stellar wings. The selected passive spirals have a similar distribution to the general quiescent galaxies on the EWHδ–Dn4000 diagram and concentration indices. Moreover, we detected an enhanced passive fraction of spiral galaxies in X-ray clusters. Passive spirals in galaxy clusters are preferentially located in the midterm or late infall phase on the phase–space diagram, supporting the ram pressure scenario, which has been widely advocated in previous studies. The source catalog and gri-composite images are available on the HSC-SSP PDR3 website 〈https://hsc.mtk.nao.ac.jp/ssp/data-release/〉. Future updates, including integration with a citizen science project dedicated to the HSC data, will achieve more effective and comprehensive classifications.

Shimakawa, Rhythm (ORCID:0000000344422750)↗
DOE OSTI2022

Deblurring galaxy images with Tikhonov regularization on magnitude domain

Abstract We propose a regularization-based deblurring method that works efficiently for galaxy images. The spatial resolution of a ground-based telescope is generally limited by seeing conditions and is much worse than space-based telescopes. This circumstance has generated considerable research interest in the restoration of spatial resolution. Since image deblurring is a typical inverse problem and often ill-posed, solutions tend to be unstable. To obtain a stable solution, much research has adopted regularization-based methods for image deblurring, but the regularization term is not necessarily appropriate for galaxy images. Although galaxies have an exponential or Sérsic profile, the conventional regularization assumes the image profiles to behave linearly in space. The significant deviation between the assumption and real situations leads to blurring of the images and smoothing out the detailed structures. Clearly, regularization on logarithmic domain, i.e., magnitude domain, should provide a more appropriate assumption, which we explore in this study. We formulate a problem of deblurring galaxy images by an objective function with a Tikhonov regularization term on a magnitude domain. We introduce an iterative algorithm minimizing the objective function with a primal–dual splitting method. We investigate the feasibility of the proposed method using simulation and observation images. In the simulation, we blur galaxy images with a realistic point spread function and add both Gaussian and Poisson noise. For the evaluation with the observed images, we use galaxy images taken by the Subaru HSC-SSP. Both of these evaluations show that our method successfully recovers the spatial resolution of the deblurred images and significantly outperforms the conventional methods. The code is publicly available from the GitHub 〈https://github.com/kzmurata-astro/PSFdeconv_amag〉.

Murata, Kazumi↗
DOE OSTI2023

The entropy of galaxy spectra: how much information is encoded?

Abstract The inverse problem of extracting the stellar population content of galaxy spectra is analysed here from a basic standpoint based on information theory. By interpreting spectra as probability distribution functions, we find that galaxy spectra have high entropy, thus leading to a rather low effective information content. The highest variation in entropy is unsurprisingly found in regions that have been well studied for decades with the conventional approach. We target a set of six spectral regions that show the highest variation in entropy – the 4000 Å break being the most informative one. As a test case with real data, we measure the entropy of a set of high-quality spectra from the Sloan Digital Sky Survey, and contrast entropy-based results with the traditional method based on line strengths. The data are classified into star-forming (SF), quiescent (Q), and active galactic nucleus (AGN) galaxies, and show – independently of any physical model – that AGN spectra can be interpreted as a transition between SF and Q galaxies, with SF galaxies featuring a more diverse variation in entropy. The high level of entanglement complicates the determination of population parameters in a robust, unbiased way, and affects traditional methods that compare models with observations, as well as machine learning (especially deep learning) algorithms that rely on the statistical properties of the data to assess the variations among spectra. Entropy provides a new avenue to improve population synthesis models so that they give a more faithful representation of real galaxy spectra.

Ferreras, Ignacio (ORCID:0000000345843127)↗
DOE OSTI2026

Probing cosmic velocities with the pairwise kinematic Sunyaev-Zel’dovich signal in DESI Bright Galaxy Sample DR1 and ACT DR6

We present a measurement of the pairwise kinematic Sunyaev-Zel’dovich (kSZ) signal using the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Sample (BGS) Data Release 1 (DR1) galaxy sample overlapping with the Atacama Cosmology Telescope (ACT) CMB temperature map. Our analysis makes use of 1.6 million galaxies with stellar masses log⁡ 𝑀 ⋆ /𝑀 ⊙ >10, and we explore measurements across a range of aperture sizes (2.1′ <𝜃 ap <3.5′) and stellar mass selections. This statistic directly probes the velocity field of the large-scale structure, a unique observable of cosmic dynamics and modified gravity. In particular, at low redshifts, this quantity is especially interesting, as deviations from General Relativity are expected to be largest. Notably, our result represents the highest-significance low-redshift (𝑧 ∼ 0.3) detection of the kSZ pairwise effect yet. In our most optimal configuration (𝜃 ap =3.3′, log⁡ 𝑀 ⋆ >11), we achieve a 5⁢𝜎 detection. Assuming that an estimate of the optical depth and galaxy bias of the sample exists via e.g., external observables, this measurement constrains the fundamental cosmological combination 𝐻 0 ⁡𝑓⁡𝜎$^2_8$. A key challenge is the degeneracy with the galaxy optical depth. We address this by combining CMB lensing, which allows us to infer the halo mass and galaxy population properties, with hydrodynamical simulation estimates of the mean optical depth, $\bar{𝜏}$ . We stress that this is a proof-of-concept analysis; with BGS DR2 data we expect to improve the statistical precision by roughly a factor of two, paving the way toward robust tests of modified gravity with kSZ-informed velocity-field measurements at low redshift.

Hadzhiyska, Boryana [Institute of Astronomy; Kavli↗
DOE OSTI2021

Self-interacting dark matter and small-scale gravitational lenses in galaxy clusters

Recently, Meneghetti et al. reported an excess of small-scale gravitational lenses in galaxy clusters. We study its implications for self-interacting dark matter (SIDM) compared with standard cold dark matter (CDM). We design controlled N-body simulations that incorporate observational constraints. The presence of early-type galaxies in cluster substructures can deepen gravitational potential and reduce tidal mass loss. Both scenarios require a relatively high baryon concentration in the substructure to accommodate the lensing measurements, and their tangential caustics are similar. The SIDM substructure can experience gravothermal collapse and produce a steeper density profile than its CDM counterpart, leading to a larger radial galaxy-galaxy strong-lensing cross section, although this effect is hard to observe. Our results indicate that SIDM can provide a unified explanation to small-scale lenses in galaxy clusters and stellar motion in dwarf galaxies.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Constraints on f ( R ) and normal-branch Dvali-Gabadadze-Porrati modified gravity model parameters with cluster abundances and galaxy clustering

In this report we present forecasted cosmological constraints from combined measurements of galaxy cluster abundances from the Simons Observatory and galaxy clustering from a DESI-like experiment on two well-studied modified gravity models, the chameleon-screened Hu-Sawicki f(R) model and the nDGP braneworld Vainshtein model. A Fisher analysis is conducted using σ 8 constraints derived from thermal Sunyaev-Zel’dovich (tSZ) selected galaxy clusters as well as linear and quasilinear redshift-space 2-point galaxy correlation functions. We find that the cluster abundances drive the constraints on the nDGP model while f(R) constraints are led by galaxy clustering. The two tracers of the cosmological gravitational field are found to be complementary, and their combination significantly improves constraints on the f(R) in particular in comparison to each individual tracer alone. For a model of f(R) with a general relativity (GR) fiducial case (f R0 = 0), we find a 2-σ upper limit of f R0 ≤ 5.68 x10 -7 . For the well-studied log-based fiducial parameter value in f(R), log 10 (f R0 ) = -5, paired with the parameter value n = 1, we find combined 1-σ constraints of σ(log 10 (f R0 )) = 0.12 and σ(n) = 0.36. For the nDGP model with fiducial n nDGP = 1 we find σ( n nDGP ) = 0.087. Our results present the exciting potential to utilize upcoming galaxy and CMB survey data available in the near future to discern and/or constrain cosmic deviations from GR.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

The Ellipticity of Galaxy Clusters at a Large Radius

Galaxy clusters are the largest known gravitationally bound structures in the universe, consisting of hundreds to thousands of galaxies (Figure 1). Dark matter contributes the majority of mass to galaxy clusters, and therefore has a strong influence on the arrangement of member galaxies. By determining the shape of galaxy clusters, we can figure out the shape of the dark matter, which is important for cosmology and galaxy formation studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

DeepMerge: Studying Distant Merging Galaxies with Deep Neural Networks

The hierarchical merging of galaxies is a probe of the cosmos to test the canonical ?CDM cosmology paradigm. A particularly interesting period is "cosmic high noon" at redshifts z? 2?3, during which star formation rates were the highest, and significant amounts of stellar mass assembled into galaxy-scale bodies. Detecting galaxy mergers in observations by conventional automated methods (which use extracted parameters of galaxy structure - asymmetry, clumpiness, concentration etc.) or by visual inspection has proven to be quite time-consuming and prone to errors. Convolutional Neural Network (CNNs) are a primary representative of deep learning algorithms which are used in computer vision tasks by training to detect features in images. CNNs were already used for classification of low-redshift merging galaxies [1, 2]. Here we will use CNN to to learn directly from images (without the need to extract morphology parameters) of distant merging galaxies in order to distinguish between merging and non-merging objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Measurement and calibration of non-linear shear terms in galaxy cluster fields

Introduction Galaxy cluster lensing is a powerful tool for measuring the mass of galaxy clusters, but accurate shear measurement and calibration are critical to obtaining reliable results. This study focuses on the measurement and calibration of weak lensing shears to improve mass estimates in cluster lensing. To deal with the problem, we first developed an image simulation pipeline, jedisim, which utilizes galaxy images extracted from the Hubble Space Telescope (HST) Ultra Deep Field (UDF) and the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS). Methods The simulations represent realistic galaxy distributions and morphologies as input sources. The foreground halo with a Navarro–Frenk–White (NFW) profile is constructed such that the lensing signals of background galaxies can be measured by the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) Science Pipelines. By comparing the measured reduced shear g meas and the true reduced shear g true , we observe non-linearity up to g ≲ 0.6 . We fit polynomials to the data with quadratic correction adequate to g ≲ 0.4 . Meanwhile, we conduct mass estimates using the pzmassfitter code on four different clusters. Results The mass estimate results are significantly improved after applying the shear calibration derived from the present work—from 4.954 ± 0.504 × 1 0 14 M ⊙ to 10.507 ± 0.498 × 1 0 14 M ⊙ after calibration for a simulated cluster with the mass of 10 × 1 0 14 M ⊙ . In multiple cases of validation, the estimated results are all consistent with true cluster mass. Discussion This study yields the first relationship between reality and shape measurement of the LSST Science Pipelines and serves as the first step toward the overall goal of mass calibration in cluster lensing. By addressing the challenges in shear measurement and calibration, we aim to enhance the accuracy and reliability of mass estimates in galaxy cluster lensing studies.

Astronomy & Astrophysics↗
DOE OSTI2023

Identification of Galaxy Shreds in Large Photometric Catalogs Using Convolutional Neural Networks

Contamination from galaxy fragments, identified as sources, is a major issue in large photometric galaxy catalogs. In this paper, we prove that this problem can be easily addressed with computer vision techniques. We use image cutouts to train a convolutional neural network (CNN) to identify cataloged sources that are in reality just star-formation regions and/or shreds of larger galaxies. The CNN reaches an accuracy ~98% on our testing data sets. We apply this CNN to galaxy catalogs from three among the largest surveys available today: the Sloan Digital Sky Survey, the DESI Legacy Imaging Surveys, and the Panoramic Survey Telescope and Rapid Response System Survey. We find that, even when strict selection criteria are used, all catalogs still show a ~5% level of contamination from galaxy shreds. Our CNN gives a simple yet effective solution to clean galaxy catalogs from these contaminants.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Catching Tidal Dwarf Galaxies at a Later Evolutionary Stage with ALFALFA

We present deep optical imaging and photometry of four objects classified as “Almost-Dark” galaxies in the Arecibo Legacy Fast Arecibo L-band Feed Array (ALFALFA) survey because of their gas-rich nature and extremely faint or missing optical emission in existing catalogs. They have H I masses of 10 7 –10 9 M ⊙ and distances of ~9–100 Mpc. Observations with the WIYN 3.5 m telescope and One Degree Imager reveal faint stellar components with central surface brightnesses of ~24–25 m - ag arcsec 2 in the g band. We also present the results of H I synthesis observations with the Westerbork Synthesis Radio Telescope. These Almost-Dark galaxies have been identified as possible tidal dwarf galaxies (TDGs) based on their proximity to one or more massive galaxies. We demonstrate that AGC 229398 and AGC 333576 likely have the low dark matter content and large effective radii representative of TDGs. They are located much farther from their progenitors than previously studied TDGs, suggesting they are older and more evolved. AGC 219369 is likely dark matter dominated, while AGC 123216 has a dark matter content that is unusually high for a TDG, but low for a normal dwarf galaxy. We consider possible mechanisms for the formation of the TDG candidates such as a traditional major merger scenario and gas ejection from a high-velocity flyby. Blind H I surveys like ALFALFA enable the detection of gas-rich, optically faint TDGs that can be overlooked in other surveys, thereby providing a more complete census of the low-mass galaxy population and an opportunity to study TDGs at a more advanced stage of their life cycle.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Milky Way Satellite Census -- II. Galaxy-Halo Connection Constraints Including the Impact of the Large Magellanic Cloud

The population of Milky Way (MW) satellites contains the faintest known galaxies, and thus provides essential insight into galaxy formation and dark matter microphysics. Here, we combine a model of the galaxy--halo connection with newly derived observational selection functions based on searches for satellites in photometric surveys over nearly the entire high-Galactic-latitude sky. In particular, we use cosmological zoom-in simulations of MW-like halos that include realistic Large Magellanic Cloud (LMC) analogs to fit the position-dependent MW satellite luminosity function. We report decisive evidence for the statistical impact of the LMC on the MW satellite population due to an estimated $6.5\pm 1.5$ observed LMC-associated satellites, consistent with the number of LMC satellites inferred from $\textit{Gaia}$ proper motion measurements, confirming the predictions of cold dark matter models for the existence of satellites within satellite halos. Moreover, we infer that the LMC fell into the MW within the last $2\ \rm{Gyr}$ at high confidence. Based on our detailed full-sky modeling, we find that the faintest observed satellites inhabit halos with peak virial masses below $2.2\times 10^{8}\ M_{\rm{\odot}}$ at $95\%$ confidence, and we place the first robust constraints on the fraction of halos that host galaxies in this regime. We predict that the faintest detectable satellites occupy halos with peak virial masses above $10^{6}\ M_{\rm{\odot}}$, highlighting the potential for powerful galaxy formation and dark matter constraints from future dwarf galaxy searches.

79 ASTRONOMY AND ASTROPHYSICS↗