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  1. Article: Verification of a neuromorphic computing network simulator using experimental traffic data.

    Kleijnen, Robert / Robens, Markus / Schiek, Michael / van Waasen, Stefan

    Frontiers in neuroscience

    2022  Volume 16, Page(s) 958343

    Abstract: Simulations are a powerful tool to explore the design space of hardware systems, offering the flexibility to analyze different designs by simply changing parameters within the simulator setup. A precondition for the effectiveness of this methodology is ... ...

    Abstract Simulations are a powerful tool to explore the design space of hardware systems, offering the flexibility to analyze different designs by simply changing parameters within the simulator setup. A precondition for the effectiveness of this methodology is that the simulation results accurately represent the real system. In a previous study, we introduced a simulator specifically designed to estimate the network load and latency to be observed on the connections in neuromorphic computing (NC) systems. The simulator was shown to be especially valuable in the case of large scale heterogeneous neural networks (NNs). In this work, we compare the network load measured on a SpiNNaker board running a NN in different configurations reported in the literature to the results obtained with our simulator running the same configurations. The simulated network loads show minor differences from the values reported in the ascribed publication but fall within the margin of error, considering the generation of the test case NN based on statistics that introduced variations. Having shown that the network simulator provides representative results for this type of -biological plausible-heterogeneous NNs, it also paves the way to further use of the simulator for more complex network analyses.
    Language English
    Publishing date 2022-08-08
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2411902-7
    ISSN 1662-453X ; 1662-4548
    ISSN (online) 1662-453X
    ISSN 1662-4548
    DOI 10.3389/fnins.2022.958343
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Model-Based Correction of Temperature-Dependent Measurement Errors in Frequency Domain Electromagnetic Induction (FDEMI) Systems.

    Tazifor, Martial / Zimmermann, Egon / Huisman, Johan Alexander / Dick, Markus / Mester, Achim / Van Waasen, Stefan

    Sensors (Basel, Switzerland)

    2022  Volume 22, Issue 10

    Abstract: Data measured using electromagnetic induction (EMI) systems are known to be susceptible to measurement influences associated with time-varying external ambient factors. Temperature variation is one of the most prominent factors causing drift in EMI data, ...

    Abstract Data measured using electromagnetic induction (EMI) systems are known to be susceptible to measurement influences associated with time-varying external ambient factors. Temperature variation is one of the most prominent factors causing drift in EMI data, leading to non-reproducible measurement results. Typical approaches to mitigate drift effects in EMI instruments rely on a temperature drift calibration, where the instrument is heated up to specific temperatures in a controlled environment and the observed drift is determined to derive a static thermal apparent electrical conductivity (ECa) drift correction. In this study, a novel correction method is presented that models the dynamic characteristics of drift using a low-pass filter (LPF) and uses it for correction. The method is developed and tested using a customized EMI device with an intercoil spacing of 1.2 m, optimized for low drift and equipped with ten temperature sensors that simultaneously measure the internal ambient temperature across the device. The device is used to perform outdoor calibration measurements over a period of 16 days for a wide range of temperatures. The measured temperature-dependent ECa drift of the system without corrections is approximately 2.27 mSm
    Language English
    Publishing date 2022-05-20
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s22103882
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Low-Pass Filters for a Temperature Drift Correction Method for Electromagnetic Induction Systems.

    Tazifor Tchantcho, Martial / Zimmermann, Egon / Huisman, Johan Alexander / Dick, Markus / Mester, Achim / van Waasen, Stefan

    Sensors (Basel, Switzerland)

    2023  Volume 23, Issue 17

    Abstract: Electromagnetic induction (EMI) systems are used for mapping the soil's electrical conductivity in near-surface applications. EMI measurements are commonly affected by time-varying external environmental factors, with temperature fluctuations being a big ...

    Abstract Electromagnetic induction (EMI) systems are used for mapping the soil's electrical conductivity in near-surface applications. EMI measurements are commonly affected by time-varying external environmental factors, with temperature fluctuations being a big contributing factor. This makes it challenging to obtain stable and reliable data from EMI measurements. To mitigate these temperature drift effects, it is customary to perform a temperature drift calibration of the instrument in a temperature-controlled environment. This involves recording the apparent electrical conductivity (ECa) values at specific temperatures to obtain a look-up table that can subsequently be used for static ECa drift correction. However, static drift correction does not account for the delayed thermal variations of the system components, which affects the accuracy of drift correction. Here, a drift correction approach is presented that accounts for delayed thermal variations of EMI system components using two low-pass filters (LPF). Scenarios with uniform and non-uniform temperature distributions in the measurement device are both considered. The approach is developed using a total of 15 measurements with a custom-made EMI device in a wide range of temperature conditions ranging from 10 °C to 50 °C. The EMI device is equipped with eight temperature sensors spread across the device that simultaneously measure the internal ambient temperature during measurements. To parameterize the proposed correction approach, a global optimization algorithm called Shuffled Complex Evolution (SCE-UA) was used for efficient estimation of the calibration parameters. Using the presented drift model to perform corrections for each individual measurement resulted in a root mean square error (RMSE) of <1 mSm
    Language English
    Publishing date 2023-08-22
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s23177322
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Book ; Online ; Thesis: Detector modeling and its applications in PET simulation and image reconstruction

    Xu, Hancong [Verfasser] / Shah, N. Jon [Akademischer Betreuer] / van Waasen, Stefan [Akademischer Betreuer] / Feld, Lutz [Akademischer Betreuer]

    2020  

    Author's details Hancong Xu ; Nadim Joni Shah, Stefan van Waasen, Lutz Feld
    Keywords Medizin, Gesundheit ; Medicine, Health
    Subject code sg610
    Language English
    Publisher Universitätsbibliothek der RWTH Aachen
    Publishing place Aachen
    Document type Book ; Online ; Thesis
    Database Digital theses on the web

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  5. Book ; Online: Control Electronics For Semiconductor Spin Qubits

    Geck, Lotte / Kruth, Andre / Bluhm, Hendrik / van Waasen, Stefan / Heinen, Stefan

    2019  

    Abstract: Future universal quantum computers solving problems of practical relevance are expected to require at least $10^6$ qubits, which is a massive scale-up from the present numbers of less than 50 qubits operated together. Out of the different types of qubits, ...

    Abstract Future universal quantum computers solving problems of practical relevance are expected to require at least $10^6$ qubits, which is a massive scale-up from the present numbers of less than 50 qubits operated together. Out of the different types of qubits, solid state qubits are considered to be viable candidates for this scale-up, but interfacing to and controlling such a large number of qubits is a complex challenge that has not been solved yet. One possibility to address this challenge is to use qubit control circuits located close to the qubits at cryogenic temperatures. In this work we evaluate the feasibility of this idea, taking as a reference the physical requirements of a two-electron spin qubit and the specifications of a standard 65 nm complementary metal-oxide-semiconductor (CMOS) process. Using principles and flows from electrical systems engineering we provide realistic estimates of the footprint and of the power consumption of a complete control-circuit architecture. Our results show that with further research it is possible to provide scalable electrical control in the vicinity of the qubit, with our concept.
    Keywords Quantum Physics ; Computer Science - Emerging Technologies
    Subject code 600
    Publishing date 2019-03-12
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Multiple Vital-Sign-Based Infection Screening Outperforms Thermography Independent of the Classification Algorithm.

    Yao, Yu / Sun, Guanghao / Matsui, Takemi / Hakozaki, Yukiya / van Waasen, Stefan / Schiek, Michael

    IEEE transactions on bio-medical engineering

    2015  Volume 63, Issue 5, Page(s) 1025–1033

    Abstract: Goal: Thermography-based infection screening at international airports plays an important role in the prevention of pandemics. However, studies show that thermography suffers from low sensitivity and specificity. To achieve higher screening accuracy, we ...

    Abstract Goal: Thermography-based infection screening at international airports plays an important role in the prevention of pandemics. However, studies show that thermography suffers from low sensitivity and specificity. To achieve higher screening accuracy, we developed a screening system based on the acquisition of multiple vital-signs. This multimodal approach increases accuracy, but introduces the need for sophisticated classification methods. This paper presents a comprehensive analysis of the multimodal approach to infection screening from a machine learning perspective.
    Methods: We conduct an empirical study applying six classification algorithms to measurements from the multimodal screening system and comparing their performance among each other, as well as to the performance of thermography. In addition, we provide an information theoretic view on the use of multiple vital-signs for infection screening. The classification methods are tested using the same clinical data, which has been analyzed in our previous study using linear discriminant analysis. A total of 92 subjects were recruited for influenza screening using the system, consisting of 57 inpatients diagnosed to have seasonal influenza and 35 healthy controls.
    Results: Our study revealed that the multimodal screening system reduces the misclassification rate by more than 50% compared to thermography. At the same time, none of the multimodal classifiers needed more than 6 ms for classification, which is negligible for practical purposes.
    Conclusion: Among the tested classifiers k-nearest neighbors, support vector machine and quadratic discriminant analysis achieved the highest cross-validated sensitivity score of 93%.
    Significance: Multimodal infection screening might be able to address the shortcomings of thermography.
    MeSH term(s) Adult ; Algorithms ; Communicable Diseases/diagnosis ; Diagnosis, Computer-Assisted/methods ; Female ; Humans ; Influenza, Human/diagnosis ; Male ; Sensitivity and Specificity ; Signal Processing, Computer-Assisted ; Supervised Machine Learning ; Thermography/methods ; Young Adult
    Keywords covid19
    Language English
    Publishing date 2015-09-17
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 160429-6
    ISSN 1558-2531 ; 0018-9294
    ISSN (online) 1558-2531
    ISSN 0018-9294
    DOI 10.1109/TBME.2015.2479716
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Model-based verification of a non-linear separation scheme for ballistocardiography.

    Yao, Yu / Brüser, Christoph / Pietrzyk, Uwe / Leonhardt, Steffen / van Waasen, Stefan / Schiek, Michael

    IEEE journal of biomedical and health informatics

    2014  Volume 18, Issue 1, Page(s) 174–182

    Abstract: The current rise in popularity of ballisto-cardiography-related research has led to the development of new sensor concepts and recording methods. Measuring the ballistocardiogram using bed mounted pressure sensors opens up new possibilities for home ... ...

    Abstract The current rise in popularity of ballisto-cardiography-related research has led to the development of new sensor concepts and recording methods. Measuring the ballistocardiogram using bed mounted pressure sensors opens up new possibilities for home monitoring applications. The signals measured with these sensors contain a mixture of cardiac and respiratory components, which can be used for detection of comorbidities of heart failure like apnea or arrhythmia. However, the separation of the cardiac and respiratory components has proven to be difficult, since there is significant overlap in the spectra of both components. In this paper, an algorithm for the separation task is presented, which can overcome the problem of overlapping spectra. Additionally, a model has been developed for the generation of artificial ballistocardiograms, which are used to analyze the separation performance. Furthermore, the algorithm is tested on preliminary data from a clinical study.
    MeSH term(s) Algorithms ; Ballistocardiography/methods ; Heart Rate/physiology ; Humans ; Models, Theoretical ; Nonlinear Dynamics ; Normal Distribution ; Respiration ; Signal Processing, Computer-Assisted
    Language English
    Publishing date 2014-01
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2695320-1
    ISSN 2168-2208 ; 2168-2194
    ISSN (online) 2168-2208
    ISSN 2168-2194
    DOI 10.1109/JBHI.2013.2261820
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Book ; Online: TAO Conceptual Design Report

    JUNO Collaboration / Abusleme, Angel / Adam, Thomas / Ahmad, Shakeel / Aiello, Sebastiano / Akram, Muhammad / Ali, Nawab / An, Fengpeng / An, Guangpeng / An, Qi / Andronico, Giuseppe / Anfimov, Nikolay / Antonelli, Vito / Antoshkina, Tatiana / Asavapibhop, Burin / de André, João Pedro Athayde Marcondes / Auguste, Didier / Babic, Andrej / Baldini, Wander /
    Barresi, Andrea / Baussan, Eric / Bellato, Marco / Bergnoli, Antonio / Bernieri, Enrico / Biare, David / Birkenfeld, Thilo / Blin, Sylvie / Blum, David / Blyth, Simon / Bolshakova, Anastasia / Bongrand, Mathieu / Bordereau, Clément / Breton, Dominique / Brigatti, Augusto / Brugnera, Riccardo / Budano, Antonio / Buscemi, Mario / Busto, Jose / Butorov, Ilya / Cabrera, Anatael / Cai, Hao / Cai, Xiao / Cai, Yanke / Cai, Zhiyan / Cammi, Antonio / Campeny, Agustin / Cao, Chuanya / Cao, Guofu / Cao, Jun / Caruso, Rossella / Cerna, Cédric / Chakaberia, Irakli / Chang, Jinfan / Chang, Yun / Chen, Pingping / Chen, Po-An / Chen, Shaomin / Chen, Shenjian / Chen, Xurong / Chen, Yi-Wen / Chen, Yixue / Chen, Yu / Chen, Zhang / Cheng, Jie / Cheng, Yaping / Chepurnov, Alexander / Chiesa, Davide / Chimenti, Pietro / Chukanov, Artem / Chuvashova, Anna / Claverie, Gérard / Clementi, Catia / Clerbaux, Barbara / Di Lorenzo, Selma Conforti / Corti, Daniele / Costa, Salvatore / Corso, Flavio Dal / De La Taille, Christophe / Deng, Jiawei / Deng, Zhi / Deng, Ziyan / Depnering, Wilfried / Diaz, Marco / Ding, Xuefeng / Ding, Yayun / Dirgantara, Bayu / Dmitrievsky, Sergey / Dohnal, Tadeas / Donchenko, Georgy / Dong, Jianmeng / Dornic, Damien / Doroshkevich, Evgeny / Dracos, Marcos / Druillole, Frédéric / Du, Shuxian / Dusini, Stefano / Dvorak, Martin / Enqvist, Timo / Enzmann, Heike / Fabbri, Andrea / Fajt, Lukas / Fan, Donghua / Fan, Lei / Fang, Can / Fang, Jian / Fatkina, Anna / Fedoseev, Dmitry / Fekete, Vladko / Feng, Li-Cheng / Feng, Qichun / Ford, Richard / Formozov, Andrey / Fournier, Amélie / Gan, Haonan / Gao, Feng / Garfagnini, Alberto / Göttel, Alexandre / Genster, Christoph / Giammarchi, Marco / Giaz, Agnese / Giudice, Nunzio / Giuliani, Franco / Gonchar, Maxim / Gong, Guanghua / Gong, Hui / Gorchakov, Oleg / Gornushkin, Yuri / Grassi, Marco / Grewing, Christian / Gromov, Maxim / Gromov, Vasily / Gu, Minghao / Gu, Xiaofei / Gu, Yu / Guan, Mengyun / Guardone, Nunzio / Gul, Maria / Guo, Cong / Guo, Jingyuan / Guo, Wanlei / Guo, Xinheng / Guo, Yuhang / Haacke, Michael / Hackspacher, Paul / Hagner, Caren / Han, Ran / Han, Yang / He, Miao / He, Wei / Heinz, Tobias / Hellmuth, Patrick / Heng, Yuekun / Herrera, Rafael / Hong, Daojin / Hou, Shaojing / Hsiung, Yee / Hu, Bei-Zhen / Hu, Hang / Hu, Jianrun / Hu, Jun / Hu, Shouyang / Hu, Tao / Hu, Zhuojun / Huang, Chunhao / Huang, Guihong / Huang, Hanxiong / Huang, Qinhua / Huang, Wenhao / Huang, Xingtao / Huang, Yongbo / Hui, Jiaqi / Huo, Lei / Huo, Wenju / Huss, Cédric / Hussain, Safeer / Insolia, Antonio / Ioannisian, Ara / Isocrate, Roberto / Jen, Kuo-Lun / Ji, Xiaolu / Ji, Xingzhao / Jia, Huihui / Jia, Junji / Jian, Siyu / Jiang, Di / Jiang, Xiaoshan / Jin, Ruyi / Jing, Xiaoping / Jollet, Cécile / Joutsenvaara, Jari / Jungthawan, Sirichok / Kalousis, Leonidas / Kampmann, Philipp / Kang, Li / Karagounis, Michael / Kazarian, Narine / Khan, Amir / Khan, Waseem / Khosonthongkee, Khanchai / Kinz, Patrick / Korablev, Denis / Kouzakov, Konstantin / Krasnoperov, Alexey / Krokhaleva, Svetlana / Krumshteyn, Zinovy / Kruth, Andre / Kutovskiy, Nikolay / Kuusiniemi, Pasi / Lachenmaier, Tobias / Landini, Cecilia / Leblanc, Sébastien / Lefevre, Frederic / Lei, Liping / Lei, Ruiting / Leitner, Rupert / Leung, Jason / Li, Chao / Li, Demin / Li, Fei / Li, Fule / Li, Haitao / Li, Huiling / Li, Jiaqi / Li, Jin / Li, Kaijie / Li, Mengzhao / Li, Nan / Li, Qingjiang / Li, Ruhui / Li, Shanfeng / Li, Shuaijie / Li, Tao / Li, Teng / Li, Weidong / Li, Weiguo / Li, Xiaomei / Li, Xiaonan / Li, Xinglong / Li, Yi / Li, Yufeng / Li, Zhibing / Li, Ziyuan / Liang, Hao / Liang, Jingjing / 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, Hu / Liu, Hui / Liu, Jianglai / Liu, Jinchang / Liu, Min / Liu, Qian / Liu, Qin / Liu, Runxuan / Liu, Shuangyu / Liu, Shubin / Liu, Shulin / Liu, Xiaowei / Liu, Yan / 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 / Luo, Fengjiao / Luo, Guang / Luo, Pengwei / Luo, Shu / Luo, Wuming / Lyashuk, Vladimir / Ma, Qiumei / Ma, Si / Ma, Xiaoyan / Ma, Xubo / Maalmi, Jihane / Malyshkin, Yury / Mantovani, Fabio / Manzali, Francesco / Mao, Xin / Mao, Yajun / Mari, Stefano M. / Marini, Filippo / Marium, Sadia / Martellini, Cristina / Martin-Chassard, Gisele / Martini, Agnese / Mayilyan, Davit / Müller, Axel / Meng, Yue / Meregaglia, Anselmo / Meroni, Emanuela / Meyhöfer, David / Mezzetto, Mauro / Miller, Jonathan / Miramonti, Lino / Monforte, Salvatore / Montini, Paolo / Montuschi, Michele / Morozov, Nikolay / Muralidharan, Pavithra / Nastasi, Massimiliano / Naumov, Dmitry V. / Naumova, Elena / Nemchenok, Igor / Nikolaev, Alexey / Ning, Feipeng / Ning, Zhe / Nunokawa, Hiroshi / Oberauer, Lothar / Ochoa-Ricoux, Juan Pedro / Olshevskiy, Alexander / Orestano, Domizia / Ortica, Fausto / Pan, Hsiao-Ru / Paoloni, Alessandro / Parkalian, Nina / Parmeggiano, Sergio / Payupol, Teerapat / Pei, Yatian / Pelliccia, Nicomede / Peng, Anguo / Peng, Haiping / Perrot, Frédéric / Petitjean, Pierre-Alexandre / Petrucci, Fabrizio / Rico, Luis Felipe Piñeres / Popov, Artyom / Poussot, Pascal / Pratumwan, Wathan / Previtali, Ezio / Qi, Fazhi / Qi, Ming / Qian, Sen / Qian, Xiaohui / Qiao, Hao / Qin, Zhonghua / Qiu, Shoukang / Rajput, Muhammad / Ranucci, Gioacchino / Raper, Neill / Re, Alessandra / Rebber, Henning / Rebii, Abdel / Ren, Bin / Ren, Jie / Rezinko, Taras / Ricci, Barbara / Robens, Markus / Roche, Mathieu / Rodphai, Narongkiat / Romani, Aldo / Roskovec, Bedřich / Roth, Christian / Ruan, Xiangdong / Ruan, Xichao / Rujirawat, Saroj / Rybnikov, Arseniy / Sadovsky, Andrey / Saggese, Paolo / Salamanna, Giuseppe / Sanfilippo, Simone / Sangka, Anut / Sanguansak, Nuanwan / Sawangwit, Utane / Sawatzki, Julia / Sawy, Fatma / Schever, Michaela / Schuler, Jacky / Schwab, Cédric / Schweizer, Konstantin / Selivanov, Dmitry / Selyunin, Alexandr / Serafini, Andrea / Settanta, Giulio / Settimo, Mariangela / Shahzad, Muhammad / Shi, Gang / Shi, Jingyan / Shi, Yongjiu / Shutov, Vitaly / Sidorenkov, Andrey / Simkovic, Fedor / Sirignano, Chiara / Siripak, Jaruchit / Sisti, Monica / Slupecki, Maciej / Smirnov, Mikhail / Smirnov, Oleg / Sogo-Bezerra, Thiago / Songwadhana, Julanan / Soonthornthum, Boonrucksar / Sotnikov, Albert / Sramek, Ondrej / Sreethawong, Warintorn / Stahl, Achim / Stanco, Luca / Stankevich, Konstantin / Stefanik, Dus / Steiger, Hans / Steinmann, Jochen / Sterr, Tobias / Stock, Matthias Raphael / Strati, Virginia / Studenikin, Alexander / Sun, Gongxing / 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 / Treskov, Konstantin / Triossi, Andrea / Troni, Giancarlo / Trzaska, Wladyslaw / Tuve, Cristina / van Waasen, Stefan / Boom, Johannes Vanden / Vanroyen, Guillaume / Vassilopoulos, Nikolaos / Vedin, Vadim / Verde, Giuseppe / Vialkov, Maxim / Viaud, Benoit / Volpe, Cristina / Vorobel, Vit / 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 / Watcharangkool, Apimook / Wei, Lianghong / Wei, Wei / Wei, Yadong / Wen, Liangjian / Wiebusch, Christopher / Wong, Steven Chan-Fai / Wonsak, Bjoern / Wu, Diru / Wu, Fangliang / Wu, Qun / Wu, Wenjie / Wu, Zhi / Wurm, Michael / Wurtz, Jacques / Wysotzki, Christian / Xi, Yufei / Xia, Dongmei / Xie, Yuguang / Xie, Zhangquan / Xing, Zhizhong / Xu, Benda / Xu, Donglian / Xu, Fanrong / Xu, Jilei / Xu, Jing / Xu, Meihang / Xu, Yin / Xu, Yu / Yan, Baojun / Yan, Xiongbo / Yan, Yupeng / Yang, Anbo / Yang, Changgen / Yang, Huan / Yang, Jie / Yang, Lei / Yang, Xiaoyu / Yang, Yifan / Yao, Haifeng / Yasin, Zafar / Ye, Jiaxuan / Ye, Mei / Yegin, Ugur / Yermia, Frédéric / Yi, Peihuai / Yin, Xiangwei / You, Zhengyun / Yu, Boxiang / Yu, Chiye / Yu, Chunxu / Yu, Hongzhao / Yu, Miao / Yu, Xianghui / Yu, Zeyuan / Yuan, Chengzhuo / Yuan, Ying / Yuan, Zhenxiong / Yuan, Ziyi / Yue, Baobiao / Zafar, Noman / Zambanini, Andre / Zeng, Pan / Zeng, Shan / Zeng, Tingxuan / Zeng, Yuda / Zhan, Liang / Zhang, Feiyang / Zhang, Guoqing / Zhang, Haiqiong / Zhang, Honghao / Zhang, Jiawen / Zhang, Jie / Zhang, Jingbo / Zhang, Peng / Zhang, Qingmin / Zhang, Shiqi / Zhang, Tao / Zhang, Xiaomei / Zhang, Xuantong / Zhang, Yan / Zhang, Yinhong / Zhang, Yiyu / Zhang, Yongpeng / Zhang, Yuanyuan / Zhang, Yumei / Zhang, Zhenyu / Zhang, Zhijian / Zhao, Fengyi / Zhao, Jie / Zhao, Rong / Zhao, Shujun / Zhao, Tianchi / Zheng, Dongqin / Zheng, Hua / Zheng, Minshan / Zheng, Yangheng / Zhong, Weirong / Zhou, Jing / Zhou, Li / Zhou, Nan / Zhou, Shun / Zhou, Xiang / Zhu, Jiang / Zhu, Kejun / Zhuang, Honglin / Zong, Liang / Zou, Jiaheng

    A Precision Measurement of the Reactor Antineutrino Spectrum with Sub-percent Energy Resolution

    2020  

    Abstract: The Taishan Antineutrino Observatory (TAO, also known as JUNO-TAO) is a satellite experiment of the Jiangmen Underground Neutrino Observatory (JUNO). A ton-level liquid scintillator detector will be placed at about 30 m from a core of the Taishan Nuclear ...

    Abstract The Taishan Antineutrino Observatory (TAO, also known as JUNO-TAO) is a satellite experiment of the Jiangmen Underground Neutrino Observatory (JUNO). A ton-level liquid scintillator detector will be placed at about 30 m from a core of the Taishan Nuclear Power Plant. The reactor antineutrino spectrum will be measured with sub-percent energy resolution, to provide a reference spectrum for future reactor neutrino experiments, and to provide a benchmark measurement to test nuclear databases. A spherical acrylic vessel containing 2.8 ton gadolinium-doped liquid scintillator will be viewed by 10 m^2 Silicon Photomultipliers (SiPMs) of >50% photon detection efficiency with almost full coverage. The photoelectron yield is about 4500 per MeV, an order higher than any existing large-scale liquid scintillator detectors. The detector operates at -50 degree C to lower the dark noise of SiPMs to an acceptable level. The detector will measure about 2000 reactor antineutrinos per day, and is designed to be well shielded from cosmogenic backgrounds and ambient radioactivities to have about 10% background-to-signal ratio. The experiment is expected to start operation in 2022.

    Comment: 134 pages, 114 figures
    Keywords Physics - Instrumentation and Detectors ; High Energy Physics - Experiment ; Nuclear Experiment
    Subject code 660
    Publishing date 2020-05-18
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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