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1. Calibration strategy of the JUNO-TAO experiment

Author

Hangkun Xu, Angel Abusleme, Nikolay V. Anfimov, Stéphane Callier, Agustin Campeny, Guofu Cao, Jun Cao, Cedric Cerna, Yu Chen, Alexander Chepurnov, Yayun Ding, Frederic Druillole, Andrea Fabbri, Zhengyong Fei, Maxim Gromov, Miao He, Wei He, Yuanqiang He, Joseph Y. K. Hor, Shaojing Hou, Jianrun Hu, Jun Hu, Cédric Huss, Xiaolu Ji, Tao Jiang, Xiaoshan Jiang, Cécile Jolliet, Daozheng Li, Min Li, Ruhui Li, Yichen Li, Caimei Liu, Mengchao Liu, Yunzhe Liu, Claudio Lombardo, Selma Conforti Di Lorenzo, Peizhi Lu, Guang Luo, Stefano M. Mari, Xiaoyan Ma, Paolo Montini, Juan Pedro Ochoa-Ricoux, Yatian Pei, Frédéric Perrot, Fabrizio Petrucci, Xiaohui Qian, Abdel Rebii, Bedr̆ich Roskovec, Arsenij Rybnikov, Hans Steiger, Xilei Sun, Pablo Walker, Derun Wang, Meifen Wang, Wei Wang, Zhimin Wang, Diru Wu, Xiang Xiao, Yuguang Xie, Zhangquan Xie, Wenqi Yan, Huan Yang, Haifeng Yao, Mei Ye, Chengzhuo Yuan, Kirill Zamogilnyi, Liang Zhan, Jie Zhang, Shuihan Zhang, and Rong Zhao

Subjects
Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract The Taishan Antineutrino Observatory (TAO or JUNO-TAO) is a satellite experiment of the Jiangmen Underground Neutrino Observatory (JUNO). Located near a reactor of the Taishan Nuclear Power Plant, TAO will measure the reactor antineutrino energy spectrum with an unprecedented energy resolution of $$

Published
2022
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2. Potential for a precision measurement of solar pp neutrinos in the Serappis experiment

Author

Lukas Bieger, Thilo Birkenfeld, David Blum, Wilfried Depnering, Timo Enqvist, Heike Enzmann, Feng Gao, Christoph Genster, Alexandre Göttel, Christian Grewing, Maxim Gromov, Paul Hackspacher, Caren Hagner, Tobias Heinz, Philipp Kampmann, Michael Karagounis, Andre Kruth, Pasi Kuusiniemi, Tobias Lachenmaier, Daniel Liebau, Runxuan Liu, Kai Loo, Livia Ludhova, David Meyhöfer, Axel Müller, Pavithra Muralidharan, Lothar Oberauer, Rainer Othegraven, Nina Parkalian, Yatian Pei, Oliver Pilarczyk, Henning Rebber, Markus Robens, Christian Roth, Julia Sawatzki, Konstantin Schweizer, Giulio Settanta, Maciej Slupecki, Oleg Smirnov, Achim Stahl, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Jian Tang, Eric Theisen, Alexander Tietzsch, Wladyslaw Trzaska, Johannes van den Boom, Stefan van Waasen, Cornelius Vollbrecht, Christopher Wiebusch, Bjoern Wonsak, Michael Wurm, Christian Wysotzki, Yu Xu, Ugur Yegin, Andre Zambanini, and Jan Züfle

Subjects
Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract The Serappis (SEarch for RAre PP-neutrinos In Scintillator) project aims at a precision measurement of the flux of solar pp neutrinos on the few-percent level. Such a measurement will be a relevant contribution to the study of solar neutrino oscillation parameters and a sensitive test of the equilibrium between solar energy output in neutrinos and electromagnetic radiation (solar luminosity constraint). The concept of Serappis relies on a small organic liquid scintillator detector ( $$\sim $$ ∼ 20 m $$^3$$ 3 ) with excellent energy resolution ( $$\sim $$ ∼ 2.5% at 1 MeV), low internal background and sufficient shielding from surrounding radioactivity. This can be achieved by a minor upgrade of the OSIRIS facility at the site of the JUNO neutrino experiment in southern China. To go substantially beyond current accuracy levels for the pp flux, an organic scintillator with ultra-low $$ {^{14}\hbox {C}}$$ 14 C levels (below $$10^{-18}$$ 10 - 18 ) is required. The existing OSIRIS detector and JUNO infrastructure will be instrumental in identifying suitable scintillator materials, offering a unique chance for a low-budget high-precision measurement of a fundamental property of our Sun that will be otherwise hard to access.

Published
2022
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3. Model-independent Approach of the JUNO 8B Solar Neutrino Program

Author

Jie Zhao, Baobiao Yue, Haoqi Lu, Yufeng Li, Jiajie Ling, Zeyuan Yu, Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Abid Aleem, Tsagkarakis Alexandros, Fengpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Weidong Bai, Nikita Balashov, Wander Baldini, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Bellato, Antonio Bergnoli, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Jose Busto, Ilya Butorov, Anatael Cabrera, Barbara Caccianiga, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Riccardo Callegari, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Chi Chan, Jinfan Chang, Yun Chang, Guoming Chen, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yixue Chen, Yu Chen, Zhiyuan Chen, Zikang Chen, Jie Cheng, Yaping Cheng, Alexander Chepurnov, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Marta Colomer Molla, Selma Conforti Di Lorenzo, Daniele Corti, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Dmitry Dolzhikov, Georgy Donchenko, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Ran Du, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Donghua Fan, Lei Fan, Jian Fang, Wenxing Fang, Marco Fargetta, Dmitry Fedoseev, Zhengyong Fei, Li-Cheng Feng, Qichun Feng, Richard Ford, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Arsenii Gavrikov, Marco Giammarchi, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Yuri Gornushkin, Alexandre Göttel, Marco Grassi, Maxim Gromov, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Yuduo Guan, Nunzio Guardone, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Yuxiang Hu, Zhuojun Hu, Guihong Huang, Hanxiong Huang, Kaixuan Huang, Wenhao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Ignacio Jeria, Xiaolu Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Wei Jiang, Xiaoshan Jiang, Xiaoping Jing, Cécile Jollet, Leonidas Kalousis, Philipp Kampmann, Li Kang, Rebin Karaparambil, Narine Kazarian, Amina Khatun, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, 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, Zepeng Li, Zhaohan Li, Zhibing Li, Ziyuan Li, Zonghai Li, Hao Liang, Jiajun Liao, Ayut Limphirat, Guey-Lin Lin, Shengxin Lin, Tao Lin, Ivano Lippi, 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 Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Arslan Lukanov, Daibin Luo, Fengjiao Luo, Guang Luo, Shu Luo, Wuming Luo, Xiaojie Luo, Vladimir Lyashuk, Bangzheng Ma, Bing Ma, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Jingyu Mai, Yury Malyshkin, Roberto Carlos Mandujano, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Matthias Mayer, Davit Mayilyan, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Paolo Montini, Michele Montuschi, Axel Müller, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, Minh Thuan Nguyen Thi, Alexey Nikolaev, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Alessandro Paoloni, Sergio Parmeggiano, Yatian Pei, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Yu Peng, Zhaoyuan Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Luis Felipe Piñeres Rico, Artyom Popov, Pascal Poussot, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhen Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Mariia Redchuk, Bin Ren, Jie Ren, Barbara Ricci, Mariam Rifai, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Xichao Ruan, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Simone Sanfilippo, Anut Sangka, Utane Sawangwit, Julia Sawatzki, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Arina Shaydurova, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondřej Šrámek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Jun Su, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Zhengyang Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Marco Danilo Claudio Torri, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Nikita Ushakov, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Cornelius Moritz Vollbrecht, Cristina Volpe, Katharina von Sturm, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Pablo Walker, 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 Wang, Apimook Watcharangkool, Wei Wei, Wenlu Wei, Yadong Wei, Kaile Wen, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Qun Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Xiang Xiao, Xiaochuan Xie, Yuguang Xie, Zhangquan Xie, Zhao Xin, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Hangkun Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Taylor Yan, Wenqi Yan, Xiongbo Yan, Yupeng Yan, Changgen Yang, Chengfeng Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Jiaxuan Ye, Mei Ye, Ziping Ye, Frédéric Yermia, Na Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zezhong Yu, Cenxi Yuan, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Noman Zafar, Vitalii Zavadskyi, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, 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, Xueyao Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yu Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Rong Zhao, Runze Zhao, Shujun Zhao, Dongqin Zheng, Hua Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Jiang Zhu, Jingsen Zhu, Kangfu Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, and Jiaheng Zou

Subjects
Solar neutrinos, Astrophysics, QB460-466
Abstract

The physics potential of detecting ^8 B solar neutrinos will be exploited at the Jiangmen Underground Neutrino Observatory (JUNO), in a model-independent manner by using three distinct channels of the charged current (CC), neutral current (NC), and elastic scattering (ES) interactions. Due to the largest-ever mass of ^13 C nuclei in the liquid scintillator detectors and the expected low background level, ^8 B solar neutrinos are observable in the CC and NC interactions on ^13 C for the first time. By virtue of optimized event selections and muon veto strategies, backgrounds from the accidental coincidence, muon-induced isotopes, and external backgrounds can be greatly suppressed. Excellent signal-to-background ratios can be achieved in the CC, NC, and ES channels to guarantee the observation of the ^8 B solar neutrinos. From the sensitivity studies performed in this work, we show that JUNO, with 10 yr of data, can reach the 1 σ precision levels of 5%, 8%, and 20% for the ^8 B neutrino flux, ${\sin }^{2}{\theta }_{12}$ , and ${\rm{\Delta }}{m}_{21}^{2}$ , respectively. Probing the details of both solar physics and neutrino physics would be unique and helpful. In addition, when combined with the Sudbury Neutrino Observatory measurement, the world's best precision of 3% is expected for the measurement of the ^8 B neutrino flux.

Published
2024
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4. Hybrid Ultra-Low-Radioactive Material for Protecting Dark Matter Detector from Background Neutrons

Author

Marina Zykova, Mikhail Grishechkin, Andrew Khomyakov, Elena Mozhevitina, Roman Avetisov, Nadezda Surikova, Maxim Gromov, Alexander Chepurnov, Ivan Nikulin, and Igor Avetissov

Subjects
polymethylmethacrylate, gadolinium, uranium, thorium, hybrid material, inductively coupled plasma mass spectrometry, Technology, Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Engineering (General). Civil engineering (General), TA1-2040, Microscopy, QH201-278.5, Descriptive and experimental mechanics, QC120-168.85
Abstract

A laboratory technology for a new ultra-low background hybrid material (HM) which meets the requirements for neutron absorption with simultaneous neutron detection has been developed. The technology and hybrid material can be useful for future low background underground detectors designed to directly search for dark matter with liquid noble gases. The HM is based on a polymethylmethacrylate (PMMA) polymer matrix in which gadolinium nuclei are homogeneously distributed up to 1.5 wt% concentration in polymer slabs of 5 cm thickness. To determine the 65 impurity elements by the inductively coupled plasma mass-spectrometry (ICP-MS) technique in the Gd-based preparations in 100–0.01 ppb range, the corresponding method has been developed. Limits of determination (LD) of 0.011 ppb for uranium, and 0.016 ppb for thorium were achieved. An analysis of Gd raw materials showed that the lowest contents of U and Th (1.2–0.2 ppb) were detected in commercial Gd-based preparations. They were manufactured either from secondary raw materials (extraction phosphoric acid) or from mineral raw materials formed in sedimentary rocks (phosphogypsum). To produce the Gd-doped HM the commercial GdCl3 was purified and used for synthesis of low-background coordination compound, namely, acetylacetonate gadolinium (Gd(acac)3) with U/Th contents less than LD. When dissolving Gd(acac)3 in methylmethacrylate, the true solution was obtained and its further thermal polymerization allowed fabrication of the Gd-doped PMMA with ultra-low background.

Published
2021
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5. Solar Neutrinos Spectroscopy with Borexino Phase-II

Author

Lino Miramonti, Matteo Agostini, Konrad Altenmueller, Simon Appel, Victor Atroshchenko, Zara Bagdasarian, Davide Basilico, Gianpaolo Bellini, Jay Benziger, Daniel Bick, Irene Bolognino, Giuseppe Bonfini, David Bravo, Barbara Caccianiga, Frank Calaprice, Alessio Caminata, Silvia Caprioli, Marco Carlini, Paolo Cavalcante, Francesca Cavanna, Alexander Chepurnov, Koun Choi, Laura Collica, Stefano Davini, Alexander Derbin, XueFeng Ding, Antonio Di Ludovico, Lea Di Noto, Ilia Drachnev, Kirill Fomenko, Andrey Formozov, Davide Franco, Federico Gabriele, Cristiano Galbiati, Michael Gschwender, Chiara Ghiano, Marco Giammarchi, Augusto Goretti, Maxim Gromov, Daniele Guffanti, Caren Hagner, Thibaut Houdy, Ed Hungerford, Aldo Ianni, Andrea Ianni, Anna Jany, Dominik Jeschke, Vladislav Kobychev, Denis Korablev, Gyorgy Korga, Tobias Lachenmaier, Matthias Laubenstein, Evgeny Litvinovich, Francesco Lombardi, Paolo Lombardi, Livia Ludhova, Georgy Lukyanchenko, Liudmila Lukyanchenko, Igor Machulin, Giulio Manuzio, Simone Marcocci, Jelena Maricic, Johann Martyn, Emanuela Meroni, Mikko Meyer, Marcin Misiaszek, Valentina Muratova, Birgit Neumair, Lothar Oberauer, Bjoern Opitz, Vsevolod Orekhov, Fausto Ortica, Marco Pallavicini, Laszlo Papp, Omer Penek, Lidio Pietrofaccia, Nelly Pilipenko, Andrea Pocar, Alessio Porcelli, Georgy Raikov, Gioacchino Ranucci, Alessandro Razeto, Alessandra Re, Mariia Redchuk, Aldo Romani, Nicola Rossi, Sebastian Rottenanger, Stefan Schöenert, Dmitrii Semenov, Mikhail Skorokhvatov, Oleg Smirnov, Albert Sotnikov, Lee F. F. Stokes, Yura Suvorov, Roberto Tartaglia, Gemma Testera, Jan Thurn, Maria Toropova, Evgenii Unzhakov, Alina Vishneva, Bruce Vogelaar, Franz von Feilitzsch, Stefan Weinz, Marcin Wojcik, Michael Wurm, Zachary Yokley, Oleg Zaimidoroga, Sandra Zavatarelli, Kai Zuber, and Grzegorz Zuzel

Subjects
solar neutrinos, neutrino oscillation, Borexino, Elementary particle physics, QC793-793.5
Abstract

Solar neutrinos have played a central role in the discovery of the neutrino oscillation mechanism. They still are proving to be a unique tool to help investigate the fusion reactions that power stars and further probe basic neutrino properties. The Borexino neutrino observatory has been operationally acquiring data at Laboratori Nazionali del Gran Sasso in Italy since 2007. Its main goal is the real-time study of low energy neutrinos (solar or originated elsewhere, such as geo-neutrinos). The latest analysis of experimental data, taken during the so-called Borexino Phase-II (2011-present), will be showcased in this talk—yielding new high-precision, simultaneous wide band flux measurements of the four main solar neutrino components belonging to the “pp„ fusion chain (pp, pep, 7 Be, 8 B), as well as upper limits on the remaining two solar neutrino fluxes (CNO and hep).

Published
2018
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6. The measurement of the geo-neutrino flux with the Borexino detector and its geophysical implications

Author

Maxim Gromov and Sindhujha Kumaran

Abstract

The new Borexino geo-neutrino analysis includes the well-optimized cuts and increased dataset. Consequently, the exposure is doubled providing $(1.29\pm0.05)\times10^{32}$ protons$\cdot$year. The geo-neutrino signal equals $47.0_{-7.7}^{+8.4}$ (stat) $_{-1.9}^{+2.4}$ (sys) TNU corresponding to $_{-17.2}^{+18.3}\%$ total precision. The mantle signal of $21.2_{-9.0}^{+9.6}$ (stat) $_{-0.9}^{+1.1}$ (sys) TNU is derived using the geological knowledge of the local and far field lithosphere. The null-hypothesis is excluded at $99.0\%$ C.L. The total radiogenic heat of $38.2_{-12.7}^{+13.6}$ TW is obtained. The predictions of the lowest concentration of heat-producing elements in the mantle are slightly disfavored ($\sim2.4\sigma$). The constraint on the hypothetical georeactor power is $2.4$ TW at $95\%$ C.L. if located at the Earth's center.

Published
2020
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7. Minimizing Deterministic Timed Finite State Machines

Author

Maxim Gromov, Tiziano Villa, Aleksandr Tvardovskii, Nina Yevtushenko, and Davide Bresolin

Subjects
Theoretical computer science, Finite-state machine, конечные автоматы, Computer science, Timed Finite State Machines Minimization Real-time systems Automata theory Timed Automata, минимизация, 020207 software engineering, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, Minimization, Automaton, временные автоматы, 010201 computation theory & mathematics, Control and Systems Engineering, теория автоматов, 0202 electrical engineering, electronic engineering, information engineering, Automata theory, Real-time systems, Timed Automata, Timed Finite State Machines, State (computer science), Timeout, Abstraction (linguistics)
Abstract

Timed automata and timed finite state machins (TFSMs) have been proposed to represent more accurately the behaviour of systems in continuous time. Recently, we introduced a model of TFSMs that extends the expressive power of FSMs by introducing a single clock, timed guards which restrict when the input/output transitions may happen, and timeouts on the transitions. We derived an abstraction procedure to convert a TFSM into an equivalent untimed FSM. Here, we extend the model with output timeouts and derive a minimal form for deterministic TFSMs that reduces the number of states, the number of transitions and the timeout values at each state.

Published
2018

8. Derivation of the cascade parallel composition of timed finite state machines using BALM-II

Author

Maxim Gromov and Natalia Shabaldina

Subjects
0209 industrial biotechnology, Infinite set, Finite-state machine, Series (mathematics), Computer science, бинарная параллельная композиция, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, Automaton, Set (abstract data type), 020901 industrial engineering & automation, временные автоматы, 010201 computation theory & mathematics, Control and Systems Engineering, Cascade, Signal Processing, Applied mathematics, Constant (mathematics), каскадная параллельная композиция, Finite set, Software
Abstract

The paper considers the problem of deriving a cascade parallel composition of timed finite state machines (TFSMs). It can be reduced to a step-by-step derivation of a binary parallel composition. It is known that if each component of the binary parallel composition is a TFSM with constant output delays, then the composition can result in a TFSM with an infinite set of output delays given by a finite set of linear functions. Therefore, the problem of deriving a cascade composition of TFSMs with constant output delays is reduced to deriving a series of binary parallel compositions of TFSMs with output delays given either as constants or as a set of linear functions. In this paper, we refine the definition of the TFSM with particular attention to the description of the output delay. BALM-II is used as an instrument for deriving the composition. Therefore, we consider the transition from a TFSM with output delays given as a set of linear functions to the corresponding automaton. We propose a new procedure for deriving an automaton. Unlike the known procedure, it does not require subsequent determinization of the derived automaton. In addition, we provide a step-by-step description of how to derive the composition of the corresponding automata using BALM-II, discuss the procedure of reverse transformation from the automaton of the composition to the TFSM, and note some aspects associated with the composition of TFSMs with output delays as a set of linear functions. An example that illustrates the derivation of the cascade parallel composition of TFSMs is given.

Published
2017

9. Distinguishing Experiments for Timed Nondeterministic Finite State Machines

Author

Nina Yevtushenko, Maxim Gromov, Natalia Shabaldina, and Khaled El-Fakih

Subjects
Sequence, Information Systems and Management, Finite-state machine, Intersection (set theory), Management Science and Operations Research, Theoretical Computer Science, Separable space, Nondeterministic algorithm, Computer Science (miscellaneous), Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Algorithm, Software, Mathematics, Abstraction (linguistics)
Abstract

The problem of constructing distinguishing experiments is a fundamental problem in the area of finite state machines (FSMs), especially for FSM-based testing. In this paper, the problem is studied for timed nondeterministic FSMs (TFSMs) with output delays. Given two TFSMs, we derive the TFSM intersection of these machines and show that the machines can be distinguished using an appropriate (untimed) FSM abstraction of the TFSM intersection. The FSM abstraction is derived by constructing appropriate partitions for the input and output time domains of the TFSM intersection. Using the obtained abstraction, a traditional FSM-based preset algorithm can be used for deriving a separating sequence for the given TFSMs if these machines are separable. Moreover, as sometimes two non-separable TFSMs can still be distinguished by an adaptive experiment, based on the FSM abstraction we present an algorithm for deriving an r-distinguishing TFSM that represents a corresponding adaptive experiment.

Published
2013

11. Novel heuristics for deconvolution applied to picture deblurring

Author

Evgeniya Olenuk and Maxim Gromov

Subjects
Deblurring, business.industry, Function (mathematics), Division (mathematics), Convolution, symbols.namesake, Fourier transform, symbols, Computer vision, Artificial intelligence, Deconvolution, Convolution theorem, business, Heuristics, Mathematics
Abstract

In this paper we describe an implementation of a method for blurred pictures restoring. We consider uniform, linear photo-camera shift (movement) while picture is taken. In this case, a picture, formed on a chip of a camera, is not static, but moving along some straight line, and as a result photo is blurred. Blurred picture can be seen as a convolution of two functions – one describes initial picture, another is point-spread (or blurring) function (PSF) [1]–[3]. “Deblurred” picture can be found as a deconvolution of the given picture with known PSF [1], [2]. To do this it is convenient to use Fourier transform and apply the convolution theorem. But it leads to division by 0, and thus the method is unstable. We suggest two heuristics to avoid division by 0 and compare them with the known one.

Published
2012

12. Observable Form of a Timed Finite State Machine

Author

Olga Kondratjeva and Maxim Gromov

Subjects
Finite-state machine, Computer science, Observable, Algorithm, Value (mathematics)
Abstract

This paper is devoted to the problem of an observable form for a given Timed Finite State Machine. This problem, together with the problem of the number of states in the observable form, has theoretical value, since it shows the way to build an observable form, and answers the question, does an observable form exist for any TFSM. Also it has a practical use in testing, since Finite State Machine methods of test generation rely on the fact that specification of a system is an observable FSM and those methods are intended to be applied for TFSMs.

Published
2010

13. Distinguing Non-deterministic Timed Finite State Machines

Author

Khaled El-Fakih, Maxim Gromov, Nina Yevtushenko, and Natalia Shabaldina

Subjects
Infinite number, Finite-state machine, Adaptive algorithm, Computer science, Fault coverage, System requirements specification, Hardware_PERFORMANCEANDRELIABILITY, State (computer science), Conformance testing, Algorithm, Separable space
Abstract

Conformance testing with the guaranteed fault coverage is based on distinguishing faulty system implementations from the corresponding system specification. We consider timed systems modeled by timed possibly non-deterministic finite state machines (TFSMs) and propose algorithms for distinguishing two TFSMs. In particular, we present a preset algorithm for separating two separable TFSMs and an adaptive algorithm for r -distinguishing two possibly non-separable TFSMs. The proposed techniques extend existing methods for untimed non-deterministic FSMs by dealing with the fact that unlike untimed FSMs in general, a TFSM has an infinite number of timed inputs. Correspondingly we state that the upper bounds on the length of distinguishing sequences are the same as for untimed FSMs.

Published
2009

14. Software Package for Optimizing Digital Circuits

Author

Natalya Kushik and Maxim Gromov

Subjects
Digital electronics, Flexibility (engineering), Path length, business.industry, Fragment (computer graphics), Computer science, Simple (abstract algebra), Frame (networking), Function (mathematics), business, Software package, Computer hardware, Simulation
Abstract

In this paper, we describe a software tool for optimizing the path length from primary inputs to primary outputs as well as the number of gates in digital circuits. A frame for optimization is extracted from a digital circuit the extracted frame is divided into two parts and the maximum flexibility for each part is determined by the largest solution to an appropriate FSM equation. We check whether one or some output functions of each part can be replaced by a simple function of two primary input variables that can be implemented as a single gate, while preserving the behavior of the overall fragment. A developed software package can deal with digital circuits which have around 500 gates, and 40 primary inputs and outputs. Experiments were performed for a pack of benchmarks that were first resynthesised by ABC tool [1]. Our results show that the developed package can improve around 15% of benchmarks.

Published
2009

15. A novel method for derivation of a test with guaranteed coverage for LTS

Author

Maxim Gromov

Subjects
Transformation (function), Computer science, Fault coverage, Test suite, Computerized adaptive testing, Algorithm, Test (assessment)
Abstract

The paper addresses the problem of the relationship between tests with the guaranteed fault coverage which are derived from two models of finite transition systems: LTS with inputs and outputs and input/output FSM. On one hand, there are well developed methods for deriving such finite tests against FSM while the model of input/output LTSs lacks such methods. On the other hand, almost all FSM-based methods return preset test suites and there are no good FSM-based methods for deriving adaptive tests. For deriving adaptive tests, it is worth to use LTS model where all the methods return adaptive test suites. We propose the transformation between two models and show how a complete test suite with respect to one model can be transformed into a complete test suite with respect to another model.

Published
2008

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