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1,258 results on '"P., Kooijman"'

1. Scalable DAQ system operating the CHIPS-5 neutrino detector

Author

Rancurel, Belén Alonso, Cao, Son, Carroll, Thomas J., Castellan, Rhys, Catano-Mur, Erika, Cesar, John P., Coelho, João A. B., Dills, Patrick, Dodwell, Thomas, Edmondson, Jack, van Eijk, Daan, Fetterly, Quinn, Garbal, Zoé, Germani, Stefano, Gilpin, Thomas, Giraudo, Anthony, Habig, Alec, Hanuska, Daniel, Hausner, Harry, Hernandez, Wilson Y., Holin, Anna, Huang, Junting, Jones, Sebastian B., Karle, Albrecht, Kileff, George, Jenkins, Kai R., Kooijman, Paul, Kreymer, Arthur, LaFond, Gabe M., Lang, Karol, Lazar, Jeffrey P., Li, Rui, Liu, Kexin, Loving, David A., Mánek, Petr, Marshak, Marvin L., Meier, Jerry R., Miller, William, Nelson, Jeffrey K., Ng, Christopher, Nichol, Ryan J., Paolone, Vittorio, Perch, Andrew, Pfützner, Maciej M., Radovic, Alexander, Rawlins, Katherine, Roedl, Patrick, Rogers, Lucas, Safa, Ibrahim, Sousa, Alexandre, Tingey, Josh, Thomas, Jennifer, Trokan-Tenorio, Jozef, Vahle, Patricia, Wade, Richard, Wendt, Christopher, Wendt, Daniel, Whitehead, Leigh H., Wolcott, Samuel, and Yuan, Tianlu

Subjects
Physics - Instrumentation and Detectors
Abstract

The CHIPS R&D project focuses on development of low-cost water Cherenkov neutrino detectors through novel design strategies and resourceful engineering. This work presents an end-to-end DAQ solution intended for a recent 5 kt CHIPS prototype, which is largely based on affordable mass-produced components. Much like the detector itself, the presented instrumentation is composed of modular arrays that can be scaled up and easily serviced. A single such array can carry up to 30 photomultiplier tubes (PMTs) accompanied by electronics that generate high voltage in-situ and deliver time resolution of up to 0.69 ns. In addition, the technology is compatible with the White Rabbit timing system, which can synchronize its elements to within 100 ps. While deployment issues did not permit the presented DAQ system to operate beyond initial evaluation, the presented hardware and software successfully passed numerous commissioning tests that demonstrated their viability for use in a large-scale neutrino detector, instrumented with thousands of PMTs., Comment: 30 pages, 28 figures, submitted to MDPI Applied Sciences, Special Issue: Advanced Neutrino Detector Development and Application

Published
2024

3. Cross-species comparison reveals that Hmga1 reduces H3K27me3 levels to promote cardiomyocyte proliferation and cardiac regeneration

Author

Bouwman, Mara, de Bakker, Dennis E. M., Honkoop, Hessel, Giovou, Alexandra E., Versteeg, Danielle, Boender, Arie R., Nguyen, Phong D., Slotboom, Merel, Colquhoun, Daniel, Vigil-Garcia, Marta, Kooijman, Lieneke, Janssen, Rob, Hooijkaas, Ingeborg B., Günthel, Marie, Visser, Kimberly J., Klerk, Mischa, Zentilin, Lorena, Giacca, Mauro, Kaslin, Jan, Boink, Gerard J. J., van Rooij, Eva, Christoffels, Vincent M., and Bakkers, Jeroen

Published
2025
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4. NK2R control of energy expenditure and feeding to treat metabolic diseases

Author

Sass, Frederike, Ma, Tao, Ekberg, Jeppe H., Kirigiti, Melissa, Ureña, Mario G., Dollet, Lucile, Brown, Jenny M., Basse, Astrid L., Yacawych, Warren T., Burm, Hayley B., Andersen, Mette K., Nielsen, Thomas S., Tomlinson, Abigail J., Dmytiyeva, Oksana, Christensen, Dan P., Bader, Lindsay, Vo, Camilla T., Wang, Yaxu, Rausch, Dylan M., Kristensen, Cecilie K., Gestal-Mato, María, In het Panhuis, Wietse, Sjøberg, Kim A., Kernodle, Stace, Petersen, Jacob E., Pavlovskyi, Artem, Sandhu, Manbir, Moltke, Ida, Jørgensen, Marit E., Albrechtsen, Anders, Grarup, Niels, Babu, M. Madan, Rensen, Patrick C. N., Kooijman, Sander, Seeley, Randy J., Worthmann, Anna, Heeren, Joerg, Pers, Tune H., Hansen, Torben, Gustafsson, Magnus B. F., Tang-Christensen, Mads, Kilpeläinen, Tuomas O., Myers, Jr, Martin G., Kievit, Paul, Schwartz, Thue W., Hansen, Jakob B., and Gerhart-Hines, Zachary

Published
2024
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9. The Design and Construction of the Chips Water Cherenkov Neutrino Detector

Author

Rancurel, B. Alonso, Angelides, N., Augustoni, G., Bash, S., Bergmann, B., Bertschinger, N., Bizouard, P., Campbell, M., Cao, S., Carroll, T. J., Castellan, R., Catano-Mur, E., Cesar, J. P., Coelho, J. A. B., Dills, P., Dodwell, T., Edmondson, J., van Eijk, D., Fetterly, Q., Garbal, Z., Germani, S., Gilpin, T., Giraudo, A., Habig, A., Hanuska, D., Hausner, H., Hernandez, W. Y., Holin, A., Huang, J., Jones, S. B., Karle, A., Kileff, G., Jenkins, K. R., Kooijman, P., Kreymer, A., Loving, D. A., LaFond, G. M., Lang, K., Lazar, J. P., Li, R., Liu, K., Mánek, P., Marshak, M. L., Meier, J. R., Miller, W., Nelson, J. K., Ng, C., Nichol, R. J., Paolone, V., Perch, A., Pfützner, M. M., Radovic, A., Rawlins, K., Roedl, P., Rogers, L., Safa, I., Sousa, A., Tingey, J., Thomas, J., Trokan-Tenorio, J., Vahle, P., Wade, R., Wendt, C., Wendt, D., Whitehead, L. H., Wolcott, S., and Yuan, T.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

CHIPS (CHerenkov detectors In mine PitS) was a prototype large-scale water Cherenkov detector located in northern Minnesota. The main aim of the R&D project was to demonstrate that construction costs of neutrino oscillation detectors could be reduced by at least an order of magnitude compared to other equivalent experiments. This article presents design features of the CHIPS detector along with details of the implementation and deployment of the prototype. While issues during and after the deployment of the detector prevented data taking, a number of key concepts and designs were successfully demonstrated.

Published
2024

16. Synthesis and preclinical evaluation of [11C]EAI045 as a PET tracer for imaging tumors expressing mutated epidermal growth factor receptor

Author

Högnäsbacka, Antonia A., Poot, Alex J., Plisson, Christophe, Bergare, Jonas, Bonsall, David R., McCluskey, Stuart P., Wells, Lisa A., Kooijman, Esther, Schuit, Robert C., Verlaan, Mariska, Beaino, Wissam, van Dongen, Guus A. M. S., Vugts, Danielle J., Elmore, Charles S., Passchier, Jan, and Windhorst, Albert D.

Published
2024
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17. Selective CK1α degraders exert antiproliferative activity against a broad range of human cancer cell lines

Author

Nishiguchi, Gisele, Mascibroda, Lauren G., Young, Sarah M., Caine, Elizabeth A., Abdelhamed, Sherif, Kooijman, Jeffrey J., Miller, Darcie J., Das, Sourav, McGowan, Kevin, Mayasundari, Anand, Shi, Zhe, Barajas, Juan M., Hiltenbrand, Ryan, Aggarwal, Anup, Chang, Yunchao, Mishra, Vibhor, Narina, Shilpa, Thomas, Melvin, Loughran, Allister J., Kalathur, Ravi, Yu, Kaiwen, Zhou, Suiping, Wang, Xusheng, High, Anthony A., Peng, Junmin, Pruett-Miller, Shondra M., Daniels, Danette L., Urh, Marjeta, Shelat, Anang A., Mullighan, Charles G., Riching, Kristin M., Zaman, Guido J. R., Fischer, Marcus, Klco, Jeffery M., and Rankovic, Zoran

Published
2024
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18. Neural Networks for Fast Optimisation in Model Predictive Control: A Review

Author

Gonzalez, Camilo, Asadi, Houshyar, Kooijman, Lars, and Lim, Chee Peng

Subjects
Electrical Engineering and Systems Science - Systems and Control, Mathematics - Optimization and Control
Abstract

Model Predictive Control (MPC) is an optimal control algorithm with strong stability and robustness guarantees. Despite its popularity in robotics and industrial applications, the main challenge in deploying MPC is its high computation cost, stemming from the need to solve an optimisation problem at each control interval. There are several methods to reduce this cost. This survey focusses on approaches where a neural network is used to approximate an existing controller. Herein, relevant and unique neural approximation methods for linear, nonlinear, and robust MPC are presented and compared. Comparisons are based on the theoretical guarantees that are preserved, the factor by which the original controller is sped up, and the size of problem that a framework is applicable to. Research contributions include: a taxonomy that organises existing knowledge, a summary of literary gaps, discussion on promising research directions, and simple guidelines for choosing an approximation framework. The main conclusions are that (1) new benchmarking tools are needed to help prove the generalisability and scalability of approximation frameworks, (2) future breakthroughs most likely lie in the development of ties between control and learning, and (3) the potential and applicability of recently developed neural architectures and tools remains unexplored in this field., Comment: 60 pages, 6 figures 3 tables. Submitted to Annual Reviews in Control

Published
2023

19. Probing invisible neutrino decay with KM3NeT-ORCA

Author

KM3NeT Collaboration, Aiello, S., Albert, A., Garre, S. Alves, Aly, Z., Ambrosone, A., Ameli, F., Andre, M., Anghinolfi, M., Anguita, M., Ardid, M., Ardid, S., Aublin, J., Bagatelas, C., Bailly-Salins, L., Baret, B., Pree, S. Basegmez du, Becherini, Y., Bendahman, M., Benfenati, F., Berbee, E., Bertin, V., Biagi, S., Boettcher, M., Cabo, M. Bou, Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Brânzaş, H., Bruijn, R., Brunner, J., Bruno, R., Buis, E., Buompane, R., Busto, J., Caiffi, B., Calvo, D., Campion, S., Capone, A., Carenini, F., Carretero, V., Castaldi, P., Celli, S., Cerisy, L., Chabab, M., Chau, N., Chen, A., Moursli, R. Cherkaoui El, Cherubini, S., Chiarella, V., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Coniglione, R., Coyle, P., Creusot, A., Cruz, A., Cuttone, G., Dallier, R., Darras, Y., De Benedittis, A., De Martino, B., Decoene, V., Del Burgo, R., Di Palma, I., Díaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donzaud, C., Dornic, D., Dörr, M., Drakopoulou, E., Drouhin, D., Eberl, T., Eddyamoui, A., van Eeden, T., Eff, M., van Eijk, D., Bojaddaini, I. El, Hedri, S. El, Enzenhöfer, A., Espinosa, V., Ferrara, G., Filipović, M. D., Filippini, F., Fusco, L. A., Gabriel, J., Gal, T., Méndez, J. García, Soto, A. Garcia, Garufi, F., Oliver, C. Gatius, Geißelbrecht, N., Gialanella, L., Giorgio, E., Girardi, A., Goos, I., Gozzini, S. R., Gracia, R., Graf, K., Guderian, D., Guidi, C., Guillon, B., Gutiérrez, M., Haegel, L., van Haren, H., Heijboer, A., Hekalo, A., Hennig, L., Hernández-Rey, J. J., Huang, F., Ibnsalih, W. Idrissi, Illuminati, G., James, C. W., Janezashvili, D., de Jong, M., de Jong, P., Jung, B. J., Kalaczyński, P., Kalekin, O., Katz, U. F., Chowdhury, N. R. Khan, Kistauri, G., van der Knaap, F., Kooijman, P., Kouchner, A., Kulikovskiy, V., Labalme, M., Lahmann, R., Lakhal, A., Lamoureux, M., Larosa, G., Lastoria, C., Lazo, A., Breton, R. Le, Stum, S. Le, Lehaut, G., Leonora, E., Lessing, N., Levi, G., Liang, S., Clark, M. Lindsey, Longhitano, F., Maderer, L., Majumdar, J., Mańczak, J., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Martìnez-Mora, J. A., Martini, A., Marzaioli, F., Mastrodicasa, M., Mastroianni, S., Melis, K. W., Miccichè, S., Miele, G., Migliozzi, P., Migneco, E., Mijakowski, P., Mollo, C. M., Morales-Gallegos, L., Morley-Wong, C., Moussa, A., Muller, R., Musone, M. R., Musumeci, M., Nauta, L., Navas, S., Nicolau, C. A., Nkosi, B., Fearraigh, B. Ó, Orlando, A., Oukacha, E., González, J. Palacios, Papalashvili, G., Papaleo, R., Gomez, E. J. Pastor, Păun, A. M., Păvălaş, G. E., Pellegrino, C., Martínez, S. Peña, Perrin-Terrin, M., Perronnel, J., Pestel, V., Piattelli, P., Pisanti, O., Poirè, C., Popa, V., Pradier, T., Pulvirenti, S., Quéméner, G., Rahaman, U., Randazzo, N., Razzaque, S., Rea, I. C., Real, D., Reck, S., Riccobene, G., Robinson, J., Romanov, A., Greus, F. Salesa, Samtleben, D. F. E., Losa, A. Sánchez, Sanguineti, M., Santonastaso, C., Santonocito, D., Sapienza, P., Sathe, A., Schnabel, J., Schneider, M. F., Schumann, J., Schutte, H. M., Seneca, J., Sgura, I., Shanidze, R., Sharma, A., Simonelli, A., Sinopoulou, A., Smirnov, M. V., Spisso, B., Spurio, M., Stavropoulos, D., Stellacci, S. M., Taiuti, M., Tavzarashvili, K., Tayalati, Y., Tedjditi, H., Thakore, T., Thiersen, H., Tsagkli, S., Tsourapis, V., Tzamariudaki, E., Van Elewyck, V., Vannoye, G., Vasileiadis, G., Versari, F., Viola, S., Vivolo, D., Warnhofer, H., Wilms, J., de Wolf, E., Yepes-Ramirez, H., Yousfi, T., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zúñiga, J., and Zywucka, N.

Subjects
High Energy Physics - Experiment
Abstract

In the era of precision measurements of the neutrino oscillation parameters, upcoming neutrino experiments will also be sensitive to physics beyond the Standard Model. KM3NeT/ORCA is a neutrino detector optimised for measuring atmospheric neutrinos from a few GeV to around 100 GeV. In this paper, the sensitivity of the KM3NeT/ORCA detector to neutrino decay has been explored. A three-flavour neutrino oscillation scenario, where the third neutrino mass state $\nu_3$ decays into an invisible state, e.g. a sterile neutrino, is considered. We find that KM3NeT/ORCA would be sensitive to invisible neutrino decays with $1/\alpha_3=\tau_3/m_3 < 180$~$\mathrm{ps/eV}$ at $90\%$ confidence level, assuming true normal ordering. Finally, the impact of neutrino decay on the precision of KM3NeT/ORCA measurements for $\theta_{23}$, $\Delta m^2_{31}$ and mass ordering have been studied. No significant effect of neutrino decay on the sensitivity to these measurements has been found., Comment: 27 pages, 14 figures, bibliography updated, typos corrected

Published
2023
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22. Role of thermogenic adipose tissue in lipid metabolism and atherosclerotic cardiovascular disease: lessons from studies in mice and humans.

Author

Ying, Zhixiong, Tramper, Naomi, Zhou, Enchen, Boon, Mariëtte, Rensen, Patrick, and Kooijman, Sander

Subjects
Adipose tissue, Atherosclerosis, Cardiovascular disease, Dyslipidaemia, Non-shivering thermogenesis, Humans, Animals, Mice, Lipid Metabolism, Cardiovascular Diseases, Triglycerides, Cholesterol, Adipose Tissue, Brown, Atherosclerosis, Cholesterol, HDL, Apolipoproteins E, Thermogenesis, Energy Metabolism
Abstract

Brown adipocytes within brown adipose tissue (BAT) and beige adipocytes within white adipose tissue dissipate nutritional energy as heat. Studies in mice have shown that activation of thermogenesis in brown and beige adipocytes enhances the lipolytic processing of triglyceride-rich lipoproteins (TRLs) in plasma to supply these adipocytes with fatty acids for oxidation. This process results in formation of TRL remnants that are removed from the circulation through binding of apolipoprotein E (ApoE) on their surface to the LDL receptor (LDLR) on hepatocytes, followed by internalization. Concomitantly, lipolytic processing of circulating TRLs leads to generation of excess surface phospholipids that are transferred to nascent HDLs, increasing their capacity for reverse cholesterol transport. Activation of thermogenic adipocytes thus lowers circulating triglycerides and non-HDL-cholesterol, while it increases HDL-cholesterol. The combined effect is protection from atherosclerosis development, which becomes evident in humanized mouse models with an intact ApoE-LDLR clearance pathway only, and is additive to the effects of classical lipid-lowering drugs including statins and proprotein convertase subtilisin/kexin type 9 inhibitors. A large recent study revealed that the presence of metabolically active BAT in humans is associated with lower triglycerides, higher HDL-cholesterol and lower risk of cardiovascular diseases. This narrative review aims to provide leads for further exploration of thermogenic adipose tissue as a therapeutic target. To this end, we describe the latest knowledge on the role of BAT in lipoprotein metabolism and address, for example, the discovery of the β2-adrenergic receptor as the dominant adrenergic receptor in human thermogenic adipocytes.

Published
2023

24. Neutrino Characterisation using Convolutional Neural Networks in CHIPS water Cherenkov detectors

Author

Tingey, Josh, Bash, Simeon, Cesar, John, Dodwell, Thomas, Germani, Stefano, Kooijman, Paul, Mánek, Petr, Ozkaynak, Mustafa, Perch, Andy, Thomas, Jennifer, and Whitehead, Leigh

Subjects
High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract

This work presents a novel approach to water Cherenkov neutrino detector event reconstruction and classification. Three forms of a Convolutional Neural Network have been trained to reject cosmic muon events, classify beam events, and estimate neutrino energies, using only a slightly modified version of the raw detector event as input. When evaluated on a realistic selection of simulated CHIPS-5kton prototype detector events, this new approach significantly increases performance over the standard likelihood-based reconstruction and simple neural network classification., Comment: 45 pages, 22 figures, 5 tables, to be submitted to Nuclear Instruments and Methods in Physics Research - section A

Published
2022
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25. Dietary butyrate ameliorates metabolic health associated with selective proliferation of gut Lachnospiraceae bacterium 28-4.

Author

Li, Zhuang, Zhou, Enchen, Liu, Cong, Wicks, Hope, Yildiz, Sena, Razack, Farhana, Ying, Zhixiong, Kooijman, Sander, Koonen, Debby, Heijink, Marieke, Kostidis, Sarantos, Giera, Martin, Sanders, Ingrid, Kuijper, Ed, Smits, Wiep, van Dijk, Ko, Rensen, Patrick, and Wang, Yanan

Subjects
Endocrinology, Microbiology, Obesity, Humans, Animals, Mice, Butyrates, Obesity, Metabolic Syndrome, RNA, Ribosomal, 16S, Weight Gain, Cell Proliferation
Abstract

Short-chain fatty acids, including butyrate, have multiple metabolic benefits in individuals who are lean but not in individuals with metabolic syndrome, with the underlying mechanisms still being unclear. We aimed to investigate the role of gut microbiota in the induction of metabolic benefits of dietary butyrate. We performed antibiotic-induced microbiota depletion of the gut and fecal microbiota transplantation (FMT) in APOE*3-Leiden.CETP mice, a well-established translational model for developing human-like metabolic syndrome, and revealed that dietary butyrate reduced appetite and ameliorated high-fat diet-induced (HFD-induced) weight gain dependent on the presence of gut microbiota. FMT from butyrate-treated lean donor mice, but not butyrate-treated obese donor mice, into gut microbiota-depleted recipient mice reduced food intake, attenuated HFD-induced weight gain, and improved insulin resistance. 16S rRNA and metagenomic sequencing on cecal bacterial DNA of recipient mice implied that these effects were accompanied by the selective proliferation of Lachnospiraceae bacterium 28-4 in the gut as induced by butyrate. Collectively, our findings reveal a crucial role of gut microbiota in the beneficial metabolic effects of dietary butyrate as strongly associated with the abundance of Lachnospiraceae bacterium 28-4.

Published
2023

26. Nanobeacon: A time calibration device for the KM3NeT neutrino telescope

Author

Aiello, S., Albert, A., Alshamsi, M., Garre, S. Alves, Aly, Z., Ambrosone, A., Ameli, F., Andre, M., Androulakis, G., Anghinolfi, M., Anguita, M., Ardid, M., Ardid, S., Aublin, J., Bagatelas, C., Baret, B., Pree, S. Basegmez du, Bendahman, M., Benfenati, F., Berbee, E., Berg, A. M. van den, Bertine, V., Biagi, S., Boettcher, M., Cabo, M. Bou, Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Branza, H., Bruijn, R., Brunner, J., Bruno, R., Buis, E., Buompane, R., Busto, J., Caiffi, B., Calvo, D., Campion, S., Capone, A., Carretero, V., Castaldi, P., Celli, S., Chabab, M., Chau, N., Chena, A., Cherubini, S., Chiarella, V., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Molla, M. Colomer, Coniglione, R., Coyle, P., Creusot, A., Cruza, A., Cuttone, G., Dalliera, R., De Martino, B., Di Palma, I., Diaz, A. F., Tortosa, D. Diego, Distefano, C., Domi, A., Donzau, C., Dornic, D., Dorra, M., Drouhin, D., Eberla, T., Eddyamoui, A., van Eeden, T., van Eijk, D., Bojaddaini, I. El, Hedri, S. El, Enzenhofer, A., Espinosa, V., Fermani, P., Ferrara, G., Filipovic, M. D., Filippini, F., Fusco, L. A., Gala, T., Mendez, J. Garcia, Garufi, F., Gatelet, Y., Oliver, C. Gatius, Geisselbrecht, N., Gialanella, L., Giorgio, E., Gozzini, S. R., Gracia, R., Grafa, K., Grella, G., Guderian, D., Guidi, C., Guillon, B., Gutierrez, M., Haefner, J., Hallmann, S., Hamdaoui, H., van Harena, H., Heijboer, A., Hekaloa, A., Henniga, L., Hernandez-Rey, J. J., Hofestadt, J., Huang, F., Ibnsalih, W. Idrissi, Illuminati, G., James, C. W., Janezashvili, D., de Jong, M., de Jong, P., Jung, B. J., Kalaczynski, P., Kalekin, O., Katz, U. F., Chowdhury, N. R. Khan, Kistauri, G., van der Knaap, F., Kooijman, P., Kouchner, A., Kulikovskiy, V., Labalme, M., Lahmann, R., Lamoureux, M., Larosa, G., Lastori, C., Lazo, A., Breton, R. Le, Stum, S. Le, Lehaut, G., Leonardi, O., Leone, F., Leonora, E., Lessing, N., Levi, G., Lincetto, M., Clark, M. Lindsey, Lipreau, T., Alvarez, C. LLorens, Longhitano, F., Lopez-Coto, D., Maderer, L., Majumdar, J., Manczak, J., Margiotta, A., Marinelli, A., Markou, C., Martina, L., Martinez-Mora, J. A., Martini, A., Marzaioli, F., Mastroianni, S., Melis, K. W., Miele, G., Migliozzi, P., Migneco, E., Mijakowski, P., Miranda, L. S., Mollo, C. M., Moser, M., Moussa, A., Muller, R., Musumeci, M., Nauta, L., Navas, S., Nicolau, C. A., Nkosi, B., OFearraigh, B., OSullivan, M., Organokov, M., Orlando, A., Gonzalez, J. Palacios, Papalashvilia, G., Papaleo, R., Paun, A. M., Pavala, G. E., Pellegrino, C., Perrin-Terrin, M., Pestel, V., Piattelli, P., Pieterse, C., Pisanti, O., Poire, C., Popa, V., Pradier, T., Probsta, I., Pulvirenti, S., Quemenera, G., Randazzo, N., Razzaquea, S., Real, D., Recka, S., Riccobene, G., Romanov, A., Rovelli, A., Greus, F. Salesa, Samtlebe, D. F. E., Losa, A. Sanchez, Sanguineti, M., Santonocito, D., Sapienza, P., Schnabel, J., Schneidera, M. F., Schumann, J., Schutte, H. M., Seneca, J., Sgura, I., Shanidze, R., Sharma, A., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Stellaccian, S. M., Taiutik, M., Tayalati, Y., Thiersen, H., Tingay, S., Tsagkli, S., Tsourapis, V., Tzamariudaki, E., Tzanetatos, D., Van Elewyck, V., Vasileiadis, G., Versari, F., Vivolo, D., de Wasseige, G., Wilmsa, J., Wojaczynski, R., de Wolf, E., Yousfi, T., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zuniga, J., and Zywucka, N.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Instrumentation and Detectors
Abstract

The KM3NeT Collaboration is currently constructing a multi-site high-energy neutrino telescope in the Mediterranean Sea consisting of matrices of pressure-resistant glass spheres, each holding a set of 31 small-area photomultipliers. The main goals of the telescope are the observation of neutrino sources in the Universe and the measurement of the neutrino oscillation parameters with atmospheric neutrinos. Both extraterrestrial and atmospheric neutrinos are detected through the Cherenkov light induced in seawater by charged particles produced in neutrino interactions in the surrounding medium. A relative time synchronization between photomultipliers of the order of 1 ns is needed to guarantee the required angular resolution of the detector. Due to the large detector volumes to be instrumented by KM3NeT, a cost reduction of the different systems is a priority. To this end, the inexpensive Nanobeacon has been designed and developed by the KM3NeT Collaboration to be used for detector time-calibration studies. At present, more than 600 Nanobeacons have been already produced. The characterization of the optical pulse and the wavelength emission profile of the devices are critical for the time calibration. In this paper, the main features of the Nanobeacon design, production and operation, together with the main properties of the light pulse generated are described.

Published
2021
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27. Implementation and first results of the KM3NeT real-time core-collapse supernova neutrino search

Author

KM3NeT Collaboration, Aiello, S., Albert, A., Alshamsi, M., Garre, S. Alves, Aly, Z., Ambrosone, A., Ameli, F., Andre, M., Androulakis, G., Anghinolfi, M., Anguita, M., Ardid, M., Ardid, S., Aublin, J., Bagatelas, C., Baret, B., Pree, S. Basegmez du, Bendahman, M., Benfenati, F., Berbee, E., Berg, A. M. van den, Bertin, V., Biagi, S., Boettcher, M., Cabo, M. Bou, Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Brânzaş, H., Bruijn, R., Brunner, J., Bruno, R., Buis, E., Buompane, R., Busto, J., Caiffi, B., Calvo, D., Campion, S., Capone, A., Carretero, V., Castaldi, P., Celli, S., Chabab, M., Chau, N., Chen, A., Cherubini, S., Chiarella, V., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Molla, M. Colomer, Coniglione, R., Coyle, P., Creusot, A., Cruz, A., Cuttone, G., Dallier, R., De Martino, B., Di Palma, I., Díaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donzaud, C., Dornic, D., Dörr, M., Drouhin, D., Eberl, T., Eddyamoui, A., van Eeden, T., van Eijk, D., Bojaddaini, I. El, Hedri, S. El, Enzenhöfer, A., Espinosa, V., Fermani, P., Ferrara, G., Filipović, M. D., Filippini, F., Fusco, L. A., Gal, T., Méndez, J. García, Soto, A. Garcia, Garufi, F., Gatelet, Y., Oliver, C. Gatius, Geißelbrecht, N., Gialanella, L., Giorgio, E., Gozzini, S. R., Gracia, R., Graf, K., Grella, G., Guderian, D., Guidi, C., Guillon, B., Gutiérrez, M., Haefner, J., Hallmann, S., Hamdaoui, H., van Haren, H., Heijboer, A., Hekalo, A., Hennig, L., Hernández-Rey, J. J., Hofestädt, J., Huang, F., Ibnsalih, W. Idrissi, Illuminati, G., James, C. W., Janezashvili, D., de Jong, M., de Jong, P., Jung, B. J., Kalaczyński, P., Kalekin, O., Katz, U. F., Chowdhury, N. R. Khan, Kistauri, G., van der Knaap, F., Kooijman, P., Kouchner, A., Kulikovskiy, V., Labalme, M., Lahmann, R., Lamoureux, M., Larosa, G., Lastoria, C., Lazo, A., Breton, R. Le, Stum, S. Le, Lehaut, G., Leonardi, O., Leone, F., Leonora, E., Lessing, N., Levi, G., Lincetto, M., Clark, M. Lindsey, Lipreau, T., Alvarez, C. LLorens, Longhitano, F., Lopez-Coto, D., Maderer, L., Majumdar, J., Mańczak, J., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Martínez-Mora, J. A., Martini, A., Marzaioli, F., Mastroianni, S., Melis, K. W., Miele, G., Migliozzi, P., Migneco, E., Mijakowski, P., Miranda, L. S., Mollo, C. M., Moser, M., Moussa, A., Muller, R., Musumeci, M., Nauta, L., Navas, S., Nicolau, C. A., Nkosi, B., Fearraigh, B. Ó, O'Sullivan, M., Organokov, M., Orlando, A., González, J. Palacios, Papalashvili, G., Papaleo, R., P{ă}un, A. M., Păvălaş, G. E., Pellegrino, C., Perrin-Terrin, M., Pestel, V., Piattelli, P., Pieterse, C., Pisanti, O., Poirè, C., Popa, V., Pradier, T., Probst, I., Pulvirenti, S., Quéméner, G., Randazzo, N., Razzaque, S., Real, D., Reck, S., Riccobene, G., Romanov, A., Rovelli, A., Greus, F. Salesa, Samtleben, D. F. E., Losa, A. Sánchez, Sanguineti, M., Santonocito, D., Sapienza, P., Schnabel, J., Schneider, M. F., Schumann, J., Schutte, H. M., Seneca, J., Sgura, I., Shanidze, R., Sharma, A., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Stellacci, S. M., Taiuti, M., Tayalati, Y., Thiersen, H., Tingay, S., Tsagkli, S., Tsourapis, V., Tzamariudaki, E., Tzanetatos, D., Van Elewyck, V., Vannoye, G., Vasileiadis, G., Versari, F., Viola, S., Vivolo, D., de Wasseige, G., Wilms, J., Wojaczyński, R., de Wolf, E., Yousfi, T., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zúñiga, J., and Zywucka, N.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The KM3NeT research infrastructure is under construction in the Mediterranean Sea. KM3NeT will study atmospheric and astrophysical neutrinos with two multi-purpose neutrino detectors, ARCA and ORCA, primarily aimed at GeV-PeV neutrinos. Thanks to the multi-photomultiplier tube design of the digital optical modules, KM3NeT is capable of detecting the neutrino burst from a Galactic or near-Galactic core-collapse supernova. This potential is already exploitable with the first detection units deployed in the sea. This paper describes the real-time implementation of the supernova neutrino search, operating on the two KM3NeT detectors since the first months of 2019. A quasi-online astronomy analysis is introduced to study the time profile of the detected neutrinos for especially significant events. The mechanism of generation and distribution of alerts, as well as the integration into the SNEWS and SNEWS 2.0 global alert systems are described. The approach for the follow-up of external alerts with a search for a neutrino excess in the archival data is defined. Finally, an overview of the current detector capabilities and a report after the first two years of operation are given., Comment: 19 pages, 9 figures

Published
2021
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28. Combined sensitivity of JUNO and KM3NeT/ORCA to the neutrino mass ordering

Author

KM3NeT Collaboration, Aiello, S., Albert, A., Alshamsi, M., Garre, S. Alves, Aly, Z., Ambrosone, A., Ameli, F., Andre, M., Androulakis, G., Anghinolfi, M., Anguita, M., Ardid, M., Ardid, S., Aublin, J., Bagatelas, C., Baret, B., Pree, S. Basegmez du, Bendahman, M., Benfenati, F., Berbee, E., Berg, A. M. van den, Bertin, V., Biagi, S., Boettcher, M., Cabo, M. Bou, Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Brânzaş, H., Bruijn, R., Brunner, J., Bruno, R., Buis, E., Buompane, R., Busto, J., Caiffi, B., Calvo, D., Campion, S., Capone, A., Carretero, V., Castaldi, P., Celli, S., Chabab, M., Chau, N., Chen, A., Cherubini, S., Chiarella, V., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Molla, M. Colomer, Coniglione, R., Coyle, P., Creusot, A., Cruz, A., Cuttone, G., Dallier, R., De Martino, B., Di Palma, I., Díaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donzaud, C., Dornic, D., Dörr, M., Drouhin, D., Eberl, T., Eddyamoui, A., van Eeden, T., van Eijk, D., Bojaddaini, I. El, Enzenhöfer, A., Espinosa, V., Fermani, P., Ferrara, G., Filipovic, M. D., Filippini, F., Fusco, L. A., Gal, T., Méndez, J. García, Soto, A. Garcia, Garufi, F., Gatelet, Y., Gatius, C., Geisselbrecht, N., Gialanella, L., Giorgio, E., Gozzini, S. R., Gracia, R., Graf, K., Grella, G., Guderian, D., Guidi, C., Guillon, B., Gutiérrez, M., Haefner, J., Hallmann, S., Hamdaoui, H., van Haren, H., Heijboer, A., Hekalo, A., Hennig, L., Hernández-Rey, J. J., Hofestädt, J., Huang, F., Ibnsalih, W. Idrissi, Illuminati, G., James, C. W., de Jong, M., de Jong, P., Jung, B. J., Kalaczynski, P., Kalekin, O., Katz, U. F., Chowdhury, N. R. Khan, Kistauri, G., van der Knaap, F., Kooijman, P., Kouchner, A., Kulikovskiy, V., Labalme, M., Lahmann, R., Lamoureux, M., Larosa, G., Lastoria, C., Lazo, A., Breton, R. Le, Stum, S. Le, Lehaut, G., Leonardi, O., Leone, F., Leonora, E., Lessing, N., Levi, G., Lincetto, M., Clark, M. Lindsey, Lipreau, T., Alvarez, C. Llorens, Longhitano, F., Lopez-Coto, D., Lygda, A., Maderer, L., Majumdar, J., Mańczak, J., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Martínez-Mora, J. A., Martini, A., Marzaioli, F., Mastroianni, S., Melis, K. W., Miele, G., Migliozzi, P., Migneco, E., Mijakowski, P., Miranda, L. S., Mollo, C. M., Moser, M., Moussa, A., Muller, R., Musumeci, M., Nauta, L., Navas, S., Nicolau, C. A., Nkosi, B., Fearraigh, B. Ó, O'Sullivan, M., Organokov, M., Orlando, A., González, J. Palacios, Papalashvili, G., Papaleo, R., Păun, A. M., Păvălaş, G. E., Pellegrino, C., Perrin-Terrin, M., Pestel, V., Piattelli, P., Pieterse, C., Pisanti, O., Poirè, C., Popa, V., Pradier, T., Probst, I., Pulvirenti, S., Quéméner, G., Randazzo, N., Razzaque, S., Real, D., Reck, S., Riccobene, G., Romanov, A., Rovelli, A., Greus, F. Salesa, Samtleben, D. F. E., Losa, A. Sánchez, Sanguineti, M., Santonocito, D., Sapienza, P., Schnabel, J., Schneider, M. F., Schumann, J., Schutte, H. M., Seneca, J., Sgura, I., Shanidze, R., Sharma, A., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Stellacci, S. M., Taiuti, M., Tayalati, Y., Thiersen, H., Tingay, S., Tsagkli, S., Tsourapis, V., Tzamariudaki, E., Tzanetatos, D., Van Elewyck, V., Vasileiadis, G., Versari, F., Vivolo, D., de Wasseige, G., Wilms, J., Wojaczyński, R., de Wolf, E., Yousfi, T., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zúñiga, J., Zywucka, N., members, JUNO Collaboration, Ahmad, S., de André, J. P. A. M., Baussan, E., Bordereau, C., Cabrera, A., Cerna, C., Donchenko, G., Doroshkevich, E. A., Dracos, M., Druillole, F., Jollet, C., Kalousis, L. N., Kampmann, P., Kouzakov, K., Lokhov, A., Lubsandorzhiev, B. K., Lubsandorzhiev, S. B., Meregaglia, A., Miramonti, L., Perrot, F., Rico, L. F. Piñeres, Popov, A., Rasheed, R., Settimo, M., Stankevich, K., Steiger, H., Stock, M. R., Studenikin, A., Triossi, A., Trzaska, W., Vialkov, M., Wonsak, B., Wurtz, J., and Yermia, F.

Subjects
High Energy Physics - Experiment, High Energy Physics - Phenomenology
Abstract

This article presents the potential of a combined analysis of the JUNO and KM3NeT/ORCA experiments to determine the neutrino mass ordering. This combination is particularly interesting as it significantly boosts the potential of either detector, beyond simply adding their neutrino mass ordering sensitivities, by removing a degeneracy in the determination of $\Delta m_{31}^2$ between the two experiments when assuming the wrong ordering. The study is based on the latest projected performances for JUNO, and on simulation tools using a full Monte Carlo approach to the KM3NeT/ORCA response with a careful assessment of its energy systematics. From this analysis, a $5\sigma$ determination of the neutrino mass ordering is expected after 6 years of joint data taking for any value of the oscillation parameters. This sensitivity would be achieved after only 2 years of joint data taking assuming the current global best-fit values for those parameters for normal ordering., Comment: 24 pages, 9 figures

Published
2021
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29. Sensitivity to light sterile neutrino mixing parameters with KM3NeT/ORCA

Author

Aiello, S., Albert, A., Alshamsi, M., Garre, S. Alves, Aly, Z., Ambrosone, A., Ameli, F., Andre, M., Androulakis, G., Anghinolfi, M., Anguita, M., Anton, G., Ardid, M., Ardid, S., Aublin, J., Bagatelas, C., Baret, B., Pree, S. Basegmez du, Bendahman, M., Benfenati, F., Berbee, E., Berg, A. M. van den, Bertin, V., Biagi, S., Bissinger, M., Boettcher, M., Cabo, M. Bou, Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Brânzaş, H., Bretaudeau, F., Bruijn, R., Brunner, J., Bruno, R., Buis, E., Buompane, R., Busto, J., Caiffi, B., Calvo, D., Campion, S., Capone, A., Carretero, V., Castaldi, P., Celli, S., Chabab, M., Chau, N., Chen, A., Cherubini, S., Chiarella, V., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Mollac, M. Colomer, Coniglione, R., Coyle, P., Creusot, A., Cruz, A., Cuttone, G., Dallier, R., De Martino, B., De Palma, M., Di Palma, I., Díaz, A. F., Diego-Tortosan, D., Distefano, C., Domi, A., Donzaud, C., Dornic, D., Dorr, M., Drouhin, D., Eberl, T., Eddyamoui, A., van Eeden, T., van Eijk, D., Bojaddaini, I. El, Elsaesser, D., Enzenhofer, A., Espinosa, V., Fermani, P., Ferrara, G., Filipovic, M. D., Filippini, F., Fusco, L. A., Gal, T., Mendez, J. Garcıa, Soto, A. Garcia, Garufi, F., Gatelet, Y., Geisselbrecht, N., Gialanella, L., Giorgio, E., Gozzini, S. R., Gracia, R., Graf, K., Grella, G., Guderian, D., Guid, C., Gutierrez, M., Haefner, J., Hallmann, S., Hamdaoui, H., van Haren, H., Heijboer, A., Hekalo, A., Hennig, L., Hernandez-Rey, J. J., Hofestadt, J., Huang, F., Ibnsalih, W. Idrissi, Illuminati, G., James, C. W., de Jong, M., de Jong, P., Jung, B. J., Kadler, M., Kalaczynski, P., Kalekin, O., Katz, U. F., Chowdhury, N. R. Khan, Kistauri, G., van der Knaap, F., Kooijman, P., Kouchner, A., Kulikovskiy, V., Lahmann, R., Lamoureux, M., Lara, G., Larosa, G., Lastoria, C., Breton, R. Le, Stum, S. Le, Leonardi, O., Leone, F., Leonora, E., Lessing, N., Levi, G., Lincetto, M., Clark, M. Lindsey, Lipreau, T., Longhitano, F., Lopez-Coto, D., Lygda, A., Maderer, L., Mańczak, J., Mannheim, K., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Martínez-Mora, J. A., Martini, A., Marzaioli, F., Mastroianni, S., Melis, K. W., Miele, G., Migliozzi, P., Migneco, E., Mijakowski, P., Miranda, L. S., Mollo, C. M., Moser, M., Moussa, A., Muller, R., Musumeci, M., Nauta, L., Navas, S., Nicolau, C. A., Nkosi, B., Fearraigh, B. Ó, O'Sullivan, M., Organokov, M., Orlando, A., González, J. Palacios, Papalashvili, G., Papaleo, R., Pastore, C., Păun, A. M., ălaş, G. E. Păv, Pellegrino, C., Martínez, S. Peña, Perrin-Terrin, M., Pestel, V., Piattelli, P., Pieterse, C., Pisanti, O., Poirè, C., Pontoriere, V., Popa, V., Pradier, T., Probst, I., Pühlhofer, G., Pulvirenti, S., Randazzo, N., Razzaque, S., Real, D., Reck, S., Riccobene, G., Romanov, A., Rovelli, A., Greus, F. Salesa, Samtleben, D. F. E., Losa, A. Sánchez, Sanguineti, M., Santangelo, A., Santonocito, D., Sapienza, P., Schnabel, J., Schneider, M. F., Schumann, J., Schutte, H. M., Seneca, J., Sgura, I., Shanidze, R., Sharma, A., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Stellacci, S. M., Taiuti, M., Tatone, F., Tayalati, Y., Thakore, T., Thiersen, H., Tingay, S., Tsagkli, S., Tsourapis, V., Tzamariudaki, E., Tzanetatos, D., Van Elewyck, V., Vasileiadis, G., Versari, F., Vivolo, D., de Wasseige, G., Wilms, J., Wojaczyński, R., de Wolf, E., Yousfi, T., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zúñiga, J., and Zywucka, N.

Subjects
High Energy Physics - Experiment
Abstract

KM3NeT/ORCA is a next-generation neutrino telescope optimised for atmospheric neutrino oscillations studies. In this paper, the sensitivity of ORCA to the presence of a light sterile neutrino in a 3+1 model is presented. After three years of data taking, ORCA will be able to probe the active-sterile mixing angles $\theta_{14}$, $\theta_{24}$, $\theta_{34}$ and the effective angle $\theta_{\mu e}$, over a broad range of mass squared difference $\Delta m^2_{41} \sim [10^{-5}, 10]$ $\rm{eV}^2$, allowing to test the eV-mass sterile neutrino hypothesis as the origin of short baseline anomalies, as well as probing the hypothesis of a very light sterile neutrino, not yet constrained by cosmology. ORCA will be able to explore a relevant fraction of the parameter space not yet reached by present measurements.

Published
2021

30. RCURRENCY: Live Digital Asset Trading Using a Recurrent Neural Network-based Forecasting System

Author

Hu, Yapeng Jasper, van Gurp, Ralph, Somai, Ashay, Kooijman, Hugo, and Rellermeyer, Jan S.

Subjects
Computer Science - Artificial Intelligence
Abstract

Consistent alpha generation, i.e., maintaining an edge over the market, underpins the ability of asset traders to reliably generate profits. Technical indicators and trading strategies are commonly used tools to determine when to buy/hold/sell assets, yet these are limited by the fact that they operate on known values. Over the past decades, multiple studies have investigated the potential of artificial intelligence in stock trading in conventional markets, with some success. In this paper, we present RCURRENCY, an RNN-based trading engine to predict data in the highly volatile digital asset market which is able to successfully manage an asset portfolio in a live environment. By combining asset value prediction and conventional trading tools, RCURRENCY determines whether to buy, hold or sell digital currencies at a given point in time. Experimental results show that, given the data of an interval $t$, a prediction with an error of less than 0.5\% of the data at the subsequent interval $t+1$ can be obtained. Evaluation of the system through backtesting shows that RCURRENCY can be used to successfully not only maintain a stable portfolio of digital assets in a simulated live environment using real historical trading data but even increase the portfolio value over time.

Published
2021

32. Determining the Neutrino Mass Ordering and Oscillation Parameters with KM3NeT/ORCA

Author

Aiello, S., Albert, A., Garre, S. Alves, Aly, Z., Ambrosone, A., Ameli, F., Andre, M., Androulakis, G., Anghinolfi, M., Anguita, M., Anton, G., Ardid, M., Ardid, S., Aublin, J., Bagatelas, C., Baret, B., Pree, S. Basegmez du, Bendahman, M., Benfenati, F., Berbee, E., Berg, A. M. van den, Bertin, V., Biagi, S., Bissinger, M., Boettcher, M., Cabo, M. Bou, Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Brânzaş, H., Bruijn, R., Brunner, J., Bruno, R., Buis, E., Buompane, R., Busto, J., Caiffi, B., Calvo, D., Capone, A., Carretero, V., Castaldi, P., Celli, S., Chabab, M., Chau, N., Chen, A., Cherubini, S., Chiarella, V., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Molla, M. Colomer, Coniglione, R., Coyle, P., Creusot, A., Cruz, A., Cuttone, G., Dallier, R., De Martino, B., De Palma, M., Di Marino, M., Di Palma, I., Díaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donzaud, C., Dornic, D., Dörr, M., Drouhin, D., Eberl, T., Eddyamoui, A., van Eeden, T., van Eijk, D., Bojaddaini, I. El, Elsaesser, D., Enzenhöfer, A., Espinosa, V., Fermani, P., Ferrara, G., Filipovic, M. D., Filippini, F., Fusco, L. A., Gal, T., Soto, A. Garcia, Garufi, F., Gatelet, Y., Geisselbrecht, N., Gialanella, L., Giorgio, E., Gozzini, S. R., Gracia, R., Graf, K., Grasso, D., Grella, G., Guderian, D., Guidi, C., Haefner, J., Hallmann, S., Hamdaoui, H., van Haren, H., Heijboer, A., Hekalo, A., Hennig, L., Hernández-Rey, J. J., Hofestädt, J., Huang, F., Ibnsalih, W. Idrissi, Illuminati, G., James, C. W., de Jong, M., de Jong, P., Jung, B. J., Kadler, M., Kalaczyński, P., Kalekin, O., Katz, U. F., Chowdhury, N. R. Khan, Kistauri, G., van der Knaap, F., Kooijman, P., Kouchner, A., Kreter, M., Kulikovskiy, V., Lahmann, R., Lamoureux, M., Larosa, G., Lastoria, C., Breton, R. Le, Stum, S. Le, Leonardi, O., Leone, F., Leonora, E., Lessing, N., Levi, G., Lincetto, M., Clark, M. Lindsey, Lipreau, T., Longhitano, F., Lopez-Coto, D., Maderer, L., Mańczak, J., Mannheim, K., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Martínez-Mora, J. A., Martini, A., Marzaioli, F., Mastroianni, S., Melis, K. W., Miele, G., Migliozzi, P., Migneco, E., Mijakowski, P., Miranda, L. S., Mollo, C. M., Morganti, M., Moser, M., Moussa, A., Muller, R., Musumeci, M., Nauta, L., Navas, S., Nicolau, C. A., Fearraigh, B. Ó, O'Sullivan, M., Organokov, M., Orlando, A., González, J. Palacios, Papalashvili, G., Papaleo, R., Pastore, C., Păun, A. M., Păvălaş, G. E., Pellegrino, C., Perrin-Terrin, M., Pestel, V., Piattelli, P., Pieterse, C., Pikounis, K., Pisanti, O., Poirè, C., Popa, V., Pradier, T., Pühlhofer, G., Pulvirenti, S., Rabyang, O., Raffaelli, F., Randazzo, N., Razzaque, S., Real, D., Reck, S., Riccobene, G., Romanov, A., Rovelli, A., Greus, F. Salesa, Samtleben, D. F. E., Losa, A. Sánchez, Sanguineti, M., Santangelo, A., Santonocito, D., Sapienza, P., Schnabel, J., Schneider, M. F., Schumann, J., Schutte, H. M., Seneca, J., Sgura, I., Shanidze, R., Sharma, A., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Stellacci, S. M., Taiuti, M., Tayalati, Y., Tenllado, E., Thiersen, H., Tingay, S., Tsourapis, V., Tzamariudaki, E., Tzanetatos, D., Van Elewyck, V., Vasileiadis, G., Versari, F., Vivolo, D., de Wasseige, G., Wilms, J., Wojaczyński, R., de Wolf, E., Yousfi, T., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zúñiga, J., and Zywucka, N.

Subjects
High Energy Physics - Experiment
Abstract

The next generation of water Cherenkov neutrino telescopes in the Mediterranean Sea are under construction offshore France (KM3NeT/ORCA) and Sicily (KM3NeT/ARCA). The KM3NeT/ORCA detector features an energy detection threshold which allows to collect atmospheric neutrinos to study flavour oscillation. This paper reports the KM3NeT/ORCA sensitivity to this phenomenon. The event reconstruction, selection and classification are described. The sensitivity to determine the neutrino mass ordering was evaluated and found to be 4.4 $\sigma$ if the true ordering is normal and 2.3 $\sigma$ if inverted, after three years of data taking. The precision to measure $\Delta m^2_{32}$ and $\theta_{23}$ were also estimated and found to be $85\cdot10^{-6}$ eV$^2$ and $(^{+1.9}_{-3.1})^{\circ}$ for normal neutrino mass ordering and, $75\cdot10^{-6}$ eV$^2$ and $(^{+2.0}_{-7.0})^{\circ}$ for inverted ordering. Finally, a unitarity test of the leptonic mixing matrix by measuring the rate of tau neutrinos is described. Three years of data taking were found to be sufficient to exclude $\nu_{\tau}$ and $\bar{\nu}_{\tau}$ event rate variations larger than 20% at $3\sigma$ level., Comment: Accepted for publication at EPJ-C

Published
2021
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33. Pharmacological treatment with FGF21 strongly improves plasma cholesterol metabolism to reduce atherosclerosis.

Author

Liu, Cong, Schönke, Milena, Zhou, Enchen, Li, Zhuang, Kooijman, Sander, Boon, Mariëtte, Larsson, Mikael, Wallenius, Kristina, Dekker, Niek, Barlind, Louise, Peng, Xiao-Rong, Wang, Yanan, and Rensen, Patrick

Subjects
Adipose-liver axis, Atherosclerotic cardiovascular disease, Brown adipose tissue, Dyslipidaemia, Lipoprotein metabolism, Adipose Tissue, Brown, Adipose Tissue, White, Adiposity, Animals, Anticholesteremic Agents, Apolipoprotein E3, Atherosclerosis, Biomarkers, Cholesterol, Disease Models, Animal, Energy Metabolism, Fibroblast Growth Factors, Hypercholesterolemia, Lipid Metabolism, Lipoproteins, VLDL, Liver, Mice, Transgenic, Plaque, Atherosclerotic, Recombinant Proteins, Triglycerides
Abstract

AIMS: Fibroblast growth factor (FGF) 21, a key regulator of energy metabolism, is currently evaluated in humans for treatment of type 2 diabetes and non-alcoholic steatohepatitis. However, the effects of FGF21 on cardiovascular benefit, particularly on lipoprotein metabolism in relation to atherogenesis, remain elusive. METHODS AND RESULTS: Here, the role of FGF21 in lipoprotein metabolism in relation to atherosclerosis development was investigated by pharmacological administration of a half-life extended recombinant FGF21 protein to hypercholesterolaemic APOE*3-Leiden.CETP mice, a well-established model mimicking atherosclerosis initiation and development in humans. FGF21 reduced plasma total cholesterol, explained by a reduction in non-HDL-cholesterol. Mechanistically, FGF21 promoted brown adipose tissue (BAT) activation and white adipose tissue (WAT) browning, thereby enhancing the selective uptake of fatty acids from triglyceride-rich lipoproteins into BAT and into browned WAT, consequently accelerating the clearance of the cholesterol-enriched remnants by the liver. In addition, FGF21 reduced body fat, ameliorated glucose tolerance and markedly reduced hepatic steatosis, related to up-regulated hepatic expression of genes involved in fatty acid oxidation and increased hepatic VLDL-triglyceride secretion. Ultimately, FGF21 largely decreased atherosclerotic lesion area, which was mainly explained by the reduction in non-HDL-cholesterol as shown by linear regression analysis, decreased lesion severity, and increased atherosclerotic plaque stability index. CONCLUSION: FGF21 improves hypercholesterolaemia by accelerating triglyceride-rich lipoprotein turnover as a result of activating BAT and browning of WAT, thereby reducing atherosclerotic lesion severity and increasing atherosclerotic lesion stability index. We have thus provided additional support for the clinical use of FGF21 in the treatment of atherosclerotic cardiovascular disease.

Published
2022

34. The KM3NeT potential for the next core-collapse supernova observation with neutrinos

Author

KM3NeT Collaboration, Aiello, S., Albert, A., Garre, S. Alves, Aly, Z., Ambrosone, A., Ameli, F., Andre, M., Androulakis, G., Anghinolfi, M., Anguita, M., Anton, G., Ardid, M., Ardid, S., Aublin, J., Bagatelas, C., Baret, B., Pree, S. Basegmez du, Bendahman, M., Benfenati, F., Berbee, E., Berg, A. M. van den, Bertin, V., Biagi, S., Bissinger, M., Boettcher, M., Cabo, M. Bou, Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Brânzaş, H., Bruijn, R., Brunner, J., Buis, E., Buompane, R., Busto, J., Caiffi, B., Calvo, D., Capone, A., Carretero, V., Castaldi, P., Celli, S., Chabab, M., Chau, N., Chen, A., Cherubini, S., Chiarella, V., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Molla, M. Colomer, Coniglione, R., Coyle, P., Creusot, A., Cuttone, G., Dallier, R., De Martino, B., De Palma, M., Di Marino, M., Di Palma, I., Dıaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donzaud, C., Dornic, D., Dörr, M., Drouhin, D., Eberl, T., Eddyamoui, A., van Eeden, T., van Eijk, D., Bojaddaini, I. El, Elsaesser, D., Enzenhöfer, A., Espinosa, V., Fermani, P., Ferrara, G., Filipović, M. D., Filippini, F., Fusco, L. A., Gabella, O., Gal, T., Soto, A. Garcia, Garufi, F., Gatelet, Y., Geißelbrecht, N., Gialanella, L., Giorgio, E., Gozzini, S. R., Gracia, R., Graf, K., Grasso, D., Grella, G., Guderian, D., Guidi, C., Haefner, J., Hamdaoui, H., van Haren, H., Heijboer, A., Hekalo, A., Hennig, L., Hernández-Rey, J. J., Hofestädt, J., Huang, F., Ibnsalih, W. Idrissi, Illuminati, G., James, C. W., de Jong, M., de Jong, P., Jung, B. J., Kadler, M., Kalaczyński, P., Kalekin, O., Katz, U. F., Chowdhury, N. R. Khan, Kistauri, G., van der Knaap, F., Kooijman, P., Kouchner, A., Kreter, M., Kulikovskiy, V., Lahmann, R., Lamoureux, M., Larosa, G., Breton, R. Le, Stum, S. Le, Leonardi, O., Leone, F., Leonora, E., Lessing, N., Levi, G., Lincetto, M., Clark, M. Lindsey, Lipreau, T., Longhitano, F., Lopez-Coto, D., Maderer, L., Mańczak, J., Mannheim, K., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Martınez-Mora, J. A., Martini, A., Marzaioli, F., Mastroianni, S., Mazzou, S., Melis, K. W., Miele, G., Migliozzi, P., Migneco, E., Mijakowski, P., Miranda, L. S., Mollo, C. M., Morganti, M., Moser, M., Moussa, A., Muller, R., Musumeci, M., Nauta, L., Navas, S., Nicolau, C. A., Fearraigh, B. Ó, O'Sullivan, M., Organokov, M., Orlando, A., González, J. Palacios, Papalashvili, G., Papaleo, R., Passaro, G., Pastore, C., Păun, A. M., Păvălaş, G. E., Pellegrino, C., Perrin-Terrin, M., Pestel, V., Piattelli, P., Pieterse, C., Pikounis, K., Pisanti, O., Poirè, C., Popa, V., Pradier, T., Pühlhofer, G., Pulvirenti, S., Rabyang, O., Raffaelli, F., Randazzo, N., Razzaque, S., Real, D., Reck, S., Riccobene, G., Rivoire, S., Romanov, A., Rovelli, A., Greus, F. Salesa, Samtleben, D. F. E., Losa, A. Sánchez, Sanguineti, M., Santangelo, A., Santonocito, D., Sapienza, P., Schnabel, J., Schneider, M. F., Schumann, J., Schutte, H. M., Seneca, J., Sgura, I., Shanidze, R., Sharma, A., Simeone, F., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Stellacci, S. M., Taiuti, M., Tayalati, Y., Tenllado, E., Thakore, T., Thiersen, H., Tingay, S., Tsourapis, V., Tzamariudaki, E., Tzanetatos, D., Unbehaun, T., Van Elewyck, V., Vannoye, G., Vasileiadis, G., Vermariën, G., Versari, F., Viola, S., Vivolo, D., de Wasseige, G., Wilms, J., Wojaczyński, R., de Wolf, E., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zúñiga, J., and Zywucka, N.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The KM3NeT research infrastructure is under construction in the Mediterranean Sea. It consists of two water Cherenkov neutrino detectors, ARCA and ORCA, aimed at neutrino astrophysics and oscillation research, respectively. Instrumenting a large volume of sea water with $\sim$ 6,200 optical modules comprising a total of $\sim$ 200,000 photomultiplier tubes, KM3NeT will achieve sensitivity to $\sim$ 10 MeV neutrinos from Galactic and near-Galactic core-collapse supernovae through the observation of coincident hits in photomultipliers above the background. In this paper, the sensitivity of KM3NeT to a supernova explosion is estimated from detailed analyses of background data from the first KM3NeT detection units and simulations of the neutrino signal. The KM3NeT observational horizon (for a $5\,\sigma$ discovery) covers essentially the Milky-Way and for the most optimistic model, extends to the Small Magellanic Cloud ($\sim$ 60 kpc). Detailed studies of the time profile of the neutrino signal allow assessment of the KM3NeT capability to determine the arrival time of the neutrino burst with a few milliseconds precision for sources up to 5$-$8 kpc away, and detecting the peculiar signature of the standing accretion shock instability if the core-collapse supernova explosion happens closer than 3$-$5 kpc, depending on the progenitor mass. KM3NeT's capability to measure the neutrino flux spectral parameters is also presented., Comment: submitted to EPJC

Published
2021
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36. Deep-sea deployment of the KM3NeT neutrino telescope detection units by self-unrolling

Author

The KM3NeT Collaboration, Aiello, S., Albert, A., Garre, S. Alves, Aly, Z., Ameli, F., Anassontzis, E. G., Andre, M., Androulakis, G., Anghinolfi, M., Anguita, M., Anton, G., Ardid, M., Aublin, J., Bagatelas, C., Bakker, R., Barbarino, G., Baret, B., Pree, S. Basegmez du, Bendahman, M., Berbeen, E., Berg, A. M. van den, Bertin, V., Biagi, S., Billault, M., Bissinger, M., Boettcher, M., Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Brânzaş, H., Bruijn, R., Brunner, J., Buis, E., Buompane, R., Busto, J., Cacopardo, G., Caiffi, B., Caillat, L., Calvo, D., Capone, A., Carretero, V., Castaldi, P., Celli, S., Chabab, M., Chau, N., Chen, A., Cherubini, S., Chiarella, V., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Molla, M. Colomer, Colonges, S., Coniglione, R., Corredoira, I., Cosquer, A., Coyle, P., Creusot, A., Cuttone, G., D'Amato, C., D'Onofrio, A., Dallier, R., De Palma, M., Di Palma, I., Díaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donà, R., Donzau, C., Dornic, D., Dörr, M., Drouhin, D., Eberl, T., Eddyamoui, A., van Eeden, T., van Eijk, D., Bojaddaini, I. El, Elsaesser, D., Enzenhöfer, A., Espinosa, V., Fermani, P., Ferrara, G., Filipović, M. D., Filippini, F., Fusco, L. A., Gabella, O., Gal, T., Soto, A. Garcia, Garufi, F., Gatelet, Y., Geißelbrecht, N., Gialanella, L., Giorgio, E., Gostiaux, L., Gozzini, S. R., Gracia, R., Graf, K., Grasso, D., Grella, G., Grmek, A., Guderian, D., Guidii, C., Hallmann, S., Hamdaoui, H., van Haren, H., van Heerwaarden, J., Heijboer, A., Hekaloa, A., Henry, S., Hernández-Rey, J. J., Hillebrand, T., Hofestädt, J., Huang, F., Ibnsalih, W. Idrissi, Ilioni, A., Illuminati, G., James, C. W., de Jong, M., de Jong, P., Jung, B. J., Kadler, M., Kalaczyński, P., Kalekin, O., Katz, U. F., Chowdhury, N. R. Khan, Kistauri, G., van der Knaap, F., Koffeman, E. N., Kooijman, P., Kouchner, A., Kreter, M., Kulikovskiy, V., Laan, M., Lahmann, R., Lamare, P., Larosa, G., Laurence, J., Breton, R. Le, Leonardi, O., Leone, F., Leonora, E., Levi, G., Lincetto, M., Clark, M. Lindsey, Lipreau, T., Longhitano, F., LopezCotoa, D., Maderer, L., Mańczak, J., Mannheim, K., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Martínez-Mora, J. A., Martini, A., Marzaioli, F., Mastroianni, S., Mazzou, S., Melis, K. W., Miele, G., Migliozzi, P., Migneco, E., Mijakowski, P., Miranda, L. S., Mollo, C. M., Mongelli, M., Morganti, M., Moser, M., Moussa, A., Muller, R., Pérez, D. Muñoz, Musumeci, M., Nauta, L., Navas, S., Nicolau, C. A., Fearraigh, B. Ó, O'Sullivan, M., Organokov, M., Orlando, A., González, J. Palacios, Papalashvili, G., Papaleo, R., Pastore, C., Păun, A. M., Păvălaş, G. E., Pellegrino, C., Perrin-Terrin, M., Piattelli, P., Pieterse, C., Pikounis, K., Pisanti, O., Poirè, C., Popa, V., Pradier, T., Pühlhofer, G., Pulvirenti, S., Rabyang, O., Raffaelli, F., Randazzo, N., Razzaque, S., Real, D., Reck, S., Riccobene, G., Richer, M., Rivoire, S., Rovelli, A., Greus, F. Salesa, Samtleben, D. F. E., Losa, A. Sánchez, Sanguineti, M., Santangelo, A., Santonocito, D., Sapienza, P., Schnabel, J., Schumann, J., Seneca, J., Sgura, I., Shanidze, R., Sharma, A., Simeone, F., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Steijger, J., Stellacci, S. M., Taiutii, M., Tayalati, Y., Tenllado, E., Tézier, D., Thakore, T., Tingay, S., Tzamariudaki, E., Tzanetatos, D., Van Elewyck, V., Vasileiadis, G., Versari, F., Viola, S., Vivolo, D., de Wasseige, G., Wilms, J., Wojaczyński, R., de Wolf, E., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zúñiga, J., and Zywucka, N.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

KM3NeT is a research infrastructure being installed in the deep Mediterranean Sea. It will house a neutrino telescope comprising hundreds of networked moorings - detection units or strings equipped with optical instrumentation to detect the Cherenkov radiation generated by charged particles from neutrino-induced collisions in its vicinity. In comparison to moorings typically used for oceanography, several key features of the KM3NeT string are different: the instrumentation is contained in transparent and thus unprotected glass spheres; two thin Dyneema ropes are used as strength members; and a thin delicate backbone tube with fibre-optics and copper wires for data and power transmission, respectively, runs along the full length of the mooring. Also, compared to other neutrino telescopes such as ANTARES in the Mediterranean Sea and GVD in Lake Baikal, the KM3NeT strings are more slender to minimise the amount of material used for support of the optical sensors. Moreover, the rate of deploying a large number of strings in a period of a few years is unprecedented. For all these reasons, for the installation of the KM3NeT strings, a custom-made, fast deployment method was designed. Despite the length of several hundreds of metres, the slim design of the string allows it to be compacted into a small, re-usable spherical launching vehicle instead of deploying the mooring weight down from a surface vessel. After being lowered to the seafloor, the string unfurls to its full length with the buoyant launching vehicle rolling along the two ropes.The design of the vehicle, the loading with a string, and its underwater self-unrolling are detailed in this paper.

Published
2020

37. Event reconstruction for KM3NeT/ORCA using convolutional neural networks

Author

Aiello, Sebastiano, Albert, Arnauld, Garre, Sergio Alves, Aly, Zineb, Ameli, Fabrizio, Andre, Michel, Androulakis, Giorgos, Anghinolfi, Marco, Anguita, Mancia, Anton, Gisela, Ardid, Miquel, Aublin, Julien, Bagatelas, Christos, Barbarino, Giancarlo, Baret, Bruny, Pree, Suzan Basegmez du, Bendahman, Meriem, Berbee, Edward, Bertin, Vincent, Biagi, Simone, Biagioni, Andrea, Bissinger, Matthias, Boettcher, Markus, Boumaaza, Jihad, Bouta, Mohammed, Bouwhuis, Mieke, Bozza, Cristiano, Branzas, Horea, Bruijn, Ronald, Brunner, Jürgen, Buis, Ernst-Jan, Buompane, Raffaele, Busto, Jose, Caiffi, Barbara, Calvo, David, Capone, Antonio, Carretero, Víctor, Castaldi, Paolo, Celli, Silvia, Chabab, Mohamed, Chau, Nhan, Chen, Andrew, Cherubini, Silvio, Chiarella, Vitaliano, Chiarusi, Tommaso, Circella, Marco, Cocimano, Rosanna, Coelho, Joao, Coleiro, Alexis, Molla, Marta Colomer, Coniglione, Rosa, Coyle, Paschal, Creusot, Alexandre, Cuttone, Giacomo, D'Onofrio, Antonio, Dallier, Richard, de Jong, Maarten, de Jong, Paul, De Palma, Mauro, de Wasseige, Gwenhaël, de Wolf, Els, Di Palma, Irene, Diaz, Antonio, Diego-Tortosa, Dídac, Distefano, Carla, Domi, Alba, Donà, Roberto, Donzaud, Corinne, Dornic, Damien, Dörr, Manuel, Drouhin, Doriane, Eberl, Thomas, Bojaddaini, Imad El, Elsaesser, Dominik, Enzenhöfer, Alexander, Fermani, Paolo, Ferrara, Giovanna, Filipovic, Miroslav, Filippini, Francesco, Fusco, Luigi Antonio, Gabella, Omar, Gal, Tamas, Soto, Alfonso Andres Garcia, Garufi, Fabio, Gatelet, Yoann, Geißelbrecht, Nicole, Gialanella, Lucio, Giorgio, Emidio, Gozzini, Sara Rebecca, Gracia, Rodrigo, Graf, Kay, Grasso, Dario, Grella, Giuseppe, Guidi, Carlo, Hallmann, Steffen, Hamdaoui, Hassane, Heijboer, Aart, Hekalo, Amar, Hernandez-Rey, Juan-Jose, Hofestädt, Jannik, Huang, Feifei, Ibnsalih, Walid Idrissi, Illuminati, Giulia, James, Clancy, Jung, Bouke Jisse, Kadler, Matthias, Kalaczyński, Piotr, Kalekin, Oleg, Katz, Uli, Chowdhury, Nafis Rezwan Khan, Kistauri, Giorgi, Koffeman, Els, Kooijman, Paul, Kouchner, Antoine, Kreter, Michael, Kulikovskiy, Vladimir, Lahmann, Robert, Larosa, Giuseppina, Breton, Remy Le, Leonardi, Ornella, Leone, Francesco, Leonora, Emanuele, Levi, Giuseppe, Lincetto, Massimiliano, Clark, Miles Lindsey, Lipreau, Thomas, Lonardo, Alessandro, Longhitano, Fabio, Coto, Daniel Lopez, Maderer, Lukas, Mańczak, Jerzy, Mannheim, Karl, Margiotta, Annarita, Marinelli, Antonio, Markou, Christos, Martin, Lilian, Martínez-Mora, Juan Antonio, Martini, Agnese, Marzaioli, Fabio, Mastroianni, Stefano, Mazzou, Safaa, Melis, Karel, Miele, Gennaro, Migliozzi, Pasquale, Migneco, Emilio, Mijakowski, Piotr, Palacios, Luis Salvador Miranda, Mollo, Carlos Maximiliano, Morganti, Mauro, Moser, Michael, Moussa, Abdelilah, Muller, Rasa, Musumeci, Mario, Nauta, Lodewijk, Navas, Sergio, Nicolau, Carlo Alessandro, Fearraigh, Brían Ó, Organokov, Mukharbek, Orlando, Angelo, Papalashvili, Gogita, Papaleo, Riccardo, Pastore, Cosimo, Paun, Alice, Pavalas, Gabriela Emilia, Pellegrino, Carmelo, Perrin-Terrin, Mathieu, Piattelli, Paolo, Pieterse, Camiel, Pikounis, Konstantinos, Pisanti, Ofelia, Poirè, Chiara, Popa, Vlad, Post, Maarten, Pradier, Thierry, Pühlhofer, Gerd, Pulvirenti, Sara, Rabyang, Omphile, Raffaelli, Fabrizio, Randazzo, Nunzio, Rapicavoli, Antonio, Razzaque, Soebur, Real, Diego, Reck, Stefan, Riccobene, Giorgio, Richer, Marc, Rivoire, Stephane, Rovelli, Alberto, Greus, Francisco Salesa, Samtleben, Dorothea Franziska Elisabeth, Losa, Agustín Sánchez, Sanguineti, Matteo, Santangelo, Andrea, Santonocito, Domenico, Sapienza, Piera, Schnabel, Jutta, Seneca, Jordan, Sgura, Irene, Shanidze, Rezo, Sharma, Ankur, Simeone, Francesco, Sinopoulou, Anna, Spisso, Bernardino, Spurio, Maurizio, Stavropoulos, Dimitris, Steijger, Jos, Stellacci, Simona Maria, Taiuti, Mauro, Tayalati, Yahya, Tenllado, Enrique, Thakore, Tarak, Tingay, Steven, Tzamariudaki, Ekaterini, Tzanetatos, Dimitrios, Berg, Ad van den, van der Knaap, Frits, van Eijk, Daan, Van Elewyck, Véronique, van Haren, Hans, Vannoye, Godefroy, Vasileiadis, George, Versari, Federico, Viola, Salvatore, Vivolo, Daniele, Wilms, Joern, Wojaczyński, Rafał, Zaborov, Dmitry, Zavatarelli, Sandra, Zegarelli, Angela, Zito, Daniele, Zornoza, Juan-de-Dios, Zúñiga, Juan, and Zywucka, Natalia

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches.

Published
2020
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38. gSeaGen: the KM3NeT GENIE-based code for neutrino telescopes

Author

Aiello, Sebastiano, Albert, Arnauld, Garre, Sergio Alves, Aly, Zineb, Ameli, Fabrizio, Andre, Michel, Androulakis, Giorgos, Anghinolfi, Marco, Anguita, Mancia, Anton, Gisela, Ardid, Miquel, Aublin, Julien, Bagatelas, Christos, Barbarino, Giancarlo, Baret, Bruny, Pree, Suzan Basegmez du, Bendahman, Meriem, Berbee, Edward, Bertin, Vincent, Biagi, Simone, Biagioni, Andrea, Bissinger, Matthias, Boettcher, Markus, Boumaaza, Jihad, Bourret, Simon, Bouta, Mohammed, Bouwhuis, Mieke, Bozza, Cristiano, Branzas, Horea, Bruchner, Marc, Bruijn, Ronald, Brunner, Jürgen, Buis, Ernst-Jan, Buompane, Raffaele, Busto, Jose, Calvo, David, Capone, Antonio, Carretero, Víctor, Castaldi, Paolo, Celli, Silvia, Chabab, Mohamed, Chau, Nhan, Chen, Andrew, Cherubini, Silvio, Chiarella, Vitaliano, Chiarusi, Tommaso, Circella, Marco, Cocimano, Rosanna, Coelho, Joao, Coleiro, Alexis, Molla, Marta Colomer, Coniglione, Rosa, Corredoira, Imanol, Coyle, Paschal, Creusot, Alexandre, Cuttone, Giacomo, D'Onofrio, Antonio, Dallier, Richard, de Jong, Maarten, de Jong, Paul, De Palma, Mauro, de Wasseige, Gwenhaël, de Wolf, Els, Di Palma, Irene, Diaz, Antonio, Diego-Tortosa, Dídac, Distefano, Carla, Domi, Alba, Donà, Roberto, Donzaud, Corinne, Dornic, Damien, Dörr, Manuel, Drouhin, Doriane, Durocher, Mora, Eberl, Thomas, Bojaddaini, Imad El, Elsaesser, Dominik, Enzenhöfer, Alexander, Fermani, Paolo, Ferrara, Giovanna, Filipovic, Miroslav, Filippini, Francesco, Franco, Antonio, Fusco, Luigi Antonio, Gabella, Omar, Gal, Tamas, Soto, Alfonso Andres Garcia, Garufi, Fabio, Gatelet, Yoann, Geißelbrecht, Nicole, Gialanella, Lucio, Giorgio, Emidio, Gozzini, Sara Rebecca, Gracia, Rodrigo, Graf, Kay, Grasso, Dario, Grégoire, Timothée, Grella, Giuseppe, Guidi, Carlo, Hallmann, Steffen, Hamdaoui, Hassane, Heijboer, Aart, Hekalo, Amar, Hernandez-Rey, Juan-Jose, Hofestädt, Jannik, Ibnsalih, Walid Idrissi, Illuminati, Giulia, James, Clancy, Jung, Bouke Jisse, Kadler, Matthias, Kalaczyński, Piotr, Kalekin, Oleg, Katz, Uli, Chowdhury, Nafis Rezwan Khan, Koffeman, Els, Kooijman, Paul, Kouchner, Antoine, Kreter, Michael, Kulikovskiy, Vladimir, Lahmann, Robert, Larosa, Giuseppina, Breton, Remy Le, Leonardi, Ornella, Leone, Francesco, Leonora, Emanuele, Levi, Giuseppe, Lincetto, Massimiliano, Clark, Miles Lindsey, Lipreau, Thomas, Lonardo, Alessandro, Longhitano, Fabio, Coto, Daniel Lopez, Mańczak, Jerzy, Mannheim, Karl, Margiotta, Annarita, Marinelli, Antonio, Markou, Christos, Martin, Lilian, Martínez-Mora, Juan Antonio, Martini, Agnese, Marzaioli, Fabio, Mastroianni, Stefano, Mazzou, Safaa, Melis, Karel, Miele, Gennaro, Migliozzi, Pasquale, Migneco, Emilio, Mijakowski, Piotr, Palacios, Luis Salvador Miranda, Modebadze, Zurab, Mollo, Carlos Maximiliano, Morganti, Mauro, Moser, Michael, Moussa, Abdelilah, Muller, Rasa, Musumeci, Mario, Nauta, Lodewijk, Navas, Sergio, Nicolau, Carlo Alessandro, Fearraigh, Brían Ó, Organokov, Mukharbek, Orlando, Angelo, Papalashvili, Gogita, Papaleo, Riccardo, Pastore, Cosimo, Paun, Alice, Pavalas, Gabriela Emilia, Pellegrino, Carmelo, Perrin-Terrin, Mathieu, Piattelli, Paolo, Pieterse, Camiel, Pikounis, Konstantinos, Pisanti, Ofelia, Poirè, Chiara, Popa, Vlad, Post, Maarten, Pradier, Thierry, Pühlhofer, Gerd, Pulvirenti, Sara, Quinn, Liam, Rabyang, Omphile, Raffaelli, Fabrizio, Randazzo, Nunzio, Rapicavoli, Antonio, Razzaque, Soebur, Real, Diego, Reck, Stefan, Reubelt, Jonas, Riccobene, Giorgio, Richer, Marc, Rivoire, Stephane, Rovelli, Alberto, Greus, Francisco Salesa, Samtleben, Dorothea Franziska Elisabeth, Losa, Agustín Sánchez, Sanguineti, Matteo, Santangelo, Andrea, Santonocito, Domenico, Sapienza, Piera, Schnabel, Jutta, Sciacca, Virginia, Seneca, Jordan, Sgura, Irene, Shanidze, Rezo, Sharma, Ankur, Simeone, Francesco, Sinopoulou, Anna, Spisso, Bernardino, Spurio, Maurizio, Stavropoulos, Dimitris, Steijger, Jos, Stellacci, Simona Maria, Taiuti, Mauro, Tayalati, Yahya, Tenllado, Enrique, Thakore, Tarak, Tingay, Steven, Tzamariudaki, Ekaterini, Tzanetatos, Dimitrios, Berg, Ad van den, van der Knaap, Frits, van Eijk, Daan, Van Elewyck, Véronique, Vannoye, Godefroy, Vasileiadis, George, Versari, Federico, Viola, Salvatore, Vivolo, Daniele, Wilms, Joern, Wojaczyński, Rafał, Zaborov, Dmitry, Zavatarelli, Sandra, Zegarelli, Angela, Zornoza, Juan-de-Dios, Zúñiga, Juan, and Zywucka, Natalia

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The gSeaGen code is a GENIE-based application developed to efficiently generate high statistics samples of events, induced by neutrino interactions, detectable in a neutrino telescope. The gSeaGen code is able to generate events induced by all neutrino flavours, considering topological differences between track-type and shower-like events. Neutrino interactions are simulated taking into account the density and the composition of the media surrounding the detector. The main features of gSeaGen are presented together with some examples of its application within the KM3NeT project., Comment: 45 pages, 10 figures

Published
2020
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39. Strategies for mainstreaming nature-based solutions in urban governance capacities in ten European cities

Author

Hölscher, Katharina, Frantzeskaki, Niki, Collier, Marcus John, Connop, Stuart, Kooijman, Esmee D., Lodder, Marleen, McQuaid, Siobhan, Vandergert, Paula, Xidous, Dimitra, Bešlagić, Lejla, Dick, Gillian, Dumitru, Adina, Dziubała, Agnieszka, Fletcher, Isobel, Adank, Cristian Garcia-Espina, Vázquez, María González, Madajczyk, Natalia, Malekkidou, Eleni, Mavroudi, Maria, Loizou, Eleftherios, Osipiuk, Agnieszka, Pasic, Belma, González, Antonio Prieto, Quartier, Mien, Schepers, Selina, Suljević, Nermina, Trendafilov, Ivaylo, Van De Sijpe, Katrien, Velikova, Velichka, and Vos, Peter

Published
2023
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40. The daily updated Dutch national database on COVID-19 epidemiology, vaccination and sewage surveillance

Author

Geubbels, E. L. P. E., Backer, J. A., Bakhshi-Raiez, F., van der Beek, R. F. H. J., van Benthem, B. H. B., van den Boogaard, J., Broekman, E. H., Dongelmans, D. A., Eggink, D., van Gaalen, R. D., van Gageldonk, A., Hahné, S., Hajji, K., Hofhuis, A., van Hoek, A. J., Kooijman, M. N., Kroneman, A., Lodder, W., van Rooijen, M., Roorda, W., Smorenburg, N., Zwagemaker, F., de Keizer, N. F., van Walle, I., de Roda Husman, A. M., Ruijs, C., and van den Hof, S.

Published
2023
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47. The Control Unit of the KM3NeT Data Acquisition System

Author

Aiello, S., Ameli, F., Andre, M., Androulakis, G., Anghinolfi, M., Anton, G., Ardid, M., Aublin, J., Bagatelas, C., Barbarino, G., Baret, B., Pree, S. Basegmez du, Bendahman, M., Berbee, E., Berg, A. M. van den, Bertin, V., Biagi, S., Biagioni, A., Bissinger, M., Boumaaza, J., Bourret, S., Bouta, M., Bouvet, G., Bouwhuis, M., Bozza, C., Branzas, H., Bruchner, M., Bruijn, R., Brunner, J., Buis, E., Buompane, R., Busto, J., Calvo, D., Capone, A., Celli, S., Chabab, M., Chau, N., Cherubini, S., Chiarella, V., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Molla, M. Colomer, Coniglione, R., Coyle, P., Creusot, A., Cuttone, G., D'Onofrio, A., Dallier, R., De Palma, M., Di Palma, I., Díaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donà, R., Donzaud, C., Dornic, D., Dörr, M., Durocher, M., Eberl, T., Bojaddaini, I. El, Eljarrari, H., Elsaesser, D., Enzenhöfer, A., Fermani, P., Ferrara, G., Filipovic, M. D., Franco, A., Fusco, L. A., Gal, T., Soto, A. Garcia, Garufi, F., Gialanella, L., Giorgio, E., Gozzini, S. R., Gracia, R., Graf, K., Grasso, D., Grégoire, T., Grella, G., Guderian, D., Guidi, C., Hallmann, S., Hamdaoui, H., van Haren, H., Heijboer, A., Hekalo, A., Hernández-Rey, J. J., Hofestädt, J., Huang, F., Illuminati, G., James, C. W., de Jong, M., de Jong, P., Kadler, M., Kalaczynski, P., Kalekin, O., Katz, U. F., Chowdhury, N. R. Khan, van der Knaap, F., Koffeman, E. N., Kooijman, P., Kouchner, A., Kulikovskiy, V., Lahmann, R., Larosa, G., Breton, R. Le, Leone, F., Leonora, E., Levi, G., Lincetto, M., Lonardo, A., Longhitano, F., Lopez-Coto, D., Maggi, G., Manczak, J., Mannheim, K., Margiotta, A., Marinelli, A., Markou, C., Martignac, G., Martin, L., Martínez-Mora, J. A., Martini, A., Marzaioli, F., Mazzou, S., Mele, R., Melis, K. W., Migliozzi, P., Migneco, E., Mijakowski, P., Miranda, L. S., Mollo, C. M., Morganti, M., Moser, M., Moussa, A., Muller, R., Musumeci, M., Nauta, L., Navas, S., Nicolau, C. A., Nielsen, C., Fearraigh, B. O', Organokov, M., Orlando, A., Panagopoulos, V., Papalashvili, G., Papaleo, R., Pastore, C., Pavalas, G. E., Pellegrino, C., Perrin-Terrin, M., Piattelli, P., Pieterse, C., Pikounis, K., Pisanti, O., Poirè, C., Polydefki, G., Popa, V., Post, M., Pradier, T., Puhlhofer, G., Pulvirenti, S., Quinn, L., Raffaelli, F., Randazzo, N., Rapicavoli, A., Razzaque, S., Real, D., Reck, S., Reubelt, J., Riccobene, G., Richer, M., Rigalleau, L., Rovelli, A., Salvadori, I., Samtleben, D. F. E., Losa, A. Sánchez, Sanguineti, M., Santangelo, A., Santonocito, D., Sapienza, P., Schnabel, J., Sciacca, V., Seneca, J., Sgura, I., Shanidze, R., Sharma, A., Simeone, F., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Steijger, J., Stellacci, S. M., Strandberg, B., Stransky, D., Taiuti, M., Tayalati, Y., Tenllado, E., Thakore, T., Tingay, S., Tzamariudaki, E., Tzanetatos, D., Van Elewyck, V., Vannoye, G., Versari, F., Viola, S., Vivolo, D., de Wasseige, G., Wilms, J., Wojaczynski, R., de Wolf, E., Zaborov, D., Zegarelli, A., Zornoza, J. D., and Zúñiga, J.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment
Abstract

The KM3NeT Collaboration runs a multi-site neutrino observatory in the Mediterranean Sea. Water Cherenkov particle detectors, deep in the sea and far off the coasts of France and Italy, are already taking data while incremental construction progresses. Data Acquisition Control software is operating off-shore detectors as well as testing and qualification stations for their components. The software, named Control Unit, is highly modular. It can undergo upgrades and reconfiguration with the acquisition running. Interplay with the central database of the Collaboration is obtained in a way that allows for data taking even if Internet links fail. In order to simplify the management of computing resources in the long term, and to cope with possible hardware failures of one or more computers, the KM3NeT Control Unit software features a custom dynamic resource provisioning and failover technology, which is especially important for ensuring continuity in case of rare transient events in multi-messenger astronomy. The software architecture relies on ubiquitous tools and broadly adopted technologies and has been successfully tested on several operating systems.

Published
2019
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48. KM3NeT front-end and readout electronics system: hardware, firmware and software

Author

The KM3NeT Collaboration, Aiello, S., Ameli, F., Andre, M., Androulakis, G., Anghinolfi, M., Anton, G., Ardid, M., Aublin, J., Bagatelas, C., Barbarino, G., Baret, B., Pree, S. Basegmez du, Belias, A., Berbee, E., Berg, A. M. van den, Bertin, V., van Beveren, V., Biagi, S., Biagioni, A., Bianucci, S., Billault, M., Bissinger, M., Bos, P., Boumaaza, J., Bourret, S., Bouta, M., Bouvet, G., Bouwhuis, M., Bozza, C., Brânzaş, H., Briel, M., Bruchner, M., Bruijn, R., Brunner, J., Buis, E., Buompane, R., Busto, J., Calvo, D., Capone, A., Celli, S., Chabab, M., Chau, N., Cherubini, S., Chiarella, V., Chiarusi, T., Circella, M., Cocimano, R., Coelho, B., Coleiro, A., Molla, M. Colomer, Colonges, S., Coniglione, R., Coyle, P., Creusot, A., Cuttone, G., D'Amato, C., D'Amico, A., D'Onofrio, A., Dallier, R., De Palma, M., Di Palma, I., Díaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donà, R., Donzaud, C., Dornic, D., Dörr, M., Durocher, M., Eberl, T., van Eeden, T., Bojaddaini, I. El, Eljarrari, H., Elsaesser, D., Enzenhöfer, A., Fermani, P., Ferrara, G., Filipović, M. D., Fusco, L. A., Gajanana, D., Gal, T., Soto, A. Garcia, Garufi, F., Gialanella, L., Giorgio, E., Giuliante, A., Gozzini, S. R., Gracia, R., Graf, K., Grasso, D., Grégoire, T., Grella, G., Guderian, D., Guidi, C., Hallmann, S., Hamdaoui, H., van Haren, H., Heijboer, A., Hekalo, A., Hernández-Rey, J. J., Hofestädt, J., Huang, F., Santiago, E. Huesca, Illuminati, G., James, C. W., Jansweijer, P., Jongen, M., de Jong, M., de Jong, P., Kadler, M., Kalaczyński, P., Kalekin, O., Katz, U. F., Chowdhury, N. R. Khan, van der Knaap, F., Koffeman, E. N., Kooijman, P., Kouchner, A., Kreter, M., Kulikovskiy, V., K., Meghna K., Lahmann, R., Larosa, G., Breton, R. Le, Leone, F., Leonora, E., Levi, G., Lincetto, M., Lonardo, A., Longhitano, F., Lopez-Coto, D., Maggi, G., Mańczak, J., Mannheim, K., Margiotta, A., Marinelli, A., Markou, C., Martignac, G., Martin, L., Martínez-Mora, J. A., Martini, A., Marzaioli, F., Mazzou, S., Mele, R., Melis, K. W., Migliozzi, P., Migneco, E., Mijakowski, P., Miranda, L. S., Mollo, C. M., Morganti, M., Moser, M., Moussa, A., Muller, R., Musico, P., Musumeci, M., Nauta, L., Navas, S., Nicolau, C. A., Nielsen, C., Fearraigh, B. Ó, Organokov, M., Orlando, A., Panagopoulos, V., Papalashvili, G., Papaleo, R., Pastore, C., Păvălaş, G. E., Pellegrini, G., Pellegrino, C., Perrin-Terrin, M., Piattelli, P., Pikounis, K., Pisanti, O., Poirè, C., Polydefki, G., Popa, V., Post, M., Pradier, T., Pühlhofer, G., Pulvirenti, S., Quinn, L., Raffaelli, F., Randazzo, N., Rapicavoli, A., Razzaque, S., Real, D., Reck, S., Reubelt, J., Riccobene, G., Richer, M., Rigalleau, L., Rovelli, A., Salvadori, I., Samtleben, D. F. E., Losa, A. Sánchez, Sanguineti, M., Santangelo, A., Santonocito, D., Sapienza, P., Schmelling, J., Schnabel, J., Sciacca, V., Seneca, J., Sgura, I., Shanidze, R., Sharma, A., Simeone, F., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Steijger, J., Stellacci, S. M., Strandberg, B., Stransky, D., Taiuti, M., Tayalati, Y., Tenllado, E., Thakore, T., Timmer, P., Tingay, S., Tzamariudaki, E., Tzanetatos, D., Van Elewyck, V., Versari, F., Viola, S., Vivolo, D., de Wasseige, G., Wilms, J., Wojaczyński, R., de Wolf, E., Zaborov, D., Zegarelli, A., Zornoza, J. D., and Zúñiga, J.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The KM3NeT research infrastructure being built at the bottom of the Mediterranean Sea will host water-Cherenkov telescopes for the detection of cosmic neutrinos. The neutrino telescopes will consist of large volume three-dimensional grids of optical modules to detect the Cherenkov light from charged particles produced by neutrino-induced interactions. Each optical module houses 31 3-inch photomultiplier tubes, instrumentation for calibration of the photomultiplier signal and positioning of the optical module and all associated electronics boards. By design, the total electrical power consumption of an optical module has been capped at seven watts. This paper presents an overview of the front-end and readout electronics system inside the optical module, which has been designed for a 1~ns synchronization between the clocks of all optical modules in the grid during a life time of at least 20 years., Comment: Prepared submission to Journal of Astronomical Telescopes, Instruments, and Systems (JATIS)

Published
2019

49. Trajectory Tracking for Quadrotors with Attitude Control on $\mathcal{S}^2 \times \mathcal{S}^1$

Author

Kooijman, Dave, Schoellig, Angela P., and Antunes, Duarte J.

Subjects
Computer Science - Robotics, Electrical Engineering and Systems Science - Systems and Control
Abstract

The control of a quadrotor is typically split into two subsequent problems: finding desired accelerations to control its position, and controlling its attitude and the total thrust to track these accelerations and to track a yaw angle reference. While the thrust vector, generating accelerations, and the angle of rotation about the thrust vector, determining the yaw angle, can be controlled independently, most attitude control strategies in the literature, relying on representations in terms of quaternions, rotation matrices or Euler angles, result in an unnecessary coupling between the control of the thrust vector and of the angle about this vector. This leads, for instance, to undesired position tracking errors due to yaw tracking errors. In this paper we propose to tackle the attitude control problem using an attitude representation in the Cartesian product of the 2-sphere and the 1-sphere, denoted by $\mathcal{S}^2\times \mathcal{S}^1$. We propose a non-linear tracking control law on $\mathcal{S}^2\times \mathcal{S}^1$ that decouples the control of the thrust vector and of the angle of rotation about the thrust vector, and guarantees almost global asymptotic stability. Simulation results highlight the advantages of the proposed approach over previous approaches.

Published
2019

50. Dependence of atmospheric muon flux on seawater depth measured with the first KM3NeT detection units

Author

KM3NeT Collaboration, Ageron, M., Aiello, S., Ameli, F., Andre, M., Androulakis, G., Anghinolfi, M., Anton, G., Ardid, M., Aublin, J., Bagatelas, C., Barbarino, G., Baret, B., Pree, S. Basegmez du, Belias, A., Berbee, E., Berg, A. M. van den, Bertin, V., van Beveren, V., Biagi, S., Biagioni, A., Bianucci, S., Billault, M., Bissinger, M., de Boer, R., Boumaaza, J., Bourret, S., Bouta, M., Bouwhuis, M., Bozza, C., Brânzaş, H., Briel, M., Bruchner, M., Bruijn, R., Brunner, J., Buis, E., Buompane, R., Busto, J., Cacopardo, G., Caillat, L., Calì, C., Calvo, D., Capone, A., Celli, S., Chabab, M., Chau, N., Cherubini, S., Chiarella, V., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Molla, M. Colomer, Colonges, S., Coniglione, R., Cosquer, A., Coyle, P., Creusot, A., Cuttone, G., D'Amato, C., D'Amico, A., D'Onofrio, A., Dallier, R., De Palma, M., De Sio, C., Di Palma, I., Díaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donà, R., Donzaud, C., van Dooren, L., Dornic, D., Dörr, M., Durocher, M., Eberl, T., van Eeden, T., Bojaddaini, I. El, Eljarrari, H., Elsaesser, D., Enzenhöfer, A., Fermani, P., Ferrara, G., Filipović, M. D., Fusco, L. A., Gajanana, D., Gal, T., Soto, A. Garcia, Garufi, F., Gialanella, L., Giorgio, E., Giuliante, A., Gozzini, S. R., Gracia, R., Graf, K., Grasso, D., Grégoire, T., Grella, G., Grimaldi, A., Grmek, A., Guderian, D., Guerzoni, M., Guidi, C., Hallmann, S., Hamdaoui, H., van Haren, H., Heijboer, A., Hekalo, A., Henry, S., Hernández-Rey, J. J., Hofestädt, J., Huang, F., Santiago, E. Huesca, Illuminati, G., James, C. W., Jansweijer, P., Jongen, M., de Jong, M., de Jong, P., Kadler, M., Kalaczyński, P., Kalekin, O., Katz, U. F., Kayzel, F., Keller, P., Chowdhury, N. R. Khan, van der Knaap, F., Koffeman, E. N., Kooijman, P., Koopstra, J., Kouchner, A., Kreter, M., Kulikovskiy, V., K., Meghna K., Lahmann, R., Lamare, P., Larosa, G., Laurence, J., Breton, R. Le, Leone, F., Leonora, E., Levi, G., Librizzi, F., Lincetto, M., Litrico, P., Alvarez, C. D. Llorens, Lonardo, A., Longhitano, F., Lopez-Coto, D., Maggi, G., Mańczak, J., Mannheim, K., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Martínez-Mora, J. A., Martini, A., Marzaioli, F., Mele, R., Melis, K. W., Migliozzi, P., Migneco, E., Mijakowski, P., Miranda, L. S., Mollo, C. M., Mongelli, M., Morganti, M., Moser, M., Moussa, A., Muller, R., Musico, P., Musumeci, M., Nauta, L., Navas, S., Nicolau, C. A., Nielsen, C., Fearraigh, B. Ó, Organokov, M., Orlando, A., Panagopoulos, V., Pancaldi, G., Papalashvili, G., Papaleo, R., Pastore, C., Păvălaş, G. E., Pellegrini, G., Pellegrino, C., Perrin-Terrin, M., Piattelli, P., Pikounis, K., Pisanti, O., Poirè, C., Polydefki, G., Popa, V., Post, M., Pradier, T., Pühlhofer, G., Pulvirenti, S., Quinn, L., Raffaelli, F., Randazzo, N., Rapicavoli, A., Razzaque, S., Real, D., Reck, S., Reubelt, J., Riccobene, G., Rigalleau, L., Rizza, G., Rocco, R., Rovelli, A., Royon, J., Salemi, M., Salvadori, I., Samtleben, D. F. E., Losa, A. Sánchez, Sanguineti, M., Santangelo, A., Santonocito, D., Sapienza, P., Schmelling, J., Sciacca, V., Sciliberto, D., Seneca, J., Sgura, I., Shanidze, R., Sharma, A., Simeone, F., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Steijger, J., Stellacci, S. M., Strandberg, B., Stransky, D., Stüven, T., Taiuti, M., Tayalati, Y., Tenllado, E., Tézier, D., Thakore, T., Theraube, S., Timmer, P., Tingay, S., Trovato, A., Tsagkli, S., Tzamariudaki, E., Tzanetatos, D., Valieri, C., Van Elewyck, V., Versari, F., Viola, S., Vivolo, D., de Wasseige, G., Wilms, J., Wojaczyński, R., de Wolf, E., Zaborov, D., Zegarelli, A., Zornoza, J. D., and Zúñiga, J.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

KM3NeT is a research infrastructure located in the Mediterranean Sea, that will consist of two deep-sea Cherenkov neutrino detectors. With one detector (ARCA), the KM3NeT Collaboration aims at identifying and studying TeV-PeV astrophysical neutrino sources. With the other detector (ORCA), the neutrino mass ordering will be determined by studying GeV-scale atmospheric neutrino oscillations. The first KM3NeT detection units were deployed at the Italian and French sites between 2015 and 2017. In this paper, a description of the detector is presented, together with a summary of the procedures used to calibrate the detector in-situ. Finally, the measurement of the atmospheric muon flux between 2232-3386 m seawater depth is obtained., Comment: 15 pages, 9 figures

Published
2019
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