arXiv subjects

Gabrijela Zaharijas

Publications and source records attributed to Gabrijela Zaharijas.

At least 19 recordsLinked to original sources

arXiv2026

High-energy Multi-messenger Emission from Galaxy Clusters in the Local Universe

The origin of diffuse neutrinos and $γ$-rays is unknown, and galaxy clusters hosting AGN and starburst galaxies are the most probable sources of these cosmic messengers. In this work, we investigate the diffuse $γ$-ray and neutrino emission from the Virgo, Perseus, and Coma clusters using a detailed numerical method, combining MHD simulations with Monte Carlo methods. The MHD simulation provides the distributions of temperature, gas, and magnetic field in clusters. The Monte Carlo simulations are used to investigate the cosmic-ray (CR) propagation in ICM and subsequently the secondaries stemming from CRs. Our primary assumption is that CR injection scales with the gas density of clusters, providing a physically motivated approximation. High-density regions in clusters are associated with strong turbulence and prominent shock structures, making them natural sites for efficient CR acceleration. Our predicted $γ$-ray flux from the individual clusters lies well below the present LHAASO upper limits. The MAGIC observations of the central source NGC $1275$ of the Perseus cluster are significantly higher than our results. Further, we estimated the cumulative $γ$-ray and neutrino fluxes from clusters with masses $\gtrsim 5\times 10^{13}, M_{\odot}$ in the local Universe (within $500$ Mpc). The diffuse $γ$-ray flux reported by the Fermi-LAT collaboration is significantly higher than our results. Our predictions are consistent with IceCube's existing upper limits on the unresolved neutrino flux from galaxy clusters ($M > 10^{14}, M_{\odot}$) up to $z = 2$.

astro-ph.HE↗

arXiv2026

High-energy Neutrino and Gamma Ray Emission from Clusters-like Perseus

We calculate the high-energy gamma-ray and neutrino emissions from galaxy clusters like Perseus that host active galactic nuclei (AGNs). Our primary objective is to distinguish the emission from the central source, such as NGC$1275$, from the diffuse emission originating in the outskirts of the Perseus cluster. Due to a unique magnetic-field configuration, CRs with energy $\leq 10^{17}$ eV can be confined within these structures over cosmological time scales, and generate secondary particles, including neutrinos and gamma-rays, through interactions with the background gas and photons. We employ three-dimensional cosmological magnetohydrodynamical simulations of structure formation to model the turbulent intracluster medium (ICM). We propagate CRs in intracluster medium (ICM) and intergalactic medium using multi-dimensional Monte Carlo simulations, considering all relevant photohadronic, photonuclear, and hadronuclear interactions. We also include the cosmological evolution of sources like Perseus. By comparing our results with the existing upper limits from IceCube for galaxy clusters and the sensitivity of CTA, we predict that these observatories could potentially establish a new class of astrophysical sources capable of emitting high-energy multi-messenger signals. We also compute the contribution from clusters like Perseus to the diffuse neutrino and gamma-ray background.

astro-ph.HE↗

arXiv2026

Dark Matter and Galaxy Cross-Correlations with the Cherenkov Telescope Array Observatory

The Cherenkov Telescope Array Observatory (CTAO) will be a ground-based Cherenkov telescope performing wide-sky surveys, ideal for anisotropy studies such as cross-correlations with tracers of the cosmic large-scale structure. Cross-correlations can shed light on high-energy $γ$-ray sources and potentially reveal exotic signals from particle dark matter. In this work, we investigate CTAO sensitivity to cross-correlation signals between $γ$-ray emission and galaxy distributions. We find that by using dense, low-redshift catalogs like 2MASS, and for integration times around 50 hours, this technique achieves sensitivities to both annihilating and decaying dark matter signals that are competitive with those from dwarf galaxy and cluster analyses.

astro-ph.HE↗

arXiv2026

Towards a foundation model for astrophysical source detection: An End-to-End Gamma-Ray Data Analysis Pipeline Using Deep Learning

The increasing volume of gamma-ray data demands new analysis approaches that can handle large-scale datasets while providing robustness for source detection. We present a Deep Learning (DL) based pipeline for detection, localization, and characterization of gamma-ray sources. We extend our AutoSourceID (ASID) method, initially tested with \textit{Fermi}-LAT simulated data and optical data (MeerLICHT), to Cherenkov Telescope Array Observatory (CTAO) simulated data. This end-to-end pipeline demonstrates a versatile framework for future application to other surveys and potentially serves as a building block for a foundational model for astrophysical source detection.

astro-ph.IM↗

arXiv2026

Probing the Parameter Space of Axion-Like Particles Using Simulation-Based Inference

Axion-like particles (ALPs), hypothetical pseudoscalar particles that couple to photons, are among the most actively investigated candidates for new physics beyond the Standard Model. Their interaction with gamma rays in the presence of astrophysical magnetic fields can leave characteristic, energy-dependent modulations in observed spectra. Capturing such subtle features requires precise statistical inference, but standard likelihood-based methods often fall short when faced with complex models, large number of nuisance parameters and limited analytical tractability. In this work, we investigate the application of simulation-based inference (SBI), specifically Truncated Marginal Neural Ratio Estimation (TMNRE), to constrain ALP parameters using simulated observations from the upcoming Cherenkov Telescope Array Observatory (CTAO). We model the gamma-ray emission from the active galactic nucleus NGC 1275, accounting for photon-ALP mixing, extragalactic background light (EBL) absorption, and the full CTAO instrument response. Leveraging the Swyft framework, we infer posteriors for the ALP mass and coupling strength and demonstrate its potential to extract meaningful constraints on ALPs from future real gamma-ray data with CTAO.

astro-ph.HE↗

arXiv2025

Prospects on detection of the Fermi Bubbles with CTAO

In 2010, the Fermi Gamma-ray Space Telescope observed two gamma-ray emitting structures, the Fermi Bubbles (FBs), that extend up to 55° above and below the Galactic plane and that seem to emanate from the Galactic center region. Although the spectrum at latitudes |b| > 10° has a softening or a cutoff around 100 GeV, the one at the base of the FBs, |b| <10°, extends up to about 1 TeV without a significant cutoff in the Fermi LAT data. The mechanism behind the FBs production is currently under debate. More observations of the FBs at different energies are required to improve our understanding of their origin. Recently, H.E.S.S. and HAWC observatory have set upper limits on the FBs. In this work, we assess the sensitivity of the Cherenkov Telescope Array Observatory (CTAO) using the "alpha configuration" in the South site to detect the FBs and investigate the optimal strategies for their detection at low latitudes. We simulate the observations using the official CTAO science tool gammapy, considering several benchmark models for the FBs and the interstellar emission and test different observational strategies taking advantage of the proposed CTAO consortium surveys. We use these simulations to estimate the CTAO sensitivity to the FBs.

astro-ph.HE↗

arXiv2025

Search for cosmic-ray induced gamma-ray emission from local galaxy clusters using Fermi-LAT data

Galaxy clusters are the most massive gravitationally bound structures in the Universe. Even if clusters are nearly virialized structures, they undergo merging processes, creating merging shocks, and suffer from feedback from galaxies and Active Galactic Nuclei; causing complex turbulent motions and amplifying their magnetic fields. These processes act as acceleration mechanisms for the plasma of the intracluster medium (ICM), originating a population of cosmic rays (CRs). Leptonic CRs have long been detected, but we should also expect a CR hadronic population that, through interactions with the ICM, should produce neutral pions that decay into gamma-rays. The detection of diffuse gamma-ray emission from galaxy clusters is one of the long-awaited milestones for the high-energy astroparticle physics community. Still, no unambiguous detection has yet been obtained. In this talk, we will present the results of a combined cluster analysis searching for CR-induced gamma-ray signals, using 16 years of Fermi-LAT data. In our previous work (di Mauro et al. 2023) we obtained from the combined analysis of 49 local galaxy clusters (12 years of data) a hint of signal between 2.5-3 sigma. These results are consistent with other works as well, which consistently find a non-vanishing hint of signal, around the detection threshold. In this new work, we use a sample of near, well-known galaxy clusters and develop CR-induced emission templates using well-established X-ray measurements for calibration, assuming self similarity for the members of our sample. To strengthen the robustness of our analysis, we define benchmark models to encapsulate the uncertainties in the spectral and spatial profiles for the CR-induced emission and perform the standard template-fitting analysis using the likelihood ratio test.

astro-ph.HE↗

arXiv2025

Detecting dark matter sub-halos in the Galactic plane with the Cherenkov Telescope Array Observatory

Numerous observations confirm the existence of dark matter (DM) at astrophysical and cosmological scales. Theory and simulations of galaxy formation predict that DM should cluster on small scales in bound structures called sub-halos or DM clumps. While the most massive DM sub-halos host baryonic matter, less massive, unpopulated sub-halos could be abundant in the Milky Way (MW), as well and yield high-energy gamma rays as final products of DM annihilation. Recently, it has been highlighted that the brightest halos should also have a sizeable extension in the sky. In this study, we examine the prospects offered by the Cherenkov Telescope Array Observatory (CTAO), a next-generation gamma-ray instrument, for detecting and characterizing such objects. Previous studies have primarily focused on high-latitude observations; here, we assess the potential impact of the CTAO's Galactic Plane Survey, which will provide unprecedentedly deep survey data for the inner five degrees of the Galactic plane. Our modeling accounts for tidal effects on the sub-halo population, examining the conditions under which DM sub-halos can be detected and distinguished from conventional astrophysical sources. We find that regions a few degrees above or below the Galactic plane offer the highest likelihood for DM sub-halo detection. For an individual sub-halo -- the brightest from among various realizations of the MW subhalo population -- we find that detection at the 5$σ$ level is achievable for an annihilation cross section of $\langle σv \rangle \sim 3\times10^{-25}$ cm$^3$/s for TeV-scale DM annihilating into $b\bar{b}$. For a full population study, depending on the distribution and luminosity model of Galactic sub-halos, yet unconstrained cross sections in the range $\langle σv \rangle \sim 10^{-23}-10^{-22}$ cm$^3$/s for TeV DM candidates are necessary for the brightest sub-halos to be detected.

astro-ph.HE↗

arXiv2023

Prospects for annihilating dark matter from M31 and M33 observations with the Cherenkov Telescope Array

M31 and M33 are the closest spiral galaxies and the largest members (together with the Milky Way) of the Local group, which makes them interesting targets for indirect dark matter searches. In this paper, we present studies of the expected sensitivity of the Cherenkov Telescope Array (CTA) to an annihilation signal from weakly interacting massive particles from M31 and M33. We show that a 100 h long observation campaign will allow CTA to probe annihilation cross-sections up to $\langleσ\upsilon\rangle\approx 5\cdot10^{-25}$ cm$^{3}$s$^{-1}$ for the $τ^{+}τ^{-}$ annihilation channel (for M31, at a DM mass of 0.3 TeV), improving the current limits derived by HAWC by up to an order of magnitude. We present an estimate of the expected CTA sensitivity, by also taking into account the contributions of the astrophysical background and other possible sources of systematic uncertainty. We also show that CTA might be able to detect the extended emission from the bulge of M31, detected at lower energies by the Fermi/LAT.

astro-ph.HE↗

arXiv2023

Mind the gap: The discrepancy between simulation and reality drives interpretations of the Galactic Center Excess

The Galactic Center Excess (GCE) in GeV gamma rays has been debated for over a decade, with the possibility that it might be due to dark matter annihilation or undetected point sources such as millisecond pulsars (MSPs). This study investigates how the gamma-ray emission model ($γ$EM) used in Galactic center analyses affects the interpretation of the GCE's nature. To address this issue, we construct an ultra-fast and powerful inference pipeline based on convolutional Deep Ensemble Networks. We explore the two main competing hypotheses for the GCE using a set of $γ$EMs with increasing parametric freedom. We calculate the fractional contribution ($f_{\mathrm{src}}$) of a dim population of MSPs to the total luminosity of the GCE and analyze its dependence on the complexity of the $γ$EM. For the simplest $γ$EM, we obtain $f_{\mathrm{src}} = 0.10 \pm 0.07$, while the most complex model yields $f_{\mathrm{src}} = 0.79 \pm 0.24.$ In conclusion, we find that the statement about the nature of the GCE (dark matter or not) strongly depends on the assumed $γ$EM. The quoted results for $f_{\mathrm{src}}$ do not account for the additional uncertainty arising from the fact that the observed gamma-ray sky is out-of-distribution concerning the investigated $γ$EM iterations. We quantify the reality gap between our $γ$EMs using deep-learning-based One-Class Deep Support Vector Data Description networks, revealing that all employed $γ$EMs have gaps to reality. Our study casts doubt on the validity of previous conclusions regarding the GCE and dark matter, and underscores the urgent need to account for the reality gap and consider previously overlooked ''out of domain'' uncertainties in future interpretations.

astro-ph.HE↗

arXiv2022

Detecting and characterizing pulsar haloes with the Cherenkov Telescope Array

The recently identified source class of pulsar haloes may be numerous and bright enough in the TeV range to constitute a large fraction of the sources that will be observed with the Cherenkov Telescope Array (CTA). In this work, we quantify the prospects for detecting and characterizing pulsar haloes in observations of the projected Galactic Plane Survey (GPS), using a simple phenomenological diffusion model for individual pulsar haloes and their population in the Milky Way. Our ability to uncover pulsar haloes and constrain their main physical parameters in the CTA GPS is assessed in the framework of a full spatial-spectral likelihood analysis of simulated survey observations, using the most recent estimates for the instrument response function and prototypes for the science tools. For a model setup representative of the halo around Geminga, we find that about three hundred objects could give rise to detectable emission in the GPS survey. Yet, only a third of them could be identified through their energy-dependent morphology, and only one-tenth of them would allow the derivation of strong constraints on key physical parameters like the magnitude or extent of suppressed diffusion around the pulsar. We also provide a list of known pulsars that could be hosting a detectable (Geminga-like) halo in the GPS and assess the robustness of our findings against several systematic uncertainties.

astro-ph.HE↗

arXiv2022

AutoSourceID-Light. Fast Optical Source Localization via U-Net and Laplacian of Gaussian

$\textbf{Aims}$. With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is paramount. We present AutoSourceID-Light (ASID-L), an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images. $\textbf{Methods}$. We show that the AutoSourceID-Light algorithm based on U-shaped networks and enhanced with a Laplacian of Gaussian filter (Chen et al. 1987) enables outstanding performances in the localization of sources. A U-Net (Ronneberger et al. 2015) network discerns the sources in the images from many different artifacts and passes the result to a Laplacian of Gaussian filter that then estimates the exact location. $\textbf{Results}$. Application on optical images of the MeerLICHT telescope demonstrates the great speed and localization power of the method. We compare the results with the widely used SExtractor (Bertin & Arnouts 1996) and show the out-performances of our method. AutoSourceID-Light rapidly detects more sources not only in low and mid crowded fields, but particularly in areas with more than 150 sources per square arcminute.

astro-ph.IM↗

arXiv2022

Snowmass2021 Cosmic Frontier White Paper: Puzzling Excesses in Dark Matter Searches and How to Resolve Them

Intriguing signals with excesses over expected backgrounds have been observed in many astrophysical and terrestrial settings, which could potentially have a dark matter origin. Astrophysical excesses include the Galactic Center GeV gamma-ray excess detected by the Fermi Gamma-Ray Space Telescope, the AMS antiproton and positron excesses, and the 511 and 3.5 keV X-ray lines. Direct detection excesses include the DAMA/LIBRA annual modulation signal, the XENON1T excess, and low-threshold excesses in solid state detectors. We discuss avenues to resolve these excesses, with actions the field can take over the next several years.

hep-ph↗

arXiv2022

Snowmass2021: Vera C. Rubin Observatory as a Flagship Dark Matter Experiment

Establishing that Vera C. Rubin Observatory is a flagship dark matter experiment is an essential pathway toward understanding the physical nature of dark matter. In the past two decades, wide-field astronomical surveys and terrestrial laboratories have jointly created a phase transition in the ecosystem of dark matter models and probes. Going forward, any robust understanding of dark matter requires astronomical observations, which still provide the only empirical evidence for dark matter to date. We have a unique opportunity right now to create a dark matter experiment with Rubin Observatory Legacy Survey of Space and Time (LSST). This experiment will be a coordinated effort to perform dark matter research, and provide a large collaborative team of scientists with the necessary organizational and funding supports. This approach leverages existing investments in Rubin. Studies of dark matter with Rubin LSST will also guide the design of, and confirm the results from, other dark matter experiments. Supporting a collaborative team to carry out a dark matter experiment with Rubin LSST is the key to achieving the dark matter science goals that have already been identified as high priority by the high-energy physics and astronomy communities.

hep-ex↗

arXiv2021

Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge

At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and {\it k}-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog (4FGL) in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of $\sim$ 70%, as long as balanced data sets are used in classification training. In https://github.com/bapanes/AutoSourceID, we publish our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources.

astro-ph.HE↗

arXiv2019

Probing the Fundamental Nature of Dark Matter with the Large Synoptic Survey Telescope

Astrophysical and cosmological observations currently provide the only robust, empirical measurements of dark matter. Future observations with Large Synoptic Survey Telescope (LSST) will provide necessary guidance for the experimental dark matter program. This white paper represents a community effort to summarize the science case for studying the fundamental physics of dark matter with LSST. We discuss how LSST will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational couplings to the Standard Model, and compact object abundances. Additionally, we discuss the ways that LSST will complement other experiments to strengthen our understanding of the fundamental characteristics of dark matter. More information on the LSST dark matter effort can be found at https://lsstdarkmatter.github.io/ .

astro-ph.CO↗

arXiv2019

Search for $γ$-ray emission from dark matter particle interactions from Andromeda and Triangulum Galaxies with the Fermi Large Area Telescope

The Andromeda (M31) and Triangulum (M33) galaxies are the closest Local Group galaxies to the Milky Way, being only 785 and 870 kpc away. These two galaxies provide an independent view of high-energy processes that are often obscured in our own Galaxy, including possible signals of dark matter (DM) particle interactions. The Fermi Large Area Telescope (Fermi-LAT) preliminary eight year list of sources includes both M31, which is detected as extended with a size of about 0.4$^\circ$, and M33, which is detected as a point-like source. The spatial morphology of M31 $γ$-ray emission could trace a population of unresolved sources and energetic particles originating in sources not related to massive star formation. Alternatively, the $γ$-ray emission could also be an indication of annihilation or decay of DM particles. We investigate these two possibilities using almost 10 years of data from the Fermi LAT. An interpretation that involves only a DM $γ$-ray emission is in tension with the current limits from other searches, such as those targeting Milky Way dwarf spheroidal galaxies. When we include a template of astrophysical emission, tuned on $γ$-ray data or from observations of these galaxies in other wavelengths, we do not find any significant evidence for a DM contribution and we set limits for the annihilation cross section that probe the thermal cross section for DM masses up to a few tens of GeV in the $b\bar{b}$ and $τ^+τ^-$ channels. For models where the DM substructures have masses above $10^{-6}$ solar masses our limits probe the DM interpretation of the Fermi LAT Galactic center excess. We provide also the lower limit for the DM decay time assuming the same spatial models of the DM distribution in M31 and M33.

astro-ph.HE↗

arXiv2018

Millisecond pulsar origin of the Galactic center excess and extended gamma-ray emission from Andromeda - a closer look

A new measurement of a spatially extended gamma-ray signal from the center of the Andromeda galaxy (M31) has been recently published by the Fermi-LAT collaboration, reporting that the emission broadly resembles the so-called Galactic center excess (GCE) of the Milky Way (MW). At the same time, evidence is accumulating on a millisecond pulsar (MSPs) origin for the GCE. These elements prompt us to compare the mentioned observations with what is, perhaps, the simplest model for an MSP population, solely obtained by rescaling of the MSP luminosity function determined in the local MW disk via the respective stellar mass of the systems. It is remarkable that without free fitting parameters, this model can account for both the energetics and the morphology of the GCE within uncertainties. For M31, the estimated luminosity due to primordial MSPs is expected to contribute only about a quarter of the detected emission, although a dominant contribution cannot be excluded given the large uncertainties. If correct, the model predicts that the M31 disk emission due to MSP is not far below the present upper bound. We also discuss a few refinements of this simple model. In particular, we use the correlation between globular cluster gamma-ray luminosity and stellar encounter rate to gauge the dynamical MSP formation in the bulge. This component is expected to contribute to the GCE only at a level $\lesssim 5\%$, but it may be of some importance in explaining the signal's morphology in the inner region of the Galaxy. We also comment on some effects which may lead to violations of the simple scaling used, on alternative models, and on future perspectives for improved diagnostics.

astro-ph.HE↗