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A. Bulgarelli

Publications and source records attributed to A. Bulgarelli.

At least 37 records · Page 2Linked to original sources

AGILE gamma-ray detection of the exceptional GRB 221009A

Gamma-ray emission in the MeV-GeV range from explosive cosmic events is of invaluable relevance to understanding physical processes related to the formation of neutron stars and black holes. Here we report on the detection by the AGILE satellite in the MeV-GeV energy range of the remarkable long-duration gamma-ray burst GRB 221009A. The AGILE onboard detectors have good exposure to GRB 221009A during its initial crucial phases. Hard X-ray/MeV emission in the prompt phase lasted hundreds of seconds, with the brightest radiation being emitted between 200 and 300 seconds after the initial trigger. Very intense GeV gamma-ray emission is detected by AGILE in the prompt and early afterglow phase up to 10,000 seconds. Time-resolved spectral analysis shows time-variable MeV-peaked emission simultaneous with intense power-law GeV radiation that persists in the afterglow phase. The coexistence during the prompt phase of very intense MeV emission together with highly nonthermal and hardening GeV radiation is a remarkable feature of GRB 221009A. During the prompt phase, the event shows spectrally different MeV and GeV emissions that are most likely generated by physical mechanisms occurring in different locations. AGILE observations provide crucial flux and spectral gamma-ray information regarding the early phases of GRB 221009A during which emission in the TeV range was reported.

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Quantum Convolutional Neural Networks for the detection of Gamma-Ray Bursts in the AGILE space mission data

Quantum computing represents a cutting-edge frontier in artificial intelligence. It makes use of hybrid quantum-classical computation which tries to leverage quantum mechanic principles that allow us to use a different approach to deep learning classification problems. The work presented here falls within the context of the AGILE space mission, launched in 2007 by the Italian Space Agency. We implement different Quantum Convolutional Neural Networks (QCNN) that analyze data acquired by the instruments onboard AGILE to detect Gamma-Ray Bursts from sky maps or light curves. We use several frameworks such as TensorFlow-Quantum, Qiskit and PennyLane to simulate a quantum computer. We achieved an accuracy of 95.1% on sky maps with QCNNs, while the classical counterpart achieved 98.8% on the same data, using however hundreds of thousands more parameters.

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The Online Observation Quality System Implementation for the ASTRI Mini-Array Project

The ASTRI Mini-Array project, led by the Italian National Institute for Astrophysics, aims to construct and operate nine Imaging Atmospheric Cherenkov Telescopes for high-energy gamma-ray source study and stellar intensity interferometry. Located at the Teide Astronomical Observatory in Tenerife, the project's software is essential for remote operation, emphasizing the need for prompt feedback on observations. This contribution introduces the Online Observation Quality System (OOQS) as part of the Supervisory Control And Data Acquisition (SCADA) software. OOQS performs real-time data quality checks on data from Cherenkov cameras and Intensity Interferometry instruments. It provides feedback to SCADA and operators, highlighting abnormal conditions and ensuring quick corrective actions for optimal observations. Results are archived for operator visualization and further analysis. The OOQS data quality pipeline prototype utilizes a distributed application with three main components to handle the maximum array data rate of 1.15 Gb/s. The first is a Kafka consumer that manages the data stream from the Array Data Acquisition System through Apache Kafka, handling the data serialization and deserialization involved in the transmission. The data stream is divided into batches of data written in files. The second component monitors new files and conducts analyses using the Slurm workload scheduler, leveraging its parallel processing capabilities and scalability. Finally, the process results are collected by the last component and stored in the Quality Archive.

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Deep Learning for AGILE Anticoincidence System's Background Prediction from Orbital and Attitude Parameters

AGILE is an Italian Space Agency (ASI) space mission launched in 2007 to study X-ray and gamma-ray phenomena in the energy range from $\sim$20 keV to $\sim$10 GeV. The AGILE AntiCoincidence System (ACS) detects hard-X photons in the 50 - 200 keV energy range and continuously stores each panel's count rates in the telemetry. We developed a new Deep Learning (DL) model to predict the background of the AGILE ACS top panel using the satellite's orbital and attitude parameters. This model aims to learn how the orbital and spinning modulations of the satellite impact the background level of the ACS top panel. The DL model executes a regression problem, and is trained with a supervised learning technique on a dataset larger than twenty million orbital parameters' configurations. Using a test dataset, we evaluated the trained model by comparison of the predicted count rates with the real ones. The results show that the model can reconstruct the background count rates of the ACS top panel with an accuracy of 96.7\%, considering the orbital modulation and spinning of the satellite. Starting from these promising results, we are developing an anomaly detection method to detect Gamma-ray Bursts when the differences between predicted and real count rates exceed a predefined threshold.

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Multi-wavelength observations of the lensed quasar PKS 1830$-$211 during the 2019 $γ$-ray flare

PKS 1830$-$211 is a $γ$-ray emitting, high-redshift (z $= 2.507 \pm 0.002$), lensed flat-spectrum radio quasar. During the period mid-February to mid-April 2019, this source underwent a series of strong $γ$-ray flares that were detected by both AGILE-GRID and Fermi-LAT, reaching a maximum $γ$-ray flux of $F_{\rm E>100 MeV}\approx 2.3\times10^{-5}$ ph cm$^{-2}$ s$^{-1}$. Here we report on a coordinated campaign from both on-ground (Medicina, OVRO, REM, SRT) and orbiting facilities (AGILE, Fermi, INTEGRAL, NuSTAR, Swift, Chandra), with the aim of investigating the multi-wavelength properties of PKS 1830$-$211 through nearly simultaneous observations presented here for the first time. We find a possible break in the radio spectra in different epochs above 15 GHz, and a clear maximum of the 15 GHz data approximately 110 days after the $γ$-ray main activity periods. The spectral energy distribution shows a very pronounced Compton dominance (> 200) which challenges the canonical one-component emission model. Therefore we propose that the cooled electrons of the first component are re-accelerated to a second component by, e.g., kink or tearing instability during the $γ$-ray flaring periods. We also note that PKS 1830$-$211 could be a promising candidate for future observations with both Compton satellites (e.g., e-ASTROGAM) and Cherenkov arrays (CTAO) which will help, thanks to their improved sensitivity, in extending the data availability in energy bands currently uncovered.

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Performance of the joint LST-1 and MAGIC observations evaluated with Crab Nebula data

Aims. LST-1, the prototype of the Large-Sized Telescope for the upcoming Cherenkov Telescope Array Observatory, is concluding its commissioning in Observatorio del Roque de los Muchachos on the island of La Palma. The proximity of LST-1 (Large-Sized Telescope 1) to the two MAGIC (Major Atmospheric Gamma Imaging Cherenkov) telescopes permits observations of the same gamma-ray events with both systems. Methods. We describe the joint LST-1+MAGIC analysis pipeline and use simultaneous Crab Nebula observations and Monte Carlo simulations to assess the performance of the three-telescope system. The addition of the LST-1 telescope allows the recovery of events in which one of the MAGIC images is too dim to survive analysis quality cuts. Results. Thanks to the resulting increase in the collection area and stronger background rejection, we find a significant improvement in sensitivity, allowing the detection of 30% weaker fluxes in the energy range between 200 GeV and 3 TeV. The spectrum of the Crab Nebula, reconstructed in the energy range ~60 GeV to ~10 TeV, is in agreement with previous measurements.

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Prospects for $γ$-ray observations of the Perseus galaxy cluster with the Cherenkov Telescope Array

Galaxy clusters are expected to be 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 gamma-ray energies and are predicted to be sources of large-scale gamma-ray emission due to hadronic interactions in the intracluster medium. We estimate the sensitivity of the Cherenkov Telescope Array (CTA) to detect diffuse gamma-ray emission from the Perseus galaxy cluster. We perform a detailed spatial and spectral modelling of the expected signal for the DM and the CRp components. For each, we compute the expected CTA sensitivity. The observing strategy of Perseus is also discussed. In the absence of a diffuse signal (non-detection), CTA should constrain the CRp to thermal energy ratio within the radius $R_{500}$ down to about $X_{500}<3\times 10^{-3}$, for a spatial CRp distribution that follows the thermal gas and a CRp spectral index $α_{\rm CRp}=2.3$. 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 $α_{\rm CRp}$ down to about $Δα_{\rm CRp}\simeq 0.1$ and the CRp spatial distribution with 10% precision. Regarding DM, CTA should improve the current ground-based gamma-ray DM limits from clusters observations on the velocity-averaged annihilation cross-section by a factor of up to $\sim 5$, 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 $τ_χ>10^{27}$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.

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Observations of the Crab Nebula and Pulsar with the Large-Sized Telescope Prototype of the Cherenkov Telescope Array

CTA (Cherenkov Telescope Array) is the next generation ground-based observatory for gamma-ray astronomy at very-high energies. The Large-Sized Telescope prototype (LST-1) is located at the Northern site of CTA, on the Canary Island of La Palma. LSTs are designed to provide optimal performance in the lowest part of the energy range covered by CTA, down to $\simeq 20$ GeV. LST-1 started performing astronomical observations in November 2019, during its commissioning phase, and it has been taking data since then. We present the first LST-1 observations of the Crab Nebula, the standard candle of very-high energy gamma-ray astronomy, and use them, together with simulations, to assess the basic performance parameters of the telescope. The data sample consists of around 36 hours of observations at low zenith angles collected between November 2020 and March 2022. LST-1 has reached the expected performance during its commissioning period - only a minor adjustment of the preexisting simulations was needed to match the telescope behavior. The energy threshold at trigger level is estimated to be around 20 GeV, rising to $\simeq 30$ GeV after data analysis. Performance parameters depend strongly on energy, and on the strength of the gamma-ray selection cuts in the analysis: angular resolution ranges from 0.12 to 0.40 degrees, and energy resolution from 15 to 50%. Flux sensitivity is around 1.1% of the Crab Nebula flux above 250 GeV for a 50-h observation (12% for 30 minutes). The spectral energy distribution (in the 0.03 - 30 TeV range) and the light curve obtained for the Crab Nebula agree with previous measurements, considering statistical and systematic uncertainties. A clear periodic signal is also detected from the pulsar at the center of the Nebula.

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Sensitivity of the Cherenkov Telescope Array to spectral signatures of hadronic PeVatrons with application to Galactic Supernova Remnants

The local Cosmic Ray (CR) energy spectrum exhibits a spectral softening at energies around 3~PeV. Sources which are capable of accelerating hadrons to such energies are called hadronic PeVatrons. However, hadronic PeVatrons have not yet been firmly identified within the Galaxy. Several source classes, including Galactic Supernova Remnants (SNRs), have been proposed as PeVatron candidates. The potential to search for hadronic PeVatrons with the Cherenkov Telescope Array (CTA) is assessed. The focus is on the usage of very high energy $γ$-ray spectral signatures for the identification of PeVatrons. Assuming that SNRs can accelerate CRs up to knee energies, the number of Galactic SNRs which can be identified as PeVatrons with CTA is estimated within a model for the evolution of SNRs. Additionally, the potential of a follow-up observation strategy under moonlight conditions for PeVatron searches is investigated. Statistical methods for the identification of PeVatrons are introduced, and realistic Monte--Carlo simulations of the response of the CTA observatory to the emission spectra from hadronic PeVatrons are performed. Based on simulations of a simplified model for the evolution for SNRs, the detection of a $γ$-ray signal from in average 9 Galactic PeVatron SNRs is expected to result from the scan of the Galactic plane with CTA after 10 hours of exposure. CTA is also shown to have excellent potential to confirm these sources as PeVatrons in deep observations with $\mathcal{O}(100)$ hours of exposure per source.

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Multi-wavelength study of the galactic PeVatron candidate LHAASO J2108+5157

LHAASO J2108+5157 is one of the few known unidentified Ultra-High-Energy (UHE) gamma-ray sources with no Very-High-Energy (VHE) counterpart, recently discovered by the LHAASO collaboration. We observed LHAASO J2108+5157 in the X-ray band with XMM-Newton in 2021 for a total of 3.8 hours and at TeV energies with the Large-Sized Telescope prototype (LST-1), yielding 49 hours of good quality data. In addition, we analyzed 12 years of Fermi-LAT data, to better constrain emission of its High-Energy (HE) counterpart 4FGL J2108.0+5155. We found an excess (3.7 sigma) in the LST-1 data at energies E > 3 TeV. Further analysis in the whole LST-1 energy range assuming a point-like source, resulted in a hint (2.2 sigma) of hard emission which can be described with a single power law with photon index Gamma = 1.6 +- 0.2 between 0.3 - 100 TeV. We did not find any significant extended emission which could be related to a Supernova Remnant (SNR) or Pulsar Wind Nebula (PWN) in the XMM-Newton data, which puts strong constraints on possible synchrotron emission of relativistic electrons. The LST-1 and LHAASO observations can be explained as inverse Compton-dominated leptonic emission of relativistic electrons with a cutoff energy of $100^{+70}_{-30}$ TeV. The low magnetic field in the source imposed by the X-ray upper limits on synchrotron emission is compatible with a hypothesis of a PWN or a TeV halo. The lack of a pulsar in the neighborhood of the UHE source is a challenge to the PWN/TeV-halo scenario. The UHE gamma rays can also be explained as $π^0$ decay-dominated hadronic emission due to interaction of relativistic protons with one of the two known molecular clouds in the direction of the source. The hard spectrum in the LST-1 band is compatible with protons escaping a shock around a middle-aged SNR because of their high low-energy cut-off.

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The AFISS web platform for the correlation of high-energy transient events

In the multi-messenger era, facilities share their results with the scientific community through networks such as the General Coordinates Network to study transient phenomena (e.g., Gamma-ray bursts) and implement real-time analysis pipelines to detect transient events, reacting to science alerts received from other observatories. The fast analysis of transient events is crucial for detecting counterparts of gravitational waves and neutrino candidate events. In this context, collecting scientific results from different high-energy satellites observing the same transient event represents a key step in improving the statistical significance of the high-energy candidate events. This project aims to develop a system and a web platform to share information and scientific results of transient events between high-energy satellites with INAF participation (AGILE, FERMI, INTEGRAL and SWIFT). The AFISS platform implements the COMET VO- Event broker and provides a web portal where the users visualize the list of transient events detected by multi-messenger facilities and received through the GCN. The web portal could show, for each event, a summary of the scientific results shared by the real-time analysis pipelines and a list of time-correlated transient events. In addition, the platform is ready to receive results from participating facilities on sub-threshold events (STE) that cannot be shared with the community due to the low statistical significance. If the platform finds a time correlation between two or more STEs, it can promote them to science alerts. The web interface shows the list of STEs with possible time correlation with other STEs or science alerts. The platform notifies the users with an email when a new transient event is received.

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The Online Observation Quality System Software Architecture for the ASTRI Mini-Array Project

The ASTRI Mini-Array is an international collaboration led by the Italian National Institute for Astrophysics. This project aims to construct and operate an array of nine Imaging Atmospheric Cherenkov Telescopes to study gamma-ray sources at very high energy (TeV) and perform stellar intensity interferometry observations. We describe the software architecture and the technologies used to implement the Online Observation Quality System (OOQS) for the ASTRI Mini-Array project. The OOQS aims to execute data quality checks on the data acquired in real-time by the Cherenkov cameras and intensity interferometry instruments, and provides feedback to both the Central Control System and the Operator about abnormal conditions detected. The OOQS can notify other sub-systems, triggering their reaction to promptly correct anomalies. The results from the data quality analyses (e.g. camera plots, histograms, tables, and more) are stored in the Quality Archive for further investigation and they are summarised in reports available to the Operator. Once the OOQS results are stored, the operator can visualize them using the Human Machine Interface. The OOQS is designed to manage the high data rate generated by the instruments (up to 4.5 GB/s) and received from the Array Data Acquisition System through the Kafka service. The data are serialized and deserialized during the transmission using the Avro framework. The Slurm workload scheduler executes the analyses exploiting key features such as parallel analyses and scalability.

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The RTApipe framework for the gamma-ray real-time analysis software development

In the multi-messenger era, coordinating observations between astronomical facilities is mandatory to study transient phenomena (e.g. Gamma-ray bursts) and is achieved by sharing information with the scientific community through networks such as the Gamma-ray Coordinates Network. The facilities usually develop real-time scientific analysis pipelines to detect transient events, alert the astrophysical community, and speed up the reaction time of science alerts received from other observatories. We present in this work the RTApipe framework, designed to facilitate the development of real-time scientific analysis pipelines for present and future gamma-ray observatories. This framework provides pipeline architecture and automatisms, allowing the researchers to focus on the scientific aspects and integrate existing science tools developed with different technologies. The pipelines automatically execute all the configured analyses during the data acquisition. This framework can be interfaced with science alerts networks to perform follow-up analysis of transient events shared by other facilities. The analyses are performed in parallel and can be prioritised. The workload is highly scalable on a cluster of machines. The framework provides the required services using containerisation technology for easy deployment. We present the RTA pipelines developed for the AGILE space mission and the prototype of the SAG system for the ground-based future Cherenkov Telescope Array observatory confirming that the RTApipe framework can be used to successfully develop pipelines for the gamma-ray observatories, both space and ground-based.

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Preliminary Results of a Deep Learning Anomaly Detection Method to Identify Gamma-Ray Bursts in the AGILE Anticoincidence System

AGILE is a space mission launched in 2007 to study X-ray and gamma-ray astronomy. The AGILE team developed real-time analysis pipelines to detect transient phenomena such as Gamma-Ray Bursts (GRBs) and to react to external science alerts received by other facilities. The AGILE anti-coincidence system (ACS) comprises five panels (four lateral and one on the top) that surround the AGILE detectors to reject background charged particles. It can also detect hard X-ray photons in the energy range 50 - 200 KeV. The acquisition of the ACS data produces a time series for each panel. These time series can be merged in a single multivariate time series (MTS). We present in this work a new Deep Learning model for GRBs detection in the MTSs, generated by the ACS, using an anomaly detection technique. The model is implemented with a Deep Convolutional Neural Network autoencoder architecture. We trained the model with an unsupervised learning algorithm using a dataset of MTSs randomly extracted from the AGILE ACS data. The reconstruction error of the autoencoder is used as the anomaly score to classify the MTS. If the anomaly score is higher than a predefined threshold, the MTS is flagged as a GRB. The trained model is evaluated using a list of MTSs containing GRBs. The tests confirmed the model's ability to detect transient events, providing a new promising technique to identify GRBs in the ACS data that can be implemented in the AGILE real-time analysis pipeline.

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Preliminary Results of a New Deep Learning Method to Detect and Localize GRBs in the AGILE/GRID Sky Maps

AGILE is an ASI space mission launched in 2007 to study X-ray and gamma-ray phenomena in the energy range from $\sim20$ keV to $\sim10$ GeV. The AGILE Team developed a real-time analysis pipeline for the fast detection of transient sources, and the follow-up of external science alerts received through networks such as the General Coordinates Network. We developed a new Deep Learning method for detecting and localizing Gamma-Ray Bursts (GRB) in the AGILE/GRID sky maps. We trained the model using sky maps with GRBs simulated in a radius of 20 degrees from the center of the map, which is larger than 99.5 \% of the error region present in the GRBWeb catalog. We also plan to apply this method to search for counterparts of gravitational wave events, which typically have a wider localization error region. The method comprises two Deep Learning models implemented with two Convolutional Neural Networks. The first model detects and filters sky maps containing a GRB, while the second model localizes its position. We trained and tested the models using simulated data. The detection model achieves an accuracy of 95.7 \%, and the localization model has a mean error lower than 0.8 degrees. We configured a Docker container with all the required software for data simulation and deployed it using the Amazon Web Service to calculate the p-value distribution under different conditions. With the p-value distribution, we can calculate the statistical significance of a detection.

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ASTRI Mini-Array Core Science at the Observatorio del Teide

The ASTRI (Astrofisica con Specchi a Tecnologia Replicante Italiana) Project led by the Italian National Institute for Astrophysics (INAF) is developing and will deploy at the Observatorio del Teide a mini-array (ASTRI Mini-Array) composed of nine telescopes similar to the small-size dual-mirror Schwarzschild-Couder telescope (ASTRI-Horn) currently operating on the slopes of Mt. Etna in Sicily. The ASTRI Mini-Array will surpass the current Cherenkov telescope array differential sensitivity above a few tera-electronvolt (TeV), extending the energy band well above hundreds of TeV. This will allow us to explore a new window of the electromagnetic spectrum, by convolving the sensitivity performance with excellent angular and energy resolution figures. In this paper we describe the Core Science that we will address during the first four years of operation, providing examples of the breakthrough results that we will obtain when dealing with current open questions, such as the acceleration of cosmic rays, cosmology and fundamental physics and the new window, for the TeV energy band, of the time-domain astrophysics.

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Extragalactic Observatory Science with the ASTRI Mini-Array at the Observatorio del Teide

The ASTRI Mini-Array is a next-generation system of nine imaging atmospheric Cherenkov telescopes that is going to be built at the Observatorio del Teide site. After a first phase, in which the instrument will be operated as an experiment prioritizing a schedule of primary science cases, an observatory phase is foreseen in which other significant targets will be pointed. We focus on the observational feasibility of extragalactic sources and on astrophysical processes that best complement and expand the ASTRI Mini-Array core science, presenting the most relevant examples that are at reach of detection over long-term time scales and whose observation can provide breakthrough achievements in the very-high energy extragalactic science. Such examples cover a wide range of $γ$-ray emitters, including the study of AGN low states in the multi-TeV energy range, the possible detection of Seyfert galaxies with long exposures and the searches of dark matter lines above 10 TeV. Simulations of the presented objects show that the instrument performance will be competitive at multi-TeV energies with respect to current arrays of Cherenkov telescopes.

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Galactic Observatory Science with the ASTRI Mini-Array at the Observatorio del Teide

The ASTRI (Astrofisica con Specchi a Tecnologia Replicante Italiana) Mini-Array will be composed of nine imaging atmospheric Cherenkov telescopes at the Observatorio del Teide site. The array will be best suited for astrophysical observations in the 0.3-200 TeV range with an angular resolution of few arc-minutes and an energy resolution of 10-15\%. A core-science programme in the first four years will be devoted to a limited number of key targets, addressing the most important open scientific questions in the very-high energy domain. At the same time, thanks to a wide field of view of about 10 degrees, ASTRI Mini-Array will observe many additional field sources, which will constitute the basis for the long-term observatory programme that will eventually cover all the accessible sky. In this paper, we review different astrophysical Galactic environments, e.g. pulsar wind nebulae, supernova remnants, and gamma-ray binaries, and show the results from a set of ASTRI Mini-Array simulations of some of these field sources made to highlight the expected performance of the array (even at large offset angles) and the important additional observatory science that will complement the core-science program.

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