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arXiv 2021年

作者： Lee, Benjamin D. Gitter, Anthony Greene, Casey S. Raschka, Sebastian Maguire, Finlay Titus, Alexander J. Kessler, Michael D. Lee, Alexandra J. Chevrette, Marc G. Stewart, Paul Allen Britto-Borges, Thiago Cofer, Evan M. Yu, Kun-Hsing Carmona, Juan Jose Fertig, Elana J. Kalinin, Alexandr A. Signal, Beth Lengerich, Benjamin J. Triche, Timothy J. Boca, Simina M. In-Q-Tel Labs School of Engineering and Applied Sciences Harvard University Department of Genetics Harvard Medical School United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison MadisonWI United States Morgridge Institute for Research MadisonWI United States Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine AuroraCO United States Center for Health AI University of Colorado School of Medicine AuroraCO United States Department of Statistics University of Wisconsin Madison United States Faculty of Computer Science Dalhousie University Canada University of New Hampshire Bioeconomy.XYZ United States Department of Oncology Johns Hopkins University United States Institute for Genome Sciences University of Maryland School of Medicine United States Genomics and Computational Biology Graduate Program University of Pennsylvania United States Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania United States Wisconsin Institute for Discovery Department of Plant Pathology University of Wisconsin-Madison United States Department of Biostatistics and Bioinformatics Moffitt Cancer Center TampaFL United States Section of Bioinformatics and Systems Cardiology Klaus Tschira Institute for Integrative Computational Cardiology University Hospital Heidelberg Germany University Hospital Heidelberg Germany Lewis-Sigler Institute for Integrative Genomics Princeton University PrincetonNJ United States Graduate Program in Quantitative and Computational Biology Princeton University PrincetonNJ United States Department of Biomedical Informatics Harvard Medical School United States Department of Pathology Brigham and Women's Hospital United States Philips Healthcare CambridgeMA United States Philips Research

Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling. Artificial neural networks are a particular class of machine learning algorithms and models that evolved into what is now described as deep learning. Given the computational advances made in the last decade, deep learning can now be applied to massive data sets and in innumerable contexts. Therefore, deep learning has become its own subfield of machine learning. In the context of biological research, it has been increasingly used to derive novel insights from high-dimensional biological data. To make the biological applications of deep learning more accessible to scientists who have some experience with machine learning, we solicited input from a community of researchers with varied biological and deep learning interests. These individuals collaboratively contributed to this manuscript's writing using the GitHub version control platform and the Manubot manuscript generation toolset. The goal was to articulate a practical, accessible, and concise set of guidelines and suggestions to follow when using deep learning. In the course of our discussions, several themes became clear: the importance of understanding and applying machine learning fundamentals as a baseline for utilizing deep learning, the necessity for extensive model comparisons with careful evaluation, and the need for critical thought in interpreting results generated by deep learning, among others. © 2021, CC BY.

关键词： Learning algorithms

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Generation of a Cat State in an Optical Sideband

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Physical Review Letters 2018年第14期121卷 143602-143602页

作者： Takahiro Serikawa Jun-ichi Yoshikawa Shuntaro Takeda Hidehiro Yonezawa Timothy C. Ralph Elanor H. Huntington Akira Furusawa Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo Japan School of Engineering and Information Technology The University of New South Wales Canberra Australian Capital Territory 2600 Australia Center for Quantum Computation and Communication Technology Australian Research Council Canberra Australian Capital Territory 2609 Australia School of Mathematics and Physics University of Queensland Brisbane Queensland 4072 Australia Research School of Engineering College of Engineering and Computer Science Australian National University Canberra Australian Capital Territory 2600 Australia

We propose a method to subtract a photon from a double sideband mode of continuous-wave light. The central idea is to use phase modulation as a frequency sideband beam splitter in the heralding photon subtraction scheme, where a small portion of the sideband mode is down-converted to 0 Hz to provide a trigger photon. An optical cat state is created by applying the proposed method to a squeezed state at 500 MHz sideband, which is generated by an optical parametric oscillator. The Wigner function of the cat state reconstructed from a direct homodyne measurement of the 500 MHz sideband modes shows the negativity of W(0,0)=−0.088±0.001 without any loss corrections.

关键词： Optical parametric oscillators & amplifiers Quantum state engineering Quantum states of light Squeezing of quantum noise

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Development of quantum InterConnects (QuICs) for next-generation information technologies

arXiv

引用

arXiv 2019年

作者： Awschalom, David Berggren, Karl K. Bernien, Hannes Bhave, Sunil Carr, Lincoln D. Davids, Paul Economou, Sophia E. Englund, Dirk Faraon, Andrei Fejer, Marty Guha, Saikat Gustafsson, Martin V. Hu, Evelyn Jiang, Liang Kim, Jungsang Korzh, Boris Kumar, Prem Kwiat, Paul G. Lončar, Marko Lukin, Mikhail D. Miller, David A.B. Monroe, Christopher Nam, Sae Woo Narang, Prineha Orcutt, Jason S. Raymer, Michael G. Safavi-Naeini, Amir H. Spiropulu, Maria Srinivasan, Kartik Sun, Shuo Vučković, Jelena Waks, Edo Walsworth, Ronald Weiner, Andrew M. Zhang, Zheshen Pritzker School of Molecular Engineering University of Chicago ChicagoIL60637 United States Department of Electrical Engineering and Computer Science MIT CambridgeMA02139 United States School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States Department of Physics Colorado School of Mines 1500 Illinois St. GoldenCO80401 United States Photonic & Phononic Microsystems Sandia National Laboratory AlbuquerqueNM87185 United States Department of Physics Virginia Tech BlacksburgVA24061 United States T .J. Watson Laboratory of Applied Physics California Institute of Technology PasadenaCA91125 United States Kavli Nanoscience Institute California Institute of Technology PasadenaCA91125 United States E.L. Ginzton Laboratory Stanford University StanfordCA94305 United States College of Optical Sciences University of Arizona TucsonAZ85721 United States Department of Electrical and Computer Engineering University of Arizona TucsonAZ85721 United States Department of Applied Mathematics University of Arizona TucsonAZ85721 United States Raytheon BBN Technologies CambridgeMA02138 United States John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Harvard University CambridgeMA02138 United States Department Of Electrical and Computer Engineering Duke University DurhamNC27708 United States IonQ Inc. College ParkMD20740 United States Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States Department of Physics University of Illinois at Urbana-Champaign UrbanaIL61801 United States IQUIST University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Physics Harvard University Cambridge

Just as ‘classical’ information technology rests on a foundation built of interconnected information-processing systems, quantum information technology (QIT) must do the same. A critical component of such systems is the ‘interconnect,’ a device or process that allows transfer of information between disparate physical media, for example, semiconductor electronics, individual atoms, light pulses in optical fiber, or microwave fields. While interconnects have been well engineered for decades in the realm of classical information technology, quantum interconnects (QuICs) present special challenges, as they must allow the transfer of fragile quantum states between different physical parts or degrees of freedom of the system. The diversity of QIT platforms (superconducting, atomic, solid-state color center, optical, etc.) that will form a ‘quantum internet’ poses additional challenges. As quantum systems scale to larger size, the quantum interconnect bottleneck is imminent, and is emerging as a grand challenge for QIT. For these reasons, it is the position of the community represented by participants of the NSF workshop on "Quantum Interconnects" that accelerating QuIC research is crucial for sustained development of a national quantum science and technology program. Given the diversity of QIT platforms, materials used, applications, and infrastructure required, a convergent research program including partnership between academia, industry and national laboratories is required. Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum optics

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Coupled elastic-acoustic modelling for quantitative photoacoustic tomography

arXiv

引用

arXiv 2019年

作者： Goh, Hwan Lähivaara, Timo Tarvainen, Tanja Pulkkinen, Aki Dillon, Owen Nicholson, Ruanui Kaipio, Jari Department of Mathematics University of Auckland Auckland Mail Centre Private Bag 92019 Auckland1142 New Zealand Dodd-Walls Centre for Photonic and Quantum Technologies University of Otago P.O. Box 56 Dunedin9056 New Zealand Oden Institute for Computational Engineering and Sciences University of Texas at Austin AustinTX78712 United States Department of Applied Physics University of Eastern Finland P.O. Box 1627 Kuopio70211 Finland Department of Engineering Science University of Auckland Auckland Mail Centre Private Bag 92019 Auckland1142 New Zealand Department of Computer Science University College London Gower Street LondonWCIE 6BT United Kingdom

Quantitative photoacoustic tomography (qPAT) is an imaging technique aimed at estimating chromophore concentrations inside tissues from photoacoustic images, which are formed by combining optical information and ultrasonic propagation. The application of qPAT as a transcranial imaging modality is complicated by shear waves that can be produced when ultrasound waves travel from soft tissue to bone. Because of this, the estimation of chromophores distributions near the skull can be problematic. In this paper, we take steps towards compensating for aberrations of the recorded photoacoustic signals caused by elastic wave propagation. With photoacoustic data simulated in a coupled elastic-acoustic domain, we conduct inversions in a purely acoustic domain. Estimation of the posterior density of the initial pressure is achieved by inversion under the Bayesian framework. We utilize the Bayesian approximation error approach to compensate for the modelling errors arising from approximating a coupled elastic-acoustic domain with a purely fluid domain. The resulting reconstructions and corresponding uncertainty estimates are then used to evaluate the posterior density of the optical absorption parameter. In the sense of the posterior uncertainty, the results show that the Bayesian approximation error approach yields a more feasible estimate for the posterior model of the initial pressure which, in turn, yields a more feasible estimate for the posterior model of the absorption coefficient. Copyright © 2019, The Authors. All rights reserved.

关键词： Photoacoustic effect

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Equilibrium solutions of multi-period mean-variance portfolio selection

arXiv

引用

arXiv 2018年

作者： Ni, Yuan-Hua Li, Xun Zhang, Ji-Feng Krstic, Miroslav College of Computer and Control Engineering Nankai University Tianjin300350 China Department of Applied Mathematics Hong Kong Polytechnic University Kowloon Hong Kong Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China Department of Mechanical and Aerospace Engineering University of California San Diego United States

This is a companion paper of [Mixed equilibrium solution of time-inconsistent stochastic LQ problem, arXiv:1802.03032], where general theory has been established to characterize the open-loop equilibrium control, feedback equilibrium strategy and mixed equilibrium solution for a time-inconsistent stochastic linear-quadratic problem. This note is, on the one hand to test the developed theory of that paper, and on the other hand to push the solvability of multi-period mean-variance portfolio selection. A nondegenerate assumption has been removed in this note, which is popular in existing literature about multi-period mean-variance portfolio selection;and neat conditions have been obtained to characterize the existence of equilibrium solutions. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

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Schrödinger-s cat in an optical sideband

arXiv

引用

arXiv 2018年

作者： Serikawa, Takahir Yoshikawa, Jun-Ichi Takeda, Shuntaro Yonezawa, Hidehiro Ralph, Timothy C. Huntington, Elanor H. Furusawa, Akir Department of Applied Physics School of Engineering University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo School of Engineering and Information Technology University of New South Wales CanberraACT2600 Australia Center for Quantum Computation and Communication Technology Australian Research Council School of Mathematics and Physics University of Queensland BrisbaneQLD4072 Australia Research School of Engineering College of Engineering and Computer Science Australian National University CanberraACT2600 Australia

We propose a method to subtract a photon from a double sideband mode of continuous-wave light. The central idea is to use phase modulation as a frequency sideband beamsplitter in the heralding photon subtraction scheme, where a small portion of the sideband mode is downconverted to the carrier frequency to provide a trigger photon. An optical Schrödinger-s cat state is created by applying the propesed method to a squeezed state at 500MHz sideband, which is generated by an optical parametric oscillator. The Wigner function of the cat state reconstructed from a direct homodyne measurement of the 500MHz sideband modes shows the negativity ofW(0;0) =-0:0880:001 without any loss corrections. Copyright © 2018, The Authors. All rights reserved.

关键词： Photons

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Software Performance of the ATLAS Track Reconstruction for LHC Run 3

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Computing and Software for Big Science 2024年第1期8卷 1-32页

作者： Aad, G. Abbott, B. Abeling, K. Abicht, N.J. Abidi, S.H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B.S. Bourdarios, C. Adam Adamczyk, L. Adamek, L. Addepalli, S.V. Addison, M.J. Adelman, J. Adiguzel, A. Adye, T. Affolder, A.A. Afik, Y. Agaras, M.N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ahuja, S. Ai, X. Aielli, G. Aikot, A. Tamlihat, M. Ait Aitbenchikh, B. Aizenberg, I. Akbiyik, M. Åkesson, T.P.A. Akimov, A.V. Akiyama, D. Akolkar, N.N. Khoury, K. Al Alberghi, G.L. Albert, J. Albicocco, P. Albouy, G.L. Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, F. Algren, M. Alhroob, M. Ali, B. Ali, H.M.J. Ali, S. Alibocus, S.W. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B.M.M. Allen, J.F. Flores, C. A. Allendes Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Estevez, M. Alvarez Fernandez, A. Alvarez Cardoso, M. Alves Alviggi, M.G. Aly, M. Coutinho, Y. Amaral Ambler, A. Amelung, C. Amerl, M. Ames, C.G. Amidei, D. Santos, S. P. Amor Dos Amos, K.R. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J.K. Andrean, S.Y. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antipov, E. Antonelli, M. Anulli, F. Aoki, M. Aoki, T. Pozo, J. A. Aparisi Aparo, M.A. Bella, L. Aperio Appelt, C. Apyan, A. Aranzabal, N. Val, S. J. Arbiol Arcangeletti, C. Arce, A.T.H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Arnaez, O. Arnold, H. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Assahsah, J. Assamagan, K. Astalos, R. Atashi, S. Atkin, R.J. Atkinson, M. Atmani, H. Atmasiddha, P.A. Augsten, K. Auricchio, S. Auriol, A.D. Austrup, V.A. Avolio, G. Axiotis, K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahmani, M. Bailey, A.J. Bailey, V.R. Baines, J.T. Baines, L. Baker, O.K. Bakos, E. Gupta, D. Bakshi Balakrishnan, V. Balasubramanian, R. Baldin, E.M. Balek, P. Ballabene, E. Balli, F. Baltes, L.M. Balunas, W.K. Balz, J. Banas, E. Bandieramonte CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK United States II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Physics Department Brookhaven National Laboratory Upton NY United States Faculté des sciences Université Mohammed V Rabat Morocco Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel Department of Physics New York University New York NY United States INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics Stanford University Stanford CA United States LAPP Université Savoie Mont Blanc CNRS/IN2P3 Annecy France AGH University of Krakow Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics University of Toronto Toronto ON Canada Department of Physics Brandeis University Waltham MA United States School of Physics and Astronomy University of Manchester Manchester United Kingdom Department of Physics Northern Illinois University DeKalb IL United States Department of Physics Istanbul University Istanbul Turkey Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz CA United States CERN Geneva Switzerland Institut de Física d’Altes Energies (IFAE) Barcelona Institute of Science and Technology Barcelona Spain INFN Sezione di Pavia Pavia Italy Dipartimento di Fisica Università di Pavia Pavia Italy Institut für Physik Universität Mainz Mainz Germany Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Affiliated with an international laboratory covered by a cooperation agreement with CERN Geneva Switzerland Institu

Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pile-up) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two. © The Author(s) 2024.

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The sounds of science – A symphony for many instruments and voices

arXiv

引用

arXiv 2019年

作者： Alexander, Gerianne Allen, Roland E. Atala, Anthony Bowen, Warwick P. Coley, Alan A. Goodenough, John Katsnelson, Mikhail I. Koonin, Eugene V. Krenn, Mario Madsen, Lars S. Månsson, Martin Mauranyapin, Nicolas P. Melvin, Art I. Rasel, Ernst Reichl, Linda E. Yampolskiy, Roman Yasskin, Philip B. Zeilinger, Anton Lidström, Suzy Department of Psychological and Brain Sciences Texas A&M University College StationTX United States Department of Physics and Astronomy Texas A&M University College StationTX United States Wake Forest Institute for Regenerative Medicine 391 Technology Way Winston-SalemNC27157 United States School of Mathematics and Physics University of Queensland St. Lucia4072 Australia Australian Centre for Engineered Quantum Systems University of Queensland St. Lucia4072 Australia Department of Mathematics and Statistics Dalhousie University HalifaxNSB3H 4R2 Canada Walker Department of Mechanical Engineering Cockrell Institute University of Texas at Austin AustinTX United States Institute for Molecules and Materials Radboud University Nijmegen6525AJ Netherlands National Library of Medicine National Center for Biotechnology Information BethesdaMD20894 United States Austrian Academy of Sciences Boltzmanngasse 3 Vienna1090 Austria Department of Chemistry University of Toronto Toronto Canada Dept. of Applied Physics KTH Royal Institute of Technology Stockholm KistaSE-164 40 Sweden Faculty of Physics University of Vienna Boltzmanngasse 5 Vienna1090 Austria Institut für Quantenoptik Welfengarten 1 Hannover30167 Germany Center for Complex Quantum Systems Department of Physics University of Texas at Austin AustinTX United States Department of Computer Engineering and Computer Science Duthie Center for Engineering University of Louisville LouisvilleKY40292 United States Department of Mathematics Texas A&M University College StationTX United States Department of Physics and Astronomy Texas A&M University College StationTX United States

Sounds of Science is the first movement of a symphony for many (scientific) instruments and voices, united in celebration of the frontiers of science. John Goodenough, the maestro who transformed energy usage and technology through the invention of the lithium-ion battery, opens the programme, reflecting on the ultimate limits of battery technology. This applied theme continues through the subsequent pieces on energy related topics – the sodium-ion battery and artificial fuels, by Martin Månsson – and the ultimate challenge for 3D printing, the eventual production of life, by Anthony Atala. A passage by Gerianne Alexander follows, reflecting on a related issue: How might an artificially produced human being behave? Next comes a consideration of consiousness and free will by Roland Allen and Suzy Lidström. Further voices and new instruments enter as Warwick Bowen, Nicolas Mauranyapin and Lars Madsen discuss whether dynamical processes of single molecules might be observed in their native state. The exploitation of chaos in science and technology, applications of Bose-Einstein condensates and a consideration of the significance of entropy follow in pieces by Linda Reichl, Ernst Rasel and Roland Allen, respectively. Mikhail Katsnelson and Eugene Koonin then discuss the potential generalisation of thermodynamic concepts in the context of biological evolution. Entering with the music of the cosmos, Philip Yasskin discusses whether we might be able to observe torsion in the geometry of the universe. The crescendo comes with the crisis of singularities, their nature and whether they can be resolved through quantum effects, in the composition of Alan Coley. The climax is Mario Krenn, Art Melvin and Anton Zeilinger’s consideration of how computer code can be autonomously surprising and creative. In a harmonious counterpoint – his ‘Guidelines for considering AIs as coauthors’ – Roman Yampolskiy concludes that such code is not yet able to take responsibility for coauthoring a

关键词： Metal ions

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A question answering approach to emotion cause extraction

A question answering approach to emotion cause extraction

引用

2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017

作者： Gui, Lin Hu, Jiannan He, Yulan Xu, Ruifeng Lu, Qin Du, Jiachen Shenzhen Graduate School Harbin Institute of Technology China College of Mathematics and Computer Science Fuzhou University China School of Engineering and Applied Science Aston University United Kingdom Guangdong Provincial Engineering Technology Research Center for Data Science China Department of Computing Hong Kong Polytechnic University Hong Kong

ISBN: (纸本)9781945626838

Emotion cause extraction aims to identify the reasons behind a certain emotion expressed in text. It is a much more difficult task compared to emotion classification. Inspired by recent advances in using deep memory networks for question answering (QA), we propose a new approach which considers emotion cause identification as a reading comprehension task in QA. Inspired by convolutional neural networks, we propose a new mechanism to store relevant context in different memory slots to model context information. Our proposed approach can extract both word level sequence features and lexical features. Performance evaluation shows that our method achieves the state-of-the-art performance on a recently released emotion cause dataset, outperforming a number of competitive baselines by at least 3.01% in F-measure. © 2017 Association for Computational Linguistics.

关键词： Extraction

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CEPC Technical Design Report

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Radiation Detection Technology and Methods 2024年第1期8卷 I0003-I0016,1-1091页

作者： Waleed Abdallah Tiago Carlos Adorno de Freitas Konstantin Afanaciev Shakeel Ahmad Ijaz Ahmed Xiaocong Ai Abid Aleem Wolfgang Altmannshofer Fabio Alves Weiming An Rui An Daniele Paolo Anderle Stefan Antusch Yasuo Arai Andrej Arbuzov Abdesslam Arhrib Mustafa Ashry Sha Bai Yu Bai Yang Bai Vipul Bairathi Csaba Balazs Philip Bambade Yong Ban Tripamo Bandyopadhyay Shou-Shan Bao Desmond P.Barber Ayse Bat Varvara Batozskaya Subash Chandra Behera Alexander Belyaev Michele Bertucci Xiao-Jun Bi Yuanjie Bi Tianjian Bian Fabrizio Bianchi Thomas Biekotter Michela Biglietti Shalva Bilanishvili Deng Binglin Denis Bodrov Anton Bogomyagkov Serge Bondarenko Stewart Boogert Maarten Boonekamp Marcello Borri Angelo Bosotti Vincent Boudry Mohammed Boukidi Igor Boyko Ivanka Bozovic Giuseppe Bozzi Jean-Claude Brient Anastasiia Budzinskaya Masroor Bukhari Vladimir Bytev Giacomo Cacciapaglia Hua Cai Wenyong Cai Wujun Cai Yijian Cai Yizhou Cai Yuchen Cai Haiying Cai Huacheng Cai Lorenzo Calibbi Junsong Cang Guofu Cao Jianshe Cao Antoine Chance Xuejun Chang Yue Chang Zhe Chang Xinyuan Chang Wei Chao Auttakit Chatrabhuti Yimin Che Yuzhi Che Bin Chen Danping Chen Fuqing Chen Fusan Chen Gang Chen Guoming Chen Hua-Xing Chen Huirun Chen Jinhui Chen Ji-Yuan Chen Kai Chen Mali Chen Mingjun Chen Mingshui Chen Ning Chen Shanhong Chen Shanzhen Chen Shao-Long Chen Shaomin Chen Shiqiang Chen Tianlu Chen Wei Chen Xiang Chen Xiaoyu Chen Xin Chen Xun Chen Xurong Chen Ye Chen Ying Chen Yukai Chen Zelin Chen Zilin Chen Gang Chen Boping Chen Chunhui Chen Hok Chuen Cheng Huajie Cheng Shan Cheng Tongguang Cheng Yunlong Chi Pietro Chimenti Wen Han Chiu Guk Cho Ming-Chung Chu Xiaotong Chu Ziliang Chu Guglielmo Coloretti Andreas Crivellin Hanhua Cui Xiaohao Cui Zhaoyuan Cui Brunella D'Anzi Ling-Yun Dai Xinchen Dai Xuwen Dai Antonio De Maria Nicola De Filippis Christophe De La Taille Francesca De Mori Chiara De Sio Elisa Del Core Shuangxue Deng Wei-Tian Deng Zhi Deng Ziyan Deng Bhupal Dev Tang Dewen Biagio Di Micco Ran Ding Siqin Dingl Yadong Ding Haiyi Dong Jianin AGH University of Science and Technology Faculty of Physics and Applied Computer ScienceKrakow Anhui University HefeiAnhui Applied Physics Department Federal Urdu University of ArtsScience and TechnologyIslamabad Banaras Hindu University Institute of ScienceVaranasi Bandirma Onyedi Eylul University Bandirma Beihang University Beijing Beijing Computational Science Research Center Beijing Beijing Conveyi LTD Beijing Beijing Glass Research Institute Co. LtdBeijing Beijing Institute of Technology Beijing Beijing Normal University Beijing Brown University ProvidenceRI Budker Institute of Nuclear Physics Novosibirsk Cadi Ayyad University Laboratory of Fundamental and Applied PhysicsPolydisciplinary FacultyMarrakech Cairo University Giza Center for Theory and Computation National Tsing Hua UniversityHsinchu Central China Normal University WuhanHubei Central South University ChangshaHunan Centro de Fisica Teorica de Particulas Universidade Tecnica de LisboaLisboa Chengdu KaitengSifang Digital Radio&TV Equipment Co. LtdChengduSichuan China academy of engineering physics MianyangSichuan China building materials academy Beijing China Center of Advanced Science and Technology Beijing China Institute of Atomic Energy Beijing China Jiliang University HangzhouZhejiang China Nuclear Instrument CO. LTDBeijing China University of Geosciences Beijing China University of Geosciences WuhanHubei China University of Mining and Technology XuzhouJiangsu China West Normal University NanchongSichuan Chongqing University Department of PhysicsChongqing Chulalongkorn University Bangkok City University of Hong Kong Department of PhysicsHong Kong Cockcroft Institute Daresbury Cornell University IthacaNY CPPM(AMU/IPhU&CNRS/INP) Marseille Dalian Minzu University DalianLiaoning Dalian University of Technology Department of PhysicsDalian Deutsches Elektronen-Synchrotron DESY Hamburg Dzhelepov Laboratory of Nuclear Problems of Joint Institute for Nuclear Research(DLNP JINR) Dubna East China University Of Science And Technol

The Circular Electron Positron Collider(CEPC)is a large scientific project initiated and hosted by China,fostered through extensive collaboration with international *** complex comprises four accelerators:a 30 GeV Linac,a 1.1 GeV Damping Ring,a Booster capable of achieving energies up to 180 GeV,and a Collider operating at varying energy modes(Z,W,H,and tt).The Linac and Damping Ring are situated on the surface,while the subterranean Booster and Collider are housed in a 100 km circumference underground tunnel,strategically accommodating future expansion with provisions for a potential Super Proton Proton Collider(SPPC).The CEPC primarily serves as a Higgs *** its baseline design with synchrotron radiation(SR)power of 30 MW per beam,it can achieve a luminosity of 5×10^(34)cm^(-2)s^(-1)per interaction point(IP),resulting in an integrated luminosity of 13 ab^(-1)for two IPs over a decade,producing 2.6 million Higgs *** the SR power to 50 MW per beam expands the CEPC's capability to generate 4.3 million Higgs bosons,facilitating precise measurements of Higgs coupling at sub-percent levels,exceeding the precision expected from the HL-LHC by an order of *** Technical Design Report(TDR)follows the Preliminary Conceptual Design Report(Pre-CDR,2015)and the Conceptual Design Report(CDR,2018),comprehensively detailing the machine's layout,performance metrics,physical design and analysis,technical systems design,R&D and prototyping efforts,and associated civil engineering ***,it includes a cost estimate and a preliminary construction timeline,establishing a framework for forthcoming engineering design phase and site selection *** is anticipated to begin around 2027-2028,pending government approval,with an estimated duration of 8 *** commencement of experiments and data collection could potentially be initiated in the mid-2030s.

关键词： initiated exceeding precise

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