74 research outputs found
Cosmic Rays origin studies in the W 44 region with Fermi-LAT and MAGIC observations
No full textW44 is a well-known Supernova Remnant (SNR) observed in high-energy gamma-rays, widely studied to investigate cosmic ray (CR) acceleration. Several analyses of the W44 surroundings showed the presence of a gamma-ray emission offset from the radio SNR shell. This emission is thought to originate from escaped high-energy CRs. We present a detailed analysis of the W44 region as seen by Fermi-LAT, focusing on the spatial and spectral characteristics of both W44 SNR and its surroundings. The spatial analysis was limited to energies above 1 GeV in order to exploit the improved angular resolution of the instrument, deriving a detailed description of the region morphology. The spectral analysis was extended down to 100 MeV, favouring the hadronic origin of gamma-rays. Observations of the North-Western region of W44 were conducted with the MAGIC telescopes in the very-high-energy gamma-ray band. We analysed MAGIC data above 130 GeV exploiting the spatial information derived from the Fermi-LAT analysis above 1 GeV. Here we show the results of both analyses and the combined Fermi-LAT and MAGIC spectra. An interpretation model was developed, assuming that the gamma-ray emission from the surroundings is due to clouds located near W44 and illuminated by CRs escaping along the SNR’s magnetic field lines, thus obtaining constraining information on the diffusion coefficient of the escaped CRs
MAGIC observations of the diffuse γ-ray emission in the vicinity of the Galactic center
No full textAims. In the presence of a sufficient amount of target material, γ-rays can be used as a tracer in the search for sources of Galactic cosmic rays (CRs). Here we present deep observations of the Galactic center (GC) region with the MAGIC telescopes and use them to infer the underlying CR distribution and to study the alleged PeV proton accelerator at the center of our Galaxy.Methods. We used data from ≈100 h observations of the GC region conducted with the MAGIC telescopes over five years (from 2012 to 2017). Those were collected at high zenith angles (58−70 deg), leading to a larger energy threshold, but also an increased effective collection area compared to low zenith observations. Using recently developed software tools, we derived the instrument response and background models required for extracting the diffuse emission in the region. We used existing measurements of the gas distribution in the GC region to derive the underlying distribution of CRs. We present a discussion of the associated biases and limitations of such an approach.Results. We obtain a significant detection for all four model components used to fit our data (Sgr A*, “Arc”, G0.9+0.1, and an extended component for the Galactic Ridge). We observe no significant difference between the γ-ray spectra of the immediate GC surroundings, which we model as a point source (Sgr A*) and the Galactic Ridge. The latter can be described as a power-law with index 2 and an exponential cut-off at around 20 TeV with the significance of the cut-off being only 2σ. The derived cosmic-ray profile hints to a peak at the GC position and with a measured profile index of 1.2 ± 0.3 is consistent with the 1/r radial distance scaling law, which supports the hypothesis of a CR accelerator at the GC. We argue that the measurements of this profile are presently limited by our knowledge of the gas distribution in the GC vicinity.Key words: gamma rays: general / gamma rays: ISM / Galaxy: center / cosmic rays⋆ Tables and sky maps are only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/cat/J/A+A/642/A190⋆⋆ Corresponding authors: Christian Fruck, Ievgen Vovk, Yuki Iwamura and Marcel Strzys (e-mail: [email protected])
Pybkgmodel - a background modelling toolbox for the CTA
No full textDespite the advancement in background rejection techniques, observation of the very-high-energy gamma-ray sky by imaging atmospheric Cherenkov telescopes (IACTs) are subject to an irreducible background from gamma-like hadron- or electron-induced air showers. The determination of this residual background is crucial for accurate spectral and spatial measurements. The Cherenkov Telescope Array (CTA) will become the next generation of IACTs. To unveil its full potential, the improved reconstruction performance of CTA needs to be coupled with a reliable background estimate across the entire field of view. This may become especially important in the case of the planned surveys of large areas of the sky. In this contribution we will present pybkgmodel, an open-source python software package developed for CTA. It aims at providing in a consistent way the various background modelling methods, based on the experience from current IACTs such as H.E.S.S, MAGIC, and VERITAS. It is designed as a toolbox allowing a user to easily choose the optimal reconstruction approach for various target regions or a combination of several algorithms. We will introduce the design of the package as well as demonstrate its functionality using data for the CTA Large-Sized Telescope prototype (LST-1). © Copyright owned by the author(s) under the terms of the Creative Commons
Exploring the region encompassing γ Cygni SNR and MAGIC J2019+408 with the GMRT at 325 and 610 MHz
No full textContext. γ Cygni is a young supernova remnant located in the Cygnus region. MAGIC (Major Atmospheric Gamma Imaging Cherenkov) telescopes detected TeV emission (MAGIC J2019+408) to the north-west of this remnant, ∼5′ from its border. Aims. We want to identify the radio sources within the region encompassing γ Cygni and MAGIC J2019+408 to shed light on their nature and investigate if these radio sources could be potential contributors to gamma-ray emission. Methods. We carried out a detailed study of the data we obtained with a survey of the Cygnus region at 325 and 610 MHz with the Giant Metrewave Radio Telescope. Results. We detected several radio sources in the region where the radio and the TeV emission overlap, as well as several areas of enhanced radio emission. In particular, two of these areas of diffuse enhanced emission may correspond to the supernova remnant interacting with a high density region, which seems to be the best candidate for the MAGIC source. Another two radio sources, which may or may not contribute to the gamma rays, are also spatially coincident with the emission peak of the MAGIC TeV source. One of them displays a rather peculiar extended morphology whose nature is completely unknown. Conclusions. We have identified the radio sources overlapping γ Cygni and MAGIC J2019+408 and have shown that their potential gamma-ray contribution is likely not dominant. In addition, some of the studied sources show peculiar physical characteristics that deserve deeper multi-wavelength observations
Pybkgmodel - a background modelling toolbox for the CTA
No full textDespite the advancement in background rejection techniques, observation of the very-high-energy gamma-ray sky by imaging atmospheric Cherenkov telescopes (IACTs) are subject to an irreducible background from gamma-like hadron- or electron-induced air showers. The determination of this residual background is crucial for accurate spectral and spatial measurements.
The Cherenkov Telescope Array (CTA) will become the next generation of IACTs. To unveil its full potential, the improved reconstruction performance of CTA needs to be coupled with a reliable background estimate across the entire field of view. This may become especially important in the case of the planned surveys of large areas of the sky.
In this contribution we will present pybkgmodel, an open-source python software package de-veloped for CTA. It aims at providing in a consistent way the various background modelling methods, based on the experience from current IACTs such as H.E.S.S, MAGIC, and VERITAS. It is designed as a toolbox allowing a user to easily choose the optimal reconstruction approach for various target regions or a combination of several algorithms. We will introduce the design of the package as well as demonstrate its functionality using data for the CTA Large-Sized Telescope prototype (LST-1)
Pybkgmodel - a background modelling toolbox for the CTA
No full textDespite the advancement in background rejection techniques, observation of the very-high-energy gamma-ray sky by imaging atmospheric Cherenkov telescopes (IACTs) are subject to an irreducible background from gamma-like hadron- or electron-induced air showers. The determination of this residual background is crucial for accurate spectral and spatial measurements.The Cherenkov Telescope Array (CTA) will become the next generation of IACTs. To unveil its full potential, the improved reconstruction performance of CTA needs to be coupled with a reliable background estimate across the entire field of view. This may become especially important in the case of the planned surveys of large areas of the sky.In this contribution we will present pybkgmodel, an open-source python software package developed for CTA. It aims at providing in a consistent way the various background modelling methods, based on the experience from current IACTs such as H.E.S.S, MAGIC, and VERITAS. It is designed as a toolbox allowing a user to easily choose the optimal reconstruction approach for various target regions or a combination of several algorithms. We will introduce the design of the package as well as demonstrate its performance using simulations for the CTA Large-Sized Telescope prototype (LST-1)
Author Correction: Proton acceleration in thermonuclear nova explosions revealed by gamma rays (Nature Astronomy, (2022), 6, 6, (689-697), 10.1038/s41550-022-01640-z)
No full textIn the version of this article initially published, there was an error in the scale described in the right-hand y-axis label of Fig. 1. Flux density (Jy), now presented on a scale from “1, 10, 102”, was originally shown as “10, 102”. The image has been corrected in the HTML and PDF versions of the article. Further, the Source Data for Fig. 1 have now been replaced online
Very high energy observations of the Seyfert galaxy NGC 4151 with MAGIC Indication of another gamma-ray obscured candidate neutrino source
No full textAbe, K. et al.--Full list of authors: Abe, K.; Abe, S.; Abhir, J.; Abhishek, A.; Acciari, V. A.; Aguasca-Cabot, A.; Agudo, I.; Aniello, T.; Ansoldi, S.; Antonelli, L. A.; Arbet Engels, A.; Arcaro, C.; Arnesen, T. T. H.; Asano, K.; Babić, A.; Bakshi, C.; Barres de Almeida, U.; Barrio, J. A.; Barrios-Jiménez, L.; Batković, I.; Baxter, J.; Becerra González, J.; Bednarek, W.; Bernardini, E.; Bernete, J.; Berti, A.; Besenrieder, J.; Bigongiari, C.; Biland, A.; Blanch, O.; Bonnoli, G.; Bošnjak, Ž.; Bronzini, E.; Burelli, I.; Campoy-Ordaz, A.; Carosi, A.; Carosi, R.; Carretero-Castrillo, M.; Castro-Tirado, A. J.; Cerasole, D.; Ceribella, G.; Chai, Y.; Cifuentes, A.; Contreras, J. L.; Cortina, J.; Covino, S.; D'Amico, G.; Da Vela, P.; Dazzi, F.; De Angelis, A.; De Lotto, B.; de Menezes, R.; Delfino, M.; Delgado, J.; Delgado Mendez, C.; Di Pierro, F.; Di Tria, R.; Di Venere, L.; Dinesh, A.; Dominis Prester, D.; Donini, A.; Dorner, D.; Doro, M.; Eisenberger, L.; Elsaesser, D.; Escudero, J.; Fariña, L.; Foffano, L.; Font, L.; Fröse, S.; Fukazawa, Y.; García López, R. J.; Garczarczyk, M.; Gasparyan, S.; Gaug, M.; Giesbrecht Paiva, J. G.; Giglietto, N.; Giordano, F.; Gliwny, P.; Godinović, N.; Gradetzke, T.; Grau, R.; Green, D.; Green, J. G.; Günther, P.; Hadasch, D.; Hahn, A.; Hassan, T.; Heckmann, L.; Herrera Llorente, J.; Hrupec, D.; Imazawa, R.; Israyelyan, D.; Jahanvi, J.; Jiménez Martínez, I.; Jiménez Quiles, J.; Jormanainen, J.; Kankkunen, S.; Kayanoki, T.; Konrad, J.; Kouch, P. M.; Kubo, H.; Kushida, J.; Láinez, M.; Lamastra, A.; Lindfors, E.; Lombardi, S.; Longo, F.; López-Coto, R.; López-Moya, M.; López-Oramas, A.; Loporchio, S.; Lulić, L.; Lyard, E.; Majumdar, P.; Makariev, M.; Mallamaci, M.; Maneva, G.; Manganaro, M.; Mangano, S.; Mannheim, K.; Marchesi, S.; Mariotti, M.; Martínez, M.; Maruševec, P.; Mas-Aguilar, A.; Mazin, D.; Menchiari, S.; Méndez Gallego, J.; Menon, S.; Miceli, D.; Miranda, J. M.; Mirzoyan, R.; Molero González, M.; Molina, E.; Mondal, H. A.; Moralejo, A.; Nakamori, T.; Nanci, C.; Neustroev, V.; Nickel, L.; Nievas Rosillo, M.; Nigro, C.; Nikolić, L.; Nilsson, K.; Nishijima, K.; Noda, K.; Nozaki, S.; Ohtani, Y.; Okumura, A.; Otero-Santos, J.; Paiano, S.; Paneque, D.; Paoletti, R.; Paredes, J. M.; Peresano, M.; Persic, M.; Pihet, M.; Pirola, G.; Podobnik, F.; Prada Moroni, P. G.; Prandini, E.; Rhode, W.; Ribó, M.; Rico, J.; Sahakyan, N.; Saito, T.; Saturni, F. G.; Schmitz, K.; Schmuckermaier, F.; Schubert, J. L.; Schweizer, T.; Sciaccaluga, A.; Silvestri, G.; Simongini, A.; Sitarek, J.; Sliusar, V.; Sobczynska, D.; Stamerra, A.; Strišković, J.; Strom, D.; Strzys, M.; Suda, Y.; Tajima, H.; Takahashi, M.; Takeishi, R.; Temnikov, P.; Terauchi, K.; Terzić, T.; Teshima, M.; Tutone, A.; Ubach, S.; van Scherpenberg, J.; Vazquez Acosta, M.; Ventura, S.; Verna, G.; Viale, I.; Vigliano, A.; Vigorito, C. F.; Visentin, E.; Vitale, V.; Vovk, I.; Walter, R.; Wersig, F.; Will, M.; Yamamoto, T.; Yeung, P. K. H.; Neronov, A.; Peretti, E.; Peron, G.Seyfert galaxies are emerging as a promising source class of high-energy neutrinos. The Seyfert galaxies NGC 4151 and NGC 1068 have respectively come up as the most promising counterparts of a 3σ and of a 4.2σ neutrino excesses detected by IceCube in the TeV energy range. Constraining the very high energy (VHE) emission associated with the neutrino signal is crucial to unveiling the mechanism and site of neutrino production. In this work, we present the first results of the VHE observations (∼29 hours) of NGC 4151 with the MAGIC telescopes. We detected no gamma-ray excess in the direction of NGC 4151, and we derived constraining upper limits on the VHE gamma-ray flux. The integral flux upper limit (at the 95% confidence level) above 200 GeV is f = 2.3 × 10−12 cm−2 s−1. Comparison of the MAGIC and IceCube measurements suggests the presence of a gamma-ray obscured accelerator, and it allowed us to constrain the gamma-ray optical depth and the size of the neutrino production site. © The Authors 2025.We would like to thank the Instituto de Astrofísica de Canarias for the excellent working conditions at the Observatorio del Roque de los Muchachos in La Palma. The financial support of the German BMBF, MPG and HGF; the Italian INFN and INAF; the Swiss National Fund SNF; the grants PID2019-104114RB-C31, PID2019-104114RB-C32, PID2019-104114RB-C33, PID2019-105510GB-C31, PID2019-107847RB-C41, PID2019-107847RB-C42, PID2019-107847RB-C44, PID2019-107988GB-C22, PID2022-136828NB-C41, PID2022-137810NB-C22, PID2022-138172NB-C41, PID2022-138172NB-C42, PID2022-138172NB-C43, PID2022-139117NB-C41, PID2022-139117NB-C42, PID2022-139117NB-C43, PID2022-139117NB-C44 funded by the Spanish MCIN/AEI/ 10.13039/501100011033 and “ERDF A way of making Europe”; the Indian Department of Atomic Energy; the Japanese ICRR, the University of Tokyo, JSPS, and MEXT; the Bulgarian Ministry of Education and Science, National RI Roadmap Project DO1-400/18.12.2020 and the Academy of Finland grant nr. 320045 is gratefully acknowledged. This work was also been supported by Centros de Excelencia “Severo Ochoa” y Unidades “María de Maeztu” program of the Spanish MCIN/AEI/ 10.13039/501100011033 (CEX2019-000920-S, CEX2019-000918-M, CEX2021-001131-S) and by the CERCA institution and grants 2021SGR00426 and 2021SGR00773 of the Generalitat de Catalunya; by the Croatian Science Foundation (HrZZ) Project IP-2022-10-4595 and the University of Rijeka Project uniri-prirod-18-48; by the Deutsche Forschungsgemeinschaft (SFB1491) and by the Lamarr-Institute for Machine Learning and Artificial Intelligence; by the Polish Ministry Of Education and Science grant No. 2021/WK/08; by the Brazilian MCTIC, the CNPq Productivity Grant 309053/2022-6 and FAPERJ Grants E-26/200.532/2023 and E-26/211.342/2021. E.P. was supported by Agence Nationale de la Recherche (grant ANR-21-CE31-0028) and by INAF through “Assegni di ricerca per progetti di ricerca relativi a CTA e precursori”. Author Contributions. A. Lamastra: project management, P.I. of MAGIC observations, MAGIC data analysis, theoretical interpretation, paper drafting; S. Mangano: MAGIC analysis cross-check, paper drafting; S. Menon: MAGIC data analysis, paper drafting; E. Peretti: P.I. theory, theoretical modeling and interpretation, paper drafting; G. Peron: Fermi-LAT data interpretation and paper drafting; F. G. Saturni: theoretical interpretation and paper drafting. The rest of the authors have contributed in one or several of the following ways: design, construction, maintenance and operation of the instrument(s) used to acquire the data; preparation and/or evaluation of the observation proposals; data acquisition, processing, calibration and/or reduction; production of analysis tools and/or related Monte Carlo simulations; overall discussions about the contents of the draft, as well as related refinements in the descriptions.With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2019-000920-S).With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2019-000918-M).With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).Peer reviewe
- …
