Search Results (116)

Artificial intelligence (AI) has become an integral part of our daily lives as a most extraordinary assistant for providing information and carrying out various tasks. We can have an extensive amount of work done by a dedicated AI that we cannot do ourselves due to our easily distracted minds. AI is given vast amounts of information that we have been gathering for a long time. Using that information, it can analyze large amounts of data and sort it into particular topics and narrow down the solutions or choices we are interested in. With highly sophisticated high-resolution ground- and space-based telescopes and observatories, we have been gathering huge amounts of data. The analysis of these data will require both a considerable amount of manpower and time. Both of these factors can be reduced easily if we train dedicated AIs for spectral line identification and plasma modeling for analysis. While high-accuracy atomic data are needed for precise astrophysical plasma modeling, there are many gaps in the data due to computations of these high-accuracy data being complex and numerically challenging and requiring a significant amount of time. These problems can also be tackled to a very good approximation by training AI for simulations of existing high-accuracy data and producing data that are missing. A general algorithm for such predicted data and its implementation in astrophysical applications is presented. A recent application of AI in measuring oxygen abundance in galaxies is also presented. Full article

The discrepancy between observed galaxy rotation curves and predictions based on visible baryonic matter remains a central challenge in astrophysics. Within the standard ΛCDM framework, these observations are explained through extended halos of non-baryonic dark matter, while alternative approaches such as Modified Newtonian Dynamics reproduce many galactic scaling relations through empirical modifications of low-acceleration dynamics. Recent advances in symbolic machine learning provide a complementary route for investigating whether stable empirical relations can be discovered directly from observational data without imposing strong theoretical priors. In this work, we present the Phenomenological Dark Matter Nonlinear Pipeline, an AI-assisted symbolic discovery framework designed to identify mathematical relationships linking baryonic and observed gravitational accelerations. The analysis was performed using 3175 radial measurements from 175 galaxies derived from SPARC-based rotation-curve catalogs. Symbolic regression was conducted across 173 independent leave-one-galaxy-out validation folds, followed by bootstrap analysis, residual diagnostics, and regime-specific testing. The symbolic search repeatedly converged toward a stable family of non-linear logarithmic acceleration relations exhibiting strong recurrence across independent discovery folds. The resulting empirical relation successfully reproduces the observed Radial Acceleration Relation, naturally generates Baryonic Tully–Fisher Relation like scaling without explicit enforcement during training, and consistently outperforms classical Newtonian gravity while remaining competitive with a MOND-like reference model. Global validation yielded a coefficient of determination of R² = 0.9026 compared with R² = 0.8934 for the MOND-like model and R² = −0.0485 for the Newtonian baseline. Additional analyses demonstrate stable performance across low-acceleration systems, low-surface-brightness galaxies, and other galactic environments. The recovered relation should be interpreted as an empirically discovered scaling law rather than a replacement for General Relativity, ΛCDM, or existing modified-gravity theories. Nevertheless, the repeated emergence of a common symbolic structure across independent validation folds highlights the potential of AI-assisted symbolic discovery as a tool for uncovering interpretable empirical regularities in complex astrophysical datasets. Full article

We present the EGIDE (Edge-on Galaxies in the DESI survey) project—a catalog of 149,215 edge-on galaxy candidates created using the data of the DESI Legacy Imaging Survey DR10 images. The catalog size is ten times greater than its predecessor and covers more than half of the sky. It is constructed in an automatic way, utilizing the full power of manual annotations from the GalaxyZoo volunteers, implemented in the Zoobot neural model, which was fine-tuned to search for edge-on galaxies specifically. To ensure the credibility of the dataset, subsequent manual supervision was performed. The EGIDE catalog provides homogeneous SExtractor photometry in the $griz$ bands, total stellar mass estimates, redshifts for 98% of the sample, star formation rates, and other information. All of this is publicly available at The Edge-on Galaxy Database site. The preliminary analysis focused on differences between edge-on galaxies in the so-called blue sequence and red cloud populations. These galaxies demonstrate distinct properties: the number of redder galaxies decreases with increasing $a/b$ ratio faster than that of the bluer galaxies; galaxy thickness varies with galaxy color: red sequence galaxies are thicker than blue cloud galaxies; the flattening ratio $q=b/a$ increases significantly with total stellar mass $M_{★}$ only among redder cloud galaxies. It is an intriguing result that the same trend of q increasing at the high-mass end is detected by both the statistical models of figures of revolution and direct observations of edge-on galaxies in EGIDE independently. The full extent of this relationship’s validity can only be determined after properly accounting for the contributions of the bulge and the PSF. Full article

Extragalactic background light (EBL), formed by the light radiated and re-radiated by stars, galaxies, and active galactic nuclei throughout the evolution of the Universe, brings the imprint of the history of the rate of the formation of emitting astrophysical objects and the Universe’s expansion. It makes EBL one of the fundamental quantities in cosmology. The optical depth for high-energy emission from the distant active galactic nuclei provides a constraint for the EBL density that is clear from the foreground galactic and other emissions, and, therefore, for the cosmological parameters. In this work, we investigate the high-redshift active galaxy 4C +55.17 (z = 0.902), whose unusually hard and stable high-energy spectrum makes it a valuable probe of EBL-induced absorption effects. Using observations extending from GeV to TeV energies, we reconstruct the optical depth associated with gamma-ray propagation and compare the inferred attenuation with predictions from existing EBL models. The results favor relatively low EBL intensities in the optical and infrared bands, consistent with low-level EBL models and suggesting reduced star formation activity and dust contributions over cosmic evolution. We further explore the cosmological implications of the reconstructed optical depth and derive constraints on the Hubble constant in the range $H_0\approx$ 64–74 km s⁻¹ Mpc⁻¹, with an average value of $H_0=69\pm 4$ km s⁻¹ Mpc⁻¹. These findings demonstrate the potential of hard-spectrum, high-redshift gamma-ray sources such as 4C +55.17 as cosmological probes for studying EBL evolution and addressing current tensions in cosmological parameter measurements. Full article

Simulations of intermediate-mass black holes (IMBHs) in dwarf galaxies within 10 Mpc that host bright nuclear star clusters (NSCs), prime candidates for IMBH formation, using the High Angular Resolution Monolithic Optical and Near-infrared Integral (HARMONI) field spectrograph on the Extremely Large Telescope, probe black hole formation in the early universe. Our approach combines observed surface-brightness profiles from the Hubble Space Telescope (HST), synthetic stellar population spectra, and Jeans Anisotropic Modeling (JAM) for stellar dynamics. Mock HARMONI observations were generated with the HSIM simulator and analyzed in a Bayesian framework to infer IMBH masses down to 0.5% of the NSC mass. In this work, we extend these simulations by constructing improved stellar mass models using SimCADO to simulate imaging with the Multi-AO Imaging Camera for Deep Observations (MICADO). The MICADO data are jointly analyzed with HARMONI kinematics via JAM to reassess IMBH masses and uncertainties. This combined framework enables us to examine how variations in the NSC inner surface-brightness slope influence IMBH mass estimates, providing tighter constraints on low-mass black holes and advancing models for IMBH detection in NSCs. Full article

Axion-like particles (ALPs) can induce energy-dependent irregularities in gamma-ray spectra through ALP-photon oscillation in astrophysical magnetic fields. In this study, we investigate the impact of this effect on the $\gamma$-ray emission from the Andromeda Galaxy (M31). We employ the ${\mathrm{CL}}_{\mathrm{s}}$ method to set constraints on the ALP parameters. We find that ALP-photon oscillation can produce characteristic oscillatory features in the gamma-ray spectrum within the mass range $m_a\sim {10}^{-9}$–${10}^{-7}\mathrm{eV}$. No significant deviation from the standard astrophysical model is observed, allowing us to place constraints on the ALP parameter space. The resulting limits probe a region complementary to existing constraints from other astrophysical observations. Full article

Nearby ($z<0.1$) TeV-detected, high-energy-peaked BL Lacertae objects (HBLs) are among the most prominent extragalactic sources of the highest-energy photons, sometimes detected at energies of ∼10 TeV or beyond. These objects show a strong and complex flux variability, with strong flares and exceptional outbursts, as well as very rapid and large-amplitude TeV-band variations on timescales down to a few minutes during such instances. The higher-energy component of broadband spectral energy distribution (SED) is stretched over the MeV–TeV domain and, generally peaking beyond 100 GeV, has a controversial origin, and different emission scenarios (one- or multi-zone synchrotron self-Compton, hadronic cascades, etc.) are proposed. This paper presents a review of the TeV-band timing and spectral results obtained in the framework of different observational campaigns for nearby HBLs, their implications for different emission scenarios, and basic results from the corresponding SED modelings. Finally, the prospect of filling the observational gaps above some threshold energy by means of the planned projects for the dedicated $\gamma$-ray observations and, consequently, solving the different persisting problems related to the innermost structure, particle acceleration, and emission mechanisms are also presented. Full article

About half the elements heavier than iron in the universe, like silver and gold, are created in the rapid neutron-capture (r-)process. However, today, almost 70 years after the theoretical prediction of this process, it is still highly debated in what type of stellar explosions it can take place. One of the best places to search for answers is in ancient, metal-poor stars formed from the enriched gas. Their chemical makeup is like a time capsule, a direct fingerprint of the elements produced by the stellar generations that came before them. Since the first highly r-process-enhanced star, CS 22892-052 was discovered more than 30 years ago, multiple projects like the Hamburg/ESO r-Process Enhanced Star (HERES) survey, the Chemical Evolution of r-process Elements in Stars (CERES) project, and the r-Process Alliance (RPA) have searched for more r-process-enriched stars in the Milky Way. At the same time, numerous r-process-enriched stars have been discovered in stellar streams and dwarf galaxies. Here we present an overview of recent advances in finding r-process-enriched metal-poor stars and what the detailed chemo-dynamical analysis of these stars can tell us about heavy element nucleosynthesis and the astrophysical site(s) of the r-process. Full article

In this work, the light curve of the Seyfert galaxy Mrk 6 constructed from photometric observations in the B, V, and $R_{\mathrm{c}}$ filters over the period from 5 April 2016 to 1 February 2026 is presented and analyzed. Over the entire monitoring interval (2016–2026), the variability amplitude of the light curve reaches $\mathrm{\Delta }B=1.9$ mag, $\mathrm{\Delta }V=1.5$ mag, and $\mathrm{\Delta }{R}_{\mathrm{c}}=1.4$ mag. During 2024–2026, the galaxy exhibits synchronous photometric variability in the B, V, and $R_{\mathrm{c}}$ filters with an amplitude of ∼0.3 mag. The study also uses spectroscopic observations obtained on 15 and 22 November 2025 and 16 February 2026 at the Shamakhy Astrophysical Observatory (Azerbaijan), as well as on 9 January 2026 at the Fesenkov Astrophysical Institute (Kazakhstan). The fluxes in the H$\beta$ emission line were calibrated using the [O III] $\lambda 5007$ Å line, ensuring consistent relative calibration of the spectral data. A comparison of the optical spectra reveals a pronounced transformation of the H$\beta$ line profile between November 2025 and January 2026. The broad component, clearly present in November 2025, becomes strongly suppressed and nearly disappears in January 2026, while the narrow emission lines remain stable. This behavior is consistent with a changing-look transition, indicating a temporary weakening of the broad-line region emission. The radius of the broad-line region $R_{\mathrm{BLR}}$ was taken to be equal to the average time delays (lags), amounting to ≈20 light days for the H$\beta$ emission and ≈28 light days for the H$\alpha$. Full article

Recently, the experimental realization of a Kapitza potential in a Bose–Einstein condensate (BEC) was reported for the first time in the literature, motivating further theoretical investigations of such a system. At the same time, in the astrophysical context, BEC dark matter models have been widely studied as a possible phenomenological explanation for the dark matter phenomena. We model the galactic structure with an inner cored profile obtained from the ground state equilibrium solution of the Schrödinger–Poisson together with a Kapitza–BEC-like interaction for the tail region. We find reasonable agreement of the model with representative galaxy rotation curves available in the SPARC catalogue. Full article

In this paper, we discuss the atomic models developed for the non-local thermodynamic equilibrium (LTE) analysis of the spectra of two odd-Z chemical elements, the little-studied potassium and copper, whose nuclei are often thought to form in Cosmos through different astrophysical processes. The K I and Cu I atomic models have been developed and updated over the past decade and applied to determine non-LTE abundances of these elements in the hot and cool dwarfs, giants, and supergiants of different metallicities, from solar to extremely low metallicity. The abundances of potassium and copper in old metal-poor halo stars are of considerable interest because these objects bear the imprints of nucleosynthesis in Type II supernovae and hypernovae in the early Galaxy. The vast majority of the studies of the spectra of these atoms have been based on the assumption of LTE. In some cases, this approach has led to incorrect results, which have sometimes affected our understanding of evolutionary processes in stars and stellar systems. The main objective of this article is to highlight the importance of using the non-LTE stellar abundance data to improve or modify existing theoretical models of cosmic chemical evolution. In particular, significantly different results for the copper abundance in old Galactic stars were obtained compared to LTE data. This finding could inspire specialists working in the field of chemodynamic models to search for realistic pathways for the formation of this element in massive stars. Despite this, since the first non-LTE results on the copper abundance in the oldest Galactic stars, LTE data remained in use for several years. This situation seriously hinders progress in research into some certain aspects of cosmic nucleosynthesis. Full article

Matter in the early Universe was nearly uniform, and galaxies emerged through the gravitational growth of small primordial density fluctuations. Astrophysics has been trying to unveil the complex physical phenomena that have caused the formation and evolution of galaxies throughout the 13-billion-year history of the Universe using the first principles of physics. However, since present-day astrophysical big data contain more than 100 explanatory variables, such a conventional methodology faces limits in dealing with such data. We, instead, elucidate the physics of galaxy evolution by applying manifold learning, one of the latest methods of data science, to a feature space spanned by galaxy luminosities and cosmic time. We discovered a low-dimensional nonlinear structure of data points in this space, referred to as the galaxy manifold. We found that the galaxy evolution in the ultraviolet–optical–near-infrared luminosity space is well described by two parameters, star formation and stellar mass evolution, on the manifold. We also discuss a possible way to connect the manifold coordinates to physical quantities. Full article

We show that the FLRW metric, modified to include interrelated variation in the speed of light and gravitational constants, leads to Friedmann equations containing terms that behave like dark matter and dark energy without the cosmological constant. When we permit tired light (TL) to contribute to the redshift due to the expanding universe, thus defined by covarying coupling constants (CCCs), the resulting CCC+TL model has a critical density that is just enough to account for the baryon matter in the universe. The CCC+TL cosmology model is consistent with all of the observations that we had the time and the resources to study, including BAOs (baryon acoustic oscillations), the CMB (cosmic microwave background) sound horizon angular size, the time dilation effect, galaxy formation time scales at cosmic dawn, galaxy rotation curves, gravitational lensing, galaxy cluster and ultra-faint dwarf galaxy dynamics, and the mass, size, density, and luminosity evolution of galaxies. We briefly review them in this paper. Additionally, the new model does not suffer from the coincidence problem of the ΛCDM model and complies with the recent DESI findings of an increasing dark energy density with redshift. We present the fundamentals of the CCC+TL model and discuss its applications to some decisive observations. We have considered temporal variation in the constant for cosmological studies and their spherically symmetric variation in astrophysical situations. We conclude that the illusion of dark matter and dark energy in cosmological and astrophysical observations originates from CCC. Full article

Objective: We examine whether a finite-range scalar–tensor modification of gravity can be simultaneously compatible with cosmological background data, galaxy rotation curves, and local/astrophysical consistency tests, while satisfying the luminal gravitational-wave propagation constraint ($c_T=1$) implied by GW170817 at low redshifts. Methods: We formulate the model at the level of an explicit covariant action and derive the corresponding field equations; for cosmological inferences, we adopt an effective background closure in which the late-time dark-energy density is modulated by a smooth activation function characterized by a length scale $\lambda$ and amplitude $ϵ$. We constrain this background model using Pantheon+, DESI Gaussian Baryon Acoustic Oscillations (BAOs), and a Planck acoustic-scale prior, including an explicit $\Lambda$CDM comparison. We then propagate the inferred characteristic length by fixing $\lambda$ in the weak-field Yukawa kernel used to model 175 SPARC galaxy rotation curves with standard baryonic components and a controlled spherical approximation for the scalar response. Results: The joint background fit yields ${\Omega }_m=0.293\pm 0.007$, $\lambda =7.{69}_{-1.71}^{+1.85}$$\mathrm{Mpc}$, and $H_0=72.33\pm 0.50$$\mathrm{km}{\mathrm{s}}^{-1}{\mathrm{Mpc}}^{-1}$. With $\lambda$ fixed, the baryons + scalar model describes the SPARC sample with a median reduced chi-square of ${\chi }_{\nu }^2=1.07$; for a 14-galaxy subset, this model is moderately preferred over the standard baryons + NFW halo description in the finite-sample information criteria, with a mean $\Delta$AICc outcome in favor of the baryons + scalar model (≈2.8). A Vainshtein-type screening completion with $\Lambda =1.3\times {10}^{-8}$ eV satisfies Cassini, Lunar Laser Ranging, and binary pulsar bounds while keeping the kpc scales effectively unscreened. For linear growth observables, we adopt a conservative General Relativity-like baseline (${\mu }_0=0$) and show that current $f{\sigma }_8$ data are consistent with ${\mu }_0\simeq 0$ for our best-fit background; the model predicts $S_8=0.791$, consistent with representative cosmic-shear constraints. Conclusions: Within the present scope (action-level weak-field dynamics for galaxy modeling plus an explicitly stated effective closure for background inference), the results support a mutually compatible characteristic length at the Mpc scale; however, a full perturbation-level implementation of the covariant theory remains an issue for future work, and the role of cold dark matter beyond galaxy scales is not ruled out. Full article

We present a supervised machine learning classification of sources from the Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) Pathfinder datasets: miniJPAS and J-NEP. Leveraging crossmatches with spectroscopic and photometric catalogs, we construct a robust labeled dataset comprising 14,594 sources classified into extended (galaxies) and point-like (stars and quasars) objects. We assess dataset representativeness using UMAP analysis, confirming broad and consistent coverage of feature space. An XGBoost classifier, with hyperparameters tuned using automated optimization, is trained using purely photometric data (60-band J-PAS magnitudes) and combined photometric and morphological features, with performance thoroughly evaluated via ROC and purity–completeness metrics. Incorporating morphology significantly improves classification, outperforming the baseline classifications available in the catalogs. Permutation importance analysis reveals morphological parameters, particularly concentration, normalized peak surface brightness, and PSF, alongside photometric features around 4000 and 6900 Å, as crucial for accurate classifications. We release a value-added catalog with our models for star-galaxy classification, enhancing the utility of miniJPAS and J-NEP for subsequent cosmological and astrophysical analyses. Full article