Author: "Serafini A" / Publication Type: Reports - Searchworks@Jio Institute Digital Library Search Results

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373 results on '"Serafini A"'

1. IFH: a Diffusion Framework for Flexible Design of Graph Generative Models

Author: Cognolato, Samuel, Sperduti, Alessandro, and Serafini, Luciano
Subjects: Computer Science - Machine Learning, Statistics - Machine Learning
Abstract: Graph generative models can be classified into two prominent families: one-shot models, which generate a graph in one go, and sequential models, which generate a graph by successive additions of nodes and edges. Ideally, between these two extreme models lies a continuous range of models that adopt different levels of sequentiality. This paper proposes a graph generative model, called Insert-Fill-Halt (IFH), that supports the specification of a sequentiality degree. IFH is based upon the theory of Denoising Diffusion Probabilistic Models (DDPM), designing a node removal process that gradually destroys a graph. An insertion process learns to reverse this removal process by inserting arcs and nodes according to the specified sequentiality degree. We evaluate the performance of IFH in terms of quality, run time, and memory, depending on different sequentiality degrees. We also show that using DiGress, a diffusion-based one-shot model, as a generative step in IFH leads to improvement to the model itself, and is competitive with the current state-of-the-art., Comment: Accepted at the 27th European Conference on Artificial Intelligence (ECAI 24)
Published: 2024

2. Exponential Expansion of Massive Schr\'{o}dinger Cats for Sensing and Entanglement

Author: Braccini, Lorenzo, Serafini, Alessio, and Bose, Sougato
Subjects: Quantum Physics, General Relativity and Quantum Cosmology
Abstract: Schr\"{o}dinger cat states of levitated masses have several applications in sensing and, offer an avenue to explore the fundamental nature -- classical vs nonclassical -- of gravity, eg, through gravitationally induced entanglement (GIE). The interaction between a qubit and a levitated mass is a convenient method to create such a cat state. The size of the superpositions is limited by weak mass-qubit interactions. To overcome this limitation, we propose a protocol that exponentially expands an initially small superposition via Gaussian dynamics and successfully recombines it to complete an interferometry. An unknown force can be sensed by the superposition exponentially fast in the expansion time. The entanglement between two such interferometers interacting via a quantum force is -- for the first time in qubit-based non-Gaussian protocols -- obtained by solving the full quantum dynamics using Gaussian techniques. GIE grows exponentially, thereby making it closer to experimental feasibility. Requirements of experimental precision and decoherence are obtained., Comment: 5 Pages, 2 Figures, Table, and Appendix. Comments are welcome
Published: 2024

3. Artificial Intelligence Approaches for Energy Efficiency: A Review

Author: Pasqualetto, Alberto, Serafini, Lorenzo, and Sprocatti, Michele
Subjects: Computer Science - Artificial Intelligence
Abstract: United Nations set Sustainable Development Goals and this paper focuses on 7th (Affordable and Clean Energy), 9th (Industries, Innovation and Infrastructure), and 13th (Climate Action) goals. Climate change is a major concern in our society; for this reason, a current global objective is to reduce energy waste. This work summarizes all main approaches towards energy efficiency using Artificial Intelligence with a particular focus on multi-agent systems to create smart buildings. It mentions the tight relationship between AI, especially IoT, and Big Data. It explains the application of AI to anomaly detection in smart buildings and a possible classification of Intelligent Energy Management Systems: Direct and Indirect. Finally, some drawbacks of AI approaches and some possible future research focuses are proposed.
Published: 2024

4. Full Inverse Compton Scattering: Total Transfer of Energy and Momentum from Electrons to Photons

Author: Serafini, Luca, Petrillo, Vittoria, and Samsam, Sanae
Subjects: Physics - General Physics, Physics - Accelerator Physics
Abstract: In this article we discuss a peculiar regime of Compton Scattering that assures the maximum transfer of energy and momentum from free electrons propagating in vacuum to the scattered photons. We name this regime Full Inverse Compton Scattering (FICS) because it is characterized by the maximum and full energy loss of the electrons in collision with photons: up to 100 % of the electron kinetic energy is indeed transferred to the photon. In the case of relativistic electrons, characterized by a large Lorentz factor (gamma >> 1), FICS regime corresponds to an incident photon energy equal to mec^2/2 . We interpret such an astonishing result as FICS being the time reversal of direct Compton Scattering of very energetic photons (of energy much greater than mec2) onto atomic electrons. Although the cross section of Compton scattering is decreasing with the energy of the incident photon, making the process less probable with respect to other reactions (pair production, nuclear reactions, etc) when high energetic photons are bombarding a target, the kinematics straightforwardly implies that the back-scattered photons would have an energy reaching asymptotically me^2c^2 . FICS is instead the unique suitable working point in Compton scattering for achieving the total transfer of (kinetic) energy exactly from the electron to the photon. Experiencing transitions from the initial momentum to zero in the laboratory system, in FICS the electron is also subject to very large negative acceleration; this fact can lead to possible experiments of sensing the Unruh temperature and related photon bath. On the other side of the energy dynamic range, low relativistic electrons can be completely stopped by moderate energy photons (tens of keV), leading to full exchange of temperature between electron clouds and photon baths.
Published: 2024

5. Interpretable machine learning approach for electron antineutrino selection in a large liquid scintillator detector

Author: Gavrikov, A., Cerrone, V., Serafini, A., Brugnera, R., Garfagnini, A., Grassi, M., Jelmini, B., Lastrucci, L., Aiello, S., Andronico, G., Antonelli, V., Barresi, A., Basilico, D., Beretta, M., Bergnoli, A., Borghesi, M., Brigatti, A., Bruno, R., Budano, A., Caccianiga, B., Cammi, A., Caruso, R., Chiesa, D., Clementi, C., Dusini, S., Fabbri, A., Felici, G., Ferraro, F., Giammarchi, M. G., Giugice, N., Guizzetti, R. M., Guardone, N., Landini, C., Lippi, I., Loffredo, S., Loi, L., Lombardi, P., Lombardo, C., Mantovani, F., Mari, S. M., Martini, A., Miramonti, L., Montuschi, M., Nastasi, M., Orestano, D., Ortica, F., Paoloni, A., Percalli, E., Petrucci, F., Previtali, E., Ranucci, G., Re, A. C., Redchuck, M., Ricci, B., Romani, A., Saggese, P., Sava, G., Sirignano, C., Sisti, M., Stanco, L., Farilla, E. Stanescu, Strati, V., Torri, M. D. C., Triossi, A., Tuvé, C., Venettacci, C., Verde, G., and Votano, L.
Subjects: Physics - Instrumentation and Detectors, Computer Science - Machine Learning, High Energy Physics - Experiment, Physics - Data Analysis, Statistics and Probability
Abstract: Several neutrino detectors, KamLAND, Daya Bay, Double Chooz, RENO, and the forthcoming large-scale JUNO, rely on liquid scintillator to detect reactor antineutrino interactions. In this context, inverse beta decay represents the golden channel for antineutrino detection, providing a pair of correlated events, thus a strong experimental signature to distinguish the signal from a variety of backgrounds. However, given the low cross-section of antineutrino interactions, the development of a powerful event selection algorithm becomes imperative to achieve effective discrimination between signal and backgrounds. In this study, we introduce a machine learning (ML) model to achieve this goal: a fully connected neural network as a powerful signal-background discriminator for a large liquid scintillator detector. We demonstrate, using the JUNO detector as an example, that, despite the already high efficiency of a cut-based approach, the presented ML model can further improve the overall event selection efficiency. Moreover, it allows for the retention of signal events at the detector edges that would otherwise be rejected because of the overwhelming amount of background events in that region. We also present the first interpretable analysis of the ML approach for event selection in reactor neutrino experiments. This method provides insights into the decision-making process of the model and offers valuable information for improving and updating traditional event selection approaches.
Published: 2024

6. Distillation and Stripping purification plants for JUNO liquid scintillator

Author: Landini, C., Beretta, M., Lombardi, P., Brigatti, A., Montuschi, M., Parmeggiano, S., Ranucci, G., Antonelli, V., Basilico, D., Caccianiga, B., Giammarchi, M. G., Miramonti, L., Percalli, E., Re, A. C., Saggese, P., Torri, M. D. C., Aiello, S., Andronico, G., Barresi, A., Bergnoli, A., Borghesi, M., Brugnera, R., Bruno, R., Budano, A., Cammi, A., Cerrone, V., Caruso, R., Chiesa, D., Clementi, C., Dusini, S., Fabbri, A., Felici, G., Garfagnini, A., Giudice, N., Gavrikov, A., Grassi, M., Guizzetti, R. M., Guardone, N., Jelmini, B., Lastrucci, L., Lippi, I., Loi, L., Lombardo, C., Mantovani, F., Mari, S. M., Martini, A., Nastasi, M., Orestano, D., Ortica, F., Paoloni, A., Petrucci, F., Previtali, E., Redchuck, M., Ricci, B., Romani, A., Sava, G., Serafini, A., Sirignano, C., Sisti, M., Stanco, L., Farilla, E. Stanescu, Strati, V., Triossi, A., Tuvè, C., Venettacci, C., Verde, G., and Votano, L.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: The optical and radiochemical purification of the scintillating liquid, which will fill the central detector of the JUNO experiment, plays a crucial role in achieving its scientific goals. Given its gigantic mass and dimensions and an unprecedented target value of about 3% @ 1 MeV in energy resolution, JUNO has set severe requirements on the parameters of its scintillator, such as attenuation length (Lat>20 m at 430 nm), transparency, light yield, and content of radioactive contaminants (238U,232Th<10-15 g/g). To accomplish these needs, the scintillator will be processed using several purification methods, including distillation in partial vacuum and gas stripping, which are performed in two large scale plants installed at the JUNO site. In this paper, layout, operating principles, and technical aspects which have driven the design and construction of the distil- lation and gas stripping plants are reviewed. The distillation is effective in enhancing the optical properties and removing heavy radio-impurities (238U,232Th, 40K), while the stripping process exploits pure water steam and high-purity nitrogen to extract gaseous contaminants (222Rn, 39Ar, 85Kr, O2) from the scintillator. The plant operating parameters have been tuned during the recent com- missioning phase at the JUNO site and several QA/QC measurements and tests have been performed to evaluate the performances of the plants. Some preliminary results on the efficiency of these purification processes will be shown., Comment: 11 pages, 7 figures
Published: 2024

7. Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch

Author: Bajaj, Saurabh, Guan, Hui, and Serafini, Marco
Subjects: Computer Science - Machine Learning, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract: Graph Neural Networks (GNNs) have gained significant attention in recent years due to their ability to learn representations of graph structured data. Two common methods for training GNNs are mini-batch training and full-graph training. Since these two methods require different training pipelines and systems optimizations, two separate categories of GNN training systems emerged, each tailored for one method. Works that introduce systems belonging to a particular category predominantly compare them with other systems within the same category, offering limited or no comparison with systems from the other category. Some prior work also justifies its focus on one specific training method by arguing that it achieves higher accuracy than the alternative. The literature, however, has incomplete and contradictory evidence in this regard. In this paper, we provide a comprehensive empirical comparison of full-graph and mini-batch GNN training systems to get a clearer picture of the state of the art in the field. We find that the mini-batch training systems we consider consistently converge faster than the full-graph training ones across multiple datasets, GNN models, and system configurations, with speedups between 2.4x - 15.2x. We also find that both training techniques converge to similar accuracy values, so comparing systems across the two categories in terms of time-to-accuracy is a sound approach., Comment: 12 pages, 1 appendix, 8 Figures, 16 Tables, Graph Neural Network, Graph Neural Networks, Full-graph training, Mini-batch training, full-batch training, distributed training, performance, epoch time, time to accuracy, accuracy
Published: 2024

8. Refractive index in the JUNO liquid scintillator

Author: Zhang, H. S., Beretta, M., Cialdi, S., Yang, C. X., Huang, J. H., Ferraro, F., Cao, G. F., Reina, G., Deng, Z. Y., Suerra, E., Altilia, S., Antonelli, V., Basilico, D., Brigatti, A., Caccianiga, B., Giammarchi, M. G., Landini, C., Lombardi, P., Miramonti, L., Percalli, E., Ranucci, G., Re, A. C., Saggese, P., Torri, M. D. C., Aiello, S., Andronico, G., Barresi, A., Bergnoli, A., Borghesi, M., Brugnera, R., Bruno, R., Budano, A., Cammi, A., Cerrone, V., Caruso, R., Chiesa, D., Clementi, C., Dusini, S., Fabbri, A., Felici, G., Garfagnini, A., Giudice, N., Gavrikov, A., Grassi, M., Guizzetti, R. M., Guardone, N., Jelmini, B., Lastrucci, L., Lippi, I., Loi, L., Lombardo, C., Mantovani, F., Mari, S. M., Martini, A., Montuschi, M., Nastasi, M., Orestano, D., Ortica, F., Paoloni, A., Petrucci, F., Previtali, E., Redchuck, M., Ricci, B., Romani, A., Sava, G., Serafini, A., Sirignano, C., Sisti, M., Stanco, L., Farilla, E. Stanescu, Strati, V., Triossi, A., Tuvé, C., Venettacci, C., Verde, G., and Votano, L.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: In the field of rare event physics, it is common to have huge masses of organic liquid scintillator as detection medium. In particular, they are widely used to study neutrino properties or astrophysical neutrinos. Thanks to its safety properties (such as low toxicity and high flash point) and easy scalability, linear alkyl benzene is the most common solvent used to produce liquid scintillators for large mass experiments. The knowledge of the refractive index is a pivotal point to understand the detector response, as this quantity (and its wavelength dependence) affects the Cherenkov radiation and photon propagation in the medium. In this paper, we report the measurement of the refractive index of the JUNO liquid scintillator between 260-1064 nm performed with two different methods (an ellipsometer and a refractometer), with a sub percent level precision. In addition, we used an interferometer to measure the group velocity in the JUNO liquid scintillator and verify the expected value derived from the refractive index measurements., Comment: 6 pages, 9 figures
Published: 2024

9. JUNO Sensitivity to Invisible Decay Modes of Neutrons

Author: JUNO Collaboration, Abusleme, Angel, Adam, Thomas, Adamowicz, Kai, Ahmad, Shakeel, Ahmed, Rizwan, Aiello, Sebastiano, An, Fengpeng, An, Qi, Andronico, Giuseppe, Anfimov, Nikolay, Antonelli, Vito, Antoshkina, Tatiana, de André, João Pedro Athayde Marcondes, Auguste, Didier, Bai, Weidong, Balashov, Nikita, Baldini, Wander, Barresi, Andrea, Basilico, Davide, Baussan, Eric, Bellato, Marco, Beretta, Marco, Bergnoli, Antonio, Bick, Daniel, Bieger, Lukas, Biktemerova, Svetlana, Birkenfeld, Thilo, Blake, Iwan, Blyth, Simon, Bolshakova, Anastasia, Bongrand, Mathieu, Breton, Dominique, Brigatti, Augusto, Brugnera, Riccardo, Bruno, Riccardo, Budano, Antonio, Busto, Jose, Cabrera, Anatael, Caccianiga, Barbara, Cai, Hao, Cai, Xiao, Cai, Yanke, Cai, Zhiyan, Callier, Stéphane, Calvez, Steven, Cammi, Antonio, Campeny, Agustin, Cao, Chuanya, Cao, Guofu, Cao, Jun, Caruso, Rossella, Cerna, Cédric, Cerrone, Vanessa, Chang, Jinfan, Chang, Yun, Chatrabhuti, Auttakit, Chen, Chao, Chen, Guoming, Chen, Pingping, Chen, Shaomin, Chen, Xin, Chen, Yiming, Chen, Yixue, Chen, Yu, Chen, Zelin, Chen, Zhangming, Chen, Zhiyuan, Chen, Zikang, Cheng, Jie, Cheng, Yaping, Cheng, Yu Chin, Chepurnov, Alexander, Chetverikov, Alexey, Chiesa, Davide, Chimenti, Pietro, Chin, Yen-Ting, Chou, Po-Lin, Chu, Ziliang, Chukanov, Artem, Claverie, Gérard, Clementi, Catia, Clerbaux, Barbara, Molla, Marta Colomer, Di Lorenzo, Selma Conforti, Coppi, Alberto, Corti, Daniele, Csakli, Simon, Cui, Chenyang, Corso, Flavio Dal, Dalager, Olivia, Datta, Jaydeep, De La Taille, Christophe, Deng, Zhi, Deng, Ziyan, Ding, Xiaoyu, Ding, Xuefeng, Ding, Yayun, Dirgantara, Bayu, Dittrich, Carsten, Dmitrievsky, Sergey, Dohnal, Tadeas, Dolzhikov, Dmitry, Donchenko, Georgy, Dong, Jianmeng, Doroshkevich, Evgeny, Dou, Wei, Dracos, Marcos, Druillole, Frédéric, Du, Ran, Du, Shuxian, Duan, Yujie, Dugas, Katherine, Dusini, Stefano, Duyang, Hongyue, Eck, Jessica, Enqvist, Timo, Fabbri, Andrea, Fahrendholz, Ulrike, Fan, Lei, Fang, Jian, Fang, Wenxing, Fedoseev, Dmitry, Feng, Li-Cheng, Feng, Qichun, Ferraro, Federico, Fournier, Amélie, Fritsch, Fritsch, Gan, Haonan, Gao, Feng, Garfagnini, Alberto, Gavrikov, Arsenii, Giammarchi, Marco, Giudice, Nunzio, Gonchar, Maxim, Gong, Guanghua, Gong, Hui, Gornushkin, Yuri, Grassi, Marco, Gromov, Maxim, Gromov, Vasily, Gu, Minghao, Gu, Xiaofei, Gu, Yu, Guan, Mengyun, Guan, Yuduo, Guardone, Nunzio, Guizzetti, Rosa Maria, Guo, Cong, Guo, Wanlei, Hagner, Caren, Han, Hechong, Han, Ran, Han, Yang, He, Jinhong, He, Miao, He, Wei, He, Xinhai, Heinz, Tobias, Hellmuth, Patrick, Heng, Yuekun, Herrera, Rafael, Hor, YuenKeung, Hou, Shaojing, Hsiung, Yee, Hu, Bei-Zhen, Hu, Hang, Hu, Jun, Hu, Peng, Hu, Shouyang, Hu, Tao, Hu, Yuxiang, Hu, Zhuojun, Huang, Guihong, Huang, Hanxiong, Huang, Jinhao, Huang, Junting, Huang, Kaixuan, Huang, Shengheng, Huang, Wenhao, Huang, Xin, Huang, Xingtao, Huang, Yongbo, Hui, Jiaqi, Huo, Lei, Huo, Wenju, Huss, Cédric, Hussain, Safeer, Imbert, Leonard, Ioannisian, Ara, Isocrate, Roberto, Jafar, Arshak, Jelmini, Beatrice, Jeria, Ignacio, Ji, Xiaolu, Jia, Huihui, Jia, Junji, Jian, Siyu, Jiang, Cailian, Jiang, Di, Jiang, Guangzheng, Jiang, Wei, Jiang, Xiaoshan, Jiang, Xiaozhao, Jiang, Yixuan, Jing, Xiaoping, Jollet, Cécile, Kang, Li, Karaparabil, Rebin, Kazarian, Narine, Khan, Ali, Khatun, Amina, Khosonthongkee, Khanchai, Korablev, Denis, Kouzakov, Konstantin, Krasnoperov, Alexey, Kuleshov, Sergey, Kumaran, Sindhujha, Kutovskiy, Nikolay, Labit, Loïc, Lachenmaier, Tobias, Lai, Haojing, Landini, Cecilia, Leblanc, Sébastien, Lefevre, Frederic, Lei, Ruiting, Leitner, Rupert, Leung, Jason, Li, Demin, Li, Fei, Li, Fule, Li, Gaosong, Li, Hongjian, Li, Huang, Li, Jiajun, Li, Min, Li, Nan, Li, Qingjiang, Li, Ruhui, Li, Rui, Li, Shanfeng, Li, Shuo, Li, Tao, Li, Teng, Li, Weidong, Li, Weiguo, Li, Xiaomei, Li, Xiaonan, Li, Xinglong, Li, Yi, Li, Yichen, Li, Yufeng, Li, Zhaohan, Li, Zhibing, Li, Ziyuan, Li, Zonghai, Liang, An-An, Liang, Hao, Liao, Jiajun, Liao, Yilin, Liao, Yuzhong, Limphirat, Ayut, Lin, Guey-Lin, Lin, Shengxin, Lin, Tao, Ling, Jiajie, Ling, Xin, Lippi, Ivano, Liu, Caimei, Liu, Fang, Liu, Fengcheng, Liu, Haidong, Liu, Haotian, Liu, Hongbang, Liu, Hongjuan, Liu, Hongtao, Liu, Hongyang, Liu, Jianglai, Liu, Jiaxi, Liu, Jinchang, Liu, Min, Liu, Qian, Liu, Qin, Liu, Runxuan, Liu, Shenghui, Liu, Shubin, Liu, Shulin, Liu, Xiaowei, Liu, Xiwen, Liu, Xuewei, Liu, Yankai, Liu, Zhen, Loi, Lorenzo, Lokhov, Alexey, Lombardi, Paolo, Lombardo, Claudio, Loo, Kai, Lu, Chuan, Lu, Haoqi, Lu, Jingbin, Lu, Junguang, Lu, Meishu, Lu, Peizhi, Lu, Shuxiang, Lu, Xianguo, Lubsandorzhiev, Bayarto, Lubsandorzhiev, Sultim, Ludhova, Livia, Lukanov, Arslan, Luo, Fengjiao, Luo, Guang, Luo, Jianyi, Luo, Shu, Luo, Wuming, Luo, Xiaojie, Lyashuk, Vladimir, Ma, Bangzheng, Ma, Bing, Ma, Qiumei, Ma, Si, Ma, Xiaoyan, Ma, Xubo, Maalmi, Jihane, Mai, Jingyu, Malabarba, Marco, Malyshkin, Yury, Mandujano, Roberto Carlos, Mantovani, Fabio, Mao, Xin, Mao, Yajun, Mari, Stefano M., Marini, Filippo, Martini, Agnese, Mayer, Matthias, Mayilyan, Davit, Mednieks, Ints, Meng, Yue, Meraviglia, Anita, Meregaglia, Anselmo, Meroni, Emanuela, Miramonti, Lino, Mohan, Nikhil, Montuschi, Michele, Reveco, Cristobal Morales, Nastasi, Massimiliano, Naumov, Dmitry V., Naumova, Elena, Navas-Nicolas, Diana, Nemchenok, Igor, Thi, Minh Thuan Nguyen, Nikolaev, Alexey, Ning, Feipeng, Ning, Zhe, Nunokawa, Hiroshi, Oberauer, Lothar, Ochoa-Ricoux, Juan Pedro, Olshevskiy, Alexander, Orestano, Domizia, Ortica, Fausto, Othegraven, Rainer, Paoloni, Alessandro, Parker, George, Parmeggiano, Sergio, Patsias, Achilleas, Pei, Yatian, Pelicci, Luca, Peng, Anguo, Peng, Haiping, Peng, Yu, Peng, Zhaoyuan, Percalli, Elisa, Perrin, Willy, Perrot, Frédéric, Petitjean, Pierre-Alexandre, Petrucci, Fabrizio, Pilarczyk, Oliver, Rico, Luis Felipe Piñeres, Popov, Artyom, Poussot, Pascal, Previtali, Ezio, Qi, Fazhi, Qi, Ming, Qi, Xiaohui, Qian, Sen, Qian, Xiaohui, Qian, Zhen, Qiao, Hao, Qin, Zhonghua, Qiu, Shoukang, Qu, Manhao, Qu, Zhenning, Ranucci, Gioacchino, Re, Alessandra, Rebii, Abdel, Redchuk, Mariia, Reina, Gioele, Ren, Bin, Ren, Jie, Ren, Yuhan, Ricci, Barbara, Rientong, Komkrit, Rifai, Mariam, Roche, Mathieu, Rodphai, Narongkiat, Romani, Aldo, Roskovec, Bedřich, Ruan, Xichao, Rybnikov, Arseniy, Sadovsky, Andrey, Saggese, Paolo, Sandanayake, Deshan, Sangka, Anut, Sava, Giuseppe, Sawangwit, Utane, Schever, Michaela, Schwab, Cédric, Schweizer, Konstantin, Selyunin, Alexandr, Serafini, Andrea, Settimo, Mariangela, Shao, Junyu, Sharov, Vladislav, Shi, Hexi, Shi, Jingyan, Shi, Yanan, Shutov, Vitaly, Sidorenkov, Andrey, Šimkovic, Fedor, Singhal, Apeksha, Sirignano, Chiara, Siripak, Jaruchit, Sisti, Monica, Smirnov, Mikhail, Smirnov, Oleg, Sokolov, Sergey, Songwadhana, Julanan, Soonthornthum, Boonrucksar, Sotnikov, Albert, Sreethawong, Warintorn, Stahl, Achim, Stanco, Luca, Stankevich, Konstantin, Steiger, Hans, Steinmann, Jochen, Sterr, Tobias, Stock, Matthias Raphael, Strati, Virginia, Strizh, Michail, Studenikin, Alexander, Su, Aoqi, Su, Jun, Sun, Guangbao, Sun, Shifeng, Sun, Xilei, Sun, Yongjie, Sun, Yongzhao, Sun, Zhengyang, Suwonjandee, Narumon, Takenaka, Akira, Tan, Xiaohan, Tang, Jian, Tang, Jingzhe, Tang, Qiang, Tang, Quan, Tang, Xiao, Hariharan, Vidhya Thara, Tkachev, Igor, Tmej, Tomas, Torri, Marco Danilo Claudio, Triossi, Andrea, Trzaska, Wladyslaw, Tung, Yu-Chen, Tuve, Cristina, Ushakov, Nikita, Vedin, Vadim, Venettacci, Carlo, Verde, Giuseppe, Vialkov, Maxim, Viaud, Benoit, Vollbrecht, Cornelius Moritz, von Sturm, Katharina, Vorobel, Vit, Voronin, Dmitriy, Votano, Lucia, Walker, Pablo, Wang, Caishen, Wang, Chung-Hsiang, Wang, En, Wang, Guoli, Wang, Hanwen, Wang, Jian, Wang, Jun, Wang, Li, Wang, Lu, Wang, Meng, Wang, Mingyuan, Wang, Qianchuan, Wang, Ruiguang, Wang, Sibo, Wang, Siguang, Wang, Wei, Wang, Wenshuai, Wang, Xi, Wang, Xiangyue, Wang, Yangfu, Wang, Yaoguang, Wang, Yi, Wang, Yifang, Wang, Yuanqing, Wang, Yuyi, Wang, Zhe, Wang, Zheng, Wang, Zhimin, Watcharangkool, Apimook, Wei, Wei, Wei, Wenlu, Wei, Yadong, Wei, Yuehuan, Wen, Liangjian, Weng, Jun, Wiebusch, Christopher, Wirth, Rosmarie, Wu, Chengxin, Wu, Diru, Wu, Qun, Wu, Yinhui, Wu, Yiyang, Wu, Zhi, Wurm, Michael, Wurtz, Jacques, Wysotzki, Christian, Xi, Yufei, Xia, Dongmei, Xian, Shishen, Xiang, Ziqian, Xiao, Fei, Xiao, Xiang, Xie, Xiaochuan, Xie, Yijun, Xie, Yuguang, Xin, Zhao, Xing, Zhizhong, Xu, Benda, Xu, Cheng, Xu, Donglian, Xu, Fanrong, Xu, Hangkun, Xu, Jiayang, Xu, Jilei, Xu, Jing, Xu, Jinghuan, Xu, Meihang, Xu, Xunjie, Xu, Yin, Xu, Yu, Yan, Baojun, Yan, Qiyu, Yan, Taylor, Yan, Xiongbo, Yan, Yupeng, Yang, Changgen, Yang, Chengfeng, Yang, Fengfan, Yang, Jie, Yang, Lei, Yang, Pengfei, Yang, Xiaoyu, Yang, Yifan, Yang, Yixiang, Yang, Zekun, Yao, Haifeng, Ye, Jiaxuan, Ye, Mei, Ye, Ziping, Yermia, Frédéric, You, Zhengyun, Yu, Boxiang, Yu, Chiye, Yu, Chunxu, Yu, Guojun, Yu, Hongzhao, Yu, Miao, Yu, Xianghui, Yu, Zeyuan, Yu, Zezhong, Yuan, Cenxi, Yuan, Chengzhuo, Yuan, Ying, Yuan, Zhenxiong, Yue, Baobiao, Zafar, Noman, Zamogilnyi, Kirill, Zavadskyi, Vitalii, Zeng, Fanrui, Zeng, Shan, Zeng, Tingxuan, Zeng, Yuda, Zhan, Liang, Zhang, Aiqiang, Zhang, Bin, Zhang, Binting, Zhang, Feiyang, Zhang, Hangchang, Zhang, Haosen, Zhang, Honghao, Zhang, Jialiang, Zhang, Jiawen, Zhang, Jie, Zhang, Jingbo, Zhang, Jinnan, Zhang, Junwei, Zhang, Lei, Zhang, Peng, Zhang, Ping, Zhang, Qingmin, Zhang, Shiqi, Zhang, Shu, Zhang, Shuihan, Zhang, Siyuan, Zhang, Tao, Zhang, Xiaomei, Zhang, Xin, Zhang, Xuantong, Zhang, Yibing, Zhang, Yinhong, Zhang, Yiyu, Zhang, Yongpeng, Zhang, Yu, Zhang, Yuanyuan, Zhang, Yumei, Zhang, Zhenyu, Zhang, Zhijian, Zhao, Jie, Zhao, Rong, Zhao, Runze, Zhao, Shujun, Zhao, Tianhao, Zheng, Hua, Zheng, Yangheng, Zhou, Jing, Zhou, Li, Zhou, Nan, Zhou, Shun, Zhou, Tong, Zhou, Xiang, Zhou, Xing, Zhu, Jingsen, Zhu, Kangfu, Zhu, Kejun, Zhu, Zhihang, Zhuang, Bo, Zhuang, Honglin, Zong, Liang, and Zou, Jiaheng
Subjects: High Energy Physics - Experiment, High Energy Physics - Phenomenology
Abstract: We explore the bound neutrons decay into invisible particles (e.g., $n\rightarrow 3 \nu$ or $nn \rightarrow 2 \nu$) in the JUNO liquid scintillator detector. The invisible decay includes two decay modes: $ n \rightarrow { inv} $ and $ nn \rightarrow { inv} $. The invisible decays of $s$-shell neutrons in $^{12}{\rm C}$ will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino $\bar{\nu}_e$, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are $\tau/B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, {\rm yr}$ and $\tau/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}$., Comment: 28 pages, 7 figures, 4 tables
Published: 2024

10. Towards Counting Markov Equivalence Classes with Logical Constraints

Author: Bizzaro, Davide, Serafini, Luciano, and Malhotra, Sagar
Subjects: Computer Science - Logic in Computer Science
Abstract: We initiate the study of counting Markov Equivalence Classes (MEC) under logical constraints. MECs are equivalence classes of Directed Acyclic Graphs (DAGs) that encode the same conditional independence structure among the random variables of a DAG model. Observational data can only allow to infer a DAG model up to Markov Equivalence. However, Markov equivalent DAGs can represent different causal structures, potentially super-exponentially many. Hence, understanding MECs combinatorially is critical to understanding the complexity of causal inference. In this paper, we focus on analysing MECs of size one, with logical constraints on the graph topology. We provide a polynomial-time algorithm (w.r.t. the number of nodes) for enumerating essential DAGs (the only members of an MEC of size one) with arbitrary logical constraints expressed in first-order logic with two variables and counting quantifiers (C^2). Our work brings together recent developments in tractable first-order model counting and combinatorics of MECs., Comment: Under Review
Published: 2024

11. On the Euler characteristic of $S$-arithmetic groups

Author: Kammeyer, Holger and Serafini, Giada
Subjects: Mathematics - Group Theory, Mathematics - Number Theory, 22E40, 20E18, 11E72
Abstract: We show that the sign of the Euler characteristic of an $S$-arithmetic subgroup of a simple $k$-group over a number field $k$ depends on the $S$-congruence completion only. Consequently, the sign is a profinite invariant for such $S$-arithmetic groups with the congruence subgroup property. This generalizes previous work of the first author with Kionke-Raimbault-Sauer., Comment: 19 pages. Rearranged introduction
Published: 2024

12. From Compton Scattering of photons on targets to Inverse Compton Scattering of electron and photon beams

Author: Serafini, Luca and Petrillo, Vittoria
Subjects: Physics - Accelerator Physics
Abstract: We revisit the kinematics of Compton Scattering (electron-photon interactions producing electrons and photons in the exit channel) covering the full range of energy/momenta distribution between the two colliding particles, with a dedicated view to statistical properties of secondary beams that are generated in beam-beam collisions. Starting from the Thomson inverse scattering, where electrons do not recoil and photons are back-scattered to higher energies by a Lorentz boost effect (factor $4\gamma^2$), we analyze three transition points, separating four regions. These are in sequence, given by increasing the electron recoil (numbers are for transition points, letters for regions): a) Thomson back-scattering, 1) equal sharing of total energy in the exit channel between electron and photon, b) deep recoil regime where the bandwidth/energy spread of the two interacting beams are exchanged in the exit channel, 2) electron is stopped, i.e. taken down at rest in the laboratory system by colliding with an incident photon of $mc^2/2$ energy, c) electron back-scattering region, where incident electron is back-scattered by the incident photon, 3) symmetric scattering, when the incident particles carry equal and opposite momenta, so that in the exit channel they are back-scattered with same energy/momenta, d) Compton scattering ($a'$ $la$ Arthur Compton, see ref.4), where photons carry an energy much larger than the colliding electron energy. For each region and/or transition point we discuss the potential effects of interest in diverse areas, like generating mono-chromatic gamma ray beams in deep recoil regions with spectral purification, or possible mechanisms of generation and propagation of very high energy photons in the cosmological domain.
Published: 2024

13. Loss-based prior for tree topologies in BART models

Author: Serafini, F., Leisen, F., Villa, C., and Wilson, K.
Subjects: Statistics - Methodology, Statistics - Applications
Abstract: We present a novel prior for tree topology within Bayesian Additive Regression Trees (BART) models. This approach quantifies the hypothetical loss in information and the loss due to complexity associated with choosing the wrong tree structure. The resulting prior distribution is compellingly geared toward sparsity, a critical feature considering BART models' tendency to overfit. Our method incorporates prior knowledge into the distribution via two parameters that govern the tree's depth and balance between its left and right branches. Additionally, we propose a default calibration for these parameters, offering an objective version of the prior. We demonstrate our method's efficacy on both simulated and real datasets.
Published: 2024

14. Detection of subclinical atherosclerosis by image-based deep learning on chest x-ray

Author: Gallone, Guglielmo, Iodice, Francesco, Presta, Alberto, Tore, Davide, de Filippo, Ovidio, Visciano, Michele, Barbano, Carlo Alberto, Serafini, Alessandro, Gorrini, Paola, Bruno, Alessandro, Marra, Walter Grosso, Hughes, James, Iannaccone, Mario, Fonio, Paolo, Fiandrotti, Attilio, Depaoli, Alessandro, Grangetto, Marco, de Ferrari, Gaetano Maria, and D'Ascenzo, Fabrizio
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract: Aims. To develop a deep-learning based system for recognition of subclinical atherosclerosis on a plain frontal chest x-ray. Methods and Results. A deep-learning algorithm to predict coronary artery calcium (CAC) score (the AI-CAC model) was developed on 460 chest x-ray (80% training cohort, 20% internal validation cohort) of primary prevention patients (58.4% male, median age 63 [51-74] years) with available paired chest x-ray and chest computed tomography (CT) indicated for any clinical reason and performed within 3 months. The CAC score calculated on chest CT was used as ground truth. The model was validated on an temporally-independent cohort of 90 patients from the same institution (external validation). The diagnostic accuracy of the AI-CAC model assessed by the area under the curve (AUC) was the primary outcome. Overall, median AI-CAC score was 35 (0-388) and 28.9% patients had no AI-CAC. AUC of the AI-CAC model to identify a CAC>0 was 0.90 in the internal validation cohort and 0.77 in the external validation cohort. Sensitivity was consistently above 92% in both cohorts. In the overall cohort (n=540), among patients with AI-CAC=0, a single ASCVD event occurred, after 4.3 years. Patients with AI-CAC>0 had significantly higher Kaplan Meier estimates for ASCVD events (13.5% vs. 3.4%, log-rank=0.013). Conclusion. The AI-CAC model seems to accurately detect subclinical atherosclerosis on chest x-ray with elevated sensitivity, and to predict ASCVD events with elevated negative predictive value. Adoption of the AI-CAC model to refine CV risk stratification or as an opportunistic screening tool requires prospective evaluation., Comment: Submitted to European Heart Journal - Cardiovascular Imaging Added also the additional material 44 pages (30 main paper, 14 additional material), 14 figures (5 main manuscript, 9 additional material)
Published: 2024

15. GraphMini: Accelerating Graph Pattern Matching Using Auxiliary Graphs

Author: Liu, Juelin, Polisetty, Sandeep, Guan, Hui, and Serafini, Marco
Subjects: Computer Science - Databases, Computer Science - Performance
Abstract: Graph pattern matching is a fundamental problem encountered by many common graph mining tasks and the basic building block of several graph mining systems. This paper explores for the first time how to proactively prune graphs to speed up graph pattern matching by leveraging the structure of the query pattern and the input graph. We propose building auxiliary graphs, which are different pruned versions of the graph, during query execution. This requires careful balancing between the upfront cost of building and managing auxiliary graphs and the gains of faster set operations. To this end, we propose GraphMini, a new system that uses query compilation and a new cost model to minimize the cost of building and maintaining auxiliary graphs and maximize gains. Our evaluation shows that using GraphMini can achieve one order of magnitude speedup compared to state-of-the-art subgraph enumeration systems on commonly used benchmarks.
Published: 2024
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16. Simple and Effective Transfer Learning for Neuro-Symbolic Integration

Author: Daniele, Alessandro, Campari, Tommaso, Malhotra, Sagar, and Serafini, Luciano
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: Deep Learning (DL) techniques have achieved remarkable successes in recent years. However, their ability to generalize and execute reasoning tasks remains a challenge. A potential solution to this issue is Neuro-Symbolic Integration (NeSy), where neural approaches are combined with symbolic reasoning. Most of these methods exploit a neural network to map perceptions to symbols and a logical reasoner to predict the output of the downstream task. These methods exhibit superior generalization capacity compared to fully neural architectures. However, they suffer from several issues, including slow convergence, learning difficulties with complex perception tasks, and convergence to local minima. This paper proposes a simple yet effective method to ameliorate these problems. The key idea involves pretraining a neural model on the downstream task. Then, a NeSy model is trained on the same task via transfer learning, where the weights of the perceptual part are injected from the pretrained network. The key observation of our work is that the neural network fails to generalize only at the level of the symbolic part while being perfectly capable of learning the mapping from perceptions to symbols. We have tested our training strategy on various SOTA NeSy methods and datasets, demonstrating consistent improvements in the aforementioned problems., Comment: Accepted as full paper at the International Conference on Neural-Symbolic Learning and Reasoning (NeSy 2024)
Published: 2024

17. Entanglement Entropy in Scalar Quantum Electrodynamics

Author: Fedida, Samuel, Mazumdar, Anupam, Bose, Sougato, and Serafini, Alessio
Subjects: High Energy Physics - Theory, High Energy Physics - Phenomenology, Quantum Physics
Abstract: We find the entanglement entropy of a subregion of the vacuum state in scalar quantum electrodynamics, working perturbatively to the 2-loops level. Doing so leads us to derive the Maxwell-Proca propagator in conical Euclidean space. The area law of entanglement entropy is recovered in both the massive and massless limits of the theory, as is expected. These results yield the renormalisation group flow of entanglement entropy, and we find that loop contributions suppress entanglement entropy. We highlight these results in the light of the renormalization group flow of couplings and correlators, which are increased in scalar quantum electrodynamics, so that the potential tension between the increase in correlations between two points of spacetime and the decrease in entanglement entropy between two regions of spacetime with energy is discussed. We indeed show that the vacuum of a subregion of spacetime purifies with energy in scalar quantum electrodynamics, which is related to the concept of screening., Comment: 10 pages, 1 figure
Published: 2024
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18. A GPU-Accelerated Modern Fortran Version of the ECHO Code for Relativistic Magnetohydrodynamics

Author: Del Zanna, Luca, Landi, Simone, Serafini, Lorenzo, Bugli, Matteo, and Papini, Emanuele
Subjects: Astrophysics - High Energy Astrophysical Phenomena, Physics - Computational Physics, Physics - Fluid Dynamics, Physics - Plasma Physics
Abstract: The numerical study of relativistic magnetohydrodynamics (MHD) plays a crucial role in high-energy astrophysics, but unfortunately is computationally demanding, given the complex physics involved (high Lorentz factor flows, extreme magnetization, curved spacetimes near compact objects) and the large variety of spatial scales needed to resolve turbulent motions. A great benefit comes from the porting of existing codes running on standard processors to GPU-based platforms. However, this usually requires a drastic rewriting of the original code, the use of specific languages like CUDA, and a complex analysis of data management and optimization of parallel processes. Here we describe the porting of the ECHO code for special and general relativistic MHD to accelerated devices, simply based on native Fortran language built-in constructs, especially 'do concurrent' loops, few OpenACC directives, and the straightforward data management provided by the Unified Memory option of NVIDIA compilers.Thanks to these very minor modifications to the original code, the new version of ECHO runs at least 16 times faster on GPU platforms compared to CPU-based ones. The chosen benchmark is the 3D propagation of a relativistic MHD Alfv\'en wave, for which strong and weak scaling tests performed on the LEONARDO pre-exascale supercomputer at CINECA are provided (using up to 256 nodes corresponding to 1024 GPUs, and over 14 billion cells). Finally, an example of high-resolution relativistic MHD Alfv\'enic turbulence simulation is shown, demonstrating the potential for astrophysical plasmas of the new GPU-based version of ECHO., Comment: Accepted for publication on Fluids, MDPI, 17 pages
Published: 2024

19. Enhancing Computation Pushdown for Cloud OLAP Databases

Author: Yang, Yifei, Yu, Xiangyao, Serafini, Marco, Aboulnaga, Ashraf, and Stonebraker, Michael
Subjects: Computer Science - Databases
Abstract: Network is a major bottleneck in modern cloud databases that adopt a storage-disaggregation architecture. Computation pushdown is a promising solution to tackle this issue, which offloads some computation tasks to the storage layer to reduce network traffic. Existing cloud OLAP systems statically decide whether to push down computation during the query optimization phase and do not consider the storage layer's computational capacity and load. Besides, there is a lack of a general principle that determines which operators are amenable for pushdown. Existing systems design and implement pushdown features empirically, which ends up picking a limited set of pushdown operators respectively. In this paper, we first design Adaptive pushdown as a new mechanism to avoid throttling the storage-layer computation during pushdown, which pushes the request back to the computation layer at runtime if the storage-layer computational resource is insufficient. Moreover, we derive a general principle to identify pushdown-amenable computational tasks, by summarizing common patterns of pushdown capabilities in existing systems. We propose two new pushdown operators, namely, selection bitmap and distributed data shuffle. Evaluation results on TPC-H show that Adaptive pushdown can achieve up to 1.9x speedup over both No pushdown and Eager pushdown baselines, and the new pushdown operators can further accelerate query execution by up to 3.0x., Comment: 13 pages, 15 figures
Published: 2023

20. Large Spin Stern-Gerlach Interferometry for Gravitational Entanglement

Author: Braccini, Lorenzo, Schut, Martine, Serafini, Alessio, Mazumdar, Anupam, and Bose, Sougato
Subjects: Quantum Physics, General Relativity and Quantum Cosmology
Abstract: Recently, there has been a proposal to test the quantum nature of gravity in the laboratory by witnessing the growth of entanglement between two masses in spatial quantum superpositions. The required superpositions can be created via Stern-Gerlach interferometers, which couple an embedded spin qubit quantum state to the spatial dynamics of each mass. The masses would entangle only if gravity is quantum in nature. Here, we generalise the experiment to an arbitrary spin $j$ or equivalently to an ensemble of uniformly coupled spins. We first exemplify how to create a generalized Stern-Gerlach interferometer, which splits the mass into $2j+1$ trajectories. This shows that a controlled protocol can be formulated to encode the amplitudes of any spin state to a spatial superposition. Secondly, two masses in spatial superpositions of the above form are left to interact via gravity, and the entanglement is computed. Different families of initial spin states are varied to find the optimal spin state that maximizes the entanglement. We conclude that larger spins can offer a modest advantage in enhancing gravity-induced entanglement., Comment: 12+7 pages, 10 figures. Comments are welcome
Published: 2023

21. Analysis of reactor burnup simulation uncertainties for antineutrino spectrum prediction

Author: Barresi, A., Borghesi, M., Cammi, A., Chiesa, D., Loi, L., Nastasi, M., Previtali, E., Sisti, M., Aiello, S., Andronico, G., Antonelli, V., Basilico, D., Beretta, M., Bergnoli, A., Brigatti, A., Brugnera, R., Bruno, R., Budano, A., Caccianiga, B., Cerrone, V., Caruso, R., Clementi, C., Dusini, S., Fabbri, A., Felici, G., Ferraro, F., Garfagnini, A., Giammarchi, M. G., Giugice, N., Gavrikov, A., Grassi, M., Guizzetti, R. M., Guardone, N., Jelmini, B., Landini, C., Lippi, I., Loffredo, S., Lombardi, P., Lombardo, C., Mantovani, F., Mari, S. M., Martini, A., Miramonti, L., Montuschi, M., Orestano, D., Ortica, F., Paoloni, A., Percalli, E., Petrucci, F., Ranucci, G., Re, A. C., Redchuck, M., Ricci, B., Romani, A., Saggese, P., Sava, G., Serafini, A., Sirignano, C., Stanco, L., Farilla, E. Stanescu, Strati, V., Torri, M. D. C., Triossi, A., Tuvè, C., Venettacci, C., Verde, G., and Votano, L.
Subjects: Physics - Instrumentation and Detectors
Abstract: Nuclear reactors are a source of electron antineutrinos due to the presence of unstable fission products that undergo $\beta^-$ decay. They will be exploited by the JUNO experiment to determine the neutrino mass ordering and to get very precise measurements of the neutrino oscillation parameters. This requires the reactor antineutrino spectrum to be characterized as precisely as possible both through high resolution measurements, as foreseen by the TAO experiment, and detailed simulation models. In this paper we present a benchmark analysis utilizing Serpent Monte Carlo simulations in comparison with real pressurized water reactor spent fuel data. Our objective is to study the accuracy of fission fraction predictions as a function of different reactor simulation approximations. Then, utilizing the BetaShape software, we construct fissile antineutrino spectra using the summation method, thereby assessing the influence of simulation uncertainties on reactor antineutrino spectrum.
Published: 2023

22. Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Author: Abusleme, Angel, Adam, Thomas, Ahmad, Shakeel, Ahmed, Rizwan, Aiello, Sebastiano, Akram, Muhammad, Aleem, Abid, An, Fengpeng, An, Qi, Andronico, Giuseppe, Anfimov, Nikolay, Antonelli, Vito, Antoshkina, Tatiana, Asavapibhop, Burin, de André, João Pedro Athayde Marcondes, Auguste, Didier, Bai, Weidong, Balashov, Nikita, Baldini, Wander, Barresi, Andrea, Basilico, Davide, Baussan, Eric, Bellato, Marco, Beretta, Marco, Bergnoli, Antonio, Bick, Daniel, Bieger, Lukas, Biktemerova, Svetlana, Birkenfeld, Thilo, Morton-Blake, Iwan, Blum, David, Blyth, Simon, Bolshakova, Anastasia, Bongrand, Mathieu, Bordereau, Clément, Breton, Dominique, Brigatti, Augusto, Brugnera, Riccardo, Bruno, Riccardo, Budano, Antonio, Busto, Jose, Cabrera, Anatael, Caccianiga, Barbara, Cai, Hao, Cai, Xiao, Cai, Yanke, Cai, Zhiyan, Callier, Stéphane, Cammi, Antonio, Campeny, Agustin, Cao, Chuanya, Cao, Guofu, Cao, Jun, Caruso, Rossella, Cerna, Cédric, Cerrone, Vanessa, Chan, Chi, Chang, Jinfan, Chang, Yun, Chatrabhuti, Auttakit, Chen, Chao, Chen, Guoming, Chen, Pingping, Chen, Shaomin, Chen, Yixue, Chen, Yu, Chen, Zhangming, Chen, Zhiyuan, Chen, Zikang, Cheng, Jie, Cheng, Yaping, Cheng, Yu Chin, Chepurnov, Alexander, Chetverikov, Alexey, Chiesa, Davide, Chimenti, Pietro, Chin, Yen-Ting, Chu, Ziliang, Chukanov, Artem, Claverie, Gérard, Clementi, Catia, Clerbaux, Barbara, Molla, Marta Colomer, Di Lorenzo, Selma Conforti, Coppi, Alberto, Corti, Daniele, Csakli, Simon, Corso, Flavio Dal, Dalager, Olivia, Datta, Jaydeep, De La Taille, Christophe, Deng, Zhi, Deng, Ziyan, Ding, Xiaoyu, Ding, Xuefeng, Ding, Yayun, Dirgantara, Bayu, Dittrich, Carsten, Dmitrievsky, Sergey, Dohnal, Tadeas, Dolzhikov, Dmitry, Donchenko, Georgy, Dong, Jianmeng, Doroshkevich, Evgeny, Dou, Wei, Dracos, Marcos, Druillole, Frédéric, Du, Ran, Du, Shuxian, Dugas, Katherine, Dusini, Stefano, Duyang, Hongyue, Eck, Jessica, Enqvist, Timo, Fabbri, Andrea, Fahrendholz, Ulrike, Fan, Lei, Fang, Jian, Fang, Wenxing, Fargetta, Marco, Fedoseev, Dmitry, Fei, Zhengyong, Feng, Li-Cheng, Feng, Qichun, Ferraro, Federico, Fournier, Amélie, Gan, Haonan, Gao, Feng, Garfagnini, Alberto, Gavrikov, Arsenii, Giammarchi, Marco, Giudice, Nunzio, Gonchar, Maxim, Gong, Guanghua, Gong, Hui, Gornushkin, Yuri, Göttel, Alexandre, Grassi, Marco, Gromov, Maxim, Gromov, Vasily, Gu, Minghao, Gu, Xiaofei, Gu, Yu, Guan, Mengyun, Guan, Yuduo, Guardone, Nunzio, Guo, Cong, Guo, Wanlei, Guo, Xinheng, Hagner, Caren, Han, Ran, Han, Yang, He, Miao, He, Wei, Heinz, Tobias, Hellmuth, Patrick, Heng, Yuekun, Herrera, Rafael, Hor, YuenKeung, Hou, Shaojing, Hsiung, Yee, Hu, Bei-Zhen, Hu, Hang, Hu, Jianrun, Hu, Jun, Hu, Shouyang, Hu, Tao, Hu, Yuxiang, Hu, Zhuojun, Huang, Guihong, Huang, Hanxiong, Huang, Jinhao, Huang, Junting, Huang, Kaixuan, Huang, Wenhao, Huang, Xin, Huang, Xingtao, Huang, Yongbo, Hui, Jiaqi, Huo, Lei, Huo, Wenju, Huss, Cédric, Hussain, Safeer, Imbert, Leonard, Ioannisian, Ara, Isocrate, Roberto, Jafar, Arshak, Jelmini, Beatrice, Jeria, Ignacio, Ji, Xiaolu, Jia, Huihui, Jia, Junji, Jian, Siyu, Jiang, Cailian, Jiang, Di, Jiang, Wei, Jiang, Xiaoshan, Jing, Xiaoping, Jollet, Cécile, Kampmann, Philipp, Kang, Li, Karaparambil, Rebin, Kazarian, Narine, Khan, Ali, Khatun, Amina, Khosonthongkee, Khanchai, Korablev, Denis, Kouzakov, Konstantin, Krasnoperov, Alexey, Kuleshov, Sergey, Kutovskiy, Nikolay, Labit, Loïc, Lachenmaier, Tobias, Landini, Cecilia, Leblanc, Sébastien, Lebrin, Victor, Lefevre, Frederic, Lei, Ruiting, Leitner, Rupert, Leung, Jason, Li, Demin, Li, Fei, Li, Fule, Li, Gaosong, Li, Huiling, Li, Jiajun, Li, Mengzhao, Li, Min, Li, Nan, Li, Qingjiang, Li, Ruhui, Li, Rui, Li, Shanfeng, Li, Tao, Li, Teng, Li, Weidong, Li, Weiguo, Li, Xiaomei, Li, Xiaonan, Li, Xinglong, Li, Yi, Li, Yichen, Li, Yufeng, Li, Zhaohan, Li, Zhibing, Li, Ziyuan, Li, Zonghai, Liang, Hao, Liao, Jiajun, Limphirat, Ayut, Lin, Guey-Lin, Lin, Shengxin, Lin, Tao, Ling, Jiajie, Ling, Xin, Lippi, Ivano, Liu, Caimei, Liu, Fang, Liu, Fengcheng, Liu, Haidong, Liu, Haotian, Liu, Hongbang, Liu, Hongjuan, Liu, Hongtao, Liu, Hui, Liu, Jianglai, Liu, Jiaxi, Liu, Jinchang, Liu, Min, Liu, Qian, Liu, Qin, Liu, Runxuan, Liu, Shenghui, Liu, Shubin, Liu, Shulin, Liu, Xiaowei, Liu, Xiwen, Liu, Xuewei, Liu, Yankai, Liu, Zhen, Lokhov, Alexey, Lombardi, Paolo, Lombardo, Claudio, Loo, Kai, Lu, Chuan, Lu, Haoqi, Lu, Jingbin, Lu, Junguang, Lu, Peizhi, Lu, Shuxiang, Lu, Xianguo, Lubsandorzhiev, Bayarto, Lubsandorzhiev, Sultim, Ludhova, Livia, Lukanov, Arslan, Luo, Daibin, Luo, Fengjiao, Luo, Guang, Luo, Jianyi, Luo, Shu, Luo, Wuming, Luo, Xiaojie, Lyashuk, Vladimir, Ma, Bangzheng, Ma, Bing, Ma, Qiumei, Ma, Si, Ma, Xiaoyan, Ma, Xubo, Maalmi, Jihane, Magoni, Marco, Mai, Jingyu, Malyshkin, Yury, Mandujano, Roberto Carlos, Mantovani, Fabio, Mao, Xin, Mao, Yajun, Mari, Stefano M., Marini, Filippo, Martini, Agnese, Mayer, Matthias, Mayilyan, Davit, Mednieks, Ints, Meng, Yue, Meraviglia, Anita, Meregaglia, Anselmo, Meroni, Emanuela, Meyhöfer, David, Miramonti, Lino, Mohan, Nikhil, Montuschi, Michele, Müller, Axel, Nastasi, Massimiliano, Naumov, Dmitry V., Naumova, Elena, Navas-Nicolas, Diana, Nemchenok, Igor, Thi, Minh Thuan Nguyen, Nikolaev, Alexey, Ning, Feipeng, Ning, Zhe, Nunokawa, Hiroshi, Oberauer, Lothar, Ochoa-Ricoux, Juan Pedro, Olshevskiy, Alexander, Orestano, Domizia, Ortica, Fausto, Othegraven, Rainer, Paoloni, Alessandro, Parmeggiano, Sergio, Pei, Yatian, Pelicci, Luca, Peng, Anguo, Peng, Haiping, Peng, Yu, Peng, Zhaoyuan, Perrot, Frédéric, Petitjean, Pierre-Alexandre, Petrucci, Fabrizio, Pilarczyk, Oliver, Rico, Luis Felipe Piñeres, Popov, Artyom, Poussot, Pascal, Previtali, Ezio, Qi, Fazhi, Qi, Ming, Qi, Xiaohui, Qian, Sen, Qian, Xiaohui, Qian, Zhen, Qiao, Hao, Qin, Zhonghua, Qiu, Shoukang, Qu, Manhao, Qu, Zhenning, Ranucci, Gioacchino, Rasheed, Reem, Re, Alessandra, Rebii, Abdel, Redchuk, Mariia, Ren, Bin, Ren, Jie, Ricci, Barbara, Rientong, Komkrit, Rifai, Mariam, Roche, Mathieu, Rodphai, Narongkiat, Romani, Aldo, Roskovec, Bedřich, Ruan, Xichao, Rybnikov, Arseniy, Sadovsky, Andrey, Saggese, Paolo, Sandanayake, Deshan, Sangka, Anut, Sava, Giuseppe, Sawangwit, Utane, Schever, Michaela, Schwab, Cédric, Schweizer, Konstantin, Selyunin, Alexandr, Serafini, Andrea, Settimo, Mariangela, Sharov, Vladislav, Shaydurova, Arina, Shi, Jingyan, Shi, Yanan, Shutov, Vitaly, Sidorenkov, Andrey, Šimkovic, Fedor, Singhal, Apeksha, Sirignano, Chiara, Siripak, Jaruchit, Sisti, Monica, Smirnov, Mikhail, Smirnov, Oleg, Sogo-Bezerra, Thiago, Sokolov, Sergey, Songwadhana, Julanan, Soonthornthum, Boonrucksar, Sotnikov, Albert, Šrámek, Ondřej, Sreethawong, Warintorn, Stahl, Achim, Stanco, Luca, Stankevich, Konstantin, Steiger, Hans, Steinmann, Jochen, Sterr, Tobias, Stock, Matthias Raphael, Strati, Virginia, Studenikin, Alexander, Su, Aoqi, Su, Jun, Sun, Shifeng, Sun, Xilei, Sun, Yongjie, Sun, Yongzhao, Sun, Zhengyang, Suwonjandee, Narumon, Szelezniak, Michal, Takenaka, Akira, Tang, Jian, Tang, Qiang, Tang, Quan, Tang, Xiao, Hariharan, Vidhya Thara, Theisen, Eric, Tietzsch, Alexander, Tkachev, Igor, Tmej, Tomas, Torri, Marco Danilo Claudio, Tortorici, Francesco, Treskov, Konstantin, Triossi, Andrea, Triozzi, Riccardo, Trzaska, Wladyslaw, Tung, Yu-Chen, Tuve, Cristina, Ushakov, Nikita, Vedin, Vadim, Venettacci, Carlo, Verde, Giuseppe, Vialkov, Maxim, Viaud, Benoit, Vollbrecht, Cornelius Moritz, von Sturm, Katharina, Vorobel, Vit, Voronin, Dmitriy, Votano, Lucia, Walker, Pablo, Wang, Caishen, Wang, Chung-Hsiang, Wang, En, Wang, Guoli, Wang, Jian, Wang, Jun, Wang, Li, Wang, Lu, Wang, Meng, Wang, Ruiguang, Wang, Siguang, Wang, Wei, Wang, Wenshuai, Wang, Xi, Wang, Xiangyue, Wang, Yangfu, Wang, Yaoguang, Wang, Yi, Wang, Yifang, Wang, Yuanqing, Wang, Yuyi, Wang, Zhe, Wang, Zheng, Wang, Zhimin, Watcharangkool, Apimook, Wei, Wei, Wei, Wenlu, Wei, Yadong, Wei, Yuehuan, Wen, Kaile, Wen, Liangjian, Weng, Jun, Wiebusch, Christopher, Wirth, Rosmarie, Wonsak, Bjoern, Wu, Diru, Wu, Qun, Wu, Yiyang, Wu, Zhi, Wurm, Michael, Wurtz, Jacques, Wysotzki, Christian, Xi, Yufei, Xia, Dongmei, Xiao, Fei, Xiao, Xiang, Xie, Xiaochuan, Xie, Yuguang, Xie, Zhangquan, Xin, Zhao, Xing, Zhizhong, Xu, Benda, Xu, Cheng, Xu, Donglian, Xu, Fanrong, Xu, Hangkun, Xu, Jilei, Xu, Jing, Xu, Meihang, Xu, Xunjie, Xu, Yin, Xu, Yu, Yan, Baojun, Yan, Qiyu, Yan, Taylor, Yan, Xiongbo, Yan, Yupeng, Yang, Changgen, Yang, Chengfeng, Yang, Jie, Yang, Lei, Yang, Xiaoyu, Yang, Yifan, Yao, Haifeng, Ye, Jiaxuan, Ye, Mei, Ye, Ziping, Yermia, Frédéric, You, Zhengyun, Yu, Boxiang, Yu, Chiye, Yu, Chunxu, Yu, Guojun, Yu, Hongzhao, Yu, Miao, Yu, Xianghui, Yu, Zeyuan, Yu, Zezhong, Yuan, Cenxi, Yuan, Chengzhuo, Yuan, Ying, Yuan, Zhenxiong, Yue, Baobiao, Zafar, Noman, Zavadskyi, Vitalii, Zeng, Fanrui, Zeng, Shan, Zeng, Tingxuan, Zeng, Yuda, Zhan, Liang, Zhang, Aiqiang, Zhang, Bin, Zhang, Binting, Zhang, Feiyang, Zhang, Haosen, Zhang, Honghao, Zhang, Jialiang, Zhang, Jiawen, Zhang, Jie, Zhang, Jingbo, Zhang, Jinnan, ZHANG, Lei, Zhang, Mohan, Zhang, Peng, Zhang, Ping, Zhang, Qingmin, Zhang, Shiqi, Zhang, Shu, Zhang, Shuihan, Zhang, Siyuan, Zhang, Tao, Zhang, Xiaomei, Zhang, Xin, Zhang, Xuantong, Zhang, Yinhong, Zhang, Yiyu, Zhang, Yongpeng, Zhang, Yu, Zhang, Yuanyuan, Zhang, Yumei, Zhang, Zhenyu, Zhang, Zhijian, Zhao, Jie, Zhao, Rong, Zhao, Runze, Zhao, Shujun, Zheng, Dongqin, Zheng, Hua, Zheng, Yangheng, Zhong, Weirong, Zhou, Jing, Zhou, Li, Zhou, Nan, Zhou, Shun, Zhou, Tong, Zhou, Xiang, Zhu, Jingsen, Zhu, Kangfu, Zhu, Kejun, Zhu, Zhihang, Zhuang, Bo, Zhuang, Honglin, Zong, Liang, Zou, Jiaheng, and Züfle, Jan
Subjects: High Energy Physics - Experiment, Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Phenomenology
Abstract: The core-collapse supernova (CCSN) is considered one of the most energetic astrophysical events in the universe. The early and prompt detection of neutrinos before (pre-SN) and during the supernova (SN) burst presents a unique opportunity for multi-messenger observations of CCSN events. In this study, we describe the monitoring concept and present the sensitivity of the system to pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton liquid scintillator detector currently under construction in South China. The real-time monitoring system is designed to ensure both prompt alert speed and comprehensive coverage of progenitor stars. It incorporates prompt monitors on the electronic board as well as online monitors at the data acquisition stage. Assuming a false alert rate of 1 per year, this monitoring system exhibits sensitivity to pre-SN neutrinos up to a distance of approximately 1.6 (0.9) kiloparsecs and SN neutrinos up to about 370 (360) kiloparsecs for a progenitor mass of 30 solar masses, considering both normal and inverted mass ordering scenarios. The pointing ability of the CCSN is evaluated by analyzing the accumulated event anisotropy of inverse beta decay interactions from pre-SN or SN neutrinos. This, along with the early alert, can play a crucial role in facilitating follow-up multi-messenger observations of the next galactic or nearby extragalactic CCSN., Comment: 24 pages, 9 figures, accepted for the publication at JCAP
Published: 2023

23. A note on typicality in random quantum scattering

Author: Avalle, Michele and Serafini, Alessio
Subjects: Quantum Physics, Condensed Matter - Statistical Mechanics
Abstract: We consider scattering processes where a quantum system is comprised of an inner subsystem and of a boundary, and is subject to Haar-averaged random unitaries acting on the boundary-environment Hilbert space only. We show that, regardless of the initial state, a single scattering event will disentangle the unconditional state (i.e., the scattered state when no information about the applied unitary is available) across the inner subsystem-boundary partition. Also, we apply Levy's lemma to constrain the trace norm fluctuations around the unconditional state. Finally, we derive analytical formulae for the mean scattered purity for initial globally pure states, and provide one with numerical evidence of the reduction of fluctuations around such mean values with increasing environmental dimension., Comment: 12 pages (5 pages of main text + 7 pages of appendices)
Published: 2023

24. Lifted Inference beyond First-Order Logic

Author: Malhotra, Sagar, Bizzaro, Davide, and Serafini, Luciano
Subjects: Computer Science - Artificial Intelligence, Computer Science - Logic in Computer Science, Mathematics - Combinatorics
Abstract: Weighted First Order Model Counting (WFOMC) is fundamental to probabilistic inference in statistical relational learning models. As WFOMC is known to be intractable in general ($\#$P-complete), logical fragments that admit polynomial time WFOMC are of significant interest. Such fragments are called domain liftable. Recent works have shown that the two-variable fragment of first order logic extended with counting quantifiers ($\mathrm{C^2}$) is domain-liftable. However, many properties of real-world data, like acyclicity in citation networks and connectivity in social networks, cannot be modeled in $\mathrm{C^2}$, or first order logic in general. In this work, we expand the domain liftability of $\mathrm{C^2}$ with multiple such properties. We show that any $\mathrm{C^2}$ sentence remains domain liftable when one of its relations is restricted to represent a directed acyclic graph, a connected graph, a tree (resp. a directed tree) or a forest (resp. a directed forest). All our results rely on a novel and general methodology of "counting by splitting". Besides their application to probabilistic inference, our results provide a general framework for counting combinatorial structures. We expand a vast array of previous results in discrete mathematics literature on directed acyclic graphs, phylogenetic networks, etc., Comment: Under Review at the Artificial Intelligence Journal. arXiv admin note: text overlap with arXiv:2302.09830
Published: 2023

25. Probing Earth's Missing Potassium using the Unique Antimatter Signature of Geoneutrinos

Author: Consortium, LiquidO, Cabrera, A., Chen, M., Mantovani, F., Serafini, A., Strati, V., Apilluelo, J., Asquith, L., Beney, J. L., Bezerra, T. J. C., Bongrand, M., Bourgeois, C., Breton, D., Briere, M., Busto, J., Cadiou, A., Calvo, E., Chaumat, V., Chauveau, E., Cattermole, B. J., Chimenti, P., Delafosse, C., de Kerret, H., Dusini, S., Earle, A., Frigerio-Martins, C., Galán, J., García, J. A., Gazzini, R., Gibson-Foster, A., Gallas, A., Girard-Carillo, C., Griffith, W. C., Haddad, F., Hartnell, J., Hourlier, A., Hull, G., Irastorza, I. G., Koch, L., Laniéce, P., Du, J. F. Le, Lefebvre, C., Lefevre, F., Legrand, F., Loaiza, P., Lock, J. A., Luzón, G., Maalmi, J., Marquet, C., Martínez, M., Mathon, B., Ménard, L., Navas-Nicolás, D., Nunokawa, H., Ochoa-Ricoux, J. P., Obolensky, M., Palomares, C., Pillot, P., Porter, J. C. C., Pravikoff, M. S., Ramarijaona, H., Roche, M., Rosier, P., Roskovec, B., Sarsa, M. L., Schoppmann, S., Shorrock, W., Simard, L., Steiger, H. Th. J., Stocco, D., Stutzmann, J. S., Suekane, F., Tunc, A., Verdier, M. -A., Verdugo, A., Viaud, B., Wakely, S. M., Weber, A., and Yermia, F.
Subjects: Physics - Geophysics, High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract: The formation of the Earth remains an epoch with mysterious puzzles extending to our still incomplete understanding of the planet's potential origin and bulk composition. Direct confirmation of the Earth's internal heat engine was accomplished by the successful observation of geoneutrinos originating from uranium (U) and thorium (Th) progenies, manifestations of the planet's natural radioactivity dominated by potassium (40K) and the decay chains of uranium (238U) and thorium (232Th). This radiogenic energy output is critical to planetary dynamics and must be accurately measured for a complete understanding of the overall heat budget and thermal history of the Earth. Detecting geoneutrinos remains the only direct probe to do so and constitutes a challenging objective in modern neutrino physics. In particular, the intriguing potassium geoneutrinos have never been observed and thus far have been considered impractical to measure. We propose here a novel approach for potassium geoneutrino detection using the unique antimatter signature of antineutrinos to reduce the otherwise overwhelming backgrounds to observing this rarest signal. The proposed detection framework relies on the innovative LiquidO detection technique to enable positron (e+) identification and antineutrino interactions with ideal isotope targets identified here for the first time. We also provide the complete experimental methodology to yield the first potassium geoneutrino discovery.
Published: 2023

26. An enhanced system for the detection and active cancellation of snoring signals

Author: Bruschi, Valeria, Cantarini, Michela, Serafini, Luca, Nobili, Stefano, Cecchi, Stefania, and Squartini, Stefano
Subjects: Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract: Snoring is a common disorder that affects people's social and marital lives. The annoyance caused by snoring can be partially solved with active noise control systems. In this context, the present work aims at introducing an enhanced system based on the use of a convolutional recurrent neural network for snoring activity detection and a delayless subband approach for active snoring cancellation. Thanks to several experiments conducted using real snoring signals, this work shows that the active snoring cancellation system achieves better performance when the snoring activity detection stage is turned on, demonstrating the beneficial effect of a preliminary snoring detection stage in the perspective of snoring cancellation.
Published: 2023

27. A Time-Frequency Generative Adversarial based method for Audio Packet Loss Concealment

Author: Aironi, Carlo, Cornell, Samuele, Serafini, Luca, and Squartini, Stefano
Subjects: Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract: Packet loss is a major cause of voice quality degradation in VoIP transmissions with serious impact on intelligibility and user experience. This paper describes a system based on a generative adversarial approach, which aims to repair the lost fragments during the transmission of audio streams. Inspired by the powerful image-to-image translation capability of Generative Adversarial Networks (GANs), we propose bin2bin, an improved pix2pix framework to achieve the translation task from magnitude spectrograms of audio frames with lost packets, to noncorrupted speech spectrograms. In order to better maintain the structural information after spectrogram translation, this paper introduces the combination of two STFT-based loss functions, mixed with the traditional GAN objective. Furthermore, we employ a modified PatchGAN structure as discriminator and we lower the concealment time by a proper initialization of the phase reconstruction algorithm. Experimental results show that the proposed method has obvious advantages when compared with the current state-of-the-art methods, as it can better handle both high packet loss rates and large gaps., Comment: Accepted at EUSIPCO - 31st European Signal Processing Conference, 2023
Published: 2023

28. Giant spin-charge conversion in ultrathin films of the MnPtSb half-Heusler compound

Author: Longo, E., Markou, A., Felser, C., Belli, M., Serafini, A., Targa, P., Codegoni, D., Fanciulli, M., and Mantovan, R.
Subjects: Condensed Matter - Materials Science
Abstract: Half-metallic half-Heusler compounds with strong spin-orbit-coupling and broken inversion symmetry in their crystal structure are promising materials for generating and absorbing spin-currents, thus enabling the electric manipulation of magnetization in energy-efficient spintronic devices. In this work, we report the spin-to-charge conversion in sputtered ultrathin films of the half-Heusler compound MnPtSb with thickness (t) in the range from 1 to 6 nm. A combination of X-ray and transmission electron microscopy measurements evidence the epitaxial nature of these ultrathin non-centrosymmetric MnPtSb films, with a clear (111)-orientation obtained on top of (0001) single-crystal sapphire substrates. The study of the thickness (t)-dependent magnetization dynamics of the MnPtSb(t)/Co(5nm)/Au(5nm) heterostructure revealed that the MnPtSb compound can be used as an efficient spin current generator, even at film thicknesses as low as 1 nm. By making use of spin pumping FMR, we measure a remarkable t-dependent spin-charge conversion in the MnPtSb layers, which clearly demonstrate the interfacial origin of the conversion. When interpreted as arising from the inverse Edelstein effect (IEE), the spin-charge conversion efficiency extracted at room temperature for the thinnest MnPtSb layer reaches {\lambda}IEE~3 nm, representing an extremely high spin-charge conversion efficiency at room temperature. The still never explored ultrathin regime of the MnPtSb films studied in this work and the discover of their outstanding functionality are two ingredients which demonstrate the potentiality of such materials for future applications in spintronics., Comment: main text: 17 pages (with 4 figures), plus additional 8 pages of Supplementary Information
Published: 2023
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29. logLTN: Differentiable Fuzzy Logic in the Logarithm Space

Author: Badreddine, Samy, Serafini, Luciano, and Spranger, Michael
Subjects: Computer Science - Artificial Intelligence
Abstract: The AI community is increasingly focused on merging logic with deep learning to create Neuro-Symbolic (NeSy) paradigms and assist neural approaches with symbolic knowledge. A significant trend in the literature involves integrating axioms and facts in loss functions by grounding logical symbols with neural networks and operators with fuzzy semantics. Logic Tensor Networks (LTN) is one of the main representatives in this category, known for its simplicity, efficiency, and versatility. However, it has been previously shown that not all fuzzy operators perform equally when applied in a differentiable setting. Researchers have proposed several configurations of operators, trading off between effectiveness, numerical stability, and generalization to different formulas. This paper presents a configuration of fuzzy operators for grounding formulas end-to-end in the logarithm space. Our goal is to develop a configuration that is more effective than previous proposals, able to handle any formula, and numerically stable. To achieve this, we propose semantics that are best suited for the logarithm space and introduce novel simplifications and improvements that are crucial for optimization via gradient-descent. We use LTN as the framework for our experiments, but the conclusions of our work apply to any similar NeSy framework. Our findings, both formal and empirical, show that the proposed configuration outperforms the state-of-the-art and that each of our modifications is essential in achieving these results.
Published: 2023

30. JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo

Author: JUNO Collaboration, Abusleme, Angel, Adam, Thomas, Ahmad, Shakeel, Ahmed, Rizwan, Aiello, Sebastiano, Akram, Muhammad, Aleem, Abid, Alexandros, Tsagkarakis, An, Fengpeng, An, Qi, Andronico, Giuseppe, Anfimov, Nikolay, Antonelli, Vito, Antoshkina, Tatiana, Asavapibhop, Burin, de André, João Pedro Athayde Marcondes, Auguste, Didier, Bai, Weidong, Balashov, Nikita, Baldini, Wander, Barresi, Andrea, Basilico, Davide, Baussan, Eric, Bellato, Marco, Bergnoli, Antonio, Bick, Daniel, Birkenfeld, Thilo, Blin, Sylvie, Blum, David, Blyth, Simon, Bolshakova, Anastasia, Bongrand, Mathieu, Bordereau, Clément, Breton, Dominique, Brigatti, Augusto, Brugnera, Riccardo, Bruno, Riccardo, Budano, Antonio, Busto, Jose, Butorov, Ilya, Cabrera, Anatael, Caccianiga, Barbara, Cai, Hao, Cai, Xiao, Cai, Yanke, Cai, Zhiyan, Callegari, Riccardo, Cammi, Antonio, Campeny, Agustin, Cao, Chuanya, Cao, Guofu, Cao, Jun, Caruso, Rossella, Cerna, Cédric, Chan, Chi, Chang, Jinfan, Chang, Yun, Chen, Guoming, Chen, Pingping, Chen, Po-An, Chen, Shaomin, Chen, Yixue, Chen, Yu, Chen, Zhiyuan, Chen, Zikang, Cheng, Jie, Cheng, Yaping, Cheng, Yu Chin, Chepurnov, Alexander, Chetverikov, Alexey, Chiesa, Davide, Chimenti, Pietro, Chu, Ziliang, Chukanov, Artem, Claverie, Gérard, Clementi, Catia, Clerbaux, Barbara, Molla, Marta Colomer, Di Lorenzo, Selma Conforti, Corti, Daniele, Corso, Flavio Dal, Dalager, Olivia, De La Taille, Christophe, Deng, Zhi, Deng, Ziyan, Depnering, Wilfried, Diaz, Marco, Ding, Xuefeng, Ding, Yayun, Dirgantara, Bayu, Dmitrievsky, Sergey, Dohnal, Tadeas, Dolzhikov, Dmitry, Donchenko, Georgy, Dong, Jianmeng, Doroshkevich, Evgeny, Dou, Wei, Dracos, Marcos, Druillole, Frédéric, Du, Ran, Du, Shuxian, Dusini, Stefano, Dvorak, Martin, Eck, Jessica, Enqvist, Timo, Fabbri, Andrea, Fahrendholz, Ulrike, Fan, Donghua, Fan, Lei, Fang, Jian, Fang, Wenxing, Fargetta, Marco, Fedoseev, Dmitry, Fei, Zhengyong, Feng, Li-Cheng, Feng, Qichun, Ford, Richard, Fournier, Amélie, Gan, Haonan, Gao, Feng, Garfagnini, Alberto, Gavrikov, Arsenii, Giammarchi, Marco, Giudice, Nunzio, Gonchar, Maxim, Gong, Guanghua, Gong, Hui, Gornushkin, Yuri, Göttel, Alexandre, Grassi, Marco, Gromov, Maxim, Gromov, Vasily, Gu, Minghao, Gu, Xiaofei, Gu, Yu, Guan, Mengyun, Guan, Yuduo, Guardone, Nunzio, Guo, Cong, Guo, Wanlei, Guo, Xinheng, Guo, Yuhang, Hagner, Caren, Han, Ran, Han, Yang, He, Miao, He, Wei, Heinz, Tobias, Hellmuth, Patrick, Heng, Yuekun, Herrera, Rafael, Hor, YuenKeung, Hou, Shaojing, Hsiung, Yee, Hu, Bei-Zhen, Hu, Hang, Hu, Jianrun, Hu, Jun, Hu, Shouyang, Hu, Tao, Hu, Yuxiang, Hu, Zhuojun, Huang, Guihong, Huang, Hanxiong, Huang, Kaixuan, Huang, Wenhao, Huang, Xin, Huang, Xingtao, Huang, Yongbo, Hui, Jiaqi, Huo, Lei, Huo, Wenju, Huss, Cédric, Hussain, Safeer, Ioannisian, Ara, Isocrate, Roberto, Jelmini, Beatrice, Jeria, Ignacio, Ji, Xiaolu, Jia, Huihui, Jia, Junji, Jian, Siyu, Jiang, Di, Jiang, Wei, Jiang, Xiaoshan, Jing, Xiaoping, Jollet, Cécile, Kalousis, Leonidas, Kampmann, Philipp, Kang, Li, Karaparambil, Rebin, Kazarian, Narine, Khatun, Amina, Khosonthongkee, Khanchai, Korablev, Denis, Kouzakov, Konstantin, Krasnoperov, Alexey, Kutovskiy, Nikolay, Kuusiniemi, Pasi, Lachenmaier, Tobias, Landini, Cecilia, Leblanc, Sébastien, Lebrin, Victor, Lefevre, Frederic, Lei, Ruiting, Leitner, Rupert, Leung, Jason, Li, Daozheng, Li, Demin, Li, Fei, Li, Fule, Li, Gaosong, Li, Huiling, Li, Mengzhao, Li, Min, Li, Nan, Li, Qingjiang, Li, Ruhui, Li, Rui, Li, Shanfeng, Li, Tao, Li, Teng, Li, Weidong, Li, Weiguo, Li, Xiaomei, Li, Xiaonan, Li, Xinglong, Li, Yi, Li, Yichen, Li, Yufeng, Li, Zepeng, Li, Zhaohan, Li, Zhibing, Li, Ziyuan, Li, Zonghai, Liang, Hao, Liao, Jiajun, Limphirat, Ayut, Lin, Guey-Lin, Lin, Shengxin, Lin, Tao, Ling, Jiajie, Lippi, Ivano, Liu, Fang, Liu, Haidong, Liu, Haotian, Liu, Hongbang, Liu, Hongjuan, Liu, Hongtao, Liu, Hui, Liu, Jianglai, Liu, Jinchang, Liu, Min, Liu, Qian, Liu, Qin, Liu, Runxuan, Liu, Shubin, Liu, Shulin, Liu, Xiaowei, Liu, Xiwen, Liu, Yan, Liu, Yunzhe, Lokhov, Alexey, Lombardi, Paolo, Lombardo, Claudio, Loo, Kai, Lu, Chuan, Lu, Haoqi, Lu, Jingbin, Lu, Junguang, Lu, Peizhi, Lu, Shuxiang, Lubsandorzhiev, Bayarto, Lubsandorzhiev, Sultim, Ludhova, Livia, Lukanov, Arslan, Luo, Daibin, Luo, Fengjiao, Luo, Guang, Luo, Shu, Luo, Wuming, Luo, Xiaojie, Lyashuk, Vladimir, Ma, Bangzheng, Ma, Bing, Ma, Qiumei, Ma, Si, Ma, Xiaoyan, Ma, Xubo, Maalmi, Jihane, Mai, Jingyu, Malyshkin, Yury, Mandujano, Roberto Carlos, Mantovani, Fabio, Mao, Xin, Mao, Yajun, Mari, Stefano M., Marini, Filippo, Martin-Chassard, Gisele, Martini, Agnese, Mayer, Matthias, Mayilyan, Davit, Mednieks, Ints, Meinusch, Artur, Meng, Yue, Meregaglia, Anselmo, Meroni, Emanuela, Meyhöfer, David, Mezzetto, Mauro, Miller, Jonathan, Miramonti, Lino, Montini, Paolo, Montuschi, Michele, Müller, Axel, Nastasi, Massimiliano, Naumov, Dmitry V., Naumova, Elena, Navas-Nicolas, Diana, Nemchenok, Igor, Thi, Minh Thuan Nguyen, Nikolaev, Alexey, Ning, Feipeng, Ning, Zhe, Nunokawa, Hiroshi, Oberauer, Lothar, Ochoa-Ricoux, Juan Pedro, Olshevskiy, Alexander, Orestano, Domizia, Ortica, Fausto, Othegraven, Rainer, Paoloni, Alessandro, Parmeggiano, Sergio, Pei, Yatian, Pelicci, Luca, Peng, Anguo, Peng, Haiping, Peng, Yu, Peng, Zhaoyuan, Perrot, Frédéric, Petitjean, Pierre-Alexandre, Petrucci, Fabrizio, Pilarczyk, Oliver, Rico, Luis Felipe Piñeres, Popov, Artyom, Poussot, Pascal, Previtali, Ezio, Qi, Fazhi, Qi, Ming, Qian, Sen, Qian, Xiaohui, Qian, Zhen, Qiao, Hao, Qin, Zhonghua, Qiu, Shoukang, Ranucci, Gioacchino, Rasheed, Reem, Re, Alessandra, Rebber, Henning, Rebii, Abdel, Redchuk, Mariia, Ren, Bin, Ren, Jie, Ricci, Barbara, Rifai, Mariam, Roche, Mathieu, Rodphai, Narongkiat, Romani, Aldo, Roskovec, Bedřich, Ruan, Xichao, Rybnikov, Arseniy, Sadovsky, Andrey, Saggese, Paolo, Sanfilippo, Simone, Sangka, Anut, Sawangwit, Utane, Sawatzki, Julia, Schever, Michaela, Schwab, Cédric, Schweizer, Konstantin, Selyunin, Alexandr, Serafini, Andrea, Settanta, Giulio, Settimo, Mariangela, Shao, Zhuang, Sharov, Vladislav, Shaydurova, Arina, Shi, Jingyan, Shi, Yanan, Shutov, Vitaly, Sidorenkov, Andrey, Šimkovic, Fedor, Sirignano, Chiara, Siripak, Jaruchit, Sisti, Monica, Slupecki, Maciej, Smirnov, Mikhail, Smirnov, Oleg, Sogo-Bezerra, Thiago, Sokolov, Sergey, Songwadhana, Julanan, Soonthornthum, Boonrucksar, Sotnikov, Albert, Šrámek, Ondřej, Sreethawong, Warintorn, Stahl, Achim, Stanco, Luca, Stankevich, Konstantin, Štefánik, Dušan, Steiger, Hans, Steinmann, Jochen, Sterr, Tobias, Stock, Matthias Raphael, Strati, Virginia, Studenikin, Alexander, Su, Jun, Sun, Shifeng, Sun, Xilei, Sun, Yongjie, Sun, Yongzhao, Sun, Zhengyang, Suwonjandee, Narumon, Szelezniak, Michal, Tang, Jian, Tang, Qiang, Tang, Quan, Tang, Xiao, Hariharan, Vidhya Thara, Theisen, Eric, Tietzsch, Alexander, Tkachev, Igor, Tmej, Tomas, Torri, Marco Danilo Claudio, Treskov, Konstantin, Triossi, Andrea, Troni, Giancarlo, Trzaska, Wladyslaw, Tung, Yu-Chen, Tuve, Cristina, Ushakov, Nikita, Vedin, Vadim, Verde, Giuseppe, Vialkov, Maxim, Viaud, Benoit, Vollbrecht, Cornelius Moritz, Volpe, Cristina, von Sturm, Katharina, Vorobel, Vit, Voronin, Dmitriy, Votano, Lucia, Walker, Pablo, Wang, Caishen, Wang, Chung-Hsiang, Wang, En, Wang, Guoli, Wang, Jian, Wang, Jun, Wang, Lu, Wang, Meifen, Wang, Meng, Wang, Ruiguang, Wang, Siguang, Wang, Wei, Wang, Wenshuai, Wang, Xi, Wang, Xiangyue, Wang, Yangfu, Wang, Yaoguang, Wang, Yi, Wang, Yifang, Wang, Yuanqing, Wang, Yuman, Wang, Zhe, Wang, Zheng, Wang, Zhimin, Wang, Zongyi, Watcharangkool, Apimook, Wei, Wei, Wei, Wenlu, Wei, Yadong, Wen, Kaile, Wen, Liangjian, Weng, Jun, Wiebusch, Christopher, Wonsak, Bjoern, Wu, Diru, Wu, Qun, Wu, Zhi, Wurm, Michael, Wurtz, Jacques, Wysotzki, Christian, Xi, Yufei, Xia, Dongmei, Xiao, Xiang, Xie, Xiaochuan, Xie, Yuguang, Xie, Zhangquan, Xin, Zhao, Xing, Zhizhong, Xu, Benda, Xu, Cheng, Xu, Donglian, Xu, Fanrong, Xu, Hangkun, Xu, Jilei, Xu, Jing, Xu, Meihang, Xu, Yin, Xu, Yu, Yan, Baojun, Yan, Qiyu, Yan, Taylor, Yan, Wenqi, Yan, Xiongbo, Yan, Yupeng, Yang, Changgen, Yang, Chengfeng, Yang, Huan, Yang, Jie, Yang, Lei, Yang, Xiaoyu, Yang, Yifan, Yao, Haifeng, Ye, Jiaxuan, Ye, Mei, Ye, Ziping, Yermia, Frédéric, You, Zhengyun, Yu, Boxiang, Yu, Chiye, Yu, Chunxu, Yu, Hongzhao, Yu, Miao, Yu, Xianghui, Yu, Zeyuan, Yu, Zezhong, Yuan, Cenxi, Yuan, Chengzhuo, Yuan, Ying, Yuan, Zhenxiong, Yue, Baobiao, Zafar, Noman, Zavadskyi, Vitalii, Zeng, Shan, Zeng, Tingxuan, Zeng, Yuda, Zhan, Liang, Zhang, Aiqiang, Zhang, Bin, Zhang, Binting, Zhang, Feiyang, Zhang, Guoqing, Zhang, Honghao, Zhang, Jialiang, Zhang, Jiawen, Zhang, Jie, Zhang, Jin, Zhang, Jingbo, Zhang, Jinnan, Zhang, Mohan, Zhang, Peng, Zhang, Qingmin, Zhang, Shiqi, Zhang, Shu, Zhang, Tao, Zhang, Xiaomei, Zhang, Xin, Zhang, Xuantong, Zhang, Yinhong, Zhang, Yiyu, Zhang, Yongpeng, Zhang, Yu, Zhang, Yuanyuan, Zhang, Yumei, Zhang, Zhenyu, Zhang, Zhijian, Zhao, Jie, Zhao, Rong, Zhao, Runze, Zhao, Shujun, Zheng, Dongqin, Zheng, Hua, Zheng, Yangheng, Zhong, Weirong, Zhou, Jing, Zhou, Li, Zhou, Nan, Zhou, Shun, Zhou, Tong, Zhou, Xiang, Zhu, Jingsen, Zhu, Kangfu, Zhu, Kejun, Zhu, Zhihang, Zhuang, Bo, Zhuang, Honglin, Zong, Liang, Zou, Jiaheng, and Zwickel, Sebastian
Subjects: High Energy Physics - Experiment, Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Phenomenology
Abstract: We discuss JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo via detecting inverse beta decay reactions of electron anti-neutrinos resulting from the annihilation. We study possible backgrounds to the signature, including the reactor neutrinos, diffuse supernova neutrino background, charged- and neutral-current interactions of atmospheric neutrinos, backgrounds from muon-induced fast neutrons and cosmogenic isotopes. A fiducial volume cut, as well as the pulse shape discrimination and the muon veto are applied to suppress the above backgrounds. It is shown that JUNO sensitivity to the thermally averaged dark matter annihilation rate in 10 years of exposure would be significantly better than the present-day best limit set by Super-Kamiokande and would be comparable to that expected by Hyper-Kamiokande., Comment: 25 pages, 9 figures, matches the publised version
Published: 2023
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31. An Experimental Review of Speaker Diarization methods with application to Two-Speaker Conversational Telephone Speech recordings

Author: Serafini, Luca, Cornell, Samuele, Morrone, Giovanni, Zovato, Enrico, Brutti, Alessio, and Squartini, Stefano
Subjects: Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Sound, Electrical Engineering and Systems Science - Signal Processing
Abstract: We performed an experimental review of current diarization systems for the conversational telephone speech (CTS) domain. In detail, we considered a total of eight different algorithms belonging to clustering-based, end-to-end neural diarization (EEND), and speech separation guided diarization (SSGD) paradigms. We studied the inference-time computational requirements and diarization accuracy on four CTS datasets with different characteristics and languages. We found that, among all methods considered, EEND-vector clustering (EEND-VC) offers the best trade-off in terms of computing requirements and performance. More in general, EEND models have been found to be lighter and faster in inference compared to clustering-based methods. However, they also require a large amount of diarization-oriented annotated data. In particular EEND-VC performance in our experiments degraded when the dataset size was reduced, whereas self-attentive EEND (SA-EEND) was less affected. We also found that SA-EEND gives less consistent results among all the datasets compared to EEND-VC, with its performance degrading on long conversations with high speech sparsity. Clustering-based diarization systems, and in particular VBx, instead have more consistent performance compared to SA-EEND but are outperformed by EEND-VC. The gap with respect to this latter is reduced when overlap-aware clustering methods are considered. SSGD is the most computationally demanding method, but it could be convenient if speech recognition has to be performed. Its performance is close to SA-EEND but degrades significantly when the training and inference data characteristics are less matched., Comment: 52 pages, 10 figures
Published: 2023

32. Weakly-Supervised Visual-Textual Grounding with Semantic Prior Refinement

Author: Rigoni, Davide, Parolari, Luca, Serafini, Luciano, Sperduti, Alessandro, and Ballan, Lamberto
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Machine Learning, Computer Science - Multimedia
Abstract: Using only image-sentence pairs, weakly-supervised visual-textual grounding aims to learn region-phrase correspondences of the respective entity mentions. Compared to the supervised approach, learning is more difficult since bounding boxes and textual phrases correspondences are unavailable. In light of this, we propose the Semantic Prior Refinement Model (SPRM), whose predictions are obtained by combining the output of two main modules. The first untrained module aims to return a rough alignment between textual phrases and bounding boxes. The second trained module is composed of two sub-components that refine the rough alignment to improve the accuracy of the final phrase-bounding box alignments. The model is trained to maximize the multimodal similarity between an image and a sentence, while minimizing the multimodal similarity of the same sentence and a new unrelated image, carefully selected to help the most during training. Our approach shows state-of-the-art results on two popular datasets, Flickr30k Entities and ReferIt, shining especially on ReferIt with a 9.6% absolute improvement. Moreover, thanks to the untrained component, it reaches competitive performances just using a small fraction of training examples.
Published: 2023

33. Disclosing Early Excited State Relaxation Events in Prototypical Linear Carbon Chains

Author: Kabaciński, Piotr, Marabotti, Pietro, Serafini, Patrick, Fazzi, Daniele, Cerullo, Giulio, Casari, Carlo S., and Zavelani-Rossi, Margherita
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics, Physics - Chemical Physics, Physics - Optics
Abstract: One-dimensional (1D) linear nanostructures comprising sp-hybridized carbon atoms, as derivatives of the prototypical allotrope known as carbyne, are predicted to possess outstanding mechanical, thermal, and electronic properties. Despite recent advances in the synthesis, their chemical and physical properties are still poorly understood. Here, we investigate the photophysics of a prototypical polyyne (i.e., 1D chain with alternating single and triple carbon bonds), as the simplest model of finite carbon wire and as a prototype of sp-carbon-based chains. We perform transient absorption experiments with high temporal resolution (<30 fs) on monodispersed hydrogen-capped hexayne H$-$(C$\equiv$C)$_6-$H synthesized by laser ablation in liquid. With the support of detailed computational studies based on ground state density functional theory (DFT) and excited state time-dependent (TD)-DFT calculations, we provide a comprehensive description of the excited state relaxation processes at early times following photoexcitation. We show that the internal conversion from a bright high-energy singlet excited state to a low-lying singlet dark state is ultrafast and takes place with a 200-fs time constant, followed by thermalization on the picosecond timescale and decay of the low-energy singlet state with hundreds of picoseconds time constant. We also show that the timescale of these processes does not depend on the end groups capping the sp-carbon chain. The understanding of the primary photo-induced events in polyynes is of key importance both for fundamental knowledge and for potential optoelectronic and light-harvesting applications of low dimensional nanostructured carbon-based materials., Comment: 24 pages, 6 figures
Published: 2023
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34. Intrinsic mono-chromatic emission of x and gamma-rays in symmetric electron-photon beam collisions

Author: Serafini, L., Petrillo, V., Bacci, A., Curatolo, C., Drebot, I., Conti, M. Rossetti, and Rossi, A. R.
Subjects: Physics - Accelerator Physics
Abstract: This paper explores the transition between Compton Scattering and Inverse Compton Scattering (ICS), which is characterized by an equal exchange of energy and momentum between the colliding particles (electrons and photons). This regime has been called Symmetric Compton Scattering (SCS) and has the unique property of cancelling the energy-angle correlation of scattered photons, and, when the electron recoil is large, transferring mono-chromaticity from one colliding beam to the other, resulting in back-scattered photon beams that are intrinsically monochromatic. The paper suggests that large-recoil SCS or quasi-SCS can be used to design compact intrinsic monochromatic gamma-ray sources based on compact linacs, thus avoiding the use of GeV-class electron beams together with powerful laser/optical systems as those typically required for ICS sources.
Published: 2023

35. Interval Logic Tensor Networks

Author: Badreddine, Samy, Apriceno, Gianluca, Passerini, Andrea, and Serafini, Luciano
Subjects: Computer Science - Artificial Intelligence
Abstract: In this paper, we introduce Interval Real Logic (IRL), a two-sorted logic that interprets knowledge such as sequential properties (traces) and event properties using sequences of real-featured data. We interpret connectives using fuzzy logic, event durations using trapezoidal fuzzy intervals, and fuzzy temporal relations using relationships between the intervals' areas. We propose Interval Logic Tensor Networks (ILTN), a neuro-symbolic system that learns by propagating gradients through IRL. In order to support effective learning, ILTN defines smoothened versions of the fuzzy intervals and temporal relations of IRL using softplus activations. We show that ILTN can successfully leverage knowledge expressed in IRL in synthetic tasks that require reasoning about events to predict their fuzzy durations. Our results show that the system is capable of making events compliant with background temporal knowledge.
Published: 2023

36. GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism

Author: Polisetty, Sandeep, Liu, Juelin, Falus, Kobi, Fung, Yi Ren, Lim, Seung-Hwan, Guan, Hui, and Serafini, Marco
Subjects: Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Machine Learning
Abstract: Graph neural networks (GNNs), an emerging class of machine learning models for graphs, have gained popularity for their superior performance in various graph analytical tasks. Mini-batch training is commonly used to train GNNs on large graphs, and data parallelism is the standard approach to scale mini-batch training across multiple GPUs. One of the major performance costs in GNN training is the loading of input features, which prevents GPUs from being fully utilized. In this paper, we argue that this problem is exacerbated by redundancies that are inherent to the data parallel approach. To address this issue, we introduce a hybrid parallel mini-batch training paradigm called split parallelism. Split parallelism avoids redundant data loads and splits the sampling and training of each mini-batch across multiple GPUs online, at each iteration, using a lightweight splitting algorithm. We implement split parallelism in GSplit and show that it outperforms state-of-the-art mini-batch training systems like DGL, Quiver, and $P^3$.
Published: 2023

37. End-to-End Integration of Speech Separation and Voice Activity Detection for Low-Latency Diarization of Telephone Conversations

Author: Morrone, Giovanni, Cornell, Samuele, Serafini, Luca, Zovato, Enrico, Brutti, Alessio, and Squartini, Stefano
Subjects: Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Machine Learning, Computer Science - Sound
Abstract: Recent works show that speech separation guided diarization (SSGD) is an increasingly promising direction, mainly thanks to the recent progress in speech separation. It performs diarization by first separating the speakers and then applying voice activity detection (VAD) on each separated stream. In this work we conduct an in-depth study of SSGD in the conversational telephone speech (CTS) domain, focusing mainly on low-latency streaming diarization applications. We consider three state-of-the-art speech separation (SSep) algorithms and study their performance both in online and offline scenarios, considering non-causal and causal implementations as well as continuous SSep (CSS) windowed inference. We compare different SSGD algorithms on two widely used CTS datasets: CALLHOME and Fisher Corpus (Part 1 and 2) and evaluate both separation and diarization performance. To improve performance, a novel, causal and computationally efficient leakage removal algorithm is proposed, which significantly decreases false alarms. We also explore, for the first time, fully end-to-end SSGD integration between SSep and VAD modules. Crucially, this enables fine-tuning on real-world data for which oracle speakers sources are not available. In particular, our best model achieves 8.8% DER on CALLHOME, which outperforms the current state-of-the-art end-to-end neural diarization model, despite being trained on an order of magnitude less data and having significantly lower latency, i.e., 0.1 vs. 1 s. Finally, we also show that the separated signals can be readily used also for automatic speech recognition, reaching performance close to using oracle sources in some configurations., Comment: 16 pages, 7 figures
Published: 2023
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38. The JUNO experiment Top Tracker

Author: JUNO Collaboration, Abusleme, Angel, Adam, Thomas, Ahmad, Shakeel, Ahmed, Rizwan, Aiello, Sebastiano, Akram, Muhammad, Aleem, Abid, Alexandros, Tsagkarakis, An, Fengpeng, An, Qi, Andronico, Giuseppe, Anfimov, Nikolay, Antonelli, Vito, Antoshkina, Tatiana, Asavapibhop, Burin, de André, João Pedro Athayde Marcondes, Auguste, Didier, Bai, Weidong, Balashov, Nikita, Baldini, Wander, Barresi, Andrea, Basilico, Davide, Baussan, Eric, Bellato, Marco, Beretta, Marco, Bergnoli, Antonio, Bick, Daniel, Birkenfeld, Thilo, Blin, Sylvie, Blum, David, Blyth, Simon, Bolshakova, Anastasia, Bongrand, Mathieu, Bordereau, Clément, Breton, Dominique, Brigatti, Augusto, Brugnera, Riccardo, Bruno, Riccardo, Budano, Antonio, Busto, Jose, Cabrera, Anatael, Caccianiga, Barbara, Cai, Hao, Cai, Xiao, Cai, Yanke, Cai, Zhiyan, Callier, Stéphane, Cammi, Antonio, Campeny, Agustin, Cao, Chuanya, Cao, Guofu, Cao, Jun, Caruso, Rossella, Cerna, Cédric, Cerrone, Vanessa, Chan, Chi, Chang, Jinfan, Chang, Yun, Chen, Chao, Chen, Guoming, Chen, Pingping, Chen, Shaomin, Chen, Yixue, Chen, Yu, Chen, Zhiyuan, Chen, Zikang, Cheng, Jie, Cheng, Yaping, Cheng, Yu Chin, Chepurnov, Alexander, Chetverikov, Alexey, Chiesa, Davide, Chimenti, Pietro, Chu, Ziliang, Chukanov, Artem, Claverie, Gérard, Clementi, Catia, Clerbaux, Barbara, Molla, Marta Colomer, Di Lorenzo, Selma Conforti, Coppi, Alberto, Corti, Daniele, Corso, Flavio Dal, Dalager, Olivia, De La Taille, Christophe, Deng, Zhi, Deng, Ziyan, Depnering, Wilfried, Diaz, Marco, Ding, Xuefeng, Ding, Yayun, Dirgantara, Bayu, Dmitrievsky, Sergey, Dohnal, Tadeas, Dolzhikov, Dmitry, Donchenko, Georgy, Dong, Jianmeng, Doroshkevich, Evgeny, Dou, Wei, Dracos, Marcos, Drapier, Olivier, Druillole, Frédéric, Du, Ran, Du, Shuxian, Dugas, Katherine, Dusini, Stefano, Duyang, Hongyue, Eck, Jessica, Enqvist, Timo, Fabbri, Andrea, Fahrendholz, Ulrike, Fan, Lei, Fang, Jian, Fang, Wenxing, Fargetta, Marco, Fedoseev, Dmitry, Fei, Zhengyong, Felici, Giulietto, Feng, Li-Cheng, Feng, Qichun, Ferraro, Federico, Fournier, Amélie, Gan, Haonan, Gao, Feng, Garfagnini, Alberto, Gavrikov, Arsenii, Gerasimov, Vladimir, Giammarchi, Marco, Giudice, Nunzio, Gonchar, Maxim, Gong, Guanghua, Gong, Hui, Gornushkin, Yuri, Göttel, Alexandre, Grassi, Marco, Gromov, Maxim, Gromov, Vasily, Gu, Minghao, Gu, Xiaofei, Gu, Yu, Guan, Mengyun, Guan, Yuduo, Guardone, Nunzio, Guo, Cong, Guo, Wanlei, Guo, Xinheng, Guo, Yuhang, Gursky, Semen, Hagner, Caren, Han, Ran, Han, Yang, He, Miao, He, Wei, Heinz, Tobias, Hellmuth, Patrick, Heng, Yuekun, Herrera, Rafael, Hor, YuenKeung, Hou, Shaojing, Hsiung, Yee, Hu, Bei-Zhen, Hu, Hang, Hu, Jianrun, Hu, Jun, Hu, Shouyang, Hu, Tao, Hu, Yuxiang, Hu, Zhuojun, Huang, Guihong, Huang, Hanxiong, Huang, Jinhao, Huang, Kaixuan, Huang, Wenhao, Huang, Qinhua, Huang, Xin, Huang, Xingtao, Huang, Yongbo, Hui, Jiaqi, Huo, Lei, Huo, Wenju, Huss, Cédric, Hussain, Safeer, Ioannisian, Ara, Isocrate, Roberto, Jelmini, Beatrice, Jeria, Ignacio, Ji, Xiaolu, Jia, Huihui, Jia, Junji, Jian, Siyu, Jiang, Di, Jiang, Wei, Jiang, Xiaoshan, Jing, Xiaoping, Jollet, Cécile, Kalousis, Leonidas, Kampmann, Philipp, Kang, Li, Karaparambil, Rebin, Kazarian, Narine, Khan, Ali, Khatun, Amina, Khosonthongkee, Khanchai, Korablev, Denis, Kouzakov, Konstantin, Krasnoperov, Alexey, Kuleshov, Sergey, Kutovskiy, Nikolay, Kuusiniemi, Pasi, Lachenmaier, Tobias, Landini, Cecilia, Leblanc, Sébastien, Lebrin, Victor, Lefevre, Frederic, Lei, Ruiting, Leitner, Rupert, Leung, Jason, Li, Demin, Li, Fei, Li, Fule, Li, Gaosong, Li, Huiling, Li, Mengzhao, Li, Min, Li, Nan, Li, Qingjiang, Li, Ruhui, Li, Rui, Li, Shanfeng, Li, Tao, Li, Teng, Li, Weidong, Li, Weiguo, Li, Xiaomei, Li, Xiaonan, Li, Xinglong, Li, Yi, Li, Yichen, Li, Yufeng, Li, Zepeng, Li, Zhaohan, Li, Zhibing, Li, Ziyuan, Li, Zonghai, Liang, Hao, Liao, Jiajun, Limphirat, Ayut, Lin, Guey-Lin, Lin, Shengxin, Lin, Tao, Ling, Jiajie, Lippi, Ivano, Liu, Caimei, Liu, Fang, Liu, Haidong, Liu, Haotian, Liu, Hongbang, Liu, Hongjuan, Liu, Hongtao, Liu, Hui, Liu, Jianglai, Liu, Jiaxi, Liu, Jinchang, Liu, Min, Liu, Qian, Liu, Qin, Liu, Runxuan, Liu, Shenghui, Liu, Shubin, Liu, Shulin, Liu, Xiaowei, Liu, Xiwen, Liu, Yankai, Liu, Yunzhe, Lokhov, Alexey, Lombardi, Paolo, Lombardo, Claudio, Loo, Kai, Lu, Chuan, Lu, Haoqi, Lu, Jingbin, Lu, Junguang, Lu, Peizhi, Lu, Shuxiang, Lubsandorzhiev, Bayarto, Lubsandorzhiev, Sultim, Ludhova, Livia, Lukanov, Arslan, Luo, Daibin, Luo, Fengjiao, Luo, Guang, Luo, Jianyi, Luo, Shu, Luo, Wuming, Luo, Xiaojie, Lyashuk, Vladimir, Ma, Bangzheng, Ma, Bing, Ma, Qiumei, Ma, Si, Ma, Xiaoyan, Ma, Xubo, Maalmi, Jihane, Magoni, Marco, Mai, Jingyu, Malyshkin, Yury, Mandujano, Roberto Carlos, Mantovani, Fabio, Mao, Xin, Mao, Yajun, Mari, Stefano M., Marini, Filippo, Martini, Agnese, Mayer, Matthias, Mayilyan, Davit, Mednieks, Ints, Meng, Yue, Meraviglia, Anita, Meregaglia, Anselmo, Meroni, Emanuela, Meyhöfer, David, Miller, Jonathan, Miramonti, Lino, Montini, Paolo, Montuschi, Michele, Müller, Axel, Nastasi, Massimiliano, Naumov, Dmitry V., Naumova, Elena, Navas-Nicolas, Diana, Nemchenok, Igor, Thi, Minh Thuan Nguyen, Nikolaev, Alexey, Ning, Feipeng, Ning, Zhe, Nunokawa, Hiroshi, Oberauer, Lothar, Ochoa-Ricoux, Juan Pedro, Olshevskiy, Alexander, Orestano, Domizia, Ortica, Fausto, Othegraven, Rainer, Paoloni, Alessandro, Parmeggiano, Sergio, Pei, Yatian, Pelicci, Luca, Peng, Anguo, Peng, Haiping, Peng, Yu, Peng, Zhaoyuan, Perrot, Frédéric, Petitjean, Pierre-Alexandre, Petrucci, Fabrizio, Pilarczyk, Oliver, Rico, Luis Felipe Piñeres, Popov, Artyom, Poussot, Pascal, Previtali, Ezio, Qi, Fazhi, Qi, Ming, Qian, Sen, Qian, Xiaohui, Qian, Zhen, Qiao, Hao, Qin, Zhonghua, Qiu, Shoukang, Ranucci, Gioacchino, Rasheed, Reem, Re, Alessandra, Rebii, Abdel, Redchuk, Mariia, Ren, Bin, Ren, Jie, Ricci, Barbara, Rifai, Mariam, Roche, Mathieu, Rodphai, Narongkiat, Romani, Aldo, Romanov, Victor, Roskovec, Bedřich, Ruan, Xichao, Rybnikov, Arseniy, Sadovsky, Andrey, Saggese, Paolo, Sandanayake, Deshan, Sanfilippo, Simone, Sangka, Anut, Sawangwit, Utane, Sawatzki, Julia, Schever, Michaela, Schuler, Jacky, Schwab, Cédric, Schweizer, Konstantin, Selyunin, Alexandr, Serafini, Andrea, Settanta, Giulio, Settimo, Mariangela, Sharov, Vladislav, Shaydurova, Arina, Shi, Jingyan, Shi, Yanan, Shutov, Vitaly, Sidorenkov, Andrey, Šimkovic, Fedor, Sirignano, Chiara, Siripak, Jaruchit, Sisti, Monica, Slupecki, Maciej, Smirnov, Mikhail, Smirnov, Oleg, Sogo-Bezerra, Thiago, Sokolov, Sergey, Songwadhana, Julanan, Soonthornthum, Boonrucksar, Sotnikov, Albert, Šrámek, Ondřej, Sreethawong, Warintorn, Stahl, Achim, Stanco, Luca, Stankevich, Konstantin, Štefánik, Dušan, Steiger, Hans, Steinmann, Jochen, Sterr, Tobias, Stock, Matthias Raphael, Strati, Virginia, Studenikin, Alexander, Su, Jun, Sun, Shifeng, Sun, Xilei, Sun, Yongjie, Sun, Yongzhao, Sun, Zhengyang, Suwonjandee, Narumon, Szelezniak, Michal, Takenaka, Akira, Tang, Jian, Tang, Qiang, Tang, Quan, Tang, Xiao, Hariharan, Vidhya Thara, Theisen, Eric, Tietzsch, Alexander, Tkachev, Igor, Tmej, Tomas, Torri, Marco Danilo Claudio, Tortorici, Francesco, Treskov, Konstantin, Triossi, Andrea, Triozzi, Riccardo, Troni, Giancarlo, Trzaska, Wladyslaw, Tung, Yu-Chen, Tuve, Cristina, Ushakov, Nikita, Vedin, Vadim, Verde, Giuseppe, Vialkov, Maxim, Viaud, Benoit, Vollbrecht, Cornelius Moritz, von Sturm, Katharina, Vorobel, Vit, Voronin, Dmitriy, Votano, Lucia, Walker, Pablo, Wang, Caishen, Wang, Chung-Hsiang, Wang, En, Wang, Guoli, Wang, Jian, Wang, Jun, Wang, Lu, Wang, Meng, Wang, Ruiguang, Wang, Siguang, Wang, Wei, Wang, Wenshuai, Wang, Xi, Wang, Xiangyue, Wang, Yangfu, Wang, Yaoguang, Wang, Yi, Wang, Yifang, Wang, Yuanqing, Wang, Zhe, Wang, Zheng, Wang, Zhimin, Watcharangkool, Apimook, Wei, Wei, Wei, Wenlu, Wei, Yadong, Wen, Kaile, Wen, Liangjian, Weng, Jun, Wiebusch, Christopher, Wirth, Rosmarie, Wonsak, Bjoern, Wu, Diru, Wu, Qun, Wu, Zhi, Wurm, Michael, Wurtz, Jacques, Wysotzki, Christian, Xi, Yufei, Xia, Dongmei, Xiao, Xiang, Xie, Xiaochuan, Xie, Yuguang, Xie, Zhangquan, Xin, Zhao, Xing, Zhizhong, Xu, Benda, Xu, Cheng, Xu, Donglian, Xu, Fanrong, Xu, Hangkun, Xu, Jilei, Xu, Jing, Xu, Meihang, Xu, Yin, Xu, Yu, Yan, Baojun, Yan, Qiyu, Yan, Taylor, Yan, Xiongbo, Yan, Yupeng, Yang, Changgen, Yang, Chengfeng, Yang, Jie, Yang, Lei, Yang, Xiaoyu, Yang, Yifan, Yao, Haifeng, Ye, Jiaxuan, Ye, Mei, Ye, Ziping, Yermia, Frédéric, You, Zhengyun, Yu, Boxiang, Yu, Chiye, Yu, Chunxu, Yu, Guojun, Yu, Hongzhao, Yu, Miao, Yu, Xianghui, Yu, Zeyuan, Yu, Zezhong, Yuan, Cenxi, Yuan, Chengzhuo, Yuan, Ying, Yuan, Zhenxiong, Yue, Baobiao, Zafar, Noman, Zavadskyi, Vitalii, Zeng, Shan, Zeng, Tingxuan, Zeng, Yuda, Zhan, Liang, Zhang, Aiqiang, Zhang, Bin, Zhang, Binting, Zhang, Feiyang, Zhang, Haosen, Zhang, Honghao, Zhang, Jialiang, Zhang, Jiawen, Zhang, Jie, Zhang, Jin, Zhang, Jingbo, Zhang, Jinnan, Zhang, Mohan, Zhang, Peng, Zhang, Qingmin, Zhang, Shiqi, Zhang, Shu, Zhang, Shuihan, Zhang, Tao, Zhang, Xiaomei, Zhang, Xin, Zhang, Xuantong, Zhang, Yinhong, Zhang, Yiyu, Zhang, Yongpeng, Zhang, Yu, Zhang, Yuanyuan, Zhang, Yumei, Zhang, Zhenyu, Zhang, Zhijian, Zhao, Jie, Zhao, Rong, Zhao, Runze, Zhao, Shujun, Zheng, Dongqin, Zheng, Hua, Zheng, Yangheng, Zhong, Weirong, Zhou, Jing, Zhou, Li, Zhou, Nan, Zhou, Shun, Zhou, Tong, Zhou, Xiang, Zhu, Jingsen, Zhu, Kangfu, Zhu, Kejun, Zhu, Zhihang, Zhuang, Bo, Zhuang, Honglin, Zong, Liang, Zou, Jiaheng, and Zwickel, Sebastian
Subjects: High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract: The main task of the Top Tracker detector of the neutrino reactor experiment Jiangmen Underground Neutrino Observatory (JUNO) is to reconstruct and extrapolate atmospheric muon tracks down to the central detector. This muon tracker will help to evaluate the contribution of the cosmogenic background to the signal. The Top Tracker is located above JUNO's water Cherenkov Detector and Central Detector, covering about 60% of the surface above them. The JUNO Top Tracker is constituted by the decommissioned OPERA experiment Target Tracker modules. The technology used consists in walls of two planes of plastic scintillator strips, one per transverse direction. Wavelength shifting fibres collect the light signal emitted by the scintillator strips and guide it to both ends where it is read by multianode photomultiplier tubes. Compared to the OPERA Target Tracker, the JUNO Top Tracker uses new electronics able to cope with the high rate produced by the high rock radioactivity compared to the one in Gran Sasso underground laboratory. This paper will present the new electronics and mechanical structure developed for the Top Tracker of JUNO along with its expected performance based on the current detector simulation., Comment: 20 pages
Published: 2023
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39. JUNO sensitivity to $^7$Be, $pep$, and CNO solar neutrinos

Author: Abusleme, Angel, Adam, Thomas, Ahmad, Shakeel, Ahmed, Rizwan, Aiello, Sebastiano, Akram, Muhammad, Aleem, Abid, Alexandros, Tsagkarakis, An, Fengpeng, An, Qi, Andronico, Giuseppe, Anfimov, Nikolay, Antonelli, Vito, Antoshkina, Tatiana, Asavapibhop, Burin, de André, João Pedro Athayde Marcondes, Auguste, Didier, Bai, Weidong, Balashov, Nikita, Baldini, Wander, Barresi, Andrea, Basilico, Davide, Baussan, Eric, Bellato, Marco, Beretta, Marco, Bergnoli, Antonio, Bick, Daniel, Bieger, Lukas, Biktemerova, Svetlana, Birkenfeld, Thilo, Blum, David, Blyth, Simon, Bolshakova, Anastasia, Bongrand, Mathieu, Bordereau, Clément, Breton, Dominique, Brigatti, Augusto, Brugnera, Riccardo, Bruno, Riccardo, Budano, Antonio, Busto, Jose, Cabrera, Anatael, Caccianiga, Barbara, Cai, Hao, Cai, Xiao, Cai, Yanke, Cai, Zhiyan, Callier, Stéphane, Cammi, Antonio, Campeny, Agustin, Cao, Chuanya, Cao, Guofu, Cao, Jun, Caruso, Rossella, Cerna, Cédric, Cerrone, Vanessa, Chan, Chi, Chang, Jinfan, Chang, Yun, Chen, Chao, Chen, Guoming, Chen, Pingping, Chen, Shaomin, Chen, Yixue, Chen, Yu, Chen, Zhiyuan, Chen, Zikang, Cheng, Jie, Cheng, Yaping, Cheng, Yu Chin, Chepurnov, Alexander, Chetverikov, Alexey, Chiesa, Davide, Chimenti, Pietro, Chu, Ziliang, Chukanov, Artem, Claverie, Gérard, Clementi, Catia, Clerbaux, Barbara, Molla, Marta Colomer, Di Lorenzo, Selma Conforti, Coppi, Alberto, Corti, Daniele, Csakli, Simon, Corso, Flavio Dal, Dalager, Olivia, Datta, Jaydeep, De La Taille, Christophe, Deng, Zhi, Deng, Ziyan, Depnering, Wilfried, Ding, Xiaoyu, Ding, Xuefeng, Ding, Yayun, Dirgantara, Bayu, Dittrich, Carsten, Dmitrievsky, Sergey, Dohnal, Tadeas, Dolzhikov, Dmitry, Donchenko, Georgy, Dong, Jianmeng, Doroshkevich, Evgeny, Dou, Wei, Dracos, Marcos, Druillole, Frédéric, Du, Ran, Du, Shuxian, Dugas, Katherine, Dusini, Stefano, Duyang, Hongyue, Eck, Jessica, Enqvist, Timo, Fabbri, Andrea, Fahrendholz, Ulrike, Fan, Lei, Fang, Jian, Fang, Wenxing, Fargetta, Marco, Fedoseev, Dmitry, Fei, Zhengyong, Feng, Li-Cheng, Feng, Qichun, Ferraro, Federico, Fournier, Amélie, Gan, Haonan, Gao, Feng, Garfagnini, Alberto, Gavrikov, Arsenii, Giammarchi, Marco, Giudice, Nunzio, Gonchar, Maxim, Gong, Guanghua, Gong, Hui, Gornushkin, Yuri, Göttel, Alexandre, Grassi, Marco, Gromov, Maxim, Gromov, Vasily, Gu, Minghao, Gu, Xiaofei, Gu, Yu, Guan, Mengyun, Guan, Yuduo, Guardone, Nunzio, Guo, Cong, Guo, Wanlei, Guo, Xinheng, Hagner, Caren, Han, Ran, Han, Yang, He, Miao, He, Wei, Heinz, Tobias, Hellmuth, Patrick, Heng, Yuekun, Herrera, Rafael, Hor, YuenKeung, Hou, Shaojing, Hsiung, Yee, Hu, Bei-Zhen, Hu, Hang, Hu, Jianrun, Hu, Jun, Hu, Shouyang, Hu, Tao, Hu, Yuxiang, Hu, Zhuojun, Huang, Guihong, Huang, Hanxiong, Huang, Jinhao, Huang, Junting, Huang, Kaixuan, Huang, Wenhao, Huang, Xin, Huang, Xingtao, Huang, Yongbo, Hui, Jiaqi, Huo, Lei, Huo, Wenju, Huss, Cédric, Hussain, Safeer, Imbert, Leonard, Ioannisian, Ara, Isocrate, Roberto, Jelmini, Beatrice, Jeria, Ignacio, Ji, Xiaolu, Jia, Huihui, Jia, Junji, Jian, Siyu, Jiang, Cailian, Jiang, Di, Jiang, Wei, Jiang, Xiaoshan, Jing, Xiaoping, Jollet, Cécile, Kampmann, Philipp, Kang, Li, Karaparambil, Rebin, Kazarian, Narine, Khan, Ali, Khatun, Amina, Khosonthongkee, Khanchai, Korablev, Denis, Kouzakov, Konstantin, Krasnoperov, Alexey, Kuleshov, Sergey, Kutovskiy, Nikolay, Lachenmaier, Tobias, Landini, Cecilia, Leblanc, Sébastien, Lebrin, Victor, Lefevre, Frederic, Lei, Ruiting, Leitner, Rupert, Leung, Jason, Li, Demin, Li, Fei, Li, Fule, Li, Gaosong, Li, Huiling, Li, Jiajun, Li, Mengzhao, Li, Min, Li, Nan, Li, Qingjiang, Li, Ruhui, Li, Rui, Li, Shanfeng, Li, Tao, Li, Teng, Li, Weidong, Li, Weiguo, Li, Xiaomei, Li, Xiaonan, Li, Xinglong, Li, Yi, Li, Yichen, Li, Yufeng, Li, Zepeng, Li, Zhaohan, Li, Zhibing, Li, Ziyuan, Li, Zonghai, Liang, Hao, Liao, Jiajun, Limphirat, Ayut, Lin, Guey-Lin, Lin, Shengxin, Lin, Tao, Ling, Jiajie, Ling, Xin, Lippi, Ivano, Liu, Caimei, Liu, Fang, Liu, Fengcheng, Liu, Haidong, Liu, Haotian, Liu, Hongbang, Liu, Hongjuan, Liu, Hongtao, Liu, Hui, Liu, Jianglai, Liu, Jiaxi, Liu, Jinchang, Liu, Min, Liu, Qian, Liu, Qin, Liu, Runxuan, Liu, Shenghui, Liu, Shubin, Liu, Shulin, Liu, Xiaowei, Liu, Xiwen, Liu, Xuewei, Liu, Yankai, Liu, Zhen, Lokhov, Alexey, Lombardi, Paolo, Lombardo, Claudio, Loo, Kai, Lu, Chuan, Lu, Haoqi, Lu, Jingbin, Lu, Junguang, Lu, Peizhi, Lu, Shuxiang, Lubsandorzhiev, Bayarto, Lubsandorzhiev, Sultim, Ludhova, Livia, Lukanov, Arslan, Luo, Daibin, Luo, Fengjiao, Luo, Guang, Luo, Jianyi, Luo, Shu, Luo, Wuming, Luo, Xiaojie, Lyashuk, Vladimir, Ma, Bangzheng, Ma, Bing, Ma, Qiumei, Ma, Si, Ma, Xiaoyan, Ma, Xubo, Maalmi, Jihane, Magoni, Marco, Mai, Jingyu, Malyshkin, Yury, Mandujano, Roberto Carlos, Mantovani, Fabio, Mao, Xin, Mao, Yajun, Mari, Stefano M., Marini, Filippo, Martini, Agnese, Mayer, Matthias, Mayilyan, Davit, Mednieks, Ints, Meng, Yue, Meraviglia, Anita, Meregaglia, Anselmo, Meroni, Emanuela, Meyhöfer, David, Miramonti, Lino, Mohan, Nikhil, Montini, Paolo, Montuschi, Michele, Müller, Axel, Nastasi, Massimiliano, Naumov, Dmitry V., Naumova, Elena, Navas-Nicolas, Diana, Nemchenok, Igor, Thi, Minh Thuan Nguyen, Nikolaev, Alexey, Ning, Feipeng, Ning, Zhe, Nunokawa, Hiroshi, Oberauer, Lothar, Ochoa-Ricoux, Juan Pedro, Olshevskiy, Alexander, Orestano, Domizia, Ortica, Fausto, Othegraven, Rainer, Paoloni, Alessandro, Parmeggiano, Sergio, Pei, Yatian, Pelicci, Luca, Peng, Anguo, Peng, Haiping, Peng, Yu, Peng, Zhaoyuan, Perrot, Frédéric, Petitjean, Pierre-Alexandre, Petrucci, Fabrizio, Pilarczyk, Oliver, Rico, Luis Felipe Piñeres, Popov, Artyom, Poussot, Pascal, Previtali, Ezio, Qi, Fazhi, Qi, Ming, Qi, Xiaohui, Qian, Sen, Qian, Xiaohui, Qian, Zhen, Qiao, Hao, Qin, Zhonghua, Qiu, Shoukang, Ranucci, Gioacchino, Rasheed, Reem, Re, Alessandra, Rebii, Abdel, Redchuk, Mariia, Ren, Bin, Ren, Jie, Ricci, Barbara, Rifai, Mariam, Roche, Mathieu, Rodphai, Narongkiat, Romani, Aldo, Roskovec, Bedřich, Ruan, Xichao, Rybnikov, Arseniy, Sadovsky, Andrey, Saggese, Paolo, Sandanayake, Deshan, Sanfilippo, Simone, Sangka, Anut, Sawangwit, Utane, Schever, Michaela, Schwab, Cédric, Schweizer, Konstantin, Selyunin, Alexandr, Serafini, Andrea, Settimo, Mariangela, Sharov, Vladislav, Shaydurova, Arina, Shi, Jingyan, Shi, Yanan, Shutov, Vitaly, Sidorenkov, Andrey, Šimkovic, Fedor, Singhal, Apeksha, Sirignano, Chiara, Siripak, Jaruchit, Sisti, Monica, Smirnov, Mikhail, Smirnov, Oleg, Sogo-Bezerra, Thiago, Sokolov, Sergey, Songwadhana, Julanan, Soonthornthum, Boonrucksar, Sotnikov, Albert, Šrámek, Ondřej, Sreethawong, Warintorn, Stahl, Achim, Stanco, Luca, Stankevich, Konstantin, Steiger, Hans, Steinmann, Jochen, Sterr, Tobias, Stock, Matthias Raphael, Strati, Virginia, Studenikin, Alexander, Su, Jun, Sun, Shifeng, Sun, Xilei, Sun, Yongjie, Sun, Yongzhao, Sun, Zhengyang, Suwonjandee, Narumon, Szelezniak, Michal, Takenaka, Akira, Tang, Jian, Tang, Qiang, Tang, Quan, Tang, Xiao, Hariharan, Vidhya Thara, Theisen, Eric, Tietzsch, Alexander, Tkachev, Igor, Tmej, Tomas, Torri, Marco Danilo Claudio, Tortorici, Francesco, Treskov, Konstantin, Triossi, Andrea, Triozzi, Riccardo, Trzaska, Wladyslaw, Tung, Yu-Chen, Tuve, Cristina, Ushakov, Nikita, Vedin, Vadim, Verde, Giuseppe, Vialkov, Maxim, Viaud, Benoit, Vollbrecht, Cornelius Moritz, von Sturm, Katharina, Vorobel, Vit, Voronin, Dmitriy, Votano, Lucia, Walker, Pablo, Wang, Caishen, Wang, Chung-Hsiang, Wang, En, Wang, Guoli, Wang, Jian, Wang, Jun, Wang, Lu, Wang, Meng, Wang, Ruiguang, Wang, Siguang, Wang, Wei, Wang, Wenshuai, Wang, Xi, Wang, Xiangyue, Wang, Yangfu, Wang, Yaoguang, Wang, Yi, Wang, Yifang, Wang, Yuanqing, Wang, Yuyi, Wang, Zhe, Wang, Zheng, Wang, Zhimin, Watcharangkool, Apimook, Wei, Wei, Wei, Wenlu, Wei, Yadong, Wen, Kaile, Wen, Liangjian, Weng, Jun, Wiebusch, Christopher, Wirth, Rosmarie, Wonsak, Bjoern, Wu, Diru, Wu, Qun, Wu, Yiyang, Wu, Zhi, Wurm, Michael, Wurtz, Jacques, Wysotzki, Christian, Xi, Yufei, Xia, Dongmei, Xiao, Xiang, Xie, Xiaochuan, Xie, Yuguang, Xie, Zhangquan, Xin, Zhao, Xing, Zhizhong, Xu, Benda, Xu, Cheng, Xu, Donglian, Xu, Fanrong, Xu, Hangkun, Xu, Jilei, Xu, Jing, Xu, Meihang, Xu, Yin, Xu, Yu, Yan, Baojun, Yan, Qiyu, Yan, Taylor, Yan, Xiongbo, Yan, Yupeng, Yang, Changgen, Yang, Chengfeng, Yang, Jie, Yang, Lei, Yang, Xiaoyu, Yang, Yifan, Yao, Haifeng, Ye, Jiaxuan, Ye, Mei, Ye, Ziping, Yermia, Frédéric, You, Zhengyun, Yu, Boxiang, Yu, Chiye, Yu, Chunxu, Yu, Guojun, Yu, Hongzhao, Yu, Miao, Yu, Xianghui, Yu, Zeyuan, Yu, Zezhong, Yuan, Cenxi, Yuan, Chengzhuo, Yuan, Ying, Yuan, Zhenxiong, Yue, Baobiao, Zafar, Noman, Zavadskyi, Vitalii, Zeng, Shan, Zeng, Tingxuan, Zeng, Yuda, Zhan, Liang, Zhang, Aiqiang, Zhang, Bin, Zhang, Binting, Zhang, Feiyang, Zhang, Haosen, Zhang, Honghao, Zhang, Jialiang, Zhang, Jiawen, Zhang, Jie, Zhang, Jingbo, Zhang, Jinnan, Zhang, Mohan, Zhang, Peng, Zhang, Qingmin, Zhang, Shiqi, Zhang, Shu, Zhang, Shuihan, Zhang, Siyuan, Zhang, Tao, Zhang, Xiaomei, Zhang, Xin, Zhang, Xuantong, Zhang, Yinhong, Zhang, Yiyu, Zhang, Yongpeng, Zhang, Yu, Zhang, Yuanyuan, Zhang, Yumei, Zhang, Zhenyu, Zhang, Zhijian, Zhao, Jie, Zhao, Rong, Zhao, Runze, Zhao, Shujun, Zheng, Dongqin, Zheng, Hua, Zheng, Yangheng, Zhong, Weirong, Zhou, Jing, Zhou, Li, Zhou, Nan, Zhou, Shun, Zhou, Tong, Zhou, Xiang, Zhu, Jingsen, Zhu, Kangfu, Zhu, Kejun, Zhu, Zhihang, Zhuang, Bo, Zhuang, Honglin, Zong, Liang, Zou, Jiaheng, Züfle, Jan, and Zwickel, Sebastian
Subjects: High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract: The Jiangmen Underground Neutrino Observatory (JUNO), the first multi-kton liquid scintillator detector, which is under construction in China, will have a unique potential to perform a real-time measurement of solar neutrinos well below the few MeV threshold typical for Water Cherenkov detectors. JUNO's large target mass and excellent energy resolution are prerequisites for reaching unprecedented levels of precision. In this paper, we provide estimation of the JUNO sensitivity to 7Be, pep, and CNO solar neutrinos that can be obtained via a spectral analysis above the 0.45 MeV threshold. This study is performed assuming different scenarios of the liquid scintillator radiopurity, ranging from the most opti mistic one corresponding to the radiopurity levels obtained by the Borexino experiment, up to the minimum requirements needed to perform the neutrino mass ordering determination with reactor antineutrinos - the main goal of JUNO. Our study shows that in most scenarios, JUNO will be able to improve the current best measurements on 7Be, pep, and CNO solar neutrino fluxes. We also perform a study on the JUNO capability to detect periodical time variations in the solar neutrino flux, such as the day-night modulation induced by neutrino flavor regeneration in Earth, and the modulations induced by temperature changes driven by helioseismic waves.
Published: 2023

40. Implementation and performances of the IPbus protocol for the JUNO Large-PMT readout electronics

Author: Triozzi, Riccardo, Serafini, Andrea, Bellato, Marco, Bergnoli, Antonio, Bolognesi, Matteo, Brugnera, Riccardo, Cerrone, Vanessa, Chen, Chao, Clerbaux, Barbara, Coppi, Alberto, Corti, Daniele, Corso, Flavio dal, Dong, Jianmeng, Dou, Wei, Fan, Lei, Garfagnini, Alberto, Gavrikov, Arsenii, Gong, Guanghua, Grassi, Marco, Guizzetti, Rosa Maria, Hang, Shuang, He, Cong, Hu, Jun, Isocrate, Roberto, Jelmini, Beatrice, Ji, Xiaolu, Jiang, Xiaoshan, Li, Fei, Liang, Zehong, Lippi, Ivano, Liu, Hongbang, Liu, Hongbin, Liu, Shenghui, Liu, Xuewei, Luo, Daibin, Luo, Ronghua, Marini, Filippo, Mazzaro, Daniele, Modenese, Luciano, Molla, Marta Colomer, Ning, Zhe, Peng, Yu, Petitjean, Pierre-Alexandre, Pitacco, Alberto, Qi, Mengyao, Ramina, Loris, Rampazzo, Mirco, Rebeschini, Massimo, Redchuk, Mariia, Sun, Yunhua, Triossi, Andrea, Veronese, Fabio, von Sturm, Katharina, Wang, Peiliang, Wang, Peng, Wang, Yangfu, Wang, Yusheng, Wang, Yuyi, Wang, Zheng, Wei, Ping, Weng, Jun, Xian, Shishen, Xie, Xiaochuan, Xu, Benda, Xu, Chuang, Xu, Donglian, Xu, Hai, Yan, Xiongbo, Yan, Ziyue, Yang, Fengfan, Yang, Yan, Yang, Yifan, Ye, Mei, Zeng, Tingxuan, Zhang, Shuihan, Zhang, Wei, Zhang, Aiqiang, Zhang, Bin, Zhao, Siyao, Zi, Changge, Aiello, Sebastiano, Andronico, Giuseppe, Antonelli, Vito, Barresi, Andrea, Basilico, Davide, Beretta, Marco, Brigatti, Augusto, Bruno, Riccardo, Budano, Antonio, Caccianiga, Barbara, Cammi, Antonio, Campese, Stefano, Chiesa, Davide, Clementi, Catia, Cordelli, Marco, Dusini, Stefano, Fabbri, Andrea, Felici, Giulietto, Ferraro, Federico, Giammarchi, Marco Giulio, Landini, Cecilia, Lombardi, Paolo, Lombardo, Claudio, Maino, Andrea, Mantovani, Fabio, Mari, Stefano Maria, Martini, Agnese, Meroni, Emanuela, Miramonti, Lino, Montuschi, Michele, Nastasi, Massimiliano, Orestano, Domizia, Ortica, Fausto, Paoloni, Alessandro, Parmeggiano, Sergio, Petrucci, Fabrizio, Previtali, Ezio, Ranucci, Gioacchino, Re, Alessandra Carlotta, Ricci, Barbara, Romani, Aldo, Saggese, Paolo, Sanfilippo, Simone, Sirignano, Chiara, Sisti, Monica, Stanco, Luca, Strati, Virginia, Tortorici, Francesco, Tuvé, Cristina, Venettacci, Carlo, Verde, Giuseppe, and Votano, Lucia
Subjects: Physics - Instrumentation and Detectors
Abstract: The Jiangmen Underground Neutrino Observatory (JUNO) is a large neutrino detector currently under construction in China. Thanks to the tight requirements on its optical and radio-purity properties, it will be able to perform leading measurements detecting terrestrial and astrophysical neutrinos in a wide energy range from tens of keV to hundreds of MeV. A key requirement for the success of the experiment is an unprecedented 3% energy resolution, guaranteed by its large active mass (20 kton) and the use of more than 20,000 20-inch photo-multiplier tubes (PMTs) acquired by high-speed, high-resolution sampling electronics located very close to the PMTs. As the Front-End and Read-Out electronics is expected to continuously run underwater for 30 years, a reliable readout acquisition system capable of handling the timestamped data stream coming from the Large-PMTs and permitting to simultaneously monitor and operate remotely the inaccessible electronics had to be developed. In this contribution, the firmware and hardware implementation of the IPbus based readout protocol will be presented, together with the performances measured on final modules during the mass production of the electronics.
Published: 2023
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41. Weighted First Order Model Counting with Directed Acyclic Graph Axioms

Author: Malhotra, Sagar and Serafini, Luciano
Subjects: Computer Science - Artificial Intelligence, Computer Science - Computational Complexity, Computer Science - Logic in Computer Science, Mathematics - Combinatorics
Abstract: Statistical Relational Learning (SRL) integrates First-Order Logic (FOL) and probability theory for learning and inference over relational data. Probabilistic inference and learning in many SRL models can be reduced to Weighted First Order Model Counting (WFOMC). However, WFOMC is known to be intractable ($\mathrm{\#P_1-}$ complete). Hence, logical fragments that admit polynomial time WFOMC are of significant interest. Such fragments are called domain liftable. Recent line of works have shown the two-variable fragment of FOL, extended with counting quantifiers ($\mathrm{C^2}$) to be domain-liftable. However, many properties of real-world data can not be modelled in $\mathrm{C^2}$. In fact many ubiquitous properties of real-world data are inexressible in FOL. Acyclicity is one such property, found in citation networks, genealogy data, temporal data e.t.c. In this paper we aim to address this problem by investigating the domain liftability of directed acyclicity constraints. We show that the fragment $\mathrm{C^2}$ with a Directed Acyclic Graph (DAG) axiom, i.e., a predicate in the language is axiomatized to represent a DAG, is domain-liftable. We present a method based on principle of inclusion-exclusion for WFOMC of $\mathrm{C^2}$ formulas extended with DAG axioms.
Published: 2023

42. C-rusted: The Advantages of Rust, in C, without the Disadvantages

Author: Bagnara, Roberto, Bagnara, Abramo, and Serafini, Federico
Subjects: Computer Science - Programming Languages, Computer Science - Cryptography and Security, Computer Science - Software Engineering, 68N15, F.3.1, D.3.0
Abstract: C-rusted is an innovative technology whereby C programs can be (partly) annotated so as to express: ownership, exclusivity and shareability of language, system and user-defined resources; dynamic properties of objects and the way they evolve during program execution; nominal typing and subtyping. The (partially) annotated C programs can be translated with unmodified versions of any compilation toolchain capable of processing ISO C code. The annotated C program parts can be validated by static analysis: if the static analyzer flags no error, then the annotations are provably coherent among themselves and with respect to annotated C code, in which case said annotated parts are provably exempt from a large class of logic, security, and run-time errors., Comment: 12 pages, 12 figures
Published: 2023

43. Planning for Learning Object Properties

Author: Lamanna, Leonardo, Serafini, Luciano, Faridghasemnia, Mohamadreza, Saffiotti, Alessandro, Saetti, Alessandro, Gerevini, Alfonso, and Traverso, Paolo
Subjects: Computer Science - Artificial Intelligence, Computer Science - Robotics
Abstract: Autonomous agents embedded in a physical environment need the ability to recognize objects and their properties from sensory data. Such a perceptual ability is often implemented by supervised machine learning models, which are pre-trained using a set of labelled data. In real-world, open-ended deployments, however, it is unrealistic to assume to have a pre-trained model for all possible environments. Therefore, agents need to dynamically learn/adapt/extend their perceptual abilities online, in an autonomous way, by exploring and interacting with the environment where they operate. This paper describes a way to do so, by exploiting symbolic planning. Specifically, we formalize the problem of automatically training a neural network to recognize object properties as a symbolic planning problem (using PDDL). We use planning techniques to produce a strategy for automating the training dataset creation and the learning process. Finally, we provide an experimental evaluation in both a simulated and a real environment, which shows that the proposed approach is able to successfully learn how to recognize new object properties.
Published: 2023

44. Mass testing of the JUNO experiment 20-inch PMTs readout electronics

Author: Coppi, Alberto, Jelmini, Beatrice, Bellato, Marco, Bergnoli, Antonio, Bolognesi, Matteo, Brugnera, Riccardo, Cerrone, Vanessa, Chen, Chao, Clerbaux, Barbara, Corti, Daniele, Corso, Flavio dal, Dong, Jianmeng, Dou, Wei, Fan, Lei, Garfagnini, Alberto, Gavrikov, Arsenii, Gong, Guanghua, Grassi, Marco, Guizzetti, Rosa Maria, Hang, Shuang, He, Cong, Hu, Jun, Isocrate, Roberto, Ji, Xiaolu, Jiang, Xiaoshan, Li, Fei, Liang, Zehong, Lippi, Ivano, Liu, Hongbang, Liu, Hongbin, Liu, Shenghui, Liu, Xuewei, Luo, Daibin, Luo, Ronghua, Marini, Filippo, Mazzaro, Daniele, Modenese, Luciano, Molla, Marta Colomer, Ning, Zhe, Peng, Yu, Petitjean, Pierre-Alexandre, Pitacco, Alberto, Qi, Mengyao, Ramina, Loris, Rampazzo, Mirco, Rebeschini, Massimo, Redchuk, Mariia, Serafini, Andrea, Sun, Yunhua, Triossi, Andrea, Triozzi, Riccardo, Veronese, Fabio, von Sturm, Katharina, Wang, Peiliang, Wang, Peng, Wang, Yangfu, Wang, Yusheng, Wang, Yuyi, Wang, Zheng, Wei, Ping, Weng, Jun, Xian, Shishen, Xie, Xiaochuan, Xu, Benda, Xu, Chuang, Xu, Donglian, Xu, Hai, Yan, Xiongbo, Yan, Ziyue, Yang, Fengfan, Yang, Yan, Yang, Yifan, Ye, Mei, Zeng, Tingxuan, Zhang, Shuihan, Zhang, Wei, Zhang, Aiqiang, Zhang, Bin, Zhao, Siyao, Zi, Changge, Aiello, Sebastiano, Andronico, Giuseppe, Antonelli, Vito, Barresi, Andrea, Basilico, Davide, Beretta, Marco, Brigatti, Augusto, Bruno, Riccardo, Budano, Antonio, Caccianiga, Barbara, Cammi, Antonio, Campese, Stefano, Chiesa, Davide, Clementi, Catia, Cordelli, Marco, Dusini, Stefano, Fabbri, Andrea, Felici, Giulietto, Ferraro, Federico, Giammarchi, Marco Giulio, Landini, Cecilia, Lombardi, Paolo, Lombardo, Claudio, Maino, Andrea, Mantovani, Fabio, Mari, Stefano Maria, Martini, Agnese, Meroni, Emanuela, Miramonti, Lino, Montuschi, Michele, Nastasi, Massimiliano, Orestano, Domizia, Ortica, Fausto, Paoloni, Alessandro, Parmeggiano, Sergio, Petrucci, Fabrizio, Previtali, Ezio, Ranucci, Gioacchino, Re, Alessandra Carlotta, Ricci, Barbara, Romani, Aldo, Saggese, Paolo, Sanfilippo, Simone, Sirignano, Chiara, Sisti, Monica, Stanco, Luca, Strati, Virginia, Tortorici, Francesco, Tuvé, Cristina, Venettacci, Carlo, Verde, Giuseppe, and Votano, Lucia
Subjects: Physics - Instrumentation and Detectors
Abstract: The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose, large size, liquid scintillator experiment under construction in China. JUNO will perform leading measurements detecting neutrinos from different sources (reactor, terrestrial and astrophysical neutrinos) covering a wide energy range (from 200 keV to several GeV). This paper focuses on the design and development of a test protocol for the 20-inch PMT underwater readout electronics, performed in parallel to the mass production line. In a time period of about ten months, a total number of 6950 electronic boards were tested with an acceptance yield of 99.1%.
Published: 2023
Full Text: View/download PDF

45. Tuning the Tail Latency of Distributed Queries Using Replication

Author: Ng, Nathan, Le, Hung, and Serafini, Marco
Subjects: Computer Science - Databases, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract: Querying graph data with low latency is an important requirement in application domains such as social networks and knowledge graphs. Graph queries perform multiple hops between vertices. When data is partitioned and stored across multiple servers, queries executing at one server often need to hop to vertices stored by another server. Such distributed traversals represent a performance bottleneck for low-latency queries. To reduce query latency, one can replicate remote data to make distributed traversals unnecessary, but replication is expensive and should be minimized. In this paper, we introduce the problem of finding data replication schemes that satisfy arbitrary user-defined query latency constraints with minimal replication cost. We propose a novel workload model to express data access causality, propose a family of heuristics, and introduce non-trivial sufficient conditions for their correctness. Our evaluation on two representative benchmarks show that our algorithms enable fine-tuning query latency with data replication and can find sweet spots in the latency/replication design space., Comment: An earlier version of this paper was submitted in April 2022. Previous versions are available at https://marcoserafini.github.io/projects/latency-replication/index.html
Published: 2022

46. JUNO Sensitivity on Proton Decay $p\to \bar\nu K^+$ Searches

Author: JUNO Collaboration, Abusleme, Angel, Adam, Thomas, Ahmad, Shakeel, Ahmed, Rizwan, Aiello, Sebastiano, Akram, Muhammad, An, Fengpeng, An, Qi, Andronico, Giuseppe, Anfimov, Nikolay, Antonelli, Vito, Antoshkina, Tatiana, Asavapibhop, Burin, de André, João Pedro Athayde Marcondes, Auguste, Didier, Balashov, Nikita, Baldini, Wander, Barresi, Andrea, Basilico, Davide, Baussan, Eric, Bellato, Marco, Bergnoli, Antonio, Birkenfeld, Thilo, Blin, Sylvie, Blum, David, Blyth, Simon, Bolshakova, Anastasia, Bongrand, Mathieu, Bordereau, Clément, Breton, Dominique, Brigatti, Augusto, Brugnera, Riccardo, Bruno, Riccardo, Budano, Antonio, Buscemi, Mario, Busto, Jose, Butorov, Ilya, Cabrera, Anatael, Caccianiga, Barbara, Cai, Hao, Cai, Xiao, Cai, Yanke, Cai, Zhiyan, Callegari, Riccardo, Cammi, Antonio, Campeny, Agustin, Cao, Chuanya, Cao, Guofu, Cao, Jun, Caruso, Rossella, Cerna, Cédric, Chang, Jinfan, Chang, Yun, Chen, Pingping, Chen, Po-An, Chen, Shaomin, Chen, Xurong, Chen, Yi-Wen, Chen, Yixue, Chen, Yu, Chen, Zhang, Cheng, Jie, Cheng, Yaping, Chetverikov, Alexey, Chiesa, Davide, Chimenti, Pietro, Chukanov, Artem, Claverie, Gérard, Clementi, Catia, Clerbaux, Barbara, Di Lorenzo, Selma Conforti, Corti, Daniele, Corso, Flavio Dal, Dalager, Olivia, De La Taille, Christophe, Deng, Zhi, Deng, Ziyan, Depnering, Wilfried, Diaz, Marco, Ding, Xuefeng, Ding, Yayun, Dirgantara, Bayu, Dmitrievsky, Sergey, Dohnal, Tadeas, Dolzhikov, Dmitry, Donchenko, Georgy, Dong, Jianmeng, Doroshkevich, Evgeny, Dracos, Marcos, Druillole, Frédéric, Du, Ran, Du, Shuxian, Dusini, Stefano, Dvorak, Martin, Enqvist, Timo, Enzmann, Heike, Fabbri, Andrea, Fahrendholz, Ulrike, Fan, Donghua, Fan, Lei, Fang, Jian, Fang, Wenxing, Fargetta, Marco, Fedoseev, Dmitry, Feng, Li-Cheng, Feng, Qichun, Ford, Richard, Fournier, Amélie, Gan, Haonan, Gao, Feng, Garfagnini, Alberto, Gavrikov, Arsenii, Giammarchi, Marco, Giaz, Agnese, Giudice, Nunzio, Gonchar, Maxim, Gong, Guanghua, Gong, Hui, Gornushkin, Yuri, Göttel, Alexandre, Grassi, Marco, Grewing, Christian, Gromov, Vasily, Gu, Minghao, Gu, Xiaofei, Gu, Yu, Guan, Mengyun, Guardone, Nunzio, Gul, Maria, Guo, Cong, Guo, Jingyuan, Guo, Wanlei, Guo, Xinheng, Guo, Yuhang, Hackspacher, Paul, Hagner, Caren, Han, Ran, Han, Yang, Hassan, Muhammad Sohaib, He, Miao, He, Wei, Heinz, Tobias, Hellmuth, Patrick, Heng, Yuekun, Herrera, Rafael, Hor, YuenKeung, Hou, Shaojing, Hsiung, Yee, Hu, Bei-Zhen, Hu, Hang, Hu, Jianrun, Hu, Jun, Hu, Shouyang, Hu, Tao, Hu, Yuxiang, Hu, Zhuojun, Huang, Chunhao, Huang, Guihong, Huang, Hanxiong, Huang, Wenhao, Huang, Xin, Huang, Xingtao, Huang, Yongbo, Hui, Jiaqi, Huo, Lei, Huo, Wenju, Huss, Cédric, Hussain, Safeer, Ioannisian, Ara, Isocrate, Roberto, Jelmini, Beatrice, Jen, Kuo-Lun, Jeria, Ignacio, Ji, Xiaolu, Ji, Xingzhao, Jia, Huihui, Jia, Junji, Jian, Siyu, Jiang, Di, Jiang, Wei, Jiang, Xiaoshan, Jin, Ruyi, Jing, Xiaoping, Jollet, Cécile, Joutsenvaara, Jari, Jungthawan, Sirichok, Kalousis, Leonidas, Kampmann, Philipp, Kang, Li, Karaparambil, Rebin, Kazarian, Narine, Khatun, Amina, Khosonthongkee, Khanchai, Korablev, Denis, Kouzakov, Konstantin, Krasnoperov, Alexey, Kruth, Andre, Kutovskiy, Nikolay, Kuusiniemi, Pasi, Lachenmaier, Tobias, Landini, Cecilia, Leblanc, Sébastien, Lebrin, Victor, Lefevre, Frederic, Lei, Ruiting, Leitner, Rupert, Leung, Jason, Li, Demin, Li, Fei, Li, Fule, Li, Gaosong, Li, Haitao, Li, Huiling, Li, Jiaqi, Li, Mengzhao, Li, Min, Li, Nan, Li, Qingjiang, Li, Ruhui, Li, Shanfeng, Li, Tao, Li, Weidong, Li, Weiguo, Li, Xiaomei, Li, Xiaonan, Li, Xinglong, Li, Yi, Li, Yichen, Li, Yufeng, Li, Zhaohan, Li, Zhibing, Li, Ziyuan, Liang, Hao, Liao, Jiajun, Liebau, Daniel, Limphirat, Ayut, Limpijumnong, Sukit, Lin, Guey-Lin, Lin, Shengxin, Lin, Tao, Ling, Jiajie, Lippi, Ivano, Liu, Fang, Liu, Haidong, Liu, Hongbang, Liu, Hongjuan, Liu, Hongtao, Liu, Hui, Liu, Jianglai, Liu, Jinchang, Liu, Min, Liu, Qian, Liu, Qin, Liu, Runxuan, Liu, Shuangyu, Liu, Shubin, Liu, Shulin, Liu, Xiaowei, Liu, Xiwen, Liu, Yan, Liu, Yunzhe, Lokhov, Alexey, Lombardi, Paolo, Lombardo, Claudio, Loo, Kai, Lu, Chuan, Lu, Haoqi, Lu, Jingbin, Lu, Junguang, Lu, Shuxiang, Lu, Xiaoxu, Lubsandorzhiev, Bayarto, Lubsandorzhiev, Sultim, Ludhova, Livia, Lukanov, Arslan, Luo, Fengjiao, Luo, Guang, Luo, Pengwei, Luo, Shu, Luo, Wuming, Lyashuk, Vladimir, Ma, Bangzheng, Ma, Qiumei, Ma, Si, Ma, Xiaoyan, Ma, Xubo, Maalmi, Jihane, Malyshkin, Yury, Mandujano, Roberto Carlos, Mantovani, Fabio, Manzali, Francesco, Mao, Xin, Mao, Yajun, Mari, Stefano M., Marini, Filippo, Marium, Sadia, Martellini, Cristina, Martin-Chassard, Gisele, Martini, Agnese, Mayer, Matthias, Mayilyan, Davit, Mednieks, Ints, Meng, Yue, Meregaglia, Anselmo, Meroni, Emanuela, Meyhöfer, David, Mezzetto, Mauro, Miller, Jonathan, Miramonti, Lino, Montini, Paolo, Montuschi, Michele, Müller, Axel, Nastasi, Massimiliano, Naumov, Dmitry V., Naumova, Elena, Navas-Nicolas, Diana, Nemchenok, Igor, Thi, Minh Thuan Nguyen, Ning, Feipeng, Ning, Zhe, Nunokawa, Hiroshi, Oberauer, Lothar, Ochoa-Ricoux, Juan Pedro, Olshevskiy, Alexander, Orestano, Domizia, Ortica, Fausto, Othegraven, Rainer, Paoloni, Alessandro, Parmeggiano, Sergio, Pei, Yatian, Pelliccia, Nicomede, Peng, Anguo, Peng, Haiping, Perrot, Frédéric, Petitjean, Pierre-Alexandre, Petrucci, Fabrizio, Pilarczyk, Oliver, Rico, Luis Felipe Piñeres, Popov, Artyom, Poussot, Pascal, Pratumwan, Wathan, Previtali, Ezio, Qi, Fazhi, Qi, Ming, Qian, Sen, Qian, Xiaohui, Qian, Zhen, Qiao, Hao, Qin, Zhonghua, Qiu, Shoukang, Rajput, Muhammad Usman, Ranucci, Gioacchino, Raper, Neill, Re, Alessandra, Rebber, Henning, Rebii, Abdel, Ren, Bin, Ren, Jie, Ricci, Barbara, Rifai, Mariam, Robens, Markus, Roche, Mathieu, Rodphai, Narongkiat, Romani, Aldo, Roskovec, Bedřich, Roth, Christian, Ruan, Xiangdong, Ruan, Xichao, Rujirawat, Saroj, Rybnikov, Arseniy, Sadovsky, Andrey, Saggese, Paolo, Sanfilippo, Simone, Sangka, Anut, Sanguansak, Nuanwan, Sawangwit, Utane, Sawatzki, Julia, Sawy, Fatma, Schever, Michaela, Schwab, Cédric, Schweizer, Konstantin, Selyunin, Alexandr, Serafini, Andrea, Settanta, Giulio, Settimo, Mariangela, Shao, Zhuang, Sharov, Vladislav, Shaydurova, Arina, Shi, Jingyan, Shi, Yanan, Shutov, Vitaly, Sidorenkov, Andrey, Šimkovic, Fedor, Sirignano, Chiara, Siripak, Jaruchit, Sisti, Monica, Slupecki, Maciej, Smirnov, Mikhail, Smirnov, Oleg, Sogo-Bezerra, Thiago, Sokolov, Sergey, Songwadhana, Julanan, Soonthornthum, Boonrucksar, Sotnikov, Albert, Šrámek, Ondřej, Sreethawong, Warintorn, Stahl, Achim, Stanco, Luca, Stankevich, Konstantin, Štefánik, Dušan, Steiger, Hans, Steinmann, Jochen, Sterr, Tobias, Stock, Matthias Raphael, Strati, Virginia, Studenikin, Alexander, Sun, Shifeng, Sun, Xilei, Sun, Yongjie, Sun, Yongzhao, Suwonjandee, Narumon, Szelezniak, Michal, Tang, Jian, Tang, Qiang, Tang, Quan, Tang, Xiao, Tietzsch, Alexander, Tkachev, Igor, Tmej, Tomas, Torri, Marco Danilo Claudio, Treskov, Konstantin, Triossi, Andrea, Troni, Giancarlo, Trzaska, Wladyslaw, Tuve, Cristina, Ushakov, Nikita, Boom, Johannes van den, van Waasen, Stefan, Vanroyen, Guillaume, Vedin, Vadim, Verde, Giuseppe, Vialkov, Maxim, Viaud, Benoit, Vollbrecht, Cornelius Moritz, Volpe, Cristina, Vorobel, Vit, Voronin, Dmitriy, Votano, Lucia, Walker, Pablo, Wang, Caishen, Wang, Chung-Hsiang, Wang, En, Wang, Guoli, Wang, Jian, Wang, Jun, Wang, Kunyu, Wang, Lu, Wang, Meifen, Wang, Meng, Wang, Ruiguang, Wang, Siguang, Wang, Wei, Wang, Wenshuai, Wang, Xi, Wang, Xiangyue, Wang, Yangfu, Wang, Yaoguang, Wang, Yi, Wang, Yifang, Wang, Yuanqing, Wang, Yuman, Wang, Zhe, Wang, Zheng, Wang, Zhimin, Wang, Zongyi, Waqas, Muhammad, Watcharangkool, Apimook, Wei, Lianghong, Wei, Wei, Wei, Wenlu, Wei, Yadong, Wen, Kaile, Wen, Liangjian, Wiebusch, Christopher, Wong, Steven Chan-Fai, Wonsak, Bjoern, Wu, Diru, Wu, Qun, Wu, Zhi, Wurm, Michael, Wurtz, Jacques, Wysotzki, Christian, Xi, Yufei, Xia, Dongmei, Xiao, Xiang, Xie, Xiaochuan, Xie, Yuguang, Xie, Zhangquan, Xing, Zhizhong, Xu, Benda, Xu, Cheng, Xu, Donglian, Xu, Fanrong, Xu, Hangkun, Xu, Jilei, Xu, Jing, Xu, Meihang, Xu, Yin, Xu, Yu, Yan, Baojun, Yan, Taylor, Yan, Wenqi, Yan, Xiongbo, Yan, Yupeng, Yang, Anbo, Yang, Changgen, Yang, Chengfeng, Yang, Huan, Yang, Jie, Yang, Lei, Yang, Xiaoyu, Yang, Yifan, Yao, Haifeng, Yasin, Zafar, Ye, Jiaxuan, Ye, Mei, Ye, Ziping, Yegin, Ugur, Yermia, Frédéric, Yi, Peihuai, Yin, Na, Yin, Xiangwei, You, Zhengyun, Yu, Boxiang, Yu, Chiye, Yu, Chunxu, Yu, Hongzhao, Yu, Miao, Yu, Xianghui, Yu, Zeyuan, Yu, Zezhong, Yuan, Chengzhuo, Yuan, Ying, Yuan, Zhenxiong, Yue, Baobiao, Zafar, Noman, Zambanini, Andre, Zavadskyi, Vitalii, Zeng, Shan, Zeng, Tingxuan, Zeng, Yuda, Zhan, Liang, Zhang, Aiqiang, Zhang, Feiyang, Zhang, Guoqing, Zhang, Haiqiong, Zhang, Honghao, Zhang, Jialiang, Zhang, Jiawen, Zhang, Jie, Zhang, Jin, Zhang, Jingbo, Zhang, Jinnan, Zhang, Peng, Zhang, Qingmin, Zhang, Shiqi, Zhang, Shu, Zhang, Tao, Zhang, Xiaomei, Zhang, Xin, Zhang, Xuantong, Zhang, Xueyao, Zhang, Yan, Zhang, Yinhong, Zhang, Yiyu, Zhang, Yongpeng, Zhang, Yu, Zhang, Yuanyuan, Zhang, Yumei, Zhang, Zhenyu, Zhang, Zhijian, Zhao, Fengyi, Zhao, Jie, Zhao, Rong, Zhao, Shujun, Zhao, Tianchi, Zheng, Dongqin, Zheng, Hua, Zheng, Yangheng, Zhong, Weirong, Zhou, Jing, Zhou, Li, Zhou, Nan, Zhou, Shun, Zhou, Tong, Zhou, Xiang, Zhu, Jiang, Zhu, Kangfu, Zhu, Kejun, Zhu, Zhihang, Zhuang, Bo, Zhuang, Honglin, Zong, Liang, and Zou, Jiaheng
Subjects: High Energy Physics - Experiment, High Energy Physics - Phenomenology
Abstract: The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel., Comment: 14 pages, 12 figures, an author added
Published: 2022
Full Text: View/download PDF

47. Validation and integration tests of the JUNO 20-inch PMTs readout electronics

Author: Cerrone, Vanessa, von Sturm, Katharina, Bellato, Marco, Bergnoli, Antonio, Bolognesi, Matteo, Brugnera, Riccardo, Chen, Chao, Clerbaux, Barbara, Coppi, Alberto, Corso, Flavio dal, Corti, Daniele, Dong, Jianmeng, Dou, Wei, Fan, Lei, Garfagnini, Alberto, Gong, Guanghua, Grassi, Marco, Hang, Shuang, Guizzetti, Rosa Maria, He, Cong, Hu, Jun, Isocrate, Roberto, Jelmini, Beatrice, Ji, Xiaolu, Jiang, Xiaoshan, Li, Fei, Liang, Zehong, Lippi, Ivano, Liu, Hongbang, Liu, Hongbin, Liu, Shenghui, Liu, Xuewei, Luo, Daibin, Luo, Ronghua, Marini, Filippo, Mazzaro, Daniele, Modenese, Luciano, Ning, Zhe, Peng, Yu, Petitjean, Pierre-Alexandre, Pitacco, Alberto, Qi, Mengyao, Ramina, Loris, Rampazzo, Mirco, Rebeschini, Massimo, Redchuk, Mariia, Serafini, Andrea, Sun, Yunhua, Triossi, Andrea, Triozzi, Riccardo, Veronese, Fabio, Wang, Peiliang, Wang, Peng, Wang, Yangfu, Wang, Yusheng, Wang, Yuyi, Wang, Zheng, Wei, Ping, Weng, Jun, Xian, Shishen, Xie, Xiaochuan, Xu, Benda, Xu, Chuang, Xu, Donglian, Xu, Hai, Yan, Xiongbo, Yan, Ziyue, Yang, Fengfan, Yang, Yan, Yang, Yifan, Ye, Mei, Zeng, Tingxuan, Zhang, Shuihan, Zhang, Wei, Zhang, Aiqiang, Zhang, Bin, Zhao, Siyao, Zi, Changge, Aiello, Sebastiano, Andronico, Giuseppe, Antonelli, Vito, Barresi, Andrea, Basilico, Davide, Beretta, Marco, Brigatti, Augusto, Bruno, Riccardo, Budano, Antonio, Caccianiga, Barbara, Cammi, Antonio, Campese, Stefano, Chiesa, Davide, Clementi, Catia, Cordelli, Marco, Dusini, Stefano, Fabbri, Andrea, Felici, Giulietto, Ferraro, Federico, Giammarchi, Marco G., Landini, Cecilia, Lombardi, Paolo, Lombardo, Claudio, Maino, Andrea, Mantovani, Fabio, Mari, Stefano Maria, Martini, Agnese, Meroni, Emanuela, Miramonti, Lino, Montuschi, Michele, Nastasi, Massimiliano, Orestano, Domizia, Ortica, Fausto, Paoloni, Alessandro, Parmeggiano, Sergio, Petrucci, Fabrizio, Previtali, Ezio, Ranucci, Gioacchino, Re, Alessandra Carlotta, Ricci, Barbara, Romani, Aldo, Saggese, Paolo, Sanfilippo, Simone, Sirignano, Chiara, Sisti, Monica, Stanco, Luca, Strati, Virginia, Tortorici, Francesco, Tuvé, Cristina, Venettacci, Carlo, Verde, Giuseppe, and Votano, Lucia
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: The Jiangmen Underground Neutrino Observatory (JUNO) is a large neutrino detector currently under construction in China. JUNO will be able to study the neutrino mass ordering and to perform leading measurements detecting terrestrial and astrophysical neutrinos in a wide energy range, spanning from 200 keV to several GeV. Given the ambitious physics goals of JUNO, the electronic system has to meet specific tight requirements, and a thorough characterization is required. The present paper describes the tests performed on the readout modules to measure their performances., Comment: 20 pages, 13 figures
Published: 2022
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48. Bayesian modelling of the temporal evolution of seismicity using the ETAS.inlabru R-package

Author: Naylor, Mark, Serafini, Francesco, Lindgren, Finn, and Main, Ian
Subjects: Statistics - Applications
Abstract: The Epidemic Type Aftershock Sequence (ETAS) model is widely used to model seismic sequences and underpins Operational Earthquake Forecasting (OEF). However, it remains challenging to assess the reliability of inverted ETAS parameters for a range of reasons. The most common algorithms just return point estimates with little quantification of uncertainty, and Bayesian Markov Chain Monte Carlo implementations remain slow to run, do not scale well and few have been extended to include spatial structure. Here we present a new approach to ETAS modelling using an alternative Bayesian method, the Integrated Nested Laplace Approximation (INLA). We have implemented this model in a new R-Package called ETAS.inlabru, which builds on the R packages R-INLA and inlabru . Whilst we just present the temporal component here, the model scales to a spatio-temporal model and may include a variety of spatial covariates. Using a series of synthetic case studies, we explore the robustness of our ETAS inversion method. We demonstrate that reliable estimates of the model parameters require that the catalogue data contains periods of relative quiescence as well as triggered sequences. We explore the robustness under stochastic uncertainty in the training data and show that the method is robust to a wide range of starting conditions. We show how the inclusion of historic earthquakes prior to the modelled domain affects the quality of the inversion. Finally, we show that rate dependent incompleteness after large earthquakes has a significant and detrimental effect on the ETAS posteriors. We believe that the speed of the inlabru inversion, which include a rigorous estimation of uncertainty, will enable a deeper exploration of how to use ETAS robustly for seismicity modelling and operational earthquake forecasting.
Published: 2022

49. Exploiting Proximity-Aware Tasks for Embodied Social Navigation

Author: Cancelli, Enrico, Campari, Tommaso, Serafini, Luciano, Chang, Angel X., and Ballan, Lamberto
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Robotics
Abstract: Learning how to navigate among humans in an occluded and spatially constrained indoor environment, is a key ability required to embodied agent to be integrated into our society. In this paper, we propose an end-to-end architecture that exploits Proximity-Aware Tasks (referred as to Risk and Proximity Compass) to inject into a reinforcement learning navigation policy the ability to infer common-sense social behaviors. To this end, our tasks exploit the notion of immediate and future dangers of collision. Furthermore, we propose an evaluation protocol specifically designed for the Social Navigation Task in simulated environments. This is done to capture fine-grained features and characteristics of the policy by analyzing the minimal unit of human-robot spatial interaction, called Encounter. We validate our approach on Gibson4+ and Habitat-Matterport3D datasets.
Published: 2022

50. The optically elusive, changing-look active nucleus in NGC 4156

Author: Tozzi, Giulia, Lusso, Elisabeta, Casetti, Lapo, Romoli, Marco, Andreuzzi, Gloria, A., Isabel Montoya, Nardini, Emanuele, Cresci, Giovanni, Middei, Riccardo, Bertolini, Silvia, Calabretto, Paolo, Cammelli, Vieri, Cuadra, Francisco, Ragione, Marco Dalla, Marconcini, Cosimo, Miceli, Adriano, Mini, Irene, Palazzini, Martina, Rotellini, Giorgio, Saccardi, Andrea, Samà, Lavinia, Sangalli, Mattia, Serafini, Lorenzo, and Spaccino, Fabio
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We report on the changing-look nature of the active galactic nucleus (AGN) in the galaxy NGC 4156, as serendipitously discovered thanks to data acquired in 2019 at the Telescopio Nazionale Galileo (TNG) during a students' observing programme. Previous optical spectra had never shown any signatures of broad-line emission, and evidence of the AGN had come only from X-ray observations, being the optical narrow-line flux ratios unable to unambiguously denote this galaxy as a Seyfert. Our 2019 TNG data unexpectedly revealed the appearance of broad-line components in both the H$\alpha$ and H$\beta$ profiles, along with a rise of the continuum, thus implying a changing-look AGN transitioning from a type 2 (no broad-line emission) towards a (nearly) type 1. The broad-line emission has then been confirmed by our 2022 follow-up observations, whereas the rising continuum has no longer been detected, which hints at a further evolution backwards to a (nearly) type 2. The presence of broad-line components also allowed us to obtain the first single-epoch estimate of the black hole mass (log(MBH/Msun) $\sim$ 8.1) in this source. The observed spectral variability might be the result of a change in the accretion activity of NGC 4156, although variable absorption cannot be completely excluded., Comment: 9 pages, 6 figures. Accepted for publication in A&A Letters
Published: 2022
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