1. Prospects for ▫$\gamma-ray$▫ observations of the Perseus galaxy cluster with the Cherenkov Telescope ArrayK. Abe, Saptashwa Bhattacharyya, Judit Pérez Romero, Samo Stanič, Veronika Vodeb, Serguei Vorobiov, Gabrijela Zaharijas, Danilo Zavrtanik, Marko Zavrtanik, Miha Živec, 2024, izvirni znanstveni članek Opis: Galaxy clusters are expected to be both dark matter (DM) reservoirs and storage rooms for the cosmic-ray protons (CRp) that accumulate along the cluster’s formation history. Accordingly, they are excellent targets to search for signals of DM annihilation and decay at γ-ray energies and are predicted to be sources of large-scale γ-ray emission due to hadronic interactions in the intracluster medium (ICM). In this paper, we estimate the sensitivity of the Cherenkov Telescope Array (CTA) to detect diffuse γ-ray emission from the Perseus galaxy cluster. We first perform a detailed spatial and spectral modelling of the expected signal for both the DM and the CRp components. For each case, we compute the expected CTA sensitivity accounting for the CTA instrument response functions. The CTA observing strategy of the Perseus cluster is also discussed. In the absence of a diffuse signal (non-detection), CTA should constrain the CRp to thermal energy ratio X500 within the characteristic radius R500 down to about X500 < 0.003, for a spatial CRp distribution that follows the thermal gas and a CRp spectral index αCRp = 2.3. Under the optimistic assumption of a pure hadronic origin of the Perseus radio mini-halo and depending on the assumed magnetic field profile, CTA should measure αCRp down to about ∆αCRp ≃ 0.1 and the CRp spatial distribution with 10% precision, respectively. Regarding DM, CTA should improve the current ground-based γ-ray DM limits from clusters observations on the velocity- averaged annihilation cross-section by a factor of up to ∼ 5, depending on the modelling of DM halo substructure. In the case of decay of DM particles, CTA will explore a new region of the parameter space, reaching models with τχ > 10[sup]27 s for DM masses above 1 TeV. These constraints will provide unprecedented sensitivity to the physics of both CRp acceleration and transport at cluster scale and to TeV DM particle models, especially in the decay scenario.
Ključne besede: cosmic ray experiments, dark matter experiments, galaxy clusters, gamma ray experiments, very-high energy gamma rays, Cherenkov Telescope Array Observatory, Perseus galaxy cluster
Objavljeno v RUNG: 09.10.2024; Ogledov: 108; Prenosov: 0
 Celotno besedilo (9,26 MB)
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2. Dark matter line searches with the Cherenkov Telescope ArrayS. Abe, Saptashwa Bhattacharyya, Christopher Eckner, Judit Pérez Romero, Samo Stanič, Veronika Vodeb, Serguei Vorobiov, Gabrijela Zaharijas, Danilo Zavrtanik, Marko Zavrtanik, Miha Živec, 2024, izvirni znanstveni članek Opis: Monochromatic gamma-ray signals constitute a potential smoking gun signature for annihilating
or decaying dark matter particles that could relatively easily be distinguished from astrophysical
or instrumental backgrounds. We provide an updated assessment of the sensitivity of
the Cherenkov Telescope Array (CTA) to such signals, based on observations of the Galactic
centre region as well as of selected dwarf spheroidal galaxies. We find that current limits
and detection prospects for dark matter masses above 300 GeV will be significantly improved,
by up to an order of magnitude in the multi-TeV range.
This demonstrates that CTA will set a new standard for gamma-ray astronomy also in this respect, as the world's largest and most sensitive high-energy gamma-ray observatory, in particular due to its exquisite energy resolution at TeV energies and the adopted observational strategy focussing
on regions with large dark matter densities.
Throughout our analysis, we use up-to-date instrument response functions, and we thoroughly
model the effect of instrumental systematic uncertainties in our statistical treatment. We further present results for other potential signatures with sharp spectral features, e.g. box-shaped spectra, that would likewise very clearly point to a particle dark matter origin.
Ključne besede: dark matter experiments, dark matter theory, gamma ray experiments, Cherenkov Telescope Array Observatory
Objavljeno v RUNG: 24.09.2024; Ogledov: 260; Prenosov: 0
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3. Search for a signal from dark matter sub-halos with the galactic plane survey of CTA Observatory : master's thesisZoja Rokavec, 2024, magistrsko delo Opis: Dark matter (DM), known to be a dominant matter component in the Universe,
has been searched for extensively, yet remains undetected. One of the promising
avenues of detecting a DM signal is to observe the so called ’DM sub-halos’ within
our galaxy. These sub-halos, which are numerous within the Milky Way, are formed
by the clustering of DM, as predicted by cosmological simulations, and most of
them lack baryonic matter counterparts, making them challenging to detect. How-
ever, the annihilation or decay of Weakly Interacting Massive Particles (WIMPs),
a leading candidate for DM, within these sub-halos is expected to produce very
high-energy (VHE) photons (called gamma-rays) at TeV energies, offering possible
indirect DM detection.
In this thesis, we focus on the Galactic Plane Survey (GPS) of the Cherenkov Tele-
scope Array Observatory (CTAO), an upcoming ground-based gamma-ray obser-
vatory, which promises unprecedented sensitivity and resolution in the detection
of cosmic gamma-ray sources in the ∼ 30 GeV to ∼ 100 TeV energy range. As
dark sub-halos are expected to appear as unidentified (point) sources in the CTAO
GPS data, we employ a machine learning (ML)-based approach, the AutoSour-
ceID framework, leveraging U-shaped networks (U-Nets) and Laplacian of Gaus-
sian (LoG) filter, for automatic source detection and localization, and apply it to
simulated GPS data. We establish detection thresholds for U-Nets trained on dif-
ferently scaled counts (counts, square root or log of counts) and identify which
approach offers best results (in terms of flux sensitivity and location accuracy).
Our findings suggest that using log-scaled counts yields a factor of 1.7 lower flux
threshold compared to counts alone. In addition, we compare our ML outcomes
with traditional methods; however, this comparison is not straightforward, as ML
and traditional approaches fundamentally differ in their methodologies and un-
derlying assumptions. Nevertheless, The flux threshold obtained using log-scaled
counts is comparable to that of the traditional likelihood-based detection method
implemented in the Gammapy library, although further study is needed to estab-
lish a more definitive comparison. These preliminary results also suggest that the
flux threshold for detecting 90% of true sources with the ML approach is approx-
imately two times lower than the sensitivity reported for the GPS in the CTAO
publication. Although these results are not directly comparable due to differences
in methodology, they hint that ML methods may offer superior performance in
certain scenarios. Furthermore, we discuss the implications of our results on the
sensitivity to DM sub-halos, improving it by a factor of 4, highlighting the possi-
bility of detecting at least one sub-halo with a cross section approximately ⟨σv⟩ =
2.4 × 10−23 cm3 /s.
Ključne besede: Cherenkov Telescope Array Observatory, dark matter, sub-halos, machine learning, gamma-rays, master's thesis
Objavljeno v RUNG: 06.09.2024; Ogledov: 401; Prenosov: 4
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4. Detection of gamma-ray sources and search for dark matter signals with Cherenkov Telescope Array surveys : dissertationVeronika Vodeb, 2024, doktorska disertacija Opis: Gamma rays serve as important messengers in modern astrophysics, offering insights into the most energetic processes in the cosmos. Advancements in gamma-ray astronomy, facilitated by international scientific collaboration, have expanded its reach and capabilities. The Fermi-Large Area Telescope (Fermi-LAT) has so far contributed immensely to our understanding of the gamma-ray sky at GeV energies, surveying numerous source classes. At the same time, ground-based observatories like H.E.S.S., MAGIC, VERITAS, HAWC, and LHASSO, enable the exploration of high-energy (HE) phenomena across various energy scales, reaching the PeV range. The collective data from Fermi-LAT and ground-based instruments provide a comprehensive picture of cosmic phenomena across diverse energy regimes. Efforts to catalog HE gamma-ray sources have resulted in the detection of several thousand sources at GeV, including Pulsar Wind Nebulae (PWNe), Supernova Remnants (SNRs), pulsars, blazars, and Gamma-Ray Bursts (GRBs), with the observational capability to study their spectral and spatial morphology enhancing our understanding of their origin and evolution.
Looking ahead, the Cherenkov Telescope Array (CTA) represents the next frontier in ground-based gamma-ray astronomy. Operating at very high energies (VHE) between 20 GeV and 300 TeV, CTA's improved sensitivity, angular resolution, and expanded field of view (FoV) promise enhanced imaging of extended sources and performance of large-scale surveys. CTA's Key Science Projects (KSPs) include the Extragalactic (EGAL) survey, a survey of a quarter of the extragalactic sky, and the Galactic Plane Survey (GPS), a survey of the entire Galactic Plane (GP). The KSPs will receive dedicated observation time and careful planning to ensure the optimization of their scientific output. As CTA is currently entering the construction phase, simulations are being extensively employed to predict its response to various signals, playing a vital role in comprehending CTA's response and sensitivity to different signals. The derived predictions are paving the way for estimating the CTA's scientific output, informing the observational strategy, and ensuring its success in maximizing the contribution to HE gamma-ray astronomy.
In this thesis, I contribute to assessing the sensitivity of the CTA surveys, particularly the GPS and the EGAL survey, to diverse astrophysical sources and signals. Focusing on the GPS, I delve into understanding the detectability of pulsar halos, which emit multi-TeV gamma rays, the detection of which was recently reported by the HAWC Observatory. The study involves a spatial-spectral likelihood analysis, evaluating sensitivity to simple Gaussian extended sources and physically modeled sources. Employing a template-fitting approach, I analyze CTA's GPS sensitivity to extended sources and explore the prospects for pulsar halo detection and characterization. A preliminary population study addresses the visibility of pulsar halos to CTA's GPS and explores the angular sensitivity to extended sources. The thesis sets the detectability prospects of pulsar halos with CTA and investigates what fraction of the preliminary pulsar halo population CTA will be able to probe.
The thesis extends its exploration into the persistent mystery of dark matter (DM), a fundamental puzzle in cosmology. The search for DM signals remains a vigorous pursuit in the physics community, utilizing various astrophysical messengers resulting from DM particle annihilation or decay. I investigate the potential of CTA's GPS to detect dark sub-halos within our galaxy, utilizing a similar approach as in the sensitivity assessment to pulsar halos, applied to recent sub-halo population simulations. Furthermore, the thesis addresses the intricate task of disentangling DM components from astrophysical contributions in the observed gamma-ray sky. In terms of the EGAL survey, employing advanced statistical methods such as the cross-correlation technique, I explore the prospects of using CTA's EGAL survey to correlate the Extragalactic Gamma-ray Background (EGRB) with galaxy catalogs, providing insights into DM properties.
While traditional methods rely on likelihood analysis with background subtraction or template fitting, the emergence of supervised machine learning (ML) offers a novel, potentially more effective approach for cataloging the sky. The thesis touches upon the usability of ML in the high and VHE gamma-ray sky. My study focuses on CTA's GPS and utilizes deep-learning-based algorithms in a detection pipeline for the automatic classification of extended sources from gamma-ray data.
As CTA stands at the forefront of gamma-ray astronomy as the next-generation observatory, the research presented in this thesis contributes a small step towards answering the open questions about pulsar halos and DM, showcasing the potential breakthroughs that may emerge from CTA's observations. The detailed likelihood analysis performed aims to advance our understanding of these enigmas, from the physical intricacies of pulsar halos to the elusive nature of DM, driven by curiosity about the continuous exploration of the Universe's mysteries.
Ključne besede: high-energy gamma-ray astronomy, astroparticle physics, Cherenkov Telescope Array, pulsar halos, dark matter, dissertations
Objavljeno v RUNG: 06.06.2024; Ogledov: 783; Prenosov: 10
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5. The third Fermi Large Area Telescope catalog of gamma-ray pulsarsD. A. Smith, S. Abdollahi, M. Ajello, M. Bailes, L. Baldini, J. Ballet, M. G. Baring, C. Bassa, J. Becerra Gonzalez, R. Bellazzini, Gabrijela Zaharijas, 2023, izvirni znanstveni članek Ključne besede: gamma ray astrophysics, catalogues, pulsars
Objavljeno v RUNG: 15.01.2024; Ogledov: 1151; Prenosov: 7
Celotno besedilo (10,64 MB)
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6. Fermi-GBM discovery of GRB 221009A : an extraordinarily bright GRB from onset to afterglowS. Lesage, P. Veres, M. S. Briggs, A. Goldstein, D. Kocevski, E. Burns, C. A. Wilson-Hodge, P. N. Bhat, D. Huppenkothen, Gabrijela Zaharijas, 2023, izvirni znanstveni članek Ključne besede: gamma-ray bursts, GRB 221009A, cosmic ray astronomy
Objavljeno v RUNG: 15.01.2024; Ogledov: 1102; Prenosov: 5
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7. Mind the gap : the discrepancy between simulation and reality drives interpretations of the Galactic Center ExcessSascha Caron, Christopher Eckner, Luc Hendriks, Gudlaugur Johannesson, Roberto Ruiz de Austri, Gabrijela Zaharijas, 2023, izvirni znanstveni članek Ključne besede: gamma-ray astrophysics, dark matter, galactic center
Objavljeno v RUNG: 15.01.2024; Ogledov: 1340; Prenosov: 7
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8. The fourth catalog of active galactic nuclei detected by the Fermi Large Area Telescope : data release 3M. Ajello, L. Baldini, J. Ballet, D. Bastieri, J. Becerra Gonzalez, R. Bellazzini, A. Berretta, E. Bissaldi, R. Bonino, Gabrijela Zaharijas, 2022, izvirni znanstveni članek Ključne besede: gamma ray astrophysics, active galactic nucleai
Objavljeno v RUNG: 15.01.2024; Ogledov: 1090; Prenosov: 6
Celotno besedilo (1,00 MB)
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9. A gamma-ray pulsar timing array constrains the nanohertz gravitational wave backgroundM. Ajello, W. B. Atwood, L. Baldini, J. Ballet, G. Barbiellini, D. Bastieri, R. Bellazzini, A. Berretta, B. Bhattacharyya, Gabrijela Zaharijas, 2022, izvirni znanstveni članek Ključne besede: pulsar timing array, gravitational waves
Objavljeno v RUNG: 15.01.2024; Ogledov: 1100; Prenosov: 0
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10. AutoSourceID-Classifier : star-galaxy classification using a convolutional neural network with spatial informationF. Stoppa, Saptashwa Bhattacharyya, R. Ruiz de Austri, P. Vreeswijk, S. Caron, Gabrijela Zaharijas, S. Bloemen, G. Principe, D. Malyshev, Veronika Vodeb, 2023, izvirni znanstveni članek Opis: Aims: Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification’s reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images.
Methods: The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts
generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and
additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results.
Results: We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor.
While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced
error propagation inherent in ASID-C’s direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.
Ključne besede: astronomical databases, data analysis, statistics, image processing
Objavljeno v RUNG: 12.12.2023; Ogledov: 1402; Prenosov: 6
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