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72 results on '"Manel Martinez"'

1. Design and Performance of a Low-Energy Gamma-Ray Trigger System for HERD

Author

Luis Fariña, Keerthana Lathika, Giulio Lucchetta, Monong Yu, Joan Boix, Laia Cardiel-Sas, Oscar Blanch, Manel Martinez, and Javier Rico

Subjects
HERD, trigger, gamma rays, Physics, QC1-999, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

The High Energy cosmic-Radiation Detection (HERD) facility has been proposed as one of the main experiments on board the Chinese space station. HERD is scheduled to be installed around 2027 and to operate for at least 10 years. Its main scientific goals are the study of the cosmic ray spectrum and composition up to the PeV energy range, indirect dark matter detection, and all-sky gamma-ray observation above 100 MeV. HERD features a novel design in order to optimize its acceptance per weight, with a central 3D imaging calorimeter surrounded on top and on its four lateral sides by complementary subdetectors. A dedicated trigger, dubbed the ultra-low-energy gamma-ray (ULEG) trigger, is required to enable the detection of gamma rays down to ~100 MeV. The ULEG trigger design is based upon the search for energy deposition patterns on the tracker and the anticoincidence shield, compatible with the conversion of a gamma ray within the tracker volume and resulting in enough tracker hits to allow for a good-quality gamma-ray direction reconstruction. We describe the current status of the design of the ULEG trigger system. We also characterize its performance in detecting gamma rays as inferred from Monte Carlo studies.

Published
2024
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2. Kernel Machine to Estimate a Lyapunov Function and Region of Attraction (ROA) for Nonlinear Systems

Author

Afroza Shirin, Manel Martinez-Ramon, and Rafael Fierro

Subjects
Lyapunov stability, region of attraction, sum-of-squares, semidefinite programming, simulating annealing, neural networks, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

The Lyapunov theory establishes the fundamental details to determine the stability and the Lyapunov function associated with an equilibrium point of a nonlinear system. Sum-of-square (SOS) optimization is a well-known technique to estimate the region of attraction (ROA) from the Lyapunov function. But if some of the system’s parameters and the controller are unknown, the Lyapunov function becomes unknown, and the ROA estimation becomes quite impossible. In this article, a methodology is proposed to use Machine Learning Kernel Method to parameterize Lyapunov function candidates, and a two steps optimization approach is adopted to determine the Lyapunov function and the system’s parameter. The objective function of the optimization is set so that (i) the Lyapunov function satisfies all the fundamental properties of the Lyapunov theory and (ii) it learns the unknown parameters of the system. The proposed methodology also finds a larger ROA than the existing methods. We provide numerical experiments on how the optimization technique works and how it can obtain high-quality solutions for challenging control problems.

Published
2023
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3. Spaghetti Technique Versus Wide Local Excision for Lentigo Maligna Affecting the Head and Neck Regions: Surgical Outcome and Descriptive Analysis of 79 Cases From a Single Practice Cohort

Author

Manel Martinez-Molina, Nina Richarz, Ane Jaka, Juli Bassas-Vila, Verónica Mora-Fernández, Ariadna Quer Pi-Sunyer, Sebastian Podlipnik, José Manuel Carrascosa, and Aram Boada

Subjects
Lentigo maligna, Spaghetti technique, Wide local excision, Melanoma, Dermatology, RL1-803
Abstract

Introduction: Lentigo maligna is a subtype of melanoma in situ that typically affects the head and neck region with an increasing incidence. Margin-controlled techniques, such as spaghetti technique (ST), have gained popularity over wide local excision (WLE) with a margin of 5 mm. Objectives: To evaluate the outcomes of lentigo maligna cases in the head and neck area treated by either WLE or ST in a tertiary referral hospital. The secondary goal was to describe the demographic and clinical characteristics of our series. Methods: Cohort study of patients diagnosed with lentigo maligna on the head and neck region between January 2014 and February 2022 in a tertiary hospital. Results: In total, 79 lentigo maligna were studied, corresponding to 77 patients. Fifty-three lesions (67%) were treated with WLE and 26 (33%) with ST. The mean age of the patients was 73 years and 58% were men. Most of the tumors were located on the cheek (50%) and mean lesion diameter was 2.2 cm for the ST group and 1.2 cm for the WLE group. Mean duration follow-up was 44 months. There were two local recurrences in the WLE group (2/53; 3.7%) and none in the ST group. Conclusions: Both WLE and ST are appropriate surgical approaches for lentigo maligna. ST offers an efficient alternative to Mohs surgery for treating lentigo maligna in the head and neck area, especially when guided by reflectance confocal microscopy.

Published
2023
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4. Designing Monte Carlo Simulation and an Optimal Machine Learning to Optimize and Model Space Missions

Author

Reza Pirayeshshirazinezhad, Sandra G. Biedron, Jorge Alberto Diaz Cruz, Salvador Sosa Guitron, and Manel Martinez-Ramon

Subjects
Virtual telescope for X-ray observation (VTXO), space mission design, Monte-Carlo simulation, optimal control, machine learning, optimization, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

This paper investigates applying artificial intelligence (AI) algorithms to attitude control system of satellites to optimally tune the controller using high performance computing. This methodology is applied to the Virtual Telescope for X-ray Observation mission, which is a precise formation of two separate spacecraft observing multiple objects in the space in the X-ray domain. The mission is divided into phases based on the instrumentation and the mission goal. To reach an stable precise formation robust to stochastic slew and slew rate (i.e., Euler angles and angular velocities) in a minimal constrained time $T$ , consumed energy of the attitude control system, denoted as $E$ , and root-mean-square state error of attitude control system, denoted as $e$ , are minimized. Monte-Carlo simulation is used for the sensitivity analysis of optimization and designing a controller. Deep neural networks (DNN), Gaussian processes (GP), and support vector regression (SVR) learn this optimization as a surrogate model, while their hyperparameters are optimized in a novel approach. THETA supercomputer at Argonne Leadership Computing Facility (ALCF) is used for optimizing the hyperparameters of DNN. The surrogate model meets the requirements of the mission, and it shows a better performance over the optimization and Monte-Carlo. The optimal DNN can satisfy the mission requirements $e$ and $T$ while reducing $E$ for 90% compared to the other given methods.

Published
2022
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5. A Deep Learning Framework for Detection of Targets in Thermal Images to Improve Firefighting

Author

Manish Bhattarai and Manel Martinez-Ramon

Subjects
Deep convolutional neural networks, infrared images, firefighting environment, firefighters, situational awareness, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Intelligent detection and processing capabilities can be instrumental in improving the safety, efficiency, and successful completion of rescue missions conducted by firefighters in emergency first response settings. The objective of this research is to create an automated system that is capable of real-time, intelligent object detection and recognition and facilitates the improved situational awareness of firefighters during an emergency response. We have explored state-of-the-art machine/deep learning techniques to achieve this objective. The goal of this work is to enhance the situational awareness of firefighters by effectively exploiting the infrared video that is actively recorded by firefighters on the scene. To accomplish this, we use a trained deep Convolutional Neural Network (CNN) system to classify and identify objects of interest from thermal imagery in real-time. In the midst of those critical circumstances created by a structure fire, this system is able to accurately inform the decision-making process of firefighters with up-to-date scene information by extracting, processing, and analyzing crucial information. Utilizing the new information produced by the framework, firefighters are able to make more informed inferences about the circumstances for their safe navigation through such hazardous and potentially catastrophic environments.

Published
2020
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6. Unsupervised Segmentation of Fire and Smoke From Infra-Red Videos

Author

Meenu Ajith and Manel Martinez-Ramon

Subjects
Fire detection, gaussian mixture models, iterated conditional modes, k-means clustering, markov random fields, optical flow, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

This paper proposes a vision-based fire and smoke segmentation system which uses spatial, temporal and motion information to extract the desired regions from the video frames. The fusion of information is done using multiple features such as optical flow, divergence and intensity values. These features extracted from the images are used to segment the pixels into different classes in an unsupervised way. A comparative analysis is done by using multiple clustering algorithms for segmentation. Here the Markov Random Field performs more accurately than other segmentation algorithms since it characterizes the spatial interactions of pixels using a finite number of parameters. It builds a probabilistic image model that selects the most likely labeling using the maximum a posteriori (MAP) estimation. This unsupervised approach is tested on various images and achieves a frame-wise fire detection rate of 95.39%. Hence this method can be used for early detection of fire in real-time and it can be incorporated into an indoor or outdoor surveillance system.

Published
2019
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11. Cognitive Radio Resource Scheduling using Multi-Agent Q-Learning for LTE

Author

Najem N. Sirhan and Manel Martinez-Ramon

Subjects
Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Computer Science - Networking and Internet Architecture, Computer Science - Machine Learning, Computer Networks and Communications, Hardware and Architecture, Machine Learning (cs.LG)
Abstract

In this paper, we propose, implement, and test two novel downlink LTE scheduling algorithms. The implementation and testing of these algorithms were in Matlab, and they are based on the use of Reinforcement Learning (RL), more specifically, the Q-learning technique for scheduling two types of users. The first algorithm is called a Collaborative scheduling algorithm, and the second algorithm is called a Competitive scheduling algorithm. The first type of the scheduled users is the Primary Users (PUs), and they are the licensed subscribers that pay for their service. The second type of the scheduled users is the Secondary Users (SUs), and they could be un-licensed subscribers that don't pay for their service, device-to-device communications, or sensors. Each user whether it’s a primary or secondary is considered as an agent. In the Collaborative scheduling algorithm, the primary user agents will collaborate in order to make a joint scheduling decision about allocating the resource blocks to each one of them, then the secondary user agents will compete among themselves to use the remaining resource blocks. In the Competitive scheduling algorithm, the primary user agents will compete among themselves over the available resources, then the secondary user agents will compete among themselves over the remaining resources. Experimental results show that both scheduling algorithms converged to almost 90% utilization of the spectrum, and provided fair shares of the spectrum among users.

Published
2022

12. Geospatial Perspective Reprojections for Ground-Based Sky Imaging Systems

Author

Guillermo Terren-Serrano and Manel Martinez-Ramon

Subjects
Computer Science::Computer Vision and Pattern Recognition, Image and Video Processing (eess.IV), FOS: Electrical engineering, electronic engineering, information engineering, FOS: Physical sciences, General Earth and Planetary Sciences, Electrical Engineering and Systems Science - Image and Video Processing, Electrical and Electronic Engineering, Astrophysics - Instrumentation and Methods for Astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM)
Abstract

Sky imaging systems use lenses to acquire images concentrating light beams in a sensor. The light beams received by the sky imager have an elevation angle with respect to the device normal. Thus, the pixels in the image contain information from different areas of the sky within the imaging system field of view. The area of the field of view contained in the pixels increases as the elevation angle of the incident light beams decreases. When the sky imager is mounted on a solar tracker, the light beam's angle of incidence in a pixel varies over time. This investigation formulates and compares two geospatial reprojections that transform the original euclidean frame of the imager plane to the geospatial atmosphere cross-section where the sky imager field of view intersects the cloud layer. One assumes that an object (i.e., cloud) moving in the troposphere is sufficiently far so the Earth's surface is approximated \emph{flat}. The other transformation takes into account the curvature of the Earth in the portion of the atmosphere (i.e., voxel) that is recorded. The results show that the differences between the dimensions calculated by both geospatial transformations are in the order of magnitude of kilometers when the Sun's elevation angle is below $30^\circ$.

Published
2022

14. QoS-based Packet Scheduling Algorithms for Heterogeneous LTE-Advanced Networks: Concepts and a Literature Survey

Author

Najem N. Sirhan, Manel Martinez-Ramon

Abstract

The number of LTE (Long-Term Evolution) users and their applications has increased significantly in the last decade, which increased the demand on the mobile network. LTE-Advanced (LTE-A) comes with many features that can support this increasing demand. LTE-A supports Heterogeneous Networks (HetNets) deployment, in which it consists of a mix of macro-cells, remote radio heads, and low power nodes such as Pico-cells, and Femto-cells. Embedding this mix of base-stations in a macro-cellular network allows for achieving significant gains in coverage, throughput and system capacity compared to the use of macrocells only. These base-stations can operate on the same wireless channel as the macro-cellular network, which will provide higher spatial reuse via cell splitting. Also, it allows network operators to support higher data traffic by offloading it to smaller cells, such as Femto-cells. Hence, it enables network operators to provide their growing number of users with the required Quality of Service (QoS) that meets with their service demands. In-order for the network operators to make the best out of the heterogeneous LTE-A network, they need to use QoS-based packet scheduling algorithms that can efficiently manage the spectrum resources in the HetNets deployment. In this paper, we survey Quality of Service (QoS) based packet scheduling algorithms that were proposed in the literature for the use of packet scheduling in Heterogeneous LTE-A Networks. We start by explaining the concepts of QoS in LTE, heterogeneous LTE-A networks, and how traffic is classified within a packet scheduling architecture for heterogeneous LTE-A networks. Then, by summarising the proposed QoS-based packet scheduling algorithms in the literature for Heterogeneous LTE-A Networks, and for Femtocells LTE-A Networks. And finally, we provide some concluding remarks in the last section.

Published
2022
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15. Quantum gravity phenomenology at the dawn of the multi-messenger era—A review

Author

A. Addazi, J. Alvarez-Muniz, R. Alves Batista, G. Amelino-Camelia, V. Antonelli, M. Arzano, M. Asorey, J.-L. Atteia, S. Bahamonde, F. Bajardi, A. Ballesteros, B. Baret, D.M. Barreiros, S. Basilakos, D. Benisty, O. Birnholtz, J.J. Blanco-Pillado, D. Blas, J. Bolmont, D. Boncioli, P. Bosso, G. Calcagni, S. Capozziello, J.M. Carmona, S. Cerci, M. Chernyakova, S. Clesse, J.A.B. Coelho, S.M. Colak, J.L. Cortes, S. Das, V. D’Esposito, M. Demirci, M.G. Di Luca, A. di Matteo, D. Dimitrijevic, G. Djordjevic, D. Dominis Prester, A. Eichhorn, J. Ellis, C. Escamilla-Rivera, G. Fabiano, S.A. Franchino-Viñas, A.M. Frassino, D. Frattulillo, S. Funk, A. Fuster, J. Gamboa, A. Gent, L.Á. Gergely, M. Giammarchi, K. Giesel, J.-F. Glicenstein, J. Gracia-Bondía, R. Gracia-Ruiz, G. Gubitosi, E.I. Guendelman, I. Gutierrez-Sagredo, L. Haegel, S. Heefer, A. Held, F.J. Herranz, T. Hinderer, J.I. Illana, A. Ioannisian, P. Jetzer, F.R. Joaquim, K.-H. Kampert, A. Karasu Uysal, T. Katori, N. Kazarian, D. Kerszberg, J. Kowalski-Glikman, S. Kuroyanagi, C. Lämmerzahl, J. Levi Said, S. Liberati, E. Lim, I.P. Lobo, M. López-Moya, G.G. Luciano, M. Manganaro, A. Marcianò, P. Martín-Moruno, Manel Martinez, Mario Martinez, H. Martínez-Huerta, P. Martínez-Miravé, M. Masip, D. Mattingly, N. Mavromatos, A. Mazumdar, F. Méndez, F. Mercati, S. Micanovic, J. Mielczarek, A.L. Miller, M. Milosevic, D. Minic, L. Miramonti, V.A. Mitsou, P. Moniz, S. Mukherjee, G. Nardini, S. Navas, M. Niechciol, A.B. Nielsen, N.A. Obers, F. Oikonomou, D. Oriti, C.F. Paganini, S. Palomares-Ruiz, R. Pasechnik, V. Pasic, C. Pérez de los Heros, C. Pfeifer, M. Pieroni, T. Piran, A. Platania, S. Rastgoo, J.J. Relancio, M.A. Reyes, A. Ricciardone, M. Risse, M.D. Rodriguez Frias, G. Rosati, D. Rubiera-Garcia, H. Sahlmann, M. Sakellariadou, F. Salamida, E.N. Saridakis, P. Satunin, M. Schiffer, F. Schüssler, G. Sigl, J. Sitarek, J. Solà Peracaula, C.F. Sopuerta, T.P. Sotiriou, M. Spurio, D. Staicova, N. Stergioulas, S. Stoica, J. Strišković, T. Stuttard, D. Sunar Cerci, Y. Tavakoli, C.A. Ternes, T. Terzić, T. Thiemann, P. Tinyakov, M.D.C. Torri, M. Tórtola, C. Trimarelli, T. Trześniewski, A. Tureanu, F.R. Urban, E.C. Vagenas, D. Vernieri, V. Vitagliano, J.-C. Wallet, J.D. Zornoza, Addazi, A., Alvarez-Muniz, J., Alves Batista, R., Amelino-Camelia, G., Antonelli, V., Arzano, M., Asorey, M., Atteia, J. -L., Bahamonde, S., Bajardi, F., Ballesteros, A., Baret, B., Barreiros, D. M., Basilakos, S., Benisty, D., Birnholtz, O., Blanco-Pillado, J. J., Blas, D., Bolmont, J., Boncioli, D., Bosso, P., Calcagni, G., Capozziello, S., Carmona, J. M., Cerci, S., Chernyakova, M., Clesse, S., Coelho, J. A. B., Colak, S. M., Cortes, J. L., Das, S., D'Esposito, V., Demirci, M., Di Luca, M. G., di Matteo, A., Dimitrijevic, D., Djordjevic, G., Prester, D. D., Eichhorn, A., Ellis, J., Escamilla-Rivera, C., Fabiano, G., Franchino-Vinas, S. A., Frassino, A. M., Frattulillo, D., Funk, S., Fuster, A., Gamboa, J., Gent, A., Gergely, L. A., Giammarchi, M., Giesel, K., Glicenstein, J. -F., Gracia-Bondia, J., Gracia-Ruiz, R., Gubitosi, G., Guendelman, E. I., Gutierrez-Sagredo, I., Haegel, L., Heefer, S., Held, A., Herranz, F. J., Hinderer, T., Illana, J. I., Ioannisian, A., Jetzer, P., Joaquim, F. R., Kampert, K. -H., Uysal, A. K., Katori, T., Kazarian, N., Kerszberg, D., Kowalski-Glikman, J., Kuroyanagi, S., Lammerzahl, C., Said, J. L., Liberati, S., Lim, E., Lobo, I. P., Lopez-Moya, M., Luciano, G. G., Manganaro, M., Marciano, A., Martin-Moruno, P., Martinez, M., Martinez-Huerta, H., Martinez-Mirave, P., Masip, M., Mattingly, D., Mavromatos, N., Mazumdar, A., Mendez, F., Mercati, F., Micanovic, S., Mielczarek, J., Miller, A. L., Milosevic, M., Minic, D., Miramonti, L., Mitsou, V. A., Moniz, P., Mukherjee, S., Nardini, G., Navas, S., Niechciol, M., Nielsen, A. B., Obers, N. A., Oikonomou, F., Oriti, D., Paganini, C. F., Palomares-Ruiz, S., Pasechnik, R., Pasic, V., Perez de los Heros, C., Pfeifer, C., Pieroni, M., Piran, T., Platania, A., Rastgoo, S., Relancio, J. J., Reyes, M. A., Ricciardone, A., Risse, M., Frias, M. D. R., Rosati, G., Rubiera-Garcia, D., Sahlmann, H., Sakellariadou, M., Salamida, F., Saridakis, E. N., Satunin, P., Schiffer, M., Schussler, F., Sigl, G., Sitarek, J., Peracaula, J. S., Sopuerta, C. F., Sotiriou, T. P., Spurio, M., Staicova, D., Stergioulas, N., Stoica, S., Striskovic, J., Stuttard, T., Cerci, D. S., Tavakoli, Y., Ternes, C. A., Terzic, T., Thiemann, T., Tinyakov, P., Torri, M. D. C., Tortola, M., Trimarelli, C., Trzesniewski, T., Tureanu, A., Urban, F. R., Vagenas, E. C., Vernieri, D., Vitagliano, V., Wallet, J. -C., Zornoza, J. D., AstroParticule et Cosmologie (APC (UMR_7164)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE (UMR_7585)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique des 2 Infinis Irène Joliot-Curie (IJCLab), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), A. Addazi, J. Alvarez-Muniz, R. Alves Batista, G. Amelino-Camelia, V. Antonelli, M. Arzano, M. Asorey, J.-L. Atteia, S. Bahamonde, F. Bajardi, A. Ballestero, B. Baret, D.M. Barreiro, S. Basilako, D. Benisty, O. Birnholtz, J.J. Blanco-Pillado, D. Bla, J. Bolmont, D. Boncioli, P. Bosso, G. Calcagni, S. Capozziello, J.M. Carmona, S. Cerci, M. Chernyakov, S. Clesse, J.A.B. Coelho, S.M. Colak, J.L. Corte, S. Da, V. D???Esposito, M. Demirci, M.G. Di Luca, A. di Matteo, D. Dimitrijevic, G. Djordjevic, D. Dominis Prester, A. Eichhorn, J. Elli, C. Escamilla-Rivera, G. Fabiano, S.A. Franchino-Vi??a, A.M. Frassino, D. Frattulillo, S. Funk, A. Fuster, J. Gamboa, A. Gent, L.??. Gergely, M. Giammarchi, K. Giesel, J.-F. Glicenstein, J. Gracia-Bond??a, R. Gracia-Ruiz, G. Gubitosi, E.I. Guendelman, I. Gutierrez-Sagredo, L. Haegel, S. Heefer, A. Held, F.J. Herranz, T. Hinderer, J.I. Illana, A. Ioannisian, P. Jetzer, F.R. Joaquim, K.-H. Kampert, A. Karasu Uysal, T. Katori, N. Kazarian, D. Kerszberg, J. Kowalski-Glikman, S. Kuroyanagi, C. L??mmerzahl, J. Levi Said, S. Liberati, E. Lim, I.P. Lobo, M. L??pez-Moya, G.G. Luciano, M. Manganaro, A. Marcian??, P. Mart??n-Moruno, Manel Martinez, Mario Martinez, H. Mart??nez-Huerta, P. Mart??nez-Mirav??, M. Masip, D. Mattingly, N. Mavromato, A. Mazumdar, F. M??ndez, F. Mercati, S. Micanovic, J. Mielczarek, A.L. Miller, M. Milosevic, D. Minic, L. Miramonti, V.A. Mitsou, P. Moniz, S. Mukherjee, G. Nardini, S. Nava, M. Niechciol, A.B. Nielsen, N.A. Ober, F. Oikonomou, D. Oriti, C.F. Paganini, S. Palomares-Ruiz, R. Pasechnik, V. Pasic, C. P??rez de los Hero, C. Pfeifer, M. Pieroni, T. Piran, A. Platania, S. Rastgoo, J.J. Relancio, M.A. Reye, A. Ricciardone, M. Risse, M.D. Rodriguez Fria, G. Rosati, D. Rubiera-Garcia, H. Sahlmann, M. Sakellariadou, F. Salamida, E.N. Saridaki, P. Satunin, M. Schiffer, F. Sch??ssler, G. Sigl, J. Sitarek, J. Sol?? Peracaula, C.F. Sopuerta, T.P. Sotiriou, M. Spurio, D. Staicova, N. Stergioula, S. Stoica, J. Stri??kovi??, T. Stuttard, D. Sunar Cerci, Y. Tavakoli, C.A. Terne, T. Terzi??, T. Thiemann, P. Tinyakov, M.D.C. Torri, M. T??rtola, C. Trimarelli, T. Trze??niewski, A. Tureanu, F.R. Urban, E.C. Vagena, D. Vernieri, V. Vitagliano, J.-C. Wallet, J.D. Zornoza, Laboratoire de Physique Théorique d'Orsay [Orsay] (LPT), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11), Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Generalitat de Catalunya, European Commission, Xunta de Galicia, Ministerio de Economía y Competitividad (España), European Research Council, Eusko Jaurlaritza, Generalitat Valenciana, Japan Society for the Promotion of Science, and Comunidad de Madrid

Subjects
High Energy Physics - Theory, CAUSAL DYNAMICAL TRIANGULATIONS, Ultra-high-energy cosmic rays, [PHYS.MPHY]Physics [physics]/Mathematical Physics [math-ph], Lorentz invariance violation and deformation, Gamma-ray astronomy, Cosmic neutrinos, Gravitational waves, General Relativity and Quantum Cosmology, Lorentz transformations, Gravitational waves -- Detection, High Energy Physics - Phenomenology (hep-ph), Astronomi, astrofysik och kosmologi, Gamma ray astronomy, Astronomy, Astrophysics and Cosmology, Cosmic neutrino, astro-ph.HE, High Energy Astrophysical Phenomena (astro-ph.HE), General Relativity and Cosmology, hep-th, hep-ph, Quantum cosmology, ENERGY COSMIC-RAYS, High Energy Physics - Phenomenology, [PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc], Neutrinos -- Scattering, Astrophysics - High Energy Astrophysical Phenomena, Particle Physics - Theory, Gravitational wave, ACTIVE GALACTIC NUCLEI, Astrophysics and Astronomy, Nuclear and High Energy Physics, [PHYS.ASTR.HE]Physics [physics]/Astrophysics [astro-ph]/High Energy Astrophysical Phenomena [astro-ph.HE], gr-qc, FOS: Physical sciences, General Relativity and Quantum Cosmology (gr-qc), GAMMA-RAY BURST, DOUBLY-SPECIAL RELATIVITY, Ultra-high-energy cosmic ray, Particle Physics - Phenomenology, PRIMORDIAL BLACK-HOLES, Matematikk og Naturvitenskap: 400::Fysikk: 430 [VDP], COHERENT STATES GCS, Quantum gravity, GENERALIZED UNCERTAINTY PRINCIPLE, EXTRAGALACTIC BACKGROUND LIGHT, High Energy Physics - Theory (hep-th), [PHYS.HPHE]Physics [physics]/High Energy Physics - Phenomenology [hep-ph], LORENTZ INVARIANCE VIOLATION
Abstract

The exploration of the universe has recently entered a new era thanks to the multimessenger paradigm, characterized by a continuous increase in the quantity and quality of experimental data that is obtained by the detection of the various cosmic messengers (photons, neutrinos, cosmic rays and gravitational waves) from numerous origins. They give us information about their sources in the universe and the properties of the intergalactic medium. Moreover, multi-messenger astronomy opens up the possibility to search for phenomenological signatures of quantum gravity. On the one hand, the most energetic events allow us to test our physical theories at energy regimes which are not directly accessible in accelerators; on the other hand, tiny effects in the propagation of very high energy particles could be amplified by cosmological distances. After decades of merely theoretical investigations, the possibility of obtaining phenomenological indications of Planck-scale effects is a revolutionary step in the quest for a quantum theory of gravity, but it requires cooperation between different communities of physicists (both theoretical and experimental). This review, prepared within the COST Action CA18108 ‘‘Quantum gravity phenomenology in the multi-messenger approach", is aimed at promoting this cooperation by giving a state-of-the art account of the interdisciplinary expertise that is needed in the effective search of quantum gravity footprints in the production, propagation and detection of cosmic messengers., Talent Scientific Research Program of College of Physics, Sichuan University 1082204112427, Fostering Program in Disciplines Possessing Novel Features for Natural Science of Sichuan University 2020SCUNL209, 1000 Talent program of Sichuan province 2021, Xunta de Galicia, European Commission European Union ERDF, "Maria de Maeztu'' Units of Excellence program MDM-2016-0692, Red Tematica Nacional de Astroparticulas RED2018-102661-T, La Caixa Foundation 100010434, European Commission 847648 LCF/BQ/PI21/11830030 754510, Ministry of Education, Science & Technological Development, Serbia 451-03-9/2021-14/200124, FSR Incoming Postdoctoral Fellowship Ministry of Education, Science and Technological Development, Serbia 451-03-9/2021-14/200124, University of Rijeka grant uniri-prirod-18-48, Croatian Science Foundation (HRZZ) IP-2016-06-9782, Villum Fonden 29405 DGA-FSE 2020-E2117R, European Regional Development Fund through the Center of Excellence (TK133) "The Dark Side of the Universe'' European Regional Development Fund (ESIF/ERDF), Ministry of Education, Youth & Sports - Czech Republic CoGraDS-CZ.02.1.01/0.0/0.0/15 003/0000437, Blavatnik grant, Basque Government IT-97916 Basque Foundation for Science (IKERBASQUE), European Space Agency C4000120711 4000132310, FNRS (Belgian Fund for Research), Programa de Apoyo a Proyectos de Investigacion e Innovacion Tecnologica (PAPIIT), Universidad Nacional Autonoma de Mexico TA100122, National University of La Plata X909 DICYT 042131GR, National Research, Development & Innovation Office (NRDIO) - Hungary 123996, FQXi, Swiss National Science Foundation (SNSF), European Commission 181461 199307, Netherlands Organization for Scientific Research (NWO) 680-91-119 15MV71, Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research (KAKENHI) 20H01899 20H05853 JP21F21789, Estonian Research Council PRG356, Julian Schwinger Foundation, Generalitat Valenciana Excellence PROMETEO-II/2017/033 PROMETEO/2018/165, Istituto Nazionale di Fisica Nucleare (INFN), European ITN project HIDDeN H2020-MSCA-ITN-2019//860881-HIDDeN, Swedish Research Council, European Commission 2016-05996 European Research Council (ERC) European Commission 668679, Advanced ERC grant TReX, Ministry of Education, Universities and Research (MIUR) 2017X7X85K, Fonds de la Recherche Scientifique - FNRS 4.4501.18, Ministry of Research, Innovation and Digitization - Romania PN19-030102-INCDFM PN-III-P4ID-PCE-2020-2374, United States Department of Energy (DOE) DE-SC0020262, Ministry of Science, ICT & Future Planning, Republic of Korea 075-15-2020-778, German Academic Scholarship Foundation German Research Foundation (DFG) 408049454 420243324 425333893 445990517 Germany's Excellence Strategy (EXC 2121 "Quantum Universe'') 390833306 390837967 Federal Ministry of Education & Research (BMBF) 05 A20GU2 05 A20PX1, Centro de Excelencia "Severo Ochoa'' SEV-2016-0588, CERCA program of the Generalitat de Catalunya, Agencia de Gestio D'Ajuts Universitaris de Recerca Agaur (AGAUR) Generalitat de Catalunya 2017-SGR-1469 2017-SGR-929 ICCUB CEX2019-000918-M, National Science Centre, Poland 2019/33/B/ST2/00050 2017/27/B/ST2/01902, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ) 306414/2020-1, Dicyt-USACH 041931MF, National Science Fund of Bulgaria KP-06-N 38/11 RCN ROMFORSK 302640, Comunidad de Madrid 2018-T1/TIC-10431 2019-T1/TIC-13177 S2018/NMT-4291, UK Research & Innovation (UKRI), Science & Technology Facilities Council (STFC) ST/T000759/1 ST/P000258/1 ST/T000732/1 ST/V005596/1, Portuguese Foundation for Science and Technology UIDB/00618/2020 UIDB/00777/2020 UIDP/00777/2020 CERN/FIS-PAR/0004/2019 PTDC/FIS-PAR/29436/2017 PTDC/FISPAR/31938/2017 PTDC/FIS-OUT/29048/2017 SFRH/BD/137127/2018, Centre National de la Recherche Scientifique (CNRS), LabEx UnivEarthS ANR-10-LABX-0023 ANR18-IDEX-0001, Junta de Andalucia European Commission A-FQM-053-UGR18, Natural Sciences and Engineering Research Council of Canada (NSERC) RGPIN-2021-03644, National Science Centre Poland Sonata Bis 2019/33/B/ST2/00050 DEC-2017/26/E/ST2/00763, Natural Sciences and Engineering Research Council of Canada (NSERC) DGIID-DGA 2015-E24/2, Spanish Research State Agency and Ministerio de Ciencia e Innovacion MCIN/AEI PID2019-104114RB-C32 PID2019-105544GB-I00 PID2019-105614GB-C21 PID2019106515GB-I00 PID2019-106802GB-I00 PID2019-107394GB-I00 PID2019-107844GB-C21 PID2019-107847RB-C41 MCIN/AEI PGC2018-095328-B-I00 PGC2018-094856-B-I00 PGC2018-096663-B-C41 PGC2018-096663-B-C44 PGC2018-094626-BC21 PGC2018-101858-B-I00 FPA2017-84543-P FPA2016-76005-C2-1-P, Spanish 'Ministerio de Universidades' BG20/00228 Spanish Government PID2020-115845GBI00 Generalitat de Catalunya Comunidad de Madrid S2018/NMT-4291 Spanish Government PID2019-105544GB-I00, Perimeter Institute for Theoretical Physics, Government of Canada through the Department of Innovation, Science and Economic Development, Province of Ontario through the Ministry of Colleges and Universities, Centre National de la Recherche Scientifique (CNRS), Netherlands Organization for Scientific Research (NWO), Fundamental Questions Institute (FQXi), European Cooperation in Science and Technology (COST) CA18108, Research Council of University of Guilan, Iniziativa Specifica TEONGRAV Iniziativa Specifica QGSKY Iniziativa Specifica QUAGRAP Iniziativa Specifica GeoSymQFT, the Spanish Research State Agency and Ministerio de Ciencia e Innovacion MCIN/AEI PID2020-115845GBI00 PID2019-108485GB-I00 PID2020-113334GB-I00 PID2020-113701GB-I00 PID2020-113775GB-I00 PID2020-118159GB-C41 PID2020-118159GA-C42 PRE2019-089024, Rothchild grant UID/MAT/00212/2020 FPU18/04571

Published
2022

16. Radio Resource Management for eICIC, CoMP, Relaying and Back-Hauls Techniques in LTE-Advanced Networks, Concepts and a Literature Survey

Author

Najem N. Sirhan and Manel Martinez-Ramon

Subjects
Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Computer Science - Networking and Internet Architecture, General Earth and Planetary Sciences, General Environmental Science
Abstract

Frequency reuse in cells is one of the strategies that LTE (Long Term Evolution) uses to maximize the spectrum efficiency. However, it leads to an interference among the cells, especially at the cell edges where the probability for a cell-edge user to be scheduled on a resource block that is being transmitted by the neighbouring cell is high; consequently, the interference is high. In-order to mitigate Inter-Cell Interference (ICI), Inter-Cell Interference Coordination (ICIC) was proposed by the Third Generation Partnership Project (3GPP) standards for the LTE network, and later on, the enhanced Inter-Cell Interference Coordination (eICIC) was proposed for the LTE-Advanced network. ICIC reduces cell-edge interference on traffic channels from neighbouring cells by the use of three interference reduction schemes that works in the power and frequency domain, and they are based on lowering the power of some channels to limit their reception to the users that are close to the base station, and by reducing the chance of frequency overlap. eICIC was proposed to handle ICI in Heterogeneous Network (HetNet) deployments. It reduces the interference on both the traffic and control channels. It uses power, frequency and also time domain to mitigate intra-frequency interference in HetNets. Another technique that was proposed by the 3GPP for the LTE-Advanced network that can reduce the ICI and improve the cell average and cell-edge user throughput is the Coordinated Multi-Point (CoMP) transmission/reception technique. CoMP can increase the cell average and cell edge user throughput in both the uplink and downlink transmission by joint scheduling and data processing in multiple cells/eNBs. Another technique that was proposed by the 3GPP for the LTE-Advanced network that can improve the LTE network coverage in difficult conditions is to deploy Relay Nodes (RNs). In this paper, we survey Radio Resource Management (RRM) for some of the techniques that are used with LTE-A. The included techniques in this paper are; the ICIC, eICIC, CoMP, Relaying and Back-hauls. We start by explaining the concepts of these techniques. Then, by summarizing the radio resource management approaches that were proposed in the literature for these techniques. And finally, we provide some concluding remarks in the last section.

Published
2022

17. Radio Resource Management for Eicic, Comp, Relaying and Back-hauls Techniques in LTE-advanced Networks: Concepts and a Literature Survey

Author

Najem N. Sirhan And Manel Martinez-Ramon

Abstract

Frequency reuse in cells is one of the strategies that LTE (Long Term Evolution) uses to maximize the spectrum efficiency. However, it leads to an interference among the cells, especially at the cell edges where the probability for a cell-edge user to be scheduled on a resource block that is being transmitted by the neighbouring cell is high; consequently, the interference is high. In-order to mitigate Inter-Cell Interference (ICI), Inter-Cell Interference Coordination (ICIC) was proposed by the Third Generation Partnership Project (3GPP) standards for the LTE network, and later on, the enhanced Inter-Cell Interference Coordination (eICIC) was proposed for the LTE-Advanced network. ICIC reduces cell-edge interference on traffic channels from neighbouring cells by the use of three interference reduction schemes that works in the power and frequency domain, and they are based on lowering the power of some channels to limit their reception to the users that are close to the base station, and by reducing the chance of frequency overlap. eICIC was proposed to handle ICI in Heterogeneous Network (HetNet) deployments. It reduces the interference on both the traffic and control channels. It uses power, frequency and also time domain to mitigate intra-frequency interference in HetNets. Another technique that was proposed by the 3GPP for the LTE-Advanced network that can reduce the ICI and improve the cell average and cell-edge user throughput is the Coordinated Multi-Point (CoMP) transmission/reception technique. CoMP can increase the cell average and cell edge user throughput in both the uplink and downlink transmission by joint scheduling and data processing in multiple cells/eNBs. Another technique that was proposed by the 3GPP for the LTE-Advanced network that can improve the LTE network coverage in difficult conditions is to deploy Relay Nodes (RNs). In this paper, we survey Radio Resource Management (RRM) for some of the techniques that are used with LTE-A. The included techniques in this paper are; the ICIC, eICIC, CoMP, Relaying and Back-hauls. We start by explaining the concepts of these techniques. Then, by summarizing the radio resource management approaches that were proposed in the literature for these techniques. And finally, we provide some concluding remarks in the last section.

Published
2022
Full Text
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18. LTE Cellular Networks Packet Scheduling Algorithms in Downlink and Uplink Transmission: A Survey

Author

Najem N. Sirhan, Manel Martinez-Ramon

Subjects
LTE cellular netwoks, Packet scheduling algorithms, Downlink, Uplink
Abstract

This survey paper provides a detailed explanation of Long Term Evolution (LTE) cellular network’s packet scheduling algorithms in both downlink and uplink directions. It starts by explaining the difference between Orthogonal Frequency Division Multiple Access (OFDMA) that is used in downlink transmission, and Single Carrier – Frequency Division Multiple Access (SC-FDMA) is used in uplink. Then, it explains the difference between the LTE scheduling process in the donwlink and uplink through explaining the interaction between users and the scheduler. Then, it explains the most commonly used downlink and uplink scheduling algorithms through analyzing their formulas, characteristics, most suitable conditions for them to work in, and the main differences among them. This explanation covers the Max Carrier-toInterference (C/I), Round Robin (RR), Proportional Fair (PF), Earliest Deadline First (EDF), Modified EDF-PF, Modified-Largest Weighted Delay First (M-LWDF), Exponential Proportional Fairness (EXPPF), Token Queues Mechanism, Packet Loss Ratio (PLR), Quality Guaranteed (QG), Opportunistic Packet Loss Fair (OPLF), Low Complexity (LC), LC-Delay, PF-Delay, Maximum Throughput (MT), First Maximum Expansion (FME), and Adaptive Resource Allocation Based Packet Scheduling (ARABPS). Lastly, it provides some concluding remarks.

Published
2022

19. Searching for VHE gamma-ray emission associated with IceCube neutrino alerts using FACT, H.E.S.S., MAGIC, and VERITAS

Author

Konstancja, Satalecka, Acciari, Victor A., Stefano, Ansoldi, Lucio Angelo Antonelli, Axel Arbet Engels, Manuel, Artero, Katsuaki, Asano, Dominik, Baack, Ana, Babic, Andr('(e))s, Baquero, Ulisses Barres de Almeida, Juan Abel Barrio, Ivana, Batkovi('(c)), Josefa Becerra Gonzalez, Wlodek, Bednarek, Lorenzo, Bellizzi, Elisa, Bernardini, Maria-Isabel, Bernardos, Alessio, Berti, Jürgen, Besenrieder, Wrijupan, Bhattacharyya, Ciro, Bigongiari, Adrian, Biland, Oscar, Blanch, Hendrik, Bökenkamp, Giacomo, Bonnoli, Zeljka, Bosnjak, Giovanni, Busetto, Roberto, Carosi, Giovanni, Ceribella, Matteo, Cerruti, Yating, Chai, Ashot, Chilingarian, Stefan, Cikota, Sidika Merve Colak, Eduardo, Colombo, Jose Luis Contreras, Juan, Cortina, Stefano, Covino, Giacomo D( extquotesingle)Amico, Valerio D( extquotesingle)Elia, Paolo Da Vela, Francesco, Dazzi, Alessandro De Angelis, Barbara De Lotto, Manuel, Delfino, Jordi, Delgado, Carlos Delgado Mendez, Davide, Depaoli, Federico Di Pierro, Leonardo Di Venere, Elia Do Souto Espi(~(n))eira, Dijana Dominis Prester, Alice, Donini, Daniela, Dorner, Michele, Doro, Dominik, Elsaesser, Vandad Fallah Ramazani, Alicia, Fattorini, Maria Victoria Fonseca, Lluis, Font, Christian, Fruck, Satoshi, Fukami, Yasushi, Fukazawa, Garc('(i))a L('(o))pez, Ramon J., Markus, Garczarczyk, Sargis, Gasparyan, Markus, Gaug, Giglietto, Nicola, Francesco, Giordano, Pawel, Gliwny, Nikola, Godinovic, David, Green, Jarred Gershon Green, Daniela, Hadasch, Alexander, Hahn, Lea, Heckmann, Javier, Herrera, John, Hoang, Dario, Hrupec, Moritz, Hütten, Tomohiro, Inada, Kazuma, Ishio, Yuki, Iwamura, Irene Jim('(e))nez Mart('(i))nez, Jenni, Jormanainen, L('(e))a, Jouvin, Marie, Karjalainen, Daniel, Kerszberg, Yukiho, Kobayashi, Hidetoshi, Kubo, Junko, Kushida, Alessandra, Lamastra, Damir, Lelas, Francesco, Leone, Elina, Lindfors, Lena, Linhoff, Saverio, Lombardi, Francesco, Longo, Ruben, Lopez-Coto, Marcos, L('(o))pez-Moya, Alicia, L('(o))pez-Oramas, Loporchio, Serena, Bernardo Machado de Oliveira Fraga, Camilla, Maggio, Pratik, Majumdar, Martin, Makariev, Manuela, Mallamaci, Galina, Maneva, Marina, Manganaro, Karl, Mannheim, Laura, Maraschi, Mos(`(e)), Mariotti, Manel, Martinez, Daniel, Mazin, Stefano, Menchiari, Simone, Mender, Sa( (s))a Mi('(c))anovi('(c)), Davide, Miceli, Tjark, Miener, Jose Miguel Miranda, Razmik, Mirzoyan, Edgar, Molina, Abelardo, Moralejo, Daniel, Morcuende, Victoria, Moreno, Elena, Moretti, Takeshi, Nakamori, Lara, Nava, Vitaly, Neustroev, Cosimo, Nigro, Kari, Nilsson, Kyoshi, Nishijima, Koji, Noda, Seiya, Nozaki, Yoshiki, Ohtani, Tomohiko, Oka, Jorge, Otero-Santos, Simona, Paiano, Michele, Palatiello, David, Paneque, Riccardo, Paoletti, Paredes, Josep M., Lovro, Pavleti('(c)), Pablo, Pe(~(n))il, Massimo, Persic, Marine, Pihet, Pier Giorgio Prada Moroni, Elisa, Prandini, Chaitanya, Priyadarshi, Ivica, Puljak, Wolfgang, Rhode, Marc, Rib('(o)), Javier, Rico, Chiara, Righi, Andrea, Rugliancich, Narek, Sahakyan, Takayuki, Saito, Shunsuke, Sakurai, Francesco Gabriele Saturni, Bernd, Schleicher, Kevin, Schmidt, Thomas, Schweizer, Julian, Sitarek, Iva, ( (S))nidari('(c)), Dorota, Sobczy('(n))ska, Alessia, Spolon, Antonio, Stamerra, Jelena Stri( (s))kovi('(c)), Derek, Strom, Marcel, Strzys, Yusuke, Suda, Tihomir, Suri('(c)), Mitsunari, Takahashi, Ryuji, Takeishi, Fabrizio, Tavecchio, Petar, Temnikov, Tomislav, Terzic, Masahiro, Teshima, Luca, Tosti, Stefano, Truzzi, Antonio, Tutone, Santiago, Ubach, Juliane van Scherpenberg, Gaia, Vanzo, Monica VAZQUEZ ACOSTA, Sofia, Ventura, Vassil, Verguilov, Carlo Francesco Vigorito, Vincenzo, Vitale, Ievgen, Vovk, Martin, Will, Carolin, Wunderlich, Tokonatsu, Yamamoto, Darko, Zari('(c)), Matteo, Balbo, Thomas, Bretz, Jens, Buss, Laura, Eisenberger, Dorothee, Hildebrand, Roman, Iotov, Adelina, Kalenski, Dominik, Neise, Maximilian, Noethe, Aleksander, Paravac, Vitalii, Sliusar, Roland, Walter, Rasha, Abbasi, Markus, Ackermann, Jenni, Adams, Juanan, Aguilar, Ahlers, M., Maryon, Ahrens, Cyril Martin Alispach, Antonio Augusto Alves Junior, Najia Moureen Binte Amin, Rui, An, Karen, Andeen, Tyler, Anderson, Gisela, Anton, Carlos, Arguelles, Yosuke, Ashida, Spencer, Axani, Xinhua, Bai, Aswathi Balagopal, V., Anastasia Maria Barbano, Barwick, S. W., Benjamin, Bastian, Vedant, Basu, Sebastian, Baur, Bay, R. C., Beatty, J. J., Becker, K. -H., Julia Becker Tjus, Chiara, Bellenghi, Segev, Benzvi, Berley, D., Besson, D. Z., Gary, Binder, Daniel, Bindig, Blaufuss, E., Summer, Blot, Matthias, Boddenberg, Federico, Bontempo, Jurgen, Borowka, Boser, S., Olga, Botner, Jakob, Bottcher, Etienne, Bourbeau, Federica, Bradascio, Braun, J., Stephanie, Bron, Jannes, Brostean-Kaiser, Sally-Ann, Browne, Alexander, Burgman, Ryan, Burley, Raffaela, Busse, Michael, Campana, Erin, Carnie-Bronca, Chujie, Chen, Dmitry, Chirkin, Koun, Choi, Bryanlee, Clark, Kenneth, Clark, Lew, Classen, Alan, Coleman, Gabriel, Collin, Conrad, J. M., Paul, Coppin, Pablo, Correa, Cowen, D. F., Cross, R., Christian, Dappen, Pranav, Dave, Catherine DE CLERCQ, James, Delaunay, Hans, Dembinski, Kunal, Deoskar, Sam De Ridder, Abhishek, Desai, Paolo, Desiati, Krijn de Vries, Gwenhaël de Wasseige, Meike De With, Tyce, Deyoung, Sukeerthi, Dharani, Alejandro, Diaz, Juan Carlos Diaz-Velez, Markus, Dittmer, Hrvoje, Dujmovic, Matt, Dunkman, Michael, Duvernois, Emily, Dvorak, Thomas, Ehrhardt, Philipp, Eller, Ralph, Engel, Hannah, Erpenbeck, John, Evans, Evenson, P. A., Kwok Lung Fan, Fazely, A. R., Sebastian, Fiedlschuster, Aaron, Fienberg, Kirill, Filimonov, Chad, Finley, Leander, Fischer, Derek, B Fox, Anna, Franckowiak, Elizabeth, Friedman, Alexander, Fritz, Philipp, Furst, Gaisser, T. K., Jay, Gallagher, Erik, Ganster, Alfonso, Garcia, Simone, Garrappa, Gerhardt, L., Ava, Ghadimi, Christian, Glaser, Theo, Glauch, Thorsten, Glusenkamp, Goldschmidt, A., Javier, Gonzalez, Sreetama, Goswami, Darren, Grant, Timoth('(e))e, Gr('(e))goire, Spencer, Griswold, Mehmet, Gunduz, Christoph, Günther, Christian, Haack, Allan, Hallgren, Halliday, R., Halve, L., Halzen, F., Martin Ha Minh, Kael, Hanson, John, Hardin, Harnisch, Alexander A., Andreas, Haungs, Simon, Hauser, Dustin, Hebecker, Helbing, K., Felix, Henningsen, Hettinger, Emma C., Stephanie, Hickford, Joshua, Hignight, Colton, Hill, Hill, G. C., Kara, Hoffman, Ruth, Hoffmann, Tobias, Hoinka, Benjamin, Hokanson-Fasig, Hoshina, K., Feifei, Huang, Matthias, Huber, Thomas, Huber, Klas, Hultqvist, Mirco, Hunnefeld, Raamis, Hussain, Seongjin, In, Nad(`(e))ge, Iovine, Aya, Ishihara, Matti, Jansson, George, Japaridze, Minjin, Jeong, Ben, Jones, Donghwa, Kang, Woosik, Kang, Xinyue, Kang, Alexander, Kappes, David, Kappesser, Timo, Karg, Martina, Karl, Karle, A., Katz, U., Kauer, M., Moritz, Kellermann, Kelley, J. L., Ali, Kheirandish, Ken( extquotesingle)ichi Kin, Thomas, Kintscher, Joanna, Kiryluk, Spencer, Klein, Ramesh, Koirala, Hermann, Kolanoski, Tomas, Kontrimas, Lutz, Kopke, Claudio, Kopper, Sandro, Kopper, Koskinen, D. J., Paras, Koundal, Michael, Kovacevich, Marek, Kowalski, Tetiana, Kozynets, Emma, Kun, Naoko, Kurahashi, Neha, Lad, Cristina Lagunas Gualda, Justin, Lanfranchi, Michael, J Larson, Frederik Hermann Lauber, Jeffrey, Lazar, Jiwoong, Lee, Kayla, Leonard, Agnieszka, Leszczy('(n))ska, Yijia, Li, Massimiliano, Lincetto, Qinrui, Liu, Maria, Liubarska, Elisa, Lohfink, Cristian Jesus Lozano Mariscal, Lu, Lu, Francesco, Lucarelli, Andrew, Ludwig, William, Luszczak, Yang, Lyu, Wing Yan Ma, James, Madsen, Kendall, Mahn, Yuya, Makino, Sarah, Mancina, Ioana Codrina Maris, Maruyama, Reina H., Mase, K., Thomas, Mcelroy, Frank, Mcnally, James Vincent Mead, Meagher, K., Andres, Medina, Maximilian, Meier, Stephan, Meighen-Berger, Jessie, Micallef, Daniela, Mockler, Teresa, Montaruli, Roger, Moore, Morse, R., Marjon, Moulai, Richard, Naab, Ryo, Nagai, Uwe, Naumann, Jannis, Necker, Le Viet Nguyen, Hans, Niederhausen, Mehr, Nisa, Sarah, Nowicki, Dave, Nygren, Anna Obertacke Pollmann, Marie, Oehler, Olivas, A., Erin O( extquotesingle)Sullivan, Hershal, Pandya, Daria, Pankova, Nahee, Park, Grant, Parker, Ek Narayan Paudel, Larissa, Paul, Carlos Perez de los Heros, Lilly, Peters, Saskia, Philippen, Damian, Pieloth, Sarah, Pieper, Martin, Pittermann, Pizzuto, A., Plum, M., Yuiry, Popovych, Alessio, Porcelli, Maria Prado Rodriguez, Buford Price, P., Brandom, Pries, Gerald, Przybylski, Christoph, Raab, Amirreza, Raissi, Mohamed, Rameez, Rawlins, K., Immacolata Carmen Rea, Abdul, Rehman, Ren('(e)), Reimann, Giovanni, Renzi, Elisa, Resconi, Simeon, Reusch, Mike, Richman, Benedikt, Riedel, Ella, Roberts, Sally, Robertson, Gerrit, Roellinghoff, Martin, Rongen, Carsten, Rott, Tim, Ruhe, Dirk, Ryckbosch, Devyn Rysewyk Cantu, Ibrahim, Safa, Julian, Saffer, Sebastian Sanchez Herrera, Alexander, Sandrock, Joakim, Sandroos, Marcos, Santander, Subir, Sarkar, Sourav, Sarkar, Maximilian Karl Scharf, Merlin, Schaufel, Harald, Schieler, Sebastian, Schindler, Schlunder, P., Torsten, Schmidt, Austin, Schneider, Judith, Schneider, Schröder, Frank G., Lisa Johanna Schumacher, Georg, Schwefer, Steve, Sclafani, Seckel, D., Surujhdeo, Seunarine, Ankur, Sharma, Shefali, Shefali, Manuel, Silva, Barbara, Skrzypek, Ben, Smithers, Robert, Snihur, Jan, Soedingrekso, Dennis, Soldin, Christian, Spannfellner, Glenn, Spiczak, Christian, Spiering, Juliana, Stachurska, Michael, Stamatikos, Stanev, T., Robert, Stein, Joeran, Stettner, Steuer, A., Stezelberger, T., Timo, Sturwald, Thomas, Stuttard, Sullivan, G. W., Taboada, I., Frederik, Tenholt, Samvel, Ter-Antonyan, Tilav, S., Franziska, Tischbein, Kirsten, Tollefson, Christoph, Tönnis, Simona, Toscano, Delia, Tosi, Alexander, Trettin, Maria, Tselengidou, Chunfai, Tung, Andrea, Turcati, Roxanne, Turcotte, Colin, Turley, Jean Pierre Twagirayezu, Bunheng, Ty, Martin Unland Elorrieta, Nora, Valtonen-Mattila, Justin, Vandenbroucke, Nick van Eijndhoven, David, Vannerom, Jakob van Santen, Stef, Verpoest, Matthias, Vraeghe, Walck, C., Timothyblake, Watson, Chris, Weaver, Philip, Weigel, Andreas, Weindl, Matthew, Weiss, Jan, Weldert, Chris, Wendt, Johannes, Werthebach, Mark, Weyrauch, Nathan, Whitehorn, Wiebusch, C. H., Dawn, Williams, Martin, Wolf, Kurt, Woschnagg, Gerrit, Wrede, Johan, Wulff, Xianwu, Xu, Yiqian, Xu, Juan Pablo Yanez, Yoshida, S., Shiqi, Yu, Tianlu, Yuan, Zelong, Zhang, Weidong, Jin, Hassan, Abdalla, Felix, Aharonian, Faical, Ait-Benkhali, Oguzhan, Anguener, Cornelia, Arcaro, Celine, Armand, Tom, Armstrong, Halim, Ashkar, Michael, Backes, Vardan, Baghmanyan, Victor Barbosa Martins, Anna, Barnacka, Monica, Barnard, Rowan, Batzofin, Yvonne, Becherini, David, Berge, Konrad, Bernlöhr, Baiyang, Bi, Markus, Boettcher, Catherine, Boisson, Julien, Bolmont, Mathieu de Bony, Mischa, Breuhaus, Robert, Brose, Francois, Brun, Tomasz, Bulik, Thomas, Bylund, Floriane, Cangemi, Sami, Caroff, Sabrina, Casanova, Jaqueline, Catalano, Pauline, Chambery, Tej Bahadur Chand, Andrew, Chen, Garret, Cotter, Malgorzata, Curlo, Jean Damascene Mbarubucyeye, Isak Delberth Davids, James, Davies, Justine, Devin, Arache, Djannati-Ataï, Anton, Dmytriiev, Axel, Donath, Victor, Doroshenko, Lente, Dreyer, Louis Du Plessis, Connor, Duffy, Kathrin, Egberts, Sabrina, Einecke, Gabriel, Emery, Jean-Pierre, Ernenwein, Steven, Fegan, Kirsty, Feijen, Armand, Fiasson, Gaëtan Fichet de Clairfontaine, Gerard, Fontaine, Lott, Frans, Matthias, Fuessling, Stefan, Funk, Stefano, Gabici, Yves, Gallant, Shahede, Ghafourizade, Gianluca, Giavitto, Luca, Giunti, Dorit, Glawion, Jean-Francois, Glicenstein, Marie-H('(e))l(`(e))ne, Grondin, Sumari, Hattingh, Maria, Haupt, German, Hermann, Jim, Hinton, Werner, Hofmann, Clemens, Hoischen, Tim, Holch, Markus, Holler, Dieter, Horns, Zhiqiu, Huang, David, Huber, Mario, Hörbe, Marek, Jamrozy, Felix, Jankowsky, Vikas, Joshi, Ira, Jung, Eli, Kasai, Krzysztof, Katarzynski, Ul(`(i)), Katz, Dmitry, Khangulyan, Bruno, Khelifi, Stefan, Klepser, Wlodek, Kluzniak, Nukri, Komin, Ruslan, Konno, Karl, Kosack, Dmitriy, Kostunin, Michael, Kreter, Ga( (s))per Kukec Mezek, Anu, Kundu, Giovanni, Lamanna, S('(e))bastien Le Stum, Anne, Lemiere, Marianne, Lemoine-Goumard, Jean-Philippe, Lenain, Fabian, Leuschner, Christelle, Levy, Thomas, Lohse, Anna, Luashvili, Iryna, Lypova, Jonathan, Mackey, Jhilik, Majumdar, Denys, Malyshev, Dmitry, Malyshev, Vincent, Marandon, Paolo, Marchegiani, Alexandre, Marcowith, Arnaud, Mares, Guillem Marti( extquotesingle)i-Devesa, Ramin, Marx, Gilles, Maurin, Pieter, Meintjes, Manuel, Meyer, Alison, Mitchell, Rafal, Moderski, Lars, Mohrmann, Alessandro, Montanari, Chris, Moore, Paul, Morris, Emmanuel, Moulin, Jacques, Muller, Thomas, Murach, Kaori, Nakashima, Mathieu Naurois (de), Amid, Nayerhoda, Hambeleleni, Ndiyavala, Jacek, Niemiec, Angel, Noel, Paul O( extquotesingle)Brien, Laenita Lorraine Oberholzer, Stefan, Ohm, Laura, Olivera-Nieto, Emma Ona-Wilhelmi (de), Michal, Ostrowski, Sebastian, Panny, Michael, Panter, Dan, Parsons, Giada, Peron, Santiago, Pita, Vincent, Poireau, Dmitry, Prokhorov, Heike, Prokoph, Gerd, Puehlhofer, Michael, Punch, Andreas, Quirrenbach, Patrick, Reichherzer, Anita, Reimer, Olaf, Reimer, Quentin, Remy, Matthieu, Renaud, Brian, Reville, Frank, Rieger, Carlo, Romoli, Gavin, Rowell, Bronislaw, Rudak, Hector Rueda Ricarte, Edna Ruiz Velasco, Vardan, Sahakian, Simon, Sailer, Heiko, Salzmann, David, Sanchez, Andrea, Santangelo, Manami, Sasaki, Johannes, Schaefer, Hester, Schutte, Ullrich, Schwanke, Fabian, Schüssler, Mohanraj, Senniappan, Albert, Seyffert, Shapopi, Jimmy N. S., Kleopas, Shiningayamwe, Rachel, Simoni, Atreyee, Sinha, Helene, Sol, Hugh, Spackman, Andreas, Specovius, Samuel Timothy Spencer, Marion, Spir-Jacob, Lukasz, Stawarz, Riaan, Steenkamp, Christian, Stegmann, Simon, Steinmassl, Constantin, Steppa, Lei, Sun, Tadayuki, Takahashi, Takaaki, Tanaka, Thomas, Tavernier, Andrew, Taylor, Regis, Terrier, Hannes, Thiersen, Charles, Thorpe-Morgan, Martin, Tluczykont, Lenka, Tomankova, Michelle, Tsirou, Naomi, Tsuji, Richard, Tuffs, Yasunobu, Uchiyama, Johann van der Walt, Christopher van Eldik, Carlo van Rensburg, Brian van Soelen, George, Vasileiadis, Johannes, Veh, Christo, Venter, Pascal, Vincent, Jacco, Vink, Völk, Heinrich J., Stefan, Wagner, Jason John Watson, Felix, Werner, Richard, White, Alicja, Wierzcholska, Yu Wun Wong, Hend, Yassin, Anke, Yusafzai, Michael, Zacharias, Roberta, Zanin, Davit, Zargaryan, Andrzej, Zdziarski, Andreas, Zech, Sylvia, Zhu, Andreas, Zmija, Samuel, Zouari, Natalia, Zywucka, The FACT Collaboration, The H.E.S.S. Collaboration, The IceCube Collaboration, The MAGIC Collaboration, The VERITAS Collaboration, and Współautorami artykułu są członkowie Magic Collaboration, IceCube Collaboration, FACT Collaboration, H.E.S.S. Collaboration, VERITAS Collaboration w liczbie 808

Subjects
Physics, High Energy Astrophysical Phenomena (astro-ph.HE), Point source, Astrophysics::High Energy Astrophysical Phenomena, Gamma ray, Astrophysics::Instrumentation and Methods for Astrophysics, FOS: Physical sciences, IACT, Astrophysics, law.invention, High Energy Physics - Experiment, Telescope, High Energy Physics - Experiment (hep-ex), law, HESS - Abteilung Hinton, ddc:530, High Energy Physics::Experiment, MAGIC (telescope), Neutrino, Blazar, Astrophysics - High Energy Astrophysical Phenomena, Cherenkov radiation
Abstract

The realtime follow-up of neutrino events is a promising approach to search for astrophysical neutrino sources. It has so far provided compelling evidence for a neutrino point source: the flaring gamma-ray blazar TXS 0506+056 observed in coincidence with the high-energy neutrino IceCube-170922A detected by IceCube. The detection of very-high-energy gamma rays (VHE, $\mathrm{E} > 100\,\mathrm{GeV}$) from this source helped establish the coincidence and constrained the modeling of the blazar emission at the time of the IceCube event. The four major imaging atmospheric Cherenkov telescope arrays (IACTs) - FACT, H.E.S.S., MAGIC, and VERITAS - operate an active follow-up program of target-of-opportunity observations of neutrino alerts sent by IceCube. This program has two main components. One are the observations of known gamma-ray sources around which a cluster of candidate neutrino events has been identified by IceCube (Gamma-ray Follow-Up, GFU). Second one is the follow-up of single high-energy neutrino candidate events of potential astrophysical origin such as IceCube-170922A. GFU has been recently upgraded by IceCube in collaboration with the IACT groups. We present here recent results from the IACT follow-up programs of IceCube neutrino alerts and a description of the upgraded IceCube GFU system., Presented at the 37th International Cosmic Ray Conference (ICRC 2021). See arXiv:2107.06966 for all IceCube contributions. See arXiv:2108.05257 for all H.E.S.S. contributions

Published
2022

20. Artificial intelligence, controls, and sensor fusion for optimization and modeling of space missions and particle accelerators

Author

Sandra Biedron, Prof. Manel Martinez-Ramon, Prof. Rafael Fierro, Prof. Yu-Lin Shen, Pirayeshshirazinezhad, Reza, Sandra Biedron, Prof. Manel Martinez-Ramon, Prof. Rafael Fierro, Prof. Yu-Lin Shen, and Pirayeshshirazinezhad, Reza

Subjects
Space mission design
Abstract

This PhD dissertation is devoted to developing artificial intelligence (AI) applications for space missions and particle accelerators considering constraints on the computational resources. The space mission studied in this research, the Virtual Telescope for X-ray Observations (VTXO), is the mission exploiting 2 6U-CubeSats operating in a precision formation. The goal of the VTXO project is to develop a space-based, X-ray imaging telescope with high angular resolution precision. VTXO space mission is designed and the mission is optimized to increase the performance of the mission. Trajectory optimization with AI, hybrid control, control algorithms, and high performance computing are all used to design the VTXO mission. In the other development, AI is applied to particle accelerators, specifically to low-level radio-frequency (LLRF) control and linear accelerator (linacs). For the LLRF, different methods involving machine learning (ML) and optimization are used to increase the control and thus performance of the LLRF. The ML-enhanced LLRF control system can help better stabilize the phase and amplitude of the RF field in particle accelerators. Specifically, we are exploring the LLRF of the the Linac Coherent Light Source II project (LCLS-II). In this accelerator genre, the quality of the electron beam drives the quality of its product - the quality of X-rays produced in a free-electron laser (FEL). Finally, we briefly explore approaches to creating a surrogate model for use to help control a linear accelerator built by Ion Linac Systems (ILS). Such a proton accelerator can be used for generating neutrons for Boron Neutron Capture Therapy (BNCT) to treat cancer. For such a system to be robust and affordable in a medical setting, AI controllers can be developed to support operational tasks.

Published
2022

22. Multiwavelength monitoring of gravitationally lensed blazar QSO B0218+357 between 2016 and 2020

Author

Julian, Sitarek, Acciari, Victor A., Stefano, Ansoldi, Lucio Angelo Antonelli, Axel Arbet Engels, Manuel, Artero, Katsuaki, Asano, Dominik, Baack, Ana, Babic, Andres, Baquero, Ulisses Barres de Almeida, Juan Abel Barrio, Ivana, Batkovic, Josefa Becerra Gonzalez, Wlodek, Bednarek, Lorenzo, Bellizzi, Elisa, Bernardini, Maria-Isabel, Bernardos, Alessio, Berti, Jürgen, Besenrieder, Wrijupan, Bhattacharyya, Ciro, Bigongiari, Adrian, Biland, Oscar, Blanch, Hendrik, Bökenkamp, Giacomo, Bonnoli, Zeljka, Bosnjak, Giovanni, Busetto, Roberto, Carosi, Giovanni, Ceribella, Matteo, Cerruti, Yating, Chai, Ashot, Chilingarian, Stefan, Cikota, Sidika Merve Colak, Eduardo, Colombo, Jose Luis Contreras, Juan, Cortina, Stefano, Covino, Giacomo, D'Amico, Valerio, D'Elia, Paolo Da Vela, Francesco, Dazzi, Alessandro De Angelis, Barbara De Lotto, Manuel, Delfino, Jordi, Delgado, Carlos Delgado Mendez, Davide, Depaoli, Federico Di Pierro, Leonardo Di Venere, Elia Do Souto Espineira, Dijana Dominis Prester, Alice, Donini, Daniela, Dorner, Michele, Doro, Dominik, Elsaesser, Vandad Fallah Ramazani, Alicia, Fattorini, Maria Victoria Fonseca, Lluis, Font, Christian, Fruck, Satoshi, Fukami, Yasushi, Fukazawa, Garcia Lopez, Ramon J., Markus, Garczarczyk, Sargis, Gasparyan, Markus, Gaug, Giglietto, Nicola, Francesco, Giordano, Pawel, Gliwny, Nikola, Godinovic, David, Green, Jarred Gershon Green, Daniela, Hadasch, Alexander, Hahn, Lea, Heckmann, Javier, Herrera, John, Hoang, Dario, Hrupec, Moritz, Hütten, Tomohiro, Inada, Kazuma, Ishio, Yuki, Iwamura, Irene Jimenez Martinez, Jenni, Jormanainen, Lea, Jouvin, Marie, Karjalainen, Daniel, Kerszberg, Yukiho, Kobayashi, Hidetoshi, Kubo, Junko, Kushida, Alessandra, Lamastra, Damir, Lelas, Francesco, Leone, Elina, Lindfors, Lena, Linhoff, Saverio, Lombardi, Francesco, Longo, Ruben, Lopez-Coto, Marcos, Lopez-Moya, Alicia, Lopez-Oramas, Loporchio, Serena, Bernardo Machado de Oliveira Fraga, Camilla, Maggio, Pratik, Majumdar, Martin, Makariev, Manuela, Mallamaci, Galina, Maneva, Marina, Manganaro, Karl, Mannheim, Laura, Maraschi, Mose, Mariotti, Manel, Martinez, Daniel, Mazin, Stefano, Menchiari, Simone, Mender, Sasa, Micanovic, Davide, Miceli, Tjark, Miener, Jose Miguel Miranda, Razmik, Mirzoyan, Edgar, Molina, Abelardo, Moralejo, Daniel, Morcuende, Victoria, Moreno, Elena, Moretti, Takeshi, Nakamori, Lara, Nava, Vitaly, Neustroev, Cosimo, Nigro, Kari, Nilsson, Kyoshi, Nishijima, Koji, Noda, Seiya, Nozaki, Yoshiki, Ohtani, Tomohiko, Oka, Jorge, Otero-Santos, Simona, Paiano, Michele, Palatiello, David, Paneque, Riccardo, Paoletti, Paredes, Josep M., Lovro, Pavletic, Pablo, Penil, Massimo, Persic, Marine, Pihet, Pier Giorgio Prada Moroni, Elisa, Prandini, Chaitanya, Priyadarshi, Ivica, Puljak, Wolfgang, Rhode, Marc, Ribo, Javier, Rico, Chiara, Righi, Andrea, Rugliancich, Narek, Sahakyan, Takayuki, Saito, Shunsuke, Sakurai, Konstancja, Satalecka, Francesco Gabriele Saturni, Bernd, Schleicher, Kevin, Schmidt, Thomas, Schweizer, Iva, Snidaric, Dorota, Sobczynska, Alessia, Spolon, Antonio, Stamerra, Jelena, Striskovic, Derek, Strom, Marcel, Strzys, Yusuke, Suda, Tihomir, Suric, Mitsunari, Takahashi, Ryuji, Takeishi, Fabrizio, Tavecchio, Petar, Temnikov, Tomislav, Terzic, Masahiro, Teshima, Luca, Tosti, Stefano, Truzzi, Antonio, Tutone, Santiago, Ubach, Juliane van Scherpenberg, Gaia, Vanzo, Monica VAZQUEZ ACOSTA, Sofia, Ventura, Vassil, Verguilov, Carlo Francesco Vigorito, Vincenzo, Vitale, Ievgen, Vovk, Martin, Will, Carolin, Wunderlich, Tokonatsu, Yamamoto, Darko, Zaric, Francesco de Palma, Filippo, D'Ammando, Anna, Barnacka, Kazuhiro, Hada, Sahu, Devendra K., Anne, Lähteenmäki, and And

Subjects
Astrophysics::High Energy Astrophysical Phenomena, Astrophysics::Cosmology and Extragalactic Astrophysics
Abstract

QSO B0218+357 is currently the only gravitationally lensed source from which very-high-energy (VHE, &100GeV) gamma-ray emission has been detected. We report the multiwavelength monitoring observations of this source performed between 2016 and 2020 in radio interferometry, optical, X-ray and gamma-ray bands. During the monitoring individual flares and hints of enhanced states in optical, X-ray and GeV bands have been observed, and the simultaneous data taken by the MAGIC telescopes allow us to search for the VHE gamma-ray emission associated with these events., PoS: Proceedings of Science, 395, ISSN:1824-8039, 37th International Cosmic Ray Conference (ICRC 2021)

Published
2022
Full Text
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23. QoS-based Packet Scheduling Algorithms for Heterogeneous LTE-Advanced Networks, Concepts and a Literature Survey

Author

Najem N. Sirhan and Manel Martinez-Ramon

Subjects
Computer Science - Networking and Internet Architecture, Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, General Earth and Planetary Sciences, General Environmental Science
Abstract

The number of LTE (Long-Term Evolution) users and their applications has increased significantly in the last decade, which increased the demand on the mobile network. LTE-Advanced (LTE-A) comes with many features that can support this increasing demand. LTE-A supports Heterogeneous Networks (HetNets) deployment, in which it consists of a mix of macro-cells, remote radio heads, and low power nodes such as Pico-cells, and Femto-cells. Embedding this mix of base-stations in a macro-cellular network allows for achieving significant gains in coverage, throughput and system capacity compared to the use of macrocells only. These base-stations can operate on the same wireless channel as the macro-cellular network, which will provide higher spatial reuse via cell splitting. Also, it allows network operators to support higher data traffic by offloading it to smaller cells, such as Femto-cells. Hence, it enables network operators to provide their growing number of users with the required Quality of Service (QoS) that meets with their service demands. In-order for the network operators to make the best out of the heterogeneous LTE-A network, they need to use QoS-based packet scheduling algorithms that can efficiently manage the spectrum resources in the HetNets deployment. In this paper, we survey Quality of Service (QoS) based packet scheduling algorithms that were proposed in the literature for the use of packet scheduling in Heterogeneous LTE-A Networks. We start by explaining the concepts of QoS in LTE, heterogeneous LTE-A networks, and how traffic is classified within a packet scheduling architecture for heterogeneous LTE-A networks. Then, by summarising the proposed QoS-based packet scheduling algorithms in the literature for Heterogeneous LTE-A Networks, and for Femtocells LTE-A Networks. And finally, we provide some concluding remarks in the last section.

Published
2022
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24. First combined study on Lorentz Invariance violation from observations of energy-dependent time delays from multiple-type gamma-ray sources. I. Motivation, method description, and validation through simulations of H.E.S.S., MAGIC, and VERITAS data sets

Author

Julien Bolmont, Sami Caroff, Markus Gaug, Alasdair Gent, Agnieszka Jacholkowska, Daniel Kerszberg, Christelle Levy, Tony Lin, Manel Martinez, Leyre Nogués, A. Nepomuk Otte, Cédric Perennes, Michele Ronco, Tomislav Terzić, European Commission, Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Generalitat de Catalunya, University of Rijeka, and Croatian Science Foundation

Subjects
Space and Planetary Science, Astronomy and Astrophysics
Abstract

Gamma-ray astronomy has become one of the main experimental ways to test the modified dispersion relations (MDRs) of photons in vacuum, obtained in some attempts to formulate a theory of quantum gravity. The MDRs in use imply time delays that depend on the energy and that increase with distance following some function of redshift. The use of transient, or variable, distant and highly energetic sources already allows us to set stringent limits on the energy scale related to this phenomenon, usually thought to be of the order of the Planck energy, but robust conclusions on the existence of MDR-related propagation effects still require the analysis of a large population of sources. In order to gather the biggest sample of sources possible for MDR searches at teraelectronvolt energies, the H.E.S.S., MAGIC, and VERITAS collaborations enacted a joint task force to combine all their relevant data to constrain the quantum gravity energy scale. In the present article, the likelihood method used to combine the data and provide a common limit is described in detail and tested through simulations of recorded data sets for a gamma-ray burst, three flaring active galactic nuclei, and two pulsars. Statistical and systematic errors are assessed and included in the likelihood as nuisance parameters. In addition, a comparison of two different formalisms for distance dependence of the time lags is performed for the first time. In a second article, to appear later, the method will be applied to all relevant data from the three experiments., This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 754510, from the ERDF under the Spanish Ministerio de Ciencia e Innovación (MICINN), grants PID2019-107847RB-C41 and PID2019-107847RB-C42, the Centro de Excelencia "Severo Ochoa" (SEV-2016-0588), and from the CERCA program of the Generalitat de Catalunya. T.T. acknowledges funding from the University of Rijeka, project number uniri-prirod-18-48, and from the Croatian Science Foundation (HrZZ), project number IP-2016-06-9782.

Published
2022

25. Search for Gamma-ray Line emission from Dark Matter annihilation in the Galactic Centre with the MAGIC telescopes

Author

Tomohiro Inada, Ana Babic, Andrés Baquero, Ivana Batković, Josefa Becerra Gonzalez, Jürgen Besenrieder, Hendrik Bökenkamp, Zeljka Bosnjak, Elia Do Souto Espiñeira, Ramon J. García López, Nikola Godinovic, Moritz Hütten, Irene Jiménez Martínez, Ruben Lopez-Coto, Marcos López-Moya, Alicia López-Oramas, Mosè Mariotti, Manel Martinez, Saša Mićanović, Lovro Pavletić, Pablo Peñil, Marc Ribó, Iva Šnidarić, Jelena Strišković, Tihomir Surić, Tomislav Terzic, Darko Zarić, Victor A. Acciari, Stefano Ansoldi, Lucio Angelo Antonelli, Axel Arbet Engels, Manuel Artero, Katsuaki Asano, Dominik Baack, Ana Babić, Ulisses Barres de Almeida, Juan Abel Barrio, Josefa Becerra González, Wlodek Bednarek, Lorenzo Bellizzi, Elisa Bernardini, Maria-Isabel Bernardos, Alessio Berti, Wrijupan Bhattacharyya, Ciro Bigongiari, Adrian Biland, Oscar Blanch, Giacomo Bonnoli, Željka Bošnjak, Giovanni Busetto, Roberto Carosi, Giovanni Ceribella, Matteo Cerruti, Yating Chai, Ashot Agassi Chilingarian, Stefan Cikota, Sidika Merve Colak, Eduardo Colombo, Jose Luis Contreras, Juan Cortina, Stefano Covino, Giacomo D'Amico, Valerio D'Elia, Paolo Da Vela, Francesco Dazzi, Alessandro De Angelis, Barbara De Lotto, Manuel Delfino, Jordi Delgado, Carlos Delgado Mendez, Davide Depaoli, Federico Di Pierro, Leonardo Di Venere, Dijana Dominis Prester, Alice Donini, Daniela Dorner, Michele Doro, Dominik Elsaesser, Vandad Fallah Ramazani, Alicia Fattorini, Maria Victoria Fonseca, Lluis Font, Christian Fruck, Satoshi Fukami, Yasushi Fukazawa, Markus Garczarczyk, Sargis Gasparyan, Markus Gaug, Nicola Giglietto, Francesco Giordano, Pawel Gliwny, Nikola Godinović, David Green, Jarred Gershon Green, Daniela Hadasch, Alexander Hahn, Lea Heckmann, Javier Herrera, John Hoang, Dario Hrupec, Kazuma Ishio, Yuki Iwamura, Irene Jimenez-Martinez, Jenni Jormanainen, Léa Jouvin, Marie Karjalainen, Daniel Kerszberg, Yukiho Kobayashi, Hidetoshi Kubo, Junko Kushida, Alessandra Lamastra, Damir LELAS, Francesco Leone, Elina Lindfors, Lena Linhoff, Saverio Lombardi, Francesco Longo, Rubén López-Coto, Serena Loporchio, Bernardo Machado de Oliveira Fraga, Camilla Maggio, Pratik Majumdar, Martin MAKARIEV, Manuela Mallamaci, Galina Maneva, Marina Manganaro, Karl Mannheim, Laura Maraschi, Manel Martínez, Daniel Mazin, Stefano Menchiari, Simone Mender, Davide Miceli, Tjark Miener, Jose Miguel Miranda, Razmik Mirzoyan, Edgar Molina, Abelardo Moralejo, Daniel Morcuende, Victoria Moreno, Elena Moretti, Takeshi Nakamori, Lara Nava, Vitaly Neustroev, Cosimo Nigro, Kari Nilsson, Kyoshi Nishijima, Koji Noda, Seiya Nozaki, Yoshiki Ohtani, Tomohiko Oka, Jorge Otero-Santos, Simona Paiano, Michele Palatiello, David Paneque, Riccardo Paoletti, Josep M. Paredes, Massimo Persic, Marine Pihet, Pier Giorgio Prada Moroni, Elisa Prandini, Chaitanya Priyadarshi, Ivica Puljak, Wolfgang Rhode, Javier Rico, Chiara Righi, Andrea Rugliancich, Narek Sahakyan, Takayuki Saito, Shunsuke Sakurai, Konstancja Satalecka, Francesco Gabriele Saturni, Bernd Schleicher, Kevin Schmidt, Thomas Schweizer, Julian Sitarek, Dorota Sobczyńska, Alessia Spolon, Antonio Stamerra, Derek Strom, Marcel C. Strzys, Yusuke Suda, Mitsunari Takahashi, Ryuji Takeishi, Fabrizio Tavecchio, Petar Temnikov, Tomislav Terzić, Masahiro Teshima, Luca Tosti, Stefano Truzzi, Antonio Tutone, Santiago Ubach, Juliane van Scherpenberg, Gaia Vanzo, Monica VAZQUEZ ACOSTA, Sofia Ventura, Vassil VERGUILOV, Carlo francesco Vigorito, Vincenzo Vitale, Ievgen Vovk, Martin Will, Carolin Wunderlich, Tokonatsu Yamamoto, and Daniele Ninci

Subjects
Physics, Annihilation, media_common.quotation_subject, Astrophysics::High Energy Astrophysical Phenomena, Dark matter, Gamma ray, Astrophysics::Instrumentation and Methods for Astrophysics, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Galaxy, Spectral line, Sky, MAGIC (telescope), Zenith, Astrophysics::Galaxy Astrophysics, media_common
Abstract

We present the first search for dark matter (DM) spectral lines in the Galactic centre (GC) region with the MAGIC telescopes. The MAGIC telescopes, located on the Canary island of La Palma (Spain), are sensitive to gamma rays in the energy range from 50 GeV to 50 TeV. MAGIC has performed indirect DM searches in various astrophysical targets, such as dwarf spheroidal galaxies and clusters of galaxies. Observations at high zenith angles significantly increase the telescopes' collection area and sensitivity for gamma rays in the TeV regime. We present the results obtained with more than 200 hours of high-zenith angle observations of the GC region with MAGIC, which allow us to probe promising heavy SUSY models, and to obtain competitive limits to the DM annihilation cross-section at high DM particle mass, compared to existing constraints. We will discuss how we exploit the data from a complex sky region to search for a line-like DM signature., PoS: Proceedings of Science, 395, ISSN:1824-8039, 37th International Cosmic Ray Conference (ICRC 2021)

Published
2022
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29. MAGIC and H.E.S.S. detect VHE gamma rays from the blazar OT081 for the first time: a deep multiwavelength study

Author

Marina, Manganaro, Monica, Seglar-Arroyo, Josefa, Becerra-Gonz('(a))lez, David, Sanchez, Matteo, Cerruti, Fabrizio, Tavecchio, Vandad, Fallah-Ramazani, Ivan, Agudo, Stefano, Ciprini, Alexei Vladimir Filippenko, Esteban-Gutierrez, A., Talvikki, Hovatta, Helen, Jermak, Jorstad, Svetlana G., Kopatskaya, Evgenia N., Larionov, Valeri M., Larionova, L. V., Anne, Lähteenmäki, Alan, Marscher, Morozova, D. A., Marko, Pahljina, Merja, Tornikoski, Yuliya, Troitskaya, Troitsky, I., Francesco, Verrecchia, Xiao, H. B., Weaver, Z. R., Weikang, Zheng, Acciari, Victor A., Stefano, Ansoldi, Lucio Angelo Antonelli, Axel Arbet Engels, Manuel, Artero, Katsuaki, Asano, Dominik, Baack, Ana, Babic, Andr('(e))s, Baquero, Ulisses Barres de Almeida, Juan Abel Barrio, Ivana, Batkovi('(c)), Josefa Becerra Gonzalez, Wlodek, Bednarek, Lorenzo, Bellizzi, Elisa, Bernardini, Maria-Isabel, Bernardos, Alessio, Berti, Jürgen, Besenrieder, Wrijupan, Bhattacharyya, Ciro, Bigongiari, Adrian, Biland, Oscar, Blanch, Hendrik, Bökenkamp, Giacomo, Bonnoli, Zeljka, Bosnjak, Giovanni, Busetto, Roberto, Carosi, Giovanni, Ceribella, Yating, Chai, Ashot, Chilingarian, Stefan, Cikota, Sidika Merve Colak, Eduardo, Colombo, Jose Luis Contreras, Juan, Cortina, Stefano, Covino, Giacomo D( extquotesingle)Amico, Valerio D( extquotesingle)Elia, Paolo Da Vela, Francesco, Dazzi, Alessandro De Angelis, Barbara De Lotto, Manuel, Delfino, Jordi, Delgado, Carlos Delgado Mendez, Davide, Depaoli, Federico Di Pierro, Leonardo Di Venere, Elia Do Souto Espi(~(n))eira, Dijana Dominis Prester, Alice, Donini, Daniela, Dorner, Michele, Doro, Dominik, Elsaesser, Vandad Fallah Ramazani, Alicia, Fattorini, Maria Victoria Fonseca, Lluis, Font, Christian, Fruck, Satoshi, Fukami, Yasushi, Fukazawa, Garc('(i))a L('(o))pez, Ramon J., Markus, Garczarczyk, Sargis, Gasparyan, Markus, Gaug, Giglietto, Nicola, Francesco, Giordano, Pawel, Gliwny, Nikola, Godinovic, David, Green, Jarred Gershon Green, Daniela, Hadasch, Alexander, Hahn, Lea, Heckmann, Javier, Herrera, John, Hoang, Dario, Hrupec, Moritz, Hütten, Tomohiro, Inada, Kazuma, Ishio, Yuki, Iwamura, Irene Jim('(e))nez Mart('(i))nez, Jenni, Jormanainen, L('(e))a, Jouvin, Marie, Karjalainen, Daniel, Kerszberg, Yukiho, Kobayashi, Hidetoshi, Kubo, Junko, Kushida, Alessandra, Lamastra, Damir, Lelas, Francesco, Leone, Elina, Lindfors, Lena, Linhoff, Saverio, Lombardi, Francesco, Longo, Ruben, Lopez-Coto, Marcos, L('(o))pez-Moya, Alicia, L('(o))pez-Oramas, Loporchio, Serena, Bernardo Machado de Oliveira Fraga, Camilla, Maggio, Pratik, Majumdar, Martin, Makariev, Manuela, Mallamaci, Galina, Maneva, Karl, Mannheim, Laura, Maraschi, Mos(`(e)), Mariotti, Manel, Martinez, Daniel, Mazin, Stefano, Menchiari, Simone, Mender, Sa( (s))a Mi('(c))anovi('(c)), Davide, Miceli, Tjark, Miener, Jose Miguel Miranda, Razmik, Mirzoyan, Edgar, Molina, Abelardo, Moralejo, Daniel, Morcuende, Victoria, Moreno, Elena, Moretti, Takeshi, Nakamori, Lara, Nava, Vitaly, Neustroev, Cosimo, Nigro, Kari, Nilsson, Kyoshi, Nishijima, Koji, Noda, Seiya, Nozaki, Yoshiki, Ohtani, Tomohiko, Oka, Jorge, Otero-Santos, Simona, Paiano, Michele, Palatiello, David, Paneque, Riccardo, Paoletti, Paredes, Josep M., Lovro, Pavleti('(c)), Pablo, Pe(~(n))il, Massimo, Persic, Marine, Pihet, Pier Giorgio Prada Moroni, Elisa, Prandini, Chaitanya, Priyadarshi, Ivica, Puljak, Wolfgang, Rhode, Marc, Rib('(o)), Javier, Rico, Chiara, Righi, Andrea, Rugliancich, Narek, Sahakyan, Takayuki, Saito, Shunsuke, Sakurai, Konstancja, Satalecka, Francesco Gabriele Saturni, Bernd, Schleicher, Kevin, Schmidt, Thomas, Schweizer, Julian, Sitarek, Iva, ( (S))nidari('(c)), Dorota, Sobczy('(n))ska, Alessia, Spolon, Antonio, Stamerra, Jelena Stri( (s))kovi('(c)), Derek, Strom, Marcel, Strzys, Yusuke, Suda, Tihomir, Suri('(c)), Mitsunari, Takahashi, Ryuji, Takeishi, Petar, Temnikov, Tomislav, Terzic, Masahiro, Teshima, Luca, Tosti, Stefano, Truzzi, Antonio, Tutone, Santiago, Ubach, Juliane van Scherpenberg, Gaia, Vanzo, Monica VAZQUEZ ACOSTA, Sofia, Ventura, Vassil, Verguilov, Carlo Francesco Vigorito, Vincenzo, Vitale, Ievgen, Vovk, Martin, Will, Carolin, Wunderlich, Tokonatsu, Yamamoto, Darko, Zari('(c)), and And

Subjects
Physics, Astrophysics::High Energy Astrophysical Phenomena, Gamma ray, Spectral energy distribution, Quasar, Astrophysics::Cosmology and Extragalactic Astrophysics, MAGIC (telescope), Astrophysics, Emission spectrum, Light curve, Blazar, Astrophysics::Galaxy Astrophysics, Fermi Gamma-ray Space Telescope
Abstract

OT 081 is a luminous blazar well known for its variability in many energy bands. The very-high-energy (VHE; E >100 GeV) gamma-ray emission from the source was discovered by MAGIC and H.E.S.S. during flaring activity in July 2016, after a trigger from the Large Area Telescope (LAT) onboard the Fermi satellite. By analysing the multiwavelength light curves andthe broadband spectral energy distribution (SED), we study the activity of the source and investigate four individual states of activity in the window from MJD 57575 to 57602. The intrinsic gamma-ray spectrum can be described by a power law with spectral indices of 3.27 ± 0.44(MAGIC)and 3.39 ± 0.58(H.E.S.S.) over energy ranges 60–300 GeV and 120–500 GeV, respectively. The combined contemporaneous high-energy (HE;E >100 MeV) through VHE SED shows curvatureand can be described by a log-parabola shape. A simple one-zone synchrotron self-Compton (SSC)model is not sufficient to describe the broadband SED. The presence of broad emission lines in the optical spectrum of the source challenges the categorisation of OT 081 as a BL Lac and, together with the emission scenarios tested, points to the possibility that the source is transitional in nature between a BL Lac and a flat-spectrum radio quasar.

Published
2021

30. Follow-up observations of GW170817 with the MAGIC telescopes

Author

Antonio Stamerra, Om Sharan Salafia, Alessio Berti, Stefano Covino, Valerio D'Elia, Davide Miceli, Lara Nava, Barbara Patricelli, Chiara Righi, Susumu Inoue, Lucio Angelo Antonelli, Stefano Ansoldi, Barbara De Lotto, Francesco Longo, Fabrizio Tavecchio, Ana Babic, Josefa Becerra Gonzalez, Zeljka Bosnjak, Nikola Godinovic, Ruben Lopez-Coto, Manel Martinez, Tomislav Terzic, Victor A. Acciari, Axel Arbet Engels, Manuel Artero, Katsuaki Asano, Dominik Baack, Ana Babić, Andrés Baquero, Ulisses Barres de Almeida, Juan Abel Barrio, Ivana Batković, Josefa Becerra González, Wlodek Bednarek, Lorenzo Bellizzi, Elisa Bernardini, Maria-Isabel Bernardos, Jürgen Besenrieder, Wrijupan Bhattacharyya, Ciro Bigongiari, Adrian Biland, Oscar Blanch, Hendrik Bökenkamp, Giacomo Bonnoli, Željka Bošnjak, Giovanni Busetto, Roberto Carosi, Giovanni Ceribella, Matteo Cerruti, Yating Chai, Ashot Agassi Chilingarian, Stefan Cikota, Sidika Merve Colak, Eduardo Colombo, Jose Luis Contreras, Juan Cortina, Giacomo D'Amico, Paolo Da Vela, Francesco Dazzi, Alessandro De Angelis, Manuel Delfino, Jordi Delgado, Carlos Delgado Mendez, Davide Depaoli, Federico Di Pierro, Leonardo Di Venere, Elia Do Souto Espiñeira, Dijana Dominis Prester, Alice Donini, Daniela Dorner, Michele Doro, Dominik Elsaesser, Vandad Fallah Ramazani, Alicia Fattorini, Maria Victoria Fonseca, Lluis Font, Christian Fruck, Satoshi Fukami, Yasushi Fukazawa, Ramon J. García López, Markus Garczarczyk, Sargis Gasparyan, Markus Gaug, Nicola Giglietto, Francesco Giordano, Pawel Gliwny, Nikola Godinović, David Green, Jarred Gershon Green, Daniela Hadasch, Alexander Hahn, Lea Heckmann, Javier Herrera, John Hoang, Dario Hrupec, Moritz Hütten, Tomohiro Inada, Kazuma Ishio, Yuki Iwamura, Irene Jiménez Martínez, Jenni Jormanainen, Léa Jouvin, Marie Karjalainen, Daniel Kerszberg, Yukiho Kobayashi, Hidetoshi Kubo, Junko Kushida, Alessandra Lamastra, Damir LELAS, Francesco Leone, Elina Lindfors, Lena Linhoff, Saverio Lombardi, Rubén López-Coto, Marcos López-Moya, Alicia López-Oramas, Serena Loporchio, Bernardo Machado de Oliveira Fraga, Camilla Maggio, Pratik Majumdar, Martin MAKARIEV, Manuela Mallamaci, Galina Maneva, Marina Manganaro, Karl Mannheim, Laura Maraschi, Mosè Mariotti, Manel Martínez, Daniel Mazin, Stefano Menchiari, Simone Mender, Saša Mićanović, Tjark Miener, Jose Miguel Miranda, Razmik Mirzoyan, Edgar Molina, Abelardo Moralejo, Daniel Morcuende, Victoria Moreno, Elena Moretti, Takeshi Nakamori, Vitaly Neustroev, Cosimo Nigro, Kari Nilsson, Kyoshi Nishijima, Koji Noda, Seiya Nozaki, Yoshiki Ohtani, Tomohiko Oka, Jorge Otero-Santos, Simona Paiano, Michele Palatiello, David Paneque, Riccardo Paoletti, Josep M. Paredes, Lovro Pavletić, Pablo Peñil, Massimo Persic, Marine Pihet, Pier Giorgio Prada Moroni, Elisa Prandini, Chaitanya Priyadarshi, Ivica Puljak, Wolfgang Rhode, Marc Ribó, Javier Rico, Andrea Rugliancich, Narek Sahakyan, Takayuki Saito, Shunsuke Sakurai, Konstancja Satalecka, Francesco Gabriele Saturni, Bernd Schleicher, Kevin Schmidt, Thomas Schweizer, Julian Sitarek, Iva Šnidarić, Dorota Sobczyńska, Alessia Spolon, Jelena Strišković, Derek Strom, Marcel C. Strzys, Yusuke Suda, Tihomir Surić, Mitsunari Takahashi, Ryuji Takeishi, Petar Temnikov, Tomislav Terzić, Masahiro Teshima, Luca Tosti, Stefano Truzzi, Antonio Tutone, Santiago Ubach, Juliane van Scherpenberg, Gaia Vanzo, Monica VAZQUEZ ACOSTA, Sofia Ventura, Vassil VERGUILOV, Carlo francesco Vigorito, Vincenzo Vitale, Ievgen Vovk, Martin Will, Carolin Wunderlich, Tokonatsu Yamamoto, and Darko Zarić

Subjects
Physics, Neutron star, Gravitational wave, Astrophysics::High Energy Astrophysical Phenomena, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics, MAGIC (telescope), Maximum flux, Gamma-ray burst
Abstract

The discovery of the electromagnetic counterpart AT2017gfo and the GRB 170817A, associated to the binary neutron star merger GW170817, was one of the major advances in the study of gamma- ray bursts (GRBs) and the hallmark of the multi-messenger astronomy with gravitational waves. Another breakthrough in GRB physics is represented by the discovery of the highly energetic, teraelectronvolt (TeV) component in the GRB 190114C, possibly an universal component in all GRBs. This conclusion is also suggested by the hint of TeV emission in the short GRB 160821B and a few more events reported in the literature. The missing observational piece is the joint detection of TeV emission and gravitational waves from a short GRB and its progenitor. MAGIC observed the counterpart AT2017gfo as soon as the visibility conditions allowed it, namely from January to June 2018. These observations correspond to the maximum flux level observed in the radio and X-ray bands. The upper limits derived from TeV observations are compared with the modelling of the late non-thermal emission using the multi-frequency SED.

Published
2021

31. Experimental optimization and evaluation of an R600a/R1150 auto-cascade refrigeration systems for ultra-low temperature applications

Author

Manel Martínez-Ángeles, Daniel Calleja-Anta, Laura Nebot-Andrés, and Rodrigo Llopis

Subjects
Auto-cascade, Autocascade, COP, Ultra-low temperature, R1150, R600a, Technology
Abstract

Auto-cascade refrigeration systems are the most employed systems for ultra-low temperature applications, especially for small capacity systems. Recent investigations have allowed to analyze them energetically and thermodynamically, starting a research line focused on enhancing their energy performance from experimental approaches. This work focuses on the energy optimization of a real auto-cascade system working with the mixture R600a/R1150 [70/30 %], which has been evaluated using two compressor models for R404A and R290 as well as the optimization of the two capillary tubes used in the system. Results indicate that overall efficiency of the R290 compressor is up to 21 % higher than with R404A, leading to COP increments between 35 and 81 %. Optimum capillary lengths have been determined in terms of COP and energy consumption, reaching similar values, however, the inner parameters of the system change as function of these lengths, which needs to be considered in prototypes design.

Published
2024
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32. Multi-epoch monitoring of {TXS} 0506$\mathplus$056 with {MAGIC} and {MWL} partners

Author

Konstancja, Satalecka, Acciari, Victor A., Stefano, Ansoldi, Lucio Angelo Antonelli, Axel Arbet Engels, Manuel, Artero, Katsuaki, Asano, Dominik, Baack, Ana, Babic, Andr('(e))s, Baquero, Ulisses Barres de Almeida, Juan Abel Barrio, Ivana, Batkovi('(c)), Josefa Becerra Gonzalez, Wlodek, Bednarek, Lorenzo, Bellizzi, Elisa, Bernardini, Maria-Isabel, Bernardos, Alessio, Berti, Jürgen, Besenrieder, Wrijupan, Bhattacharyya, Ciro, Bigongiari, Adrian, Biland, Oscar, Blanch, Hendrik, Bökenkamp, Giacomo, Bonnoli, Zeljka, Bosnjak, Giovanni, Busetto, Roberto, Carosi, Giovanni, Ceribella, Matteo, Cerruti, Yating, Chai, Ashot, Chilingarian, Stefan, Cikota, Sidika Merve Colak, Eduardo, Colombo, Jose Luis Contreras, Juan, Cortina, Stefano, Covino, Giacomo D( extquotesingle)Amico, Valerio D( extquotesingle)Elia, Paolo Da Vela, Francesco, Dazzi, Alessandro De Angelis, Barbara De Lotto, Manuel, Delfino, Jordi, Delgado, Carlos Delgado Mendez, Davide, Depaoli, Federico Di Pierro, Leonardo Di Venere, Elia Do Souto Espi(~(n))eira, Dijana Dominis Prester, Alice, Donini, Daniela, Dorner, Michele, Doro, Dominik, Elsaesser, Vandad Fallah Ramazani, Alicia, Fattorini, Maria Victoria Fonseca, Lluis, Font, Christian, Fruck, Satoshi, Fukami, Yasushi, Fukazawa, Garc('(i))a L('(o))pez, Ramon J., Markus, Garczarczyk, Sargis, Gasparyan, Markus, Gaug, Giglietto, Nicola, Francesco, Giordano, Pawel, Gliwny, Nikola, Godinovic, David, Green, Jarred Gershon Green, Daniela, Hadasch, Alexander, Hahn, Lea, Heckmann, Javier, Herrera, John, Hoang, Dario, Hrupec, Moritz, Hütten, Tomohiro, Inada, Kazuma, Ishio, Yuki, Iwamura, Irene Jim('(e))nez Mart('(i))nez, Jenni, Jormanainen, L('(e))a, Jouvin, Marie, Karjalainen, Daniel, Kerszberg, Yukiho, Kobayashi, Hidetoshi, Kubo, Junko, Kushida, Alessandra, Lamastra, Damir, Lelas, Francesco, Leone, Elina, Lindfors, Lena, Linhoff, Saverio, Lombardi, Francesco, Longo, Ruben, Lopez-Coto, Marcos, L('(o))pez-Moya, Alicia, L('(o))pez-Oramas, Loporchio, Serena, Bernardo Machado de Oliveira Fraga, Camilla, Maggio, Pratik, Majumdar, Martin, Makariev, Manuela, Mallamaci, Galina, Maneva, Marina, Manganaro, Karl, Mannheim, Laura, Maraschi, Mos(`(e)), Mariotti, Manel, Martinez, Daniel, Mazin, Stefano, Menchiari, Simone, Mender, Sa( (s))a Mi('(c))anovi('(c)), Davide, Miceli, Tjark, Miener, Jose Miguel Miranda, Razmik, Mirzoyan, Edgar, Molina, Abelardo, Moralejo, Daniel, Morcuende, Victoria, Moreno, Elena, Moretti, Takeshi, Nakamori, Lara, Nava, Vitaly, Neustroev, Cosimo, Nigro, Kari, Nilsson, Kyoshi, Nishijima, Koji, Noda, Seiya, Nozaki, Yoshiki, Ohtani, Tomohiko, Oka, Jorge, Otero-Santos, Simona, Paiano, Michele, Palatiello, David, Paneque, Riccardo, Paoletti, Paredes, Josep M., Lovro, Pavleti('(c)), Pablo, Pe(~(n))il, Massimo, Persic, Marine, Pihet, Pier Giorgio Prada Moroni, Elisa, Prandini, Chaitanya, Priyadarshi, Ivica, Puljak, Wolfgang, Rhode, Marc, Rib('(o)), Javier, Rico, Chiara, Righi, Andrea, Rugliancich, Narek, Sahakyan, Takayuki, Saito, Shunsuke, Sakurai, Francesco Gabriele Saturni, Bernd, Schleicher, Kevin, Schmidt, Thomas, Schweizer, Julian, Sitarek, Iva, ( (S))nidari('(c)), Dorota, Sobczy('(n))ska, Alessia, Spolon, Antonio, Stamerra, Jelena Stri( (s))kovi('(c)), Derek, Strom, Marcel, Strzys, Yusuke, Suda, Tihomir, Suri('(c)), Mitsunari, Takahashi, Ryuji, Takeishi, Fabrizio, Tavecchio, Petar, Temnikov, Tomislav, Terzic, Masahiro, Teshima, Luca, Tosti, Stefano, Truzzi, Antonio, Tutone, Santiago, Ubach, Juliane van Scherpenberg, Gaia, Vanzo, Monica VAZQUEZ ACOSTA, Sofia, Ventura, Vassil, Verguilov, Carlo Francesco Vigorito, Vincenzo, Vitale, Ievgen, Vovk, Martin, Will, Carolin, Wunderlich, Tokonatsu, Yamamoto, Darko, Zari('(c)), Tommaso, Aniello, Filippo D( extquotesingle)Ammando, Ilaria, Viale, Talvikki, Hovatta, Edwards, Philip G., Sebastian, Kiehlmann, Anthony, Readhead, Matthias, Kadler, Uwe, Bach, David, Berge, Sara, Buson, Florian, Eppel, Marcello, Giroletti, Olivier, Hervet, Andrea, Gokus, Jonas, He(ss)dörfer, Shoko, Koyama, Alex, Kraus, Thomas, Krichbaum, Raniere de Menezes, Roopesh, Ojha, Giorgios, Paraschos, Elisa, Pueschel, Florian, Rösch, Eduardo, Ros, Jonas, Sinapius, Jörn, Wilms, Michael, Zacharias, Jamie, Stevens, and And

Published
2021

33. Monitoring the magnetar {SGR} 1935$\mathplus$2154 with the {MAGIC} telescopes

Author

Alicia, L('(o))pez-Oramas, Irene Jim('(e))nez Mart('(i))nez, Tarek, Hassan, John, Hoang, Susumu, Inoue, Acciari, Victor A., Stefano, Ansoldi, Lucio Angelo Antonelli, Axel Arbet Engels, Manuel, Artero, Katsuaki, Asano, Dominik, Baack, Ana, Babic, Andr('(e))s, Baquero, Ulisses Barres de Almeida, Juan Abel Barrio, Ivana, Batkovi('(c)), Josefa Becerra Gonzalez, Wlodek, Bednarek, Lorenzo, Bellizzi, Elisa, Bernardini, Maria-Isabel, Bernardos, Alessio, Berti, Jürgen, Besenrieder, Wrijupan, Bhattacharyya, Ciro, Bigongiari, Adrian, Biland, Oscar, Blanch, Hendrik, Bökenkamp, Giacomo, Bonnoli, Zeljka, Bosnjak, Giovanni, Busetto, Roberto, Carosi, Giovanni, Ceribella, Matteo, Cerruti, Yating, Chai, Ashot, Chilingarian, Stefan, Cikota, Sidika Merve Colak, Eduardo, Colombo, Jose Luis Contreras, Juan, Cortina, Stefano, Covino, Giacomo D( extquotesingle)Amico, Valerio D( extquotesingle)Elia, Paolo Da Vela, Francesco, Dazzi, Alessandro De Angelis, Barbara De Lotto, Manuel, Delfino, Jordi, Delgado, Carlos Delgado Mendez, Davide, Depaoli, Federico Di Pierro, Leonardo Di Venere, Elia Do Souto Espi(~(n))eira, Dijana Dominis Prester, Alice, Donini, Daniela, Dorner, Michele, Doro, Dominik, Elsaesser, Vandad Fallah Ramazani, Alicia, Fattorini, Maria Victoria Fonseca, Lluis, Font, Christian, Fruck, Satoshi, Fukami, Yasushi, Fukazawa, Garc('(i))a L('(o))pez, Ramon J., Markus, Garczarczyk, Sargis, Gasparyan, Markus, Gaug, Giglietto, Nicola, Francesco, Giordano, Pawel, Gliwny, Nikola, Godinovic, David, Green, Jarred Gershon Green, Daniela, Hadasch, Alexander, Hahn, Lea, Heckmann, Javier, Herrera, Dario, Hrupec, Moritz, Hütten, Tomohiro, Inada, Kazuma, Ishio, Yuki, Iwamura, Jenni, Jormanainen, L('(e))a, Jouvin, Marie, Karjalainen, Daniel, Kerszberg, Yukiho, Kobayashi, Hidetoshi, Kubo, Junko, Kushida, Alessandra, Lamastra, Damir, Lelas, Francesco, Leone, Elina, Lindfors, Lena, Linhoff, Saverio, Lombardi, Francesco, Longo, Ruben, Lopez-Coto, Marcos, L('(o))pez-Moya, Loporchio, Serena, Bernardo Machado de Oliveira Fraga, Camilla, Maggio, Pratik, Majumdar, Martin, Makariev, Manuela, Mallamaci, Galina, Maneva, Marina, Manganaro, Karl, Mannheim, Laura, Maraschi, Mos(`(e)), Mariotti, Manel, Martinez, Daniel, Mazin, Stefano, Menchiari, Simone, Mender, Sa( (s))a Mi('(c))anovi('(c)), Davide, Miceli, Tjark, Miener, Jose Miguel Miranda, Razmik, Mirzoyan, Edgar, Molina, Abelardo, Moralejo, Daniel, Morcuende, Victoria, Moreno, Elena, Moretti, Takeshi, Nakamori, Lara, Nava, Vitaly, Neustroev, Cosimo, Nigro, Kari, Nilsson, Kyoshi, Nishijima, Koji, Noda, Seiya, Nozaki, Yoshiki, Ohtani, Tomohiko, Oka, Jorge, Otero-Santos, Simona, Paiano, Michele, Palatiello, David, Paneque, Riccardo, Paoletti, Paredes, Josep M., Lovro, Pavleti('(c)), Pablo, Pe(~(n))il, Massimo, Persic, Marine, Pihet, Pier Giorgio Prada Moroni, Elisa, Prandini, Chaitanya, Priyadarshi, Ivica, Puljak, Wolfgang, Rhode, Marc, Rib('(o)), Javier, Rico, Chiara, Righi, Andrea, Rugliancich, Narek, Sahakyan, Takayuki, Saito, Shunsuke, Sakurai, Konstancja, Satalecka, Francesco Gabriele Saturni, Bernd, Schleicher, Kevin, Schmidt, Thomas, Schweizer, Julian, Sitarek, Iva, ( (S))nidari('(c)), Dorota, Sobczy('(n))ska, Alessia, Spolon, Antonio, Stamerra, Jelena Stri( (s))kovi('(c)), Derek, Strom, Marcel, Strzys, Yusuke, Suda, Tihomir, Suri('(c)), Mitsunari, Takahashi, Ryuji, Takeishi, Fabrizio, Tavecchio, Petar, Temnikov, Tomislav, Terzic, Masahiro, Teshima, Luca, Tosti, Stefano, Truzzi, Antonio, Tutone, Santiago, Ubach, Juliane van Scherpenberg, Gaia, Vanzo, Monica VAZQUEZ ACOSTA, Sofia, Ventura, Vassil, Verguilov, Carlo Francesco Vigorito, Vincenzo, Vitale, Ievgen, Vovk, Martin, Will, Carolin, Wunderlich, Tokonatsu, Yamamoto, Darko, Zari('(c)), Filippo, Ambrosino, Alice, Borghese, Francesco Coti Zelati, Hessels, Jason W. T., Franz, Kirsten, Benito, Marcote, Ould-Boukattine, Omar S., Alessandro, Papitto, and Snelders and, Mark P.

Published
2021

34. The variability patterns of {PG} 1553$\mathplus$113: a {MAGIC} perspective

Author

Elisa, Prandini, Antonio, Stamerra, Talvikki, Hovatta, Tommaso, Aniello, Paolo Da Vela, Luca, Foffano, Ioannis, Liodakis, Kari, Nilsson, Pablo, Pe(~(n))il, Sofia, Ventura, Acciari, Victor A., Stefano, Ansoldi, Lucio Angelo Antonelli, Axel Arbet Engels, Manuel, Artero, Katsuaki, Asano, Dominik, Baack, Ana, Babic, Andr('(e))s, Baquero, Ulisses Barres de Almeida, Juan Abel Barrio, Ivana, Batkovi('(c)), Josefa Becerra Gonzalez, Wlodek, Bednarek, Lorenzo, Bellizzi, Elisa, Bernardini, Maria-Isabel, Bernardos, Alessio, Berti, Jürgen, Besenrieder, Wrijupan, Bhattacharyya, Ciro, Bigongiari, Adrian, Biland, Oscar, Blanch, Hendrik, Bökenkamp, Giacomo, Bonnoli, Zeljka, Bosnjak, Giovanni, Busetto, Roberto, Carosi, Giovanni, Ceribella, Matteo, Cerruti, Yating, Chai, Ashot, Chilingarian, Stefan, Cikota, Sidika Merve Colak, Eduardo, Colombo, Jose Luis Contreras, Juan, Cortina, Stefano, Covino, Giacomo D( extquotesingle)Amico, Valerio D( extquotesingle)Elia, Francesco, Dazzi, Alessandro De Angelis, Barbara De Lotto, Manuel, Delfino, Jordi, Delgado, Carlos Delgado Mendez, Davide, Depaoli, Federico Di Pierro, Leonardo Di Venere, Elia Do Souto Espi(~(n))eira, Dijana Dominis Prester, Alice, Donini, Daniela, Dorner, Michele, Doro, Dominik, Elsaesser, Vandad Fallah Ramazani, Alicia, Fattorini, Maria Victoria Fonseca, Lluis, Font, Christian, Fruck, Satoshi, Fukami, Yasushi, Fukazawa, Garc('(i))a L('(o))pez, Ramon J., Markus, Garczarczyk, Sargis, Gasparyan, Markus, Gaug, Giglietto, Nicola, Francesco, Giordano, Pawel, Gliwny, Nikola, Godinovic, David, Green, Jarred Gershon Green, Daniela, Hadasch, Alexander, Hahn, Lea, Heckmann, Javier, Herrera, John, Hoang, Dario, Hrupec, Moritz, Hütten, Tomohiro, Inada, Kazuma, Ishio, Yuki, Iwamura, Irene Jim('(e))nez Mart('(i))nez, Jenni, Jormanainen, L('(e))a, Jouvin, Marie, Karjalainen, Daniel, Kerszberg, Yukiho, Kobayashi, Hidetoshi, Kubo, Junko, Kushida, Alessandra, Lamastra, Damir, Lelas, Francesco, Leone, Elina, Lindfors, Lena, Linhoff, Saverio, Lombardi, Francesco, Longo, Ruben, Lopez-Coto, Marcos, L('(o))pez-Moya, Alicia, L('(o))pez-Oramas, Loporchio, Serena, Bernardo Machado de Oliveira Fraga, Camilla, Maggio, Pratik, Majumdar, Martin, Makariev, Manuela, Mallamaci, Galina, Maneva, Marina, Manganaro, Karl, Mannheim, Laura, Maraschi, Mos(`(e)), Mariotti, Manel, Martinez, Daniel, Mazin, Stefano, Menchiari, Simone, Mender, Sa( (s))a Mi('(c))anovi('(c)), Davide, Miceli, Tjark, Miener, Jose Miguel Miranda, Razmik, Mirzoyan, Edgar, Molina, Abelardo, Moralejo, Daniel, Morcuende, Victoria, Moreno, Elena, Moretti, Takeshi, Nakamori, Lara, Nava, Vitaly, Neustroev, Cosimo, Nigro, Kyoshi, Nishijima, Koji, Noda, Seiya, Nozaki, Yoshiki, Ohtani, Tomohiko, Oka, Jorge, Otero-Santos, Simona, Paiano, Michele, Palatiello, David, Paneque, Riccardo, Paoletti, Paredes, Josep M., Lovro, Pavleti('(c)), Massimo, Persic, Marine, Pihet, Pier Giorgio Prada Moroni, Chaitanya, Priyadarshi, Ivica, Puljak, Wolfgang, Rhode, Marc, Rib('(o)), Javier, Rico, Chiara, Righi, Andrea, Rugliancich, Narek, Sahakyan, Takayuki, Saito, Shunsuke, Sakurai, Konstancja, Satalecka, Francesco Gabriele Saturni, Bernd, Schleicher, Kevin, Schmidt, Thomas, Schweizer, Julian, Sitarek, Iva, ( (S))nidari('(c)), Dorota, Sobczy('(n))ska, Alessia, Spolon, Jelena Stri( (s))kovi('(c)), Derek, Strom, Marcel, Strzys, Yusuke, Suda, Tihomir, Suri('(c)), Mitsunari, Takahashi, Ryuji, Takeishi, Fabrizio, Tavecchio, Petar, Temnikov, Tomislav, Terzic, Masahiro, Teshima, Luca, Tosti, Stefano, Truzzi, Antonio, Tutone, Santiago, Ubach, Juliane van Scherpenberg, Gaia, Vanzo, Monica VAZQUEZ ACOSTA, Vassil, Verguilov, Carlo Francesco Vigorito, Vincenzo, Vitale, Ievgen, Vovk, Martin, Will, Carolin, Wunderlich, Tokonatsu, Yamamoto, and Darko Zari('(c)) and

Published
2021

35. Analysis of the W 44 Supernova Remnant and its surroundings with Fermi-{LAT} and {MAGIC}

Author

Leonardo Di Venere, Riccardo Di Tria, Francesco, Giordano, David, Green, Alexander, Hahn, Pantaleo, Francesca Romana, Marcel, Strzys, Acciari, Victor A., Stefano, Ansoldi, Lucio Angelo Antonelli, Axel Arbet Engels, Manuel, Artero, Katsuaki, Asano, Dominik, Baack, Ana, Babic, Andr('(e))s, Baquero, Ulisses Barres de Almeida, Juan Abel Barrio, Ivana, Batkovi('(c)), Josefa Becerra Gonzalez, Wlodek, Bednarek, Lorenzo, Bellizzi, Elisa, Bernardini, Maria-Isabel, Bernardos, Alessio, Berti, Jürgen, Besenrieder, Wrijupan, Bhattacharyya, Ciro, Bigongiari, Adrian, Biland, Oscar, Blanch, Hendrik, Bökenkamp, Giacomo, Bonnoli, Zeljka, Bosnjak, Giovanni, Busetto, Roberto, Carosi, Giovanni, Ceribella, Matteo, Cerruti, Yating, Chai, Ashot, Chilingarian, Stefan, Cikota, Sidika Merve Colak, Eduardo, Colombo, Jose Luis Contreras, Juan, Cortina, Stefano, Covino, Giacomo D( extquotesingle)Amico, Valerio D( extquotesingle)Elia, Paolo Da Vela, Francesco, Dazzi, Alessandro De Angelis, Barbara De Lotto, Manuel, Delfino, Jordi, Delgado, Carlos Delgado Mendez, Davide, Depaoli, Federico Di Pierro, Elia Do Souto Espi(~(n))eira, Dijana Dominis Prester, Alice, Donini, Daniela, Dorner, Michele, Doro, Dominik, Elsaesser, Vandad Fallah Ramazani, Alicia, Fattorini, Maria Victoria Fonseca, Lluis, Font, Christian, Fruck, Satoshi, Fukami, Yasushi, Fukazawa, Garc('(i))a L('(o))pez, Ramon J., Markus, Garczarczyk, Sargis, Gasparyan, Markus, Gaug, Giglietto, Nicola, Pawel, Gliwny, Nikola, Godinovic, Jarred Gershon Green, Daniela, Hadasch, Lea, Heckmann, Javier, Herrera, John, Hoang, Dario, Hrupec, Moritz, Hütten, Tomohiro, Inada, Kazuma, Ishio, Yuki, Iwamura, Irene Jim('(e))nez Mart('(i))nez, Jenni, Jormanainen, L('(e))a, Jouvin, Marie, Karjalainen, Daniel, Kerszberg, Yukiho, Kobayashi, Hidetoshi, Kubo, Junko, Kushida, Alessandra, Lamastra, Damir, Lelas, Francesco, Leone, Elina, Lindfors, Lena, Linhoff, Saverio, Lombardi, Francesco, Longo, Ruben, Lopez-Coto, Marcos, L('(o))pez-Moya, Alicia, L('(o))pez-Oramas, Loporchio, Serena, Bernardo Machado de Oliveira Fraga, Camilla, Maggio, Pratik, Majumdar, Martin, Makariev, Manuela, Mallamaci, Galina, Maneva, Marina, Manganaro, Karl, Mannheim, Laura, Maraschi, Mos(`(e)), Mariotti, Manel, Martinez, Daniel, Mazin, Stefano, Menchiari, Simone, Mender, Sa( (s))a Mi('(c))anovi('(c)), Davide, Miceli, Tjark, Miener, Jose Miguel Miranda, Razmik, Mirzoyan, Edgar, Molina, Abelardo, Moralejo, Daniel, Morcuende, Victoria, Moreno, Elena, Moretti, Takeshi, Nakamori, Lara, Nava, Vitaly, Neustroev, Cosimo, Nigro, Kari, Nilsson, Kyoshi, Nishijima, Koji, Noda, Seiya, Nozaki, Yoshiki, Ohtani, Tomohiko, Oka, Jorge, Otero-Santos, Simona, Paiano, Michele, Palatiello, David, Paneque, Riccardo, Paoletti, Paredes, Josep M., Lovro, Pavleti('(c)), Pablo, Pe(~(n))il, Massimo, Persic, Marine, Pihet, Pier Giorgio Prada Moroni, Elisa, Prandini, Chaitanya, Priyadarshi, Ivica, Puljak, Wolfgang, Rhode, Marc, Rib('(o)), Javier, Rico, Chiara, Righi, Andrea, Rugliancich, Narek, Sahakyan, Takayuki, Saito, Shunsuke, Sakurai, Konstancja, Satalecka, Francesco Gabriele Saturni, Bernd, Schleicher, Kevin, Schmidt, Thomas, Schweizer, Julian, Sitarek, Iva, ( (S))nidari('(c)), Dorota, Sobczy('(n))ska, Alessia, Spolon, Antonio, Stamerra, Jelena Stri( (s))kovi('(c)), Derek, Strom, Yusuke, Suda, Tihomir, Suri('(c)), Mitsunari, Takahashi, Ryuji, Takeishi, Fabrizio, Tavecchio, Petar, Temnikov, Tomislav, Terzic, Masahiro, Teshima, Luca, Tosti, Stefano, Truzzi, Antonio, Tutone, Santiago, Ubach, Juliane van Scherpenberg, Gaia, Vanzo, Monica VAZQUEZ ACOSTA, Sofia, Ventura, Vassil, Verguilov, Carlo Francesco Vigorito, Vincenzo, Vitale, Ievgen, Vovk, Martin, Will, Carolin, Wunderlich, Tokonatsu, Yamamoto, Darko, Zari('(c)), and And

Subjects
Physics, Astrophysics::High Energy Astrophysical Phenomena, Gamma ray, Angular resolution, Cosmic ray, MAGIC (telescope), Astrophysics, Diffusion (business), Supernova remnant, Spectral line, Fermi Gamma-ray Space Telescope
Abstract

The well-known supernova remnant (SNR) W 44 is observed in high-energy gamma rays and widely studied to investigate cosmic ray (CR) acceleration. Several analyses of the W 44 surroundings showed the presence of 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 W 44 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. Observations of the north-western region of W 44, also known as SRC-1 from previous works, were conducted with the MAGIC telescopes in the very high-energy gamma-ray band. We analysed MAGIC data exploiting the spatial information derived with the Fermi-LAT analysis at GeV energies. Here we show the results of both analyses and the combined Fermi-LAT and MAGIC spectra, thus obtaining constraining information on the diffusion of the escaped CRs.

Published
2021

36. A conditional one-output likelihood formulation for multitask Gaussian processes

Author

Óscar García-Hinde, Manel Martinez-Ramon, and Vanessa Gómez-Verdejo

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence, Statistics - Machine Learning, Cognitive Neuroscience, Machine Learning (stat.ML), Machine Learning (cs.LG), Computer Science Applications
Abstract

Multitask Gaussian processes (MTGP) are the Gaussian process (GP) framework's solution for multioutput regression problems in which the $T$ elements of the regressors cannot be considered conditionally independent given the observations. Standard MTGP models assume that there exist both a multitask covariance matrix as a function of an intertask matrix, and a noise covariance matrix. These matrices need to be approximated by a low rank simplification of order $P$ in order to reduce the number of parameters to be learnt from $T^2$ to $TP$. Here we introduce a novel approach that simplifies the multitask learning by reducing it to a set of conditioned univariate GPs without the need for any low rank approximations, therefore completely eliminating the requirement to select an adequate value for hyperparameter $P$. At the same time, by extending this approach with both a hierarchical and an approximate model, the proposed extensions are capable of recovering the multitask covariance and noise matrices after learning only $2T$ parameters, avoiding the validation of any model hyperparameter and reducing the overall complexity of the model as well as the risk of overfitting. Experimental results over synthetic and real problems confirm the advantages of this inference approach in its ability to accurately recover the original noise and signal matrices, as well as the achieved performance improvement in comparison to other state of art MTGP approaches. We have also integrated the model with standard GP toolboxes, showing that it is computationally competitive with state of the art options.

Published
2020

37. Raman LIDARs for the atmospheric calibration along the line-of-sight of the Cherenkov Telescope Array

Author

Johan Bregeon, Manel Martinez, Marko Zavrtanik, Markus Gaug, Raul Ramos, Oscar Martinez, Pere Munar Adrover, Oscar Blanch, Vania Da Deppo, O. Gabella, Rafael Garcia, C. Maggio, J. Boix, G. Vasileiadis, O. Ballester, ıdıka Merve Çolak, Michele Doro, Samo Stanič, Lluis Font, David Villar, Patrick Brun, Stephane Rivoire, Longlong Wang, Laboratoire Univers et Particules de Montpellier (LUPM), and Université Montpellier 2 - Sciences et Techniques (UM2)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Cherenkov Telescope Array, data acquisition, energy resolution, 7. Clean energy, symbols.namesake, Data acquisition, Observatory, site, Calibration, liquid, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], mirror, Cherenkov radiation, Remote sensing, Line-of-sight, Spectrometer, imaging, sensitivity, calibration, buildings, observatory, Cherenkov counter, gamma ray: VHE, 13. Climate action, atmosphere, symbols, readout, Environmental science, spectrometer, Raman spectroscopy, performance, on-line
Abstract

International audience; The Cherenkov Telescope Array (CTA) is the next generation ground-based observatory for gamma-ray astronomy at very-high energies. Employing more than 100 (north and south sites) Imaging Atmospheric Cherenkov Telescopes in the northern and southern hemispheres, it was designed to reach unprecedented sensitivity and energy resolution. Understanding and correcting for systematic biases on the absolute energy scale and instrument response functions will be a cru- cial issue for the performance of CTA. The Montpellier group and the Spanish/Italian/Slovenian collaboration are currently building two Raman LIDAR prototypes for the online atmospheric cal- ibration along the line-of-sight of the CTA. Requirements for such a solution include the ability to characterize aerosol extinction at two wavelengths to distances up to 30 km with an accuracy better than 5%, within exposure time scales of about a minute, steering capabilities and close interaction with the CTA array control and data acquisition system as well as other auxiliary in- struments. Our Raman LIDARs have design features that make them different from those used in atmospheric science and are characterized by large collecting mirrors (∼2.5 m2), liquid light- guides that collect the light at the focal plane and transport it to the readout system, reduced acquisition time and highly precise Raman spectrometers. The Raman LIDARs will participate in a cross-calibration and characterization campaign of the atmosphere at the CTA North site at La Palma, together with other site characterization instruments. After a one-year test period there, an in-depth evaluation of the solutions adopted by the two projects will lead to a final Raman LIDAR design proposal for both CTA sites.

Published
2019

38. Raman LIDARs for the atmospheric calibration along the line-of-sight of CTA

Author

Otger, Ballester, Oscar, Blanch, Joan, Boix, Johan, Bregeon, Patrick, Brun, Merve, Colak, Michele Doro, Da Deppo, Vania, Lluis, Font, Omar, Gabella, Rafael, Garcia, Markus, Gaug, Camilla, Maggio, Manel, Martinez, Oscar, Martinez, Pere Munar Adrover, Raul, Ramos, Stephane, Rivoire, Samo, Stanic, David, Villar, George, Vasileiadis, Longlong, Wang, Marko, Zavrtanik, Laboratoire Univers et Particules de Montpellier (LUPM), and Université Montpellier 2 - Sciences et Techniques (UM2)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Cherenkov Telescope Array, data acquisition, Astrophysics::High Energy Astrophysical Phenomena, energy resolution, FOS: Physical sciences, site, liquid, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], mirror, Instrumentation and Methods for Astrophysics (astro-ph.IM), Physics::Atmospheric and Oceanic Physics, Astrophysics::Instrumentation and Methods for Astrophysics, imaging, sensitivity, calibration, buildings, observatory, Cherenkov counter, gamma ray: VHE, astro-ph.IM, atmosphere, readout, spectrometer, Astrophysics - Instrumentation and Methods for Astrophysics, performance, on-line
Abstract

International audience; The Cherenkov Telescope Array (CTA) is the next generation ground based observatory for gamma ray astronomy at very high energies. Employing more than 100 Imaging Atmospheric Cherenkov Telescopes in the northern and southern hemispheres, it was designed to reach unprecedented sensitivity and energy resolution. Understanding and correcting for systematic biases on the absolute energy scale and instrument response functions will be a crucial issue for the performance of CTA. The LUPM group and the Spanish/Italian/Slovenian collaboration are currently building two Raman LIDAR prototypes for the online atmospheric calibration along the line of sight of the CTA. Requirements for such a solution include the ability to characterize aerosol extinction at two wavelengths to distances of 30 km with an accuracy better than 5%, within time scales of about a minute, steering capabilities and close interaction with the CTA array control and data acquisition system as well as other auxiliary instruments. Our Raman LIDARs have design features that make them different from those used in atmospheric science and are characterized by large collecting mirrors (2.5 m2), liquid light guides that collect the light at the focal plane and transport it to the readout system, reduced acquisition time and highly precise Raman spectrometers. The Raman LIDARs will participate in a cross calibration and characterization campaign of the atmosphere at the CTA North site at La Palma, together with other site characterization instruments. After a one year test period there, an in depth evaluation of the solutions adopted by the two projects will lead to a final Raman LIDAR design proposal for both CTA sites.

Published
2019

39. A semi-empirical approach to calibrate simulation models for semiconductor devices

Author

Rahul Jaiswal, Manel Martínez-Ramón, and Tito Busani

Subjects
Medicine, Science
Abstract

Abstract Semiconductor device optimization using computer-based prototyping techniques like simulation or machine learning digital twins can be time and resource efficient compared to the conventional strategy of iterating over device design variations by fabricating the actual device. Ideally, simulation models require perfect calibration of material parameters for the model to represent a particular semiconductor device. This calibration process itself can require characterization information of the device and its precursors and extensive expert knowledge of non characterizable parameters and their tuning. We propose a hybrid method to calibrate multiple simulation models for a device using minimal characterization data and machine learning-based prediction models. A photovoltaic device is chosen as the example for this technique where optical and electrical simulation models of an industrially manufactured silicon solar cell are calibrated and the simulated device performance is compared with the measurement data from the physical device.

Published
2023
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40. An unsupervised cyberattack detection scheme for AC microgrids using Gaussian process regression and one‐class support vector machine anomaly detection

Author

Jeewon Choi, Behshad Roshanzadeh, Manel Martínez‐Ramón, and Ali Bidram

Subjects
cyber‐physical systems, distributed control, Gaussian processes, microgrids, support vector machines, Renewable energy sources, TJ807-830
Abstract

Abstract This paper addresses the cybersecurity of hierarchical control of AC microgrids with distributed secondary control. The false data injection (FDI) cyberattack is assumed to alter the operating frequency of inverter‐based distributed generators (DGs) in an islanded microgrid. For the microgrids consisting of the grid‐forming inverters with the secondary control operating in a distributed manner, the attack on one DG deteriorates not only the corresponding DG but also the other DGs that receive the corrupted information via the distributed communication network. To this end, an FDI attack detection algorithm based on a combination of Gaussian process regression and one‐class support vector machine (OC‐SVM) anomaly detection is introduced. This algorithm is unsupervised in the sense that it does not require labelled abnormal data for training which is difficult to collect. The Gaussian process model predicts the response of the DG, and its prediction error and estimated variances provide input to an OC‐SVM anomaly detector. This algorithm returns enhanced detection performance than the standalone OC‐SVM. The proposed cyberattack detector is trained and tested with the data collected from a 4 DG microgrid test model and is validated in both simulation and hardware‐in‐the‐loop testbeds.

Published
2023
Full Text
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41. On Improved Accuracy Chirp Parameter Estimation using the DFRFT with Application to SAR-based Vibrometry

Author

Dr. Balu Santhanam, Dr. Majeed M. Hayat, Dr. Manel Martinez-Ramon, Mandal, Satish, Dr. Balu Santhanam, Dr. Majeed M. Hayat, Dr. Manel Martinez-Ramon, and Mandal, Satish

Subjects
satish mandal; improved chirp parameter estimation
Abstract

The Discrete Fractional Fourier Transform (DFRFT) has in recent years, become a useful tool for multicomponent chirp signal analysis. Chirp signals are transformed into spectral peaks in the chirp rate versus center frequency representation, whose coordinates are related to the underlying chirp parameters via a computed empirical peak to parameter mapping incorporated into the Santhanam-Peacock algorithm. In this thesis, we attempt to quantify the accuracy of the DFRFT approach by first studying the discretization error sources that arise from the transitioning of the continuous FRFT to DFRFT. Then, we refine prior work by Ishwor Bhatta to develop analytical expressions for the chirp rate and center frequency parameters instead of the empirical mapping approach. We further study the extensions of this refined DFRFT approach using zero padding, spectral peak interpolation, and chirp-z-transform based zooming. The performance of the refined estimators is compared versus the Cramer-Rao lower bound and shown to asymptotically approach the bound. This refined DFRFT approach is then applied to Synthetic Aperture Radar Vibrometry data from several vibrating targets and the estimated acceleration information and vibration frequencies are shown to be very close to the corresponding ground-truth accelerometer measurements.

Published
2018

42. First combined studies on Lorentz Invariance Violation from observations of astrophysical sources

Author

Cedric Perennes, Alasdair E. Gent, Robert Wagner, Manel Martinez, Tony T.Y. Lin, Markus Gaug, A. Nepomuk Otte, A. Jacholkowska, John E. Ward, Benjamin Zitzer, Julien Bolmont, L. Nogués, Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE (UMR_7585)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris Diderot - Paris 7 (UPD7)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), LIV, and Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)

Subjects
Astrophysics::High Energy Astrophysical Phenomena, FOS: Physical sciences, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Lorentz covariance, Joint analysis, time-of-flight, invariance: Lorentz, 7. Clean energy, target, search for, Pulsar, photon: emission, HESS, MAGIC (telescope), AGN, Cherenkov radiation, pulsar, Physics, High Energy Astrophysical Phenomena (astro-ph.HE), imaging, sensitivity, redshift, pulsed, MAGIC, Redshift, violation: Lorentz, Variable (computer science), gamma ray: UHE, Cherenkov counter, Photon emission, VERITAS, Astrophysics - High Energy Astrophysical Phenomena, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]
Abstract

Imaging Atmospheric Cherenkov Telescopes study the highest energy (up to tens of TeV) photon emission coming from nearby and distant astrophysical sources, thus providing valuable results from searches for Lorentz Invariance Violation (LIV) effects. Highly variable, energetic and distant sources such as Pulsars and AGNs are the best targets for the Time-of-Flight LIV studies. However, the limited number of observations of AGN flares or of high-energy pulsed emission greatly restricts the potential of such studies, especially any potential LIV effects as a function of redshift. To address these issues, an inter-experiment working group has been established by the three major collaborations taking data with Imaging Atmospheric Cherenkov Telescopes (H.E.S.S., MAGIC and VERITAS) with the aim to increase sensitivity to any effects of LIV, together with an improved control of systematic uncertainties, by sharing data samples and developing joint analysis methods. This will allow an increase in the number of available sources and to perform a sensitive search for redshift dependencies. This presentation reviews the first combined maximum likelihood method analyses using simu- lations of published source observations done in the past with H.E.S.S., MAGIC and VERITAS. The results from analyses based on combined maximum likelihood methods, the strategies to deal with data from different types of sources and instruments, as well as future plans will be presented., Comment: 8 pages, 4 figures, Proceedings of the 35th International Cosmic Ray Conference (ICRC 2017), Bexco, Busan, Korea

Published
2017

43. Prediction of Graduation Delay Based on Student Characterisitics and Performance

Author

Gregory L Heileman, Manel Martinez-Ramon, Don R Hush, Ahmad Slim, Ojha, Tushar, Gregory L Heileman, Manel Martinez-Ramon, Don R Hush, Ahmad Slim, and Ojha, Tushar

Subjects
Higer Education
Abstract

A college student's success depends on many factors including pre-university characteristics and university student support services. Student graduation rates are often used as an objective metric to measure institutional effectiveness. This work studies the impact of such factors on graduation rates, with a particular focus on delay in graduation. In this work, we used feature selection methods to identify a subset of the pre-institutional features with the highest discriminative power. In particular, Forward Selection with Linear Regression, Backward Elimination with Linear Regression, and Lasso Regression were applied. The feature sets were selected in a multivariate fashion. High school GPA, ACT scores, student's high school, financial aid received, and first generation status were found to be important for predicting success. In order to predict delay in graduation, we trained predictive models using Support Vector Machines (SVMs), Gaussian Processes (GPs), and Deep Boltzmann Machines (DBMs) on real student data. The difference in performance among the models is negligible with respect to overall accuracies obtained. Further analysis showed that DBMs outperform SVMs in terms of precision and recall for individual classes. However, the DBM and SVM implementations are computationally inexpensive compared to GPs, given the same resources.

Published
2017

44. Packet Scheduling Algorithms in LTE/LTE-A cellular Networks: Multi-agent Q-learning Approach

Author

Prof., Manel Martinez-Ramon, Prof., Gregory Heileman, Prof., Nasir Ghani, Prof., Christopher Lamb, Sirhan, Najem Nafiz, Prof., Manel Martinez-Ramon, Prof., Gregory Heileman, Prof., Nasir Ghani, Prof., Christopher Lamb, and Sirhan, Najem Nafiz

Subjects
LTE-Advanced (LTE-A)
Abstract

Spectrum utilization is vital for mobile operators. It ensures an efficient use of spectrum bands, especially when obtaining their license is highly expensive. Long Term Evolution (LTE), and LTE-Advanced (LTE-A) spectrum bands license were auctioned by the Federal Communication Commission (FCC) to mobile operators with hundreds of millions of dollars. In the first part of this dissertation, we study, analyze, and compare the QoS performance of QoS-aware/Channel-aware packet scheduling algorithms while using CA over LTE, and LTE-A heterogeneous cellular networks. This included a detailed study of the LTE/LTE-A cellular network and its features, and the modification of an open source LTE simulator in order to perform these QoS performance tests. In the second part of this dissertation, we aim to solve spectrum underutilization by proposing, implementing, and testing two novel multi-agent Q-learning-based packet scheduling algorithms for LTE cellular network. The Collaborative Competitive scheduling algorithm, and the Competitive Competitive scheduling algorithm. These algorithms schedule licensed users over the available radio resources and un-licensed users over spectrum holes. In conclusion, our results show that the spectrum band could be utilized by deploying efficient packet scheduling algorithms for licensed users, and can be further utilized by allowing unlicensed users to be scheduled on spectrum holes whenever they occur.

Published
2017

45. Cognitive Anti-Jamming Framework with Self-Interference Cancellation on a Wideband Autonomous Cognitive Radio

Author

Prof. Sudharman K. Jayaweera, Prof. Prof. Christos G. Christodoulou, Prof. Manel Martinez-Ramon, Machuzak, Stephen J, Prof. Sudharman K. Jayaweera, Prof. Prof. Christos G. Christodoulou, Prof. Manel Martinez-Ramon, and Machuzak, Stephen J

Subjects
Electrical and Computer Engineering
Abstract

With crowded usage of the wireless spectrum, full-duplex wireless systems are introduced to increase bandwidth efficiency by transmitting and receiving on the same frequency band at the same time. Full-duplex communication is a promising solution for greater wireless communications efficiency but, it requires solving the problem of self-interference. Self- Interference cancellation is the process of canceling a radio’s own transmission signal that interferes with its sensed signal which can block desired outside signals of interest. The focus of this thesis is to design and implement a novel self-interference cancellation method for the Wide-band Autonomous Cognitive Radio (WACR) with anti-jamming abil- ities which needs to be capable of canceling the WACR’s shifting transmission signal in its sensed spectrum. This is an all-digital active cancellation technique which minimizes the computational complexity of the system’s digital baseband signal processing and allows it to be dynamically adaptive to the WACR’s shifting transmission signal.

Published
2017

46. PROJECTION-BASED ROTATION ESTIMATION FOR VIDEO STABILIZATION

Author

Majeed M. Hayat, Christos Christodoulou, Manel Martinez- Ramon, Zerara, Mahdi, Mr, Majeed M. Hayat, Christos Christodoulou, Manel Martinez- Ramon, and Zerara, Mahdi, Mr

Subjects
Motion estimation
Abstract

Video stabilization has become a routine post-processing enhancement procedure, to remove unwanted shifts from video sequences. This thesis proposes a new computationally optimized approach for image rotational motion estimation, which has been studied and tested on shaky videos. The method is built upon a projection-based algorithm that reduces the 2-D video sequences into vectors of size 1 180, by averaging all the pixel values on the line-segments that cross the rotation center and form angles with the rows of the images, such that ranges from 0 to 179 . From the obtained projected vectors, we perform a 1D cross-correlation-based shift estimator, to measure the angle of the occurring rotation between each pair of successive frames. Most of the feature-based and block-based shift estimation algorithms require heavy computations, whereas the proposed method reduces the computation costs significantly, and shows high estimation performances when the center of rotation is successfully located. We rely on the mean-squared-error and the rotation estimation graphs, to provide a subjective assessment of the proposed method’s efficiency on synthetic as well as real-case data.

Published
2017

47. A NOVEL APPLICATION OF MACHINE LEARNING METHODS TO MODEL MICROCONTROLLER UPSET DUE TO INTENTIONAL ELECTROMAGNETIC INTERFERENCE

Author

Edl Schamiloglu, Christos Christodoulou, Manel Martinez-Ramon, Timothy Clarke, Trilce Estrada, Bilalic, Rusmir, Edl Schamiloglu, Christos Christodoulou, Manel Martinez-Ramon, Timothy Clarke, Trilce Estrada, and Bilalic, Rusmir

Subjects
IEMI
Abstract

A novel application of support vector machines (SVMs), artificial neural networks (ANNs), and Gaussian processes (GPs) for machine learning (GPML) to model microcontroller unit (MCU) upset due to intentional electromagnetic interference (IEMI) is presented. In this approach, an MCU performs a counting operation (0-7) while electromagnetic interference in the form of a radio frequency (RF) pulse is direct-injected into the MCU clock line. Injection times with respect to the clock signal are the clock low, clock rising edge, clock high, and the clock falling edge periods in the clock window during which the MCU is performing initialization and executing the counting procedure. The intent is to cause disruption in the counting operation and model the probability of effect (PoE) using machine learning tools. Five experiments were executed as part of this research, each of which contained a set of 38,300 training points and 38,300 test points, for a total of 383,000 total points with the following experiment variables: injection times with respect to the clock signal, injected RF power, injected RF pulse width, and injected RF frequency. For the 191,500 training points, the average training error was 12.47%, while for the 191,500 test points the average test error was 14.85%, meaning that on average, the machine was able to predict MCU upset with an 85.15% accuracy. Leaving out the results for the worst-performing model (SVM with a linear kernel), the test prediction accuracy for the remaining machines is almost 89%. All three machine learning methods (ANNs, SVMs, and GPML) showed excellent and consistent results in their ability to model and predict the PoE on an MCU due to IEMI. The GP approach performed best during training with a 7.43% average training error, while the ANN technique was most accurate during the test with a 10.80% error.

Published
2017

48. Context-Sensitive Human Activity Classification in Video Utilizing Object Recognition and Motion Estimation

Author

Marios Pattichis, Manel Martinez-Ramon, Ramiro Jordan, Jacoby, Abigail R, Marios Pattichis, Manel Martinez-Ramon, Ramiro Jordan, and Jacoby, Abigail R

Subjects
human activity classification; context-based methods
Abstract

Classification of human activity in raw video presents a challenging problem that remains unsolved, and is of great interest for large datasets. Though there have been several attempts at applying image processing techniques to video to recognize human activity in controlled video segments, few have attained a significant degree of success in raw videos. Raw video classification exhibits significant challenges that can be addressed through the use of geometric information. Current techniques employ a combination of temporal information of the feature space or a combination of Convolutional and Recurrent Neural Networks (CNN and RNNs). CNNs are used for frame feature extraction and RNNs are then applied for motion vector extraction and classification. These techniques, which utilize information from the entirety of a frame, attempt to classify action based on all motion vectors and all objects found in the video. Such methods are cumbersome, often difficult to train, and do not generalize well beyond the dataset used. This thesis explores the use of color based object detection in conjunction with contextualization of object interaction to isolate motion vectors specific to an activity sought within uncropped video. Feature extraction in this thesis differs significantly from other methods by using geometric relationships between objects to infer context. The approach avoids the need for video cropping or substantial preprocessing by significantly reducing the number of features analyzed in a single frame. The method was tested using 43 uncropped video clips with 620 video frames for writing, 1050 for typing, and 1755 frames for talking. Using simple KNN classification, the method gave accuracies of 72.6% for writing, 71% for typing and 84.6% for talking. Classification accuracy improved to 92.5% (writing), 82.5% (typing) and 99.7% (talking) with the use of a trained Deep Neural Network.

Published
2017

49. Distribution-level peak load prediction based on Bayesian Additive Regression Trees

Author

Manel Martinez-Ramonz, Tairen Chen, Jane Lehr, and Olga Lavrova

Subjects
Mean squared error, Computer science, 020209 energy, Bayesian probability, Nonparametric statistics, Feature selection, 02 engineering and technology, 01 natural sciences, Regression, Confidence interval, Support vector machine, 010104 statistics & probability, Statistics, Linear regression, 0202 electrical engineering, electronic engineering, information engineering, 0101 mathematics
Abstract

Accurate peak load prediction is an important element of the daily planning, operation, and dispatch scheduling in electric utilities. In order to build a better distribution-level peak load prediction reference model for the local utility in Albuquerque, a new nonparametric method, Bayesian Additive Regression Trees (BART), is introduced. First, a detailed analysis of peak load and local weather information from 2012 and 2013 are used. Strong linear relationship is displayed between the peak load and various weather factors during the winter and spring months and nonlinear relationship dominates in the summer and fall months. Next, the BART method is applied with a principled permutation-based inferential variable selection approach. The BART method's prediction accuracy is then compared with the Multiple Linear Regression (MLR), the result we developed when we cooperated with the local utility company, and the Support Vector Machine (SVM). After thoroughly analyzing and testing the methods based on different parameters, the methods are compared with Mean Square Error (MSE), Root Mean Square Error (RMSE), and Normalized Mean Square Error (NMSE) indexes. The BART displays the best prediction accuracy for every index in our case and its uncertain estimate further provides the confidence interval for the peak load prediction, which also has very high accuracy. Thus, the BART provides the local utility with a better reference peak load forecasting model. Last, influential weather and human factors are summarized.

Published
2016

50. Cosmology with VHE gamma-ray telescopes

Author

Manel Martinez

Subjects
Statistics and Probability, Physics, Astrophysics::High Energy Astrophysical Phenomena, Astrophysics::Instrumentation and Methods for Astrophysics, Gamma ray, General Physics and Astronomy, Astronomy, Statistical and Nonlinear Physics, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics, Cosmology, Domain (software engineering), Modeling and Simulation, Mathematical Physics, Cherenkov radiation
Abstract

Observation of the universe in the VHE gamma-ray domain with the new generation of Cherenkov telescopes is producing new measurements with a direct implication for cosmology. The present results and the future prospects will be discussed.

Published
2007

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