Characterization of exoplanets' light curves with neural networks

Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2020. Tutor: Francesc Xavier Luri CarrascosoA study of the implementation of deep learning using artificial neural networks is undertaken aiming to reduce processing time and human supervision in the characterization of exoplanets’ light curves. Firstly, to understand the problem and the techniques involved, a convolutional neural network proposed by Shallue & Vanderburg for the Kepler mission is studied and recreated. Secondly, different alternative neural networks are proposed and compared with the original one, aiming to improve the classification performanc

Collimated beam FMCW radar for vital sign patient monitoring

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Patient monitoring of vital signals such as breathing rhythm and heart beat rate can be done remotely by the use of a radar system. This approach is advantageous since it does not require any contact with the patient. Obviously contactless monitoring results in a more comfortable situation for the patient, and in occasions it is almost mandatory as in the case of heavy burnt or newborn patients. Moreover, additional information such movement patterns are also available. A 120 GHz FMCW radar is described with special focus on the design, construction and testing of a specific reflector antenna for the system. The system is based on a commercial radar chipset that includes its own antennas. The challenge has been to design the optimum reflector and to build it and test it in a cost effective way. The reflector has been 3D printed and a near-field testing technique has been implemented to assess its performance. The results show that the system is able to measure the vital signs at distances beyond one meter.Postprint (author's final draft

Multiwavelength study of the galactic PeVatron candidate LHAASO J2108+5157

Abe, S., et al.[Context] Several new ultrahigh-energy (UHE) γ-ray sources have recently been discovered by the Large High Altitude Air Shower Observatory (LHAASO) collaboration. These represent a step forward in the search for the so-called Galactic PeVatrons, the enigmatic sources of the Galactic cosmic rays up to PeV energies. However, it has been shown that multi-TeV γ-ray emission does not necessarily prove the existence of a hadronic accelerator in the source; indeed this emission could also be explained as inverse Compton scattering from electrons in a radiation-dominated environment. A clear distinction between the two major emission mechanisms would only be made possible by taking into account multi-wavelength data and detailed morphology of the source.[Aims] We aim to understand the nature of the unidentified source LHAASO J2108+5157, which is one of the few known UHE sources with no very high-energy (VHE) counterpart.[Methods] 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 used naima and jetset software packages to examine the leptonic and hadronic scenario of the multi-wavelength emission of the source.[Results] We found an excess (3.7σ) in the LST-1 data at energies E > 3 TeV. Further analysis of the whole LST-1 energy range, assuming a point-like source, resulted in a hint (2.2σ) of hard emission, which can be described with a single power law with a photon index of Γ = 1.6 ± 0.2 the range of 0.3 − 100 TeV. We did not find any significant extended emission that 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. We revealed a new potential hard source in Fermi-LAT data with a significance of 4σ and a photon index of Γ = 1.9 ± 0.2, which is not spatially correlated with LHAASO J2108+5157, but including it in the source model we were able to improve spectral representation of the HE counterpart 4FGL J2108.0+5155.[Conclusions] The LST-1 and LHAASO observations can be explained as inverse Compton-dominated leptonic emission of relativistic electrons with a cutoff energy of 100−30+70 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. Furthermore, the spectral properties of the HE counterpart are consistent with a Geminga-like pulsar, which would be able to power the VHE-UHE emission. Nevertheless, the lack of a pulsar in the neighborhood of the UHE source is a challenge to the PWN/TeV-halo scenario. The UHE γ rays can also be explained as π0 decay-dominated hadronic emission due to interaction of relativistic protons with one of the two known molecular clouds in the direction of the source. Indeed, 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, but the origin of the HE γ-ray emission remains an open question.We gratefully acknowledge financial support from the following agencies and organisations: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Fundação de Apoio à Ciência, Tecnologia e Inovação do Paraná – Fundação Araucária, Ministry of Science, Technology, Innovations and Communications (MCTIC), Brasil; Ministry of Education and Science, National RI Roadmap Project DO1-153/28.08.2018, Bulgaria; Croatian Science Foundation, Rudjer Boskovic Institute, University of Osijek, University of Rijeka, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia; Ministry of Education, Youth and Sports, MEYS LM2015046, LM2018105, LTT17006, EU/MEYS CZ.02.1.01/0.0/0.0/16_013/0001403, CZ.02.1.01/0.0/0.0/18_046/0016007 and CZ.02.1.01/0.0/0.0/16_019/0000754, Czech Republic; CNRS-IN2P3, France; Max Planck Society, German Bundesministerium für Bildung und Forschung (Verbundforschung/ErUM), Deutsche Forschungsgemeinschaft (SFBs 876 and 1491), Germany; Istituto Nazionale di Astrofisica (INAF), Istituto Nazionale di Fisica Nucleare (INFN), Italian Ministry for University and Research (MUR); ICRR, University of Tokyo, JSPS, MEXT, Japan; JST SPRING - JPMJSP2108; Narodowe Centrum Nauki, grant number 2019/34/E/ST9/00224, Poland; The Spanish groups acknowledge the Spanish Ministry of Science and Innovation and the Spanish Research State Agency (AEI) through the government budget lines PGE2021/28.06.000X.411.01, PGE2022/28.06.000X.411.01 and PGE2022/28.06.000X.711.04, and grants PGC2018-095512-B-I00, PID2019-104114RB-C31, PID2019-107847RB-C44, PID2019-104114RB-C32, PID2019-105510GB-C31, PID2019-104114RB-C33, PID2019-107847RB-C41, PID2019-107847RB-C43, PID2019-107988GB-C22; the “Centro de Excelencia Severo Ochoa” program through grants no. SEV-2017-0709, CEX2019-000920-S; the “Unidad de Excelencia María de Maeztu” program through grants no. CEX2019-000918-M, CEX2020-001058-M; the “Ramón y Cajal” program through grant RYC-2017-22665; the “Juan de la Cierva-Incorporación” program through grant no. IJC2019-040315-I. They also acknowledge the “Programa Operativo” FEDER 2014-2020, Consejería de Economía y Conocimiento de la Junta de Andalucía (Ref. 1257737), PAIDI 2020 (Ref. P18-FR-1580) and Universidad de Jaén; “Programa Operativo de Crecimiento Inteligente” FEDER 2014-2020 (Ref. ESFRI-2017-IAC-12), Ministerio de Ciencia e Innovación, 15% co-financed by Consejería de Economía, Industria, Comercio y Conocimiento del Gobierno de Canarias; the “CERCA” program of the Generalitat de Catalunya; and the European Union’s “Horizon 2020” GA:824064 and NextGenerationEU; We acknowledge the Ramon y Cajal program through grant RYC-2020-028639-I; State Secretariat for Education, Research and Innovation (SERI) and Swiss National Science Foundation (SNSF), Switzerland; the research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under grant agreements No 262053 and No 317446. This project is receiving funding from the European Union’s Horizon 2020 research and innovation programs under agreement No 676134.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 (CEX2020-001058-M).Peer reviewe

Star tracking for pointing determination of imaging Atmospheric Cherenkov Telescopes: Application to the large-sized telescope of the Cherenkov Telescope Array

Abe, K., et al.We present a novel approach to the determination of the pointing of Imaging Atmospheric Cherenkov Telescopes (IACTs) using the trajectories of the stars in their camera’s field of view. The method starts with the reconstruction of the star positions from the Cherenkov camera data, taking into account the point spread function of the telescope, to achieve a satisfying reconstruction accuracy of the pointing position. A simultaneous fit of all reconstructed star trajectories is then performed with the orthogonal distance regression (ODR) method. ODR allows us to correctly include the star position uncertainties and use the time as an independent variable. Having the time as an independent variable in the fit makes it better suitable for various star trajectories. This method can be applied to any IACT and requires neither specific hardware nor interface or special data-taking mode. In this paper, we use the Large-Sized Telescope (LST) data to validate it as a useful tool to improve the determination of the pointing direction during regular data taking. The simulation studies show that the accuracy and precision of the method are comparable with the design requirements on the pointing accuracy of the LST (≤14″). With the typical LST event acquisition rate of 10 kHz, the method can achieve up to 50 Hz pointing monitoring rate, compared to (1) Hz achievable with standard techniques. The application of the method to the LST prototype (LST-1) commissioning data shows the stable pointing performance of the telescope.This work was conducted in the context of the CTA-LST Project. We gratefully acknowledge financial support from the following agencies and organizations: Ministry of Education, Youth and Sports, MEYS LM2015046, LM2018105, LTT17006, EU/MEYS CZ.02.1.01/0.0/0.0/16_013/0001403, CZ.02.1.01/0.0/0.0/18_046/0016007 and CZ.02.1.01/0.0/0.0/16_019/0000754, Czech Republic; Max Planck Society, German Bundesministerium für Bildung und Forschung (Verbundforschung / ErUM), Deutsche Forschungsgemeinschaft (SFBs 876 and 1491), Germany; Istituto Nazionale di Astrofísica (INAF), Istituto Nazionale di Fisica Nucleare (INFN), Italian Ministry for University and Research (MUR); ICRR, University of Tokyo, JSPS, MEXT, Japan; JST SPRING - JPMJSP2108; Narodowe Centrum Nauki, grant number 2019/34/E/ST9/00224, Poland; The Spanish groups acknowledge the Spanish Ministry of Science and Innovation and the Spanish Research State Agency (AEI) through the government budget lines PGE2021/28.06.000X.411.01, PGE2022/28.06.000X.411.01 and PGE2022/28.06.000X.711.04, and grants PGC2018-095512-B-I00, PID2019-104114RB-C31, PID2019-107847RB-C44, PID2019-104114RB-C32, PID2019-105510GB-C31, PID2019-104114RB-C33, PID2019-107847RB-C41, PID2019-107847RB-C43, PID2019-107988GB-C22; the “Centro de Excelencia Severo Ochoa” program through grants no. CEX2021-001131-S, CEX2019-000920-S; the “Unidad de Excelencia María de Maeztu” program through grants no. CEX2019-000918-M, CEX2020-001058-M; the “Juan de la Cierva-Incorporación” program through grant no. IJC2019-040315-I. They also acknowledge the “Programa Operativo” FEDER 2014-2020, Consejería de Economía y Conocimiento de la Junta de Andalucía (Ref. 1257737), PAIDI 2020 (Ref. P18-FR-1580) and Universidad de Jaén; “Programa Operativo de Crecimiento Inteligente” FEDER 2014-2020 (Ref. ESFRI-2017-IAC-12), Ministerio de Ciencia e Innovación, 15% co-financed by Consejería de Economía, Industria, Comercio y Conocimiento del Gobierno de Canarias; the “CERCA” program of the Generalitat de Catalunya; and the European Union’s “Horizon 2020” GA:824064 and NextGenerationEU; We acknowledge the Ramon y Cajal program through grant RYC-2020-028639-I and RYC-2017-22665; State Secretariat for Education, Research and Innovation (SERI) and Swiss National Science Foundation (SNSF), Switzerland; The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007–2013) under grant agreements nos. 262053 and 317446. This project is receiving funding from the European Union’s Horizon 2020 research and innovation programs under agreement no. 676134. ESCAPE – The European Science Cluster of Astronomy & Particle Physics ESFRI Research Infrastructures has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no. 824064.With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).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 (CEX2020-001058-M).Peer reviewe

Sensitivity of the Cherenkov Telescope Array to TeV photon emission from the Large Magellanic Cloud

A. Acharyya et al.A deep survey of the Large Magellanic Cloud at ∼0.1–100 TeV photon energies with the Cherenkov Telescope Array is planned. We assess the detection prospects based on a model for the emission of the galaxy, comprising the four known TeV emitters, mock populations of sources, and interstellar emission on galactic scales. We also assess the detectability of 30 Doradus and SN 1987A, and the constraints that can be derived on the nature of dark matter. The survey will allow for fine spectral studies of N 157B, N 132D, LMC P3, and 30 Doradus C, and half a dozen other sources should be revealed, mainly pulsar-powered objects. The remnant from SN 1987A could be detected if it produces cosmic-ray nuclei with a flat power-law spectrum at high energies, or with a steeper index 2.3–2.4 pending a flux increase by a factor of >3–4 over ∼2015–2035. Large-scale interstellar emission remains mostly out of reach of the survey if its >10 GeV spectrum has a soft photon index ∼2.7, but degree-scale 0.1–10 TeV pion-decay emission could be detected if the cosmic-ray spectrum hardens above >100 GeV. The 30 Doradus star-forming region is detectable if acceleration efficiency is on the order of 1−10 per cent of the mechanical luminosity and diffusion is suppressed by two orders of magnitude within <100 pc. Finally, the survey could probe the canonical velocity-averaged cross-section for self-annihilation of weakly interacting massive particles for cuspy Navarro–Frenk–White profiles.We gratefully acknowledge financial support from the following agencies and organizations: State Committee of Science of Armenia, Armenia; The Australian Research Council, Astronomy Australia Ltd, The University of Adelaide, Australian National University, Monash University, The University of New South Wales, The University of Sydney, Western Sydney University, Australia; Federal Ministry of Education, Science and Research, and Innsbruck University, Austria; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Fundação de Apoio à Ciência, Tecnologia e Inovação do Paraná – Fundação Araucária, Ministry of Science, Technology, Innovations and Communications (MCTIC), Brasil; Ministry of Education and Science, National RI Roadmap Project DO1-153/28.08.2018, Bulgaria; The Natural Sciences and Engineering Research Council of Canada and the Canadian Space Agency, Canada; CONICYT-Chile grants CATA AFB 170002, ANID PIA/APOYO AFB 180002, ACT 1406, FONDECYT-Chile grants, 1161463, 1170171, 1190886, 1171421, 1170345, 1201582, Gemini-ANID 32180007, Chile; Croatian Science Foundation, Rudjer Boskovic Institute, University of Osijek, University of Rijeka, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia; Ministry of Education, Youth and Sports, MEYS LM2015046, LM2018105, LTT17006, EU/MEYS CZ.02.1.01/0.0/0.0/16_013/0001403, CZ.02.1.01/0.0/0.0/18_046/0016007 and CZ.02.1.01/0.0/0.0/16_019/0000754, Czech Republic; Academy of Finland (grants 317636 and 320045), Finland; Ministry of Higher Education and Research, CNRS-INSU and CNRS-IN2P3, CEA-Irfu, ANR, Regional Council Ile de France, Labex ENIGMASS, OCEVU, OSUG2020 and P2IO, France; Max Planck Society, BMBF, DESY, Helmholtz Association, Germany; Department of Atomic Energy, Department of Science and Technology, India; Istituto Nazionale di Astrofisica (INAF), Istituto Nazionale di Fisica Nucleare (INFN), MIUR, Istituto Nazionale di Astrofisica (INAF-OABRERA) Grant Fondazione Cariplo/Regione Lombardia ID 2014-1980/RST_ERC, Italy; ICRR, University of Tokyo, JSPS, MEXT, Japan; Netherlands Research School for Astronomy (NOVA), Netherlands Organization for Scientific Research (NWO), Netherlands; University of Oslo, Norway; Ministry of Science and Higher Education, DIR/WK/2017/12, the National Centre for Research and Development and the National Science Centre, UMO-2016/22/M/ST9/00583, Poland; Slovenian Research Agency, grants P1-0031, P1-0385, I0-0033, J1-9146, J1-1700, N1-0111, and the Young Researcher programme, Slovenia; South African Department of Science and Technology and National Research Foundation through the South African Gamma-Ray Astronomy Programme, South Africa; The Spanish groups acknowledge the Spanish Ministry of Science and Innovation and the Spanish Research State Agency (AEI) through grants AYA2016-79724-C4-1-P, AYA2016-80889-P, AYA2016-76012-C3-1-P, BES-2016-076342, FPA2017-82729-C6-1-R, FPA2017-82729-C6-2-R, FPA2017-82729-C6-3-R, FPA2017-82729-C6-4-R, FPA2017-82729-C6-5-R, FPA2017-82729-C6-6-R, PGC2018-095161-B-I00, PGC2018-095512-B-I00, PID2019-107988GB-C22; the ‘Centro de Excelencia Severo Ochoa’ programme through grants no. SEV-2016-0597, SEV-2016-0588, SEV-2017-0709, CEX2019-000920-S; the ‘Unidad de Excelencia María de Maeztu’ programme through grant no. MDM-2015-0509; the ‘Ramón y Cajal’ programme through grants RYC-2013-14511, RYC-2017-22665; and the MultiDark Consolider Network FPA2017-90566-REDC. They also acknowledge the Atracción de Talento contract no. 2016-T1/TIC-1542 granted by the Comunidad de Madrid; the ‘Postdoctoral Junior Leader Fellowship’ programme from La Caixa Banking Foundation, grants no. LCF/BQ/LI18/11630014 and LCF/BQ/PI18/11630012; the ‘Programa Operativo’ FEDER 2014–2020, Consejería de Economía y Conocimiento de la Junta de Andalucía (Ref. 1257737), PAIDI 2020 (Ref. P18-FR-1580) and Universidad de Jaén; ‘Programa Operativo de Crecimiento Inteligente’ FEDER 2014-2020 (Ref. ESFRI-2017-IAC-12), Ministerio de Ciencia e Innovación, 15 per cent co-financed by Consejería de Economía, Industria, Comercio y Conocimiento del Gobierno de Canarias; the Spanish AEI EQC2018-005094-P FEDER 2014–2020; the European Union’s ‘Horizon 2020’ research and innovation programme under Marie Sklodowska-Curie grant agreement no. 665919; and the ESCAPE project with grant no. GA:824064; Swedish Research Council, Royal Physiographic Society of Lund, Royal Swedish Academy of Sciences, The Swedish National Infrastructure for Computing (SNIC) at Lunarc (Lund), Sweden; State Secretariat for Education, Research and Innovation (SERI) and Swiss National Science Foundation (SNSF), Switzerland; Durham University, Leverhulme Trust, Liverpool University, University of Leicester, University of Oxford, Royal Society, Science and Technology Facilities Council, UK; U.S. National Science Foundation, U.S. Department of Energy, Argonne National Laboratory, Barnard College, University of California, University of Chicago, Columbia University, Georgia Institute of Technology, Institute for Nuclear and Particle Astrophysics (INPAC-MRPI programme), Iowa State University, the Smithsonian Institution, Washington University McDonnell Center for the Space Sciences, The University of Wisconsin and the Wisconsin Alumni Research Foundation, USA. This research has made use of the CTA instrument response functions provided by the CTA Consortium and Observatory, see http://www.cta-observatory.org/science/ctao-performance/ for more details. The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under grant agreements no. 262053 and no. 317446. This project is receiving funding from the European Union’s Horizon 2020 research and innovation programs under agreement no. 676134. We acknowledge financial support from the French Agence Nationale de la Recherche under reference ANR-19-CE31-0014 (GAMALO project) and the Italian grant 2017W4HA7S ‘NAT-NET: Neutrino and Astroparticle Theory Network’ (PRIN 2017) funded by the Italian Ministero dell’Istruzione, dell’Università e della Ricerca (MIUR), and Iniziativa Specifica TAsP of INFN.With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2019-000920-S).Peer reviewe

Observations of the Crab Nebula and pulsar with the large-sized telescope prototype of the Cherenkov Telescope Array

Abe et al.The Cherenkov Telescope Array (CTA) is a next-generation ground-based observatory for gamma-ray astronomy at very high energies. The Large-Sized Telescope prototype (LST-1) is located at the CTA-North site, 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 ≃20 GeV. LST-1 started performing astronomical observations in 2019 November, during its commissioning phase, and it has been taking data ever since. 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 performance of the telescope. 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's behavior. The energy threshold at trigger level is around 20 GeV, rising to ≃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 0fdg12–0fdg40, and energy resolution from 15%–50%. Flux sensitivity is around 1.1% of the Crab Nebula flux above 250 GeV for a 50 hr 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.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo ä Pesquisa do Estado do Rio de Janeiro (FAPERJ), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Fundação de Apoio à Ciência, Tecnologia e Inovação do Paraná—Fundação Araucária, Ministry of Science, Technology, Innovations and Communications (MCTIC), Brasil; Ministry of Education and Science, National RI Roadmap Project DO1-153/28.08.2018, Bulgaria; Croatian Science Foundation, Rudjer Boskovic Institute, University of Osijek, University of Rijeka, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia; Ministry of Education, Youth and Sports, MEYS LM2015046, LM2018105, LTT17006, EU/MEYS CZ.02.1.01/0.0/0.0/16_013/0001403, CZ.02.1.01/0.0/0.0/18_046/0016007 and CZ.02.1.01/0.0/0.0/16_019/0000754, Czech Republic; CNRS-IN2P3, the French Programme d'investissements d'avenir and the Enigmass Labex, This work has been done thanks to the facilities offered by the Univ. Savoie Mont Blanc—CNRS/IN2P3 MUST computing center, France; Max Planck Society, German Bundesministerium für Bildung und Forschung (Verbundforschung / ErUM), Deutsche Forschungsgemeinschaft (SFBs 876 and 1491), Germany; Istituto Nazionale di Astrofisica (INAF), Istituto Nazionale di Fisica Nucleare (INFN), Italian Ministry for University and Research (MUR); ICRR, University of Tokyo, JSPS, MEXT, Japan; JST SPRING—JPMJSP2108; Narodowe Centrum Nauki, grant No. 2019/34/E/ST9/00224, Poland. The Spanish groups acknowledge the Spanish Ministry of Science and Innovation and the Spanish Research State Agency (AEI) through the government budget lines PGE2021/28.06.000X.411.01, PGE2022/28.06.000X.411.01, and PGE2022/28.06.000X.711.04, and grants PID2022-139117NB-C44, PID2019-104114RB-C31, PID2019-107847RB-C44, PID2019-104114RB-C32, PID2019-105510GB-C31, PID2019-104114RB-C33, PID2019-107847RB-C41, PID2019-107847RB-C43, PID2019-107847RB-C42, PID2019-107988GB-C22, PID2021-124581OB-I00, PID2021-125331NB-I00; the "Centro de Excelencia Severo Ochoa" program through grant Nos. CEX2019-000920-S, CEX2020-001007-S, CEX2021-001131-S; the "Unidad de Excelencia María de Maeztu" program through grant Nos. CEX2019-000918-M, CEX2020-001058-M; the "Ramón y Cajal" program through grants RYC2021-032552-I, RYC2021-032991-I, RYC2020-028639-I, and RYC-2017-22665; the "Juan de la Cierva-Incorporación" program through grant Nos. IJC2018-037195-I and IJC2019-040315-I. They also acknowledge the "Atracción de Talento" program of Comunidad de Madrid through grant No. 2019-T2/TIC-12900; the project "Tecnologiás avanzadas para la exploracioń del universo y sus componentes" (PR47/21 TAU), funded by Comunidad de Madrid, by the Recovery, Transformation and Resilience Plan from the Spanish State, and by NextGenerationEU from the European Union through the Recovery and Resilience Facility; the La Caixa Banking Foundation, grant No. LCF/BQ/PI21/11830030; the "Programa Operativo" FEDER 2014-2020, Consejería de Economía y Conocimiento de la Junta de Andalucía (Ref. 1257737), PAIDI 2020 (Ref. P18-FR-1580) and Universidad de Jaén;"Programa Operativo de Crecimiento Inteligente" FEDER 2014-2020 (Ref. ESFRI-2017-IAC-12), Ministerio de Ciencia e Innovación, 15% co-financed by Consejería de Economía, Industria, Comercio y Conocimiento del Gobierno de Canarias; the "CERCA" program and the grant 2021SGR00426, both funded by the Generalitat de Catalunya; and the European Union's "Horizon 2020" GA:824064 and NextGenerationEU (PRTR-C17.I1). State Secretariat for Education, Research and Innovation (SERI) and Swiss National Science Foundation (SNSF), Switzerland; The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement Nos. 262053 and No 317446. This project is receiving funding from the European Union's Horizon 2020 research and innovation programs under agreement No. 676134. ESCAPE (The European Science Cluster of Astronomy & Particle Physics ESFRI Research Infrastructures) has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 824064.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 (CEX2020-001007-S).With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-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 (CEX2020-001058-M).Peer reviewe

Gammapy: A Python package for gamma-ray astronomy

In this article, we present Gammapy, an open-source Python package for the analysis of astronomical $\gamma$-ray data, and illustrate the functionalities of its first long-term-support release, version 1.0. Built on the modern Python scientific ecosystem, Gammapy provides a uniform platform for reducing and modeling data from different $\gamma$-ray instruments for many analysis scenarios. Gammapy complies with several well-established data conventions in high-energy astrophysics, providing serialized data products that are interoperable with other software packages. Starting from event lists and instrument response functions, Gammapy provides functionalities to reduce these data by binning them in energy and sky coordinates. Several techniques for background estimation are implemented in the package to handle the residual hadronic background affecting $\gamma$-ray instruments. After the data are binned, the flux and morphology of one or more $\gamma$-ray sources can be estimated using Poisson maximum likelihood fitting and assuming a variety of spectral, temporal, and spatial models. Estimation of flux points, likelihood profiles, and light curves is also supported. After describing the structure of the package, we show, using publicly available $\gamma$-ray data, the capabilities of Gammapy in multiple traditional and novel $\gamma$-ray analysis scenarios, such as spectral and spectro-morphological modeling and estimations of a spectral energy distribution and a light curve. Its flexibility and power are displayed in a final multi-instrument example, where datasets from different instruments, at different stages of data reduction, are simultaneously fitted with an astrophysical flux model.Comment: 26 pages, 16 figure

Joint Observation of the Galactic Center with MAGIC and CTA-LST-1

MAGIC is a system of two Imaging Atmospheric Cherenkov Telescopes (IACTs), designed to detect very-high-energy gamma rays, and is operating in stereoscopic mode since 2009 at the Observatorio del Roque de Los Muchachos in La Palma, Spain. In 2018, the prototype IACT of the Large-Sized Telescope (LST-1) for the Cherenkov Telescope Array, a next-generation ground-based gamma-ray observatory, was inaugurated at the same site, at a distance of approximately 100 meters from the MAGIC telescopes. Using joint observations between MAGIC and LST-1, we developed a dedicated analysis pipeline and established the threefold telescope system via software, achieving the highest sensitivity in the northern hemisphere. Based on this enhanced performance, MAGIC and LST-1 have been jointly and regularly observing the Galactic Center, a region of paramount importance and complexity for IACTs. In particular, the gamma-ray emission from the dynamical center of the Milky Way is under debate. Although previous measurements suggested that a supermassive black hole Sagittarius A* plays a primary role, its radiation mechanism remains unclear, mainly due to limited angular resolution and sensitivity. The enhanced sensitivity in our novel approach is thus expected to provide new insights into the question. We here present the current status of the data analysis for the Galactic Center joint MAGIC and LST-1 observations

Gammapy: A Python package for gamma-ray astronomy

Donath, A., et al.[Context] Traditionally, TeV-γ-ray astronomy has been conducted by experiments employing proprietary data and analysis software. However, the next generation of γ-ray instruments, such as the Cherenkov Telescope Array Observatory (CTAO), will be operated as open observatories. Alongside the data, they will also make the associated software tools available to a wider community. This necessity prompted the development of open, high-level, astronomical software customized for high-energy astrophysics.[Aims] In this article, we present Gammapy, an open-source Python package for the analysis of astronomical γ-ray data, and illustrate the functionalities of its first long-term-support release, version 1.0. Built on the modern Python scientific ecosystem, Gammapy provides a uniform platform for reducing and modeling data from different γ-ray instruments for many analysis scenarios. Gammapy complies with several well-established data conventions in high-energy astrophysics, providing serialized data products that are interoperable with other software packages.[Methods] Starting from event lists and instrument response functions, Gammapy provides functionalities to reduce these data by binning them in energy and sky coordinates. Several techniques for background estimation are implemented in the package to handle the residual hadronic background affecting γ-ray instruments. After the data are binned, the flux and morphology of one or more γ-ray sources can be estimated using Poisson maximum likelihood fitting and assuming a variety of spectral, temporal, and spatial models. Estimation of flux points, likelihood profiles, and light curves is also supported.[Results] After describing the structure of the package, we show, using publicly available gamma-ray data, the capabilities of Gammapy in multiple traditional and novel γ-ray analysis scenarios, such as spectral and spectro-morphological modeling and estimations of a spectral energy distribution and a light curve. Its flexibility and its power are displayed in a final multi-instrument example, where datasets from different instruments, at different stages of data reduction, are simultaneously fitted with an astrophysical flux model.A.A.-C. acknowledges the financial support from the Spanish Ministry of Science and Innovation and the Spanish Research State Agency (AEI) under grant PID2019-104114RB-C33/AEI/10.13039/501100011034 and the Institute of Cosmos Sciences University of Barcelona (ICCUB, Unidad de Excelencia “María de Maeztu”) through grant CEX2019-000918-M. J.L.C. acknowledges the funding from the ESCAPE H2020 project, GA No 824064. L.G. acknowledges financial support from the Agence Nationale de la Recherche (ANR-17-CE31-0014). M.L. acknowledges support by the German BMBF (ErUM) and DFG (SFBs 876 and 1491). R.L.-C. acknowledges the Ramon y Cajal program through grant RYC-2020-028639-I and the financial support from the grant CEX2021-001131-S funded by MCIN/AEI/ 10.13039/501100011033. C.N. acknowledges support by the Spanish Ministerio de Ciencia e Innovacion (MICINN), the European Union - NextGenerationEU and PRTR through the programme Juan de la Cierva (grant FJC2020-046063-I), by the MICINN (grant PID2019-107847RB-C41), and from the CERCA program of the Generalitat de Catalunya. Q. R. acknowledges support from the project “European Science Cluster of Astronomy & Particle Physics ESFRI Research Infrastructures” (ESCAPE), that has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no. 824064. J.E.R. acknowledges financial support from the grant CEX2021-001131-S funded by MCIN/AEI/10.13039/501100011033. A.S. was supported by NASA contract NAS8-03060 (Chandra X-ray Center). A.S. acknowledges support from The European Science Cluster of Astronomy & Particle Physics ESFRI Research Infrastructures funded by the European Union’s Horizon 2020 research and innovation program under Grant Agreement no. 824064 and from the Spanish Ministry of Universities through the Maria Zambrano Talent Attraction Programme, 2021–2023.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