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Quantum Simulation for High-Energy Physics

PRX Quantum 2023年第2期4卷 027001-027001页

作者： Christian W. Bauer Zohreh Davoudi A. Baha Balantekin Tanmoy Bhattacharya Marcela Carena Wibe A. de Jong Patrick Draper Aida El-Khadra Nate Gemelke Masanori Hanada Dmitri Kharzeev Henry Lamm Ying-Ying Li Junyu Liu Mikhail Lukin Yannick Meurice Christopher Monroe Benjamin Nachman Guido Pagano John Preskill Enrico Rinaldi Alessandro Roggero David I. Santiago Martin J. Savage Irfan Siddiqi George Siopsis David Van Zanten Nathan Wiebe Yukari Yamauchi Kübra Yeter-Aydeniz Silvia Zorzetti Physics Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA Department of Physics Maryland Center for Fundamental Physics and the NSF Institute for Robust Quantum Simulation University of Maryland College Park Maryland 20742 USA Department of Physics University of Wisconsin Madison Wisconsin 53706 USA T-2 Los Alamos National Laboratory Los Alamos New Mexico 87545 USA Fermi National Accelerator Laboratory Batavia Illinois 60510 USA Enrico Fermi Institute University of Chicago Chicago Illinois 60637 USA Kavli Institute for Cosmological Physics University of Chicago Chicago Illinois 60637 USA Department of Physics University of Chicago Chicago Illinois 60637 USA Department of Physics and Illinois Center for the Advanced Study of the Universe and Illinois Quantum Information Science and Technology Center University of Illinois Urbana Illinois 61801 USA QuEra Computing Inc Boston Massachusetts 02135 USA Department of Mathematics University of Surrey Guildford Surrey GU2 7XH United Kingdom Center for Nuclear Theory Department of Physics and Astronomy Stony Brook University New York 11794-3800 USA Department of Physics Brookhaven National Laboratory Upton New York 11973 USA Peng Huanwu Center for Fundamental Theory Hefei Anhui 230026 China Interdisciplinary Center for Theoretical Study University of Science and Technology of China Hefei Anhui 230026 China Pritzker School of Molecular Engineering Chicago Quantum Exchange and Kadanoff Center for Theoretical Physics University of Chicago Illinois 60637 USA qBraid Co. Harper Court 5235 Chicago Illinois 60615 USA Department of Physics Harvard University Cambridge Massachusetts 02138 USA Department of Physics and Astronomy University of Iowa Iowa City Iowa 52242 USA Duke Quantum Center Duke University Durham North Carolina 27701 USA Department of Electrical and Computer Engineering Duke University Durham North Carolina 27708 USA Department of Physics Duke University

It is for the first time that quantum simulation for high-energy physics (HEP) is studied in the U.S. decadal particle-physics community planning, and in fact until recently, this was not considered a mainstream topic in the community. This fact speaks of a remarkable rate of growth of this subfield over the past few years, stimulated by the impressive advancements in quantum information sciences (QIS) and associated technologies over the past decade, and the significant investment in this area by the government and private sectors in the U.S. and other countries. High-energy physicists have quickly identified problems of importance to our understanding of nature at the most fundamental level, from tiniest distances to cosmological extents, that are intractable with classical computers but may benefit from quantum advantage. They have initiated, and continue to carry out, a vigorous program in theory, algorithm, and hardware co-design for simulations of relevance to the HEP mission. This Roadmap is an attempt to bring this exciting and yet challenging area of research to the spotlight, and to elaborate on what the promises, requirements, challenges, and potential solutions are over the next decade and beyond.

关键词： Quantum simulation

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LSTM-based Text Emotion Recognition Using Semantic and Emotional Word Vectors

LSTM-based Text Emotion Recognition Using Semantic and Emoti...

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Asian Conference on Affective computing and Intelligent Interaction (ACII Asia)

作者： Ming-Hsiang Su Chung-Hsien Wu Kun-Yi Huang Qian-Bei Hong Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan Graduate Program of Multimedia Systems and Intelligent Computing National Cheng Kung University and Academia Sinica Tainan Taiwan

ISBN: (纸本)9781538653128

This study proposes a long-short term memory (LSTM)-based approach to text emotion recognition based on semantic word vector and emotional word vector of the input text. For each word in an input text, the semantic word vector is extracted from the word 2vec model. Besides, each lexical word is projected to all the emotional words defined in an affective lexicon to derive an emotional word vector. An autoencoder is then adopted to obtain the bottleneck features from the emotional word vector for dimensionality reduction. The autoencoder bottleneck features are then concatenated with the features in the semantic word vector to form the final textual features for emotion recognition. Finally, given the textual feature sequence of the entire sentence, the LSTM is used for emotion recognition by modeling the contextual emotion evolution of the input text. For evaluation, the NLPCC-MHMC-TE database containing seven emotion categories: anger, boredom, disgust, anxiety, happiness, sadness, and surprise was constructed and used. Five-fold cross-validation was employed to evaluate the performance of the proposed method. Experimental results show that the proposed LSTM-based method achieved a recognition accuracy of 70.66%, improving 5.33% compared with the CNN-based method. Besides, the proposed method based on integration of the semantic word vector and emotional word vector of the input text outperformed that using the individual feature vector.

关键词： Emotion recognition Databases Logic gates Feature extraction Semantics Speech recognition Computer science

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Syncgan: Synchronize the Latent Spaces of Cross-Modal Generative Adversarial Networks

Syncgan: Synchronize the Latent Spaces of Cross-Modal Genera...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Wen-Cheng Chen Chien-Wen Chen Min-Chun Hu Dept. of Computer Science and Information Engineering National Cheng Kung University Taiwan Graduate Program of Multimedia Systems and Intelligent Computing National Cheng Kung University and Academia Sinica Taiwan

Generative adversarial network (GAN) has achieved impressive success on cross-domain generation, but it faces difficulty in cross-modal generation due to the lack of a common distribution between heterogeneous data. Most existing methods of conditional based cross-modal GANs adopt the strategy of one-directional transfer and have achieved preliminary success on text-to-image transfer. Instead of learning the transfer between different modalities, we aim to learn a synchronous latent space representing the cross-modal common concept. A novel network component named synchronizer is proposed in this work to judge whether the paired data is synchronous/corresponding or not, which can constrain the latent space of generators in the GANs. Our GAN model, named as SyncGAN, can successfully generate synchronous data (e.g., a pair of image and sound) from identical random noise. For transforming data from one modality to another, we recover the latent code by inverting the mappings of a generator and use it to generate data of different modality. In addition, the proposed model can achieve semi-supervised learning, which makes our model more flexible for practical applications.

关键词： Synchronization Gallium nitride Generators Data models Training Generative adversarial networks Training data

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Exploring Macroscopic Fluctuation of Facial Expression for Mood Disorder Classification

Exploring Macroscopic Fluctuation of Facial Expression for M...

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Asian Conference on Affective computing and Intelligent Interaction (ACII Asia)

作者： Qian-Bei Hong Chung-Hsien Wu Ming-Hsiang Su Kun-Yi Huang Graduate Program of Multimedia Systems and Intelligent Computing National Cheng Kung University and Academia Sinica Tainan Taiwan Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan

ISBN: (纸本)9781538653128

In clinical diagnosis of mood disorder, a large portion of bipolar disorder patients (BDs) are misdiagnosed as unipolar depression (UDs). Clinicians have confirmed that BDs generally show "reduced affect'' during clinical treatment. Thus, it is expected to build an objective and one-time diagnosis system for diagnosis assistance by using machine-learning techniques. In this study, facial expressions of BD, UD and control group (C) elicited by emotional video clips are collected for exploring temporal fluctuation characteristics of intensities of facial muscles expression among the three groups. The differences of facial expressions among mood disorders are investigated by observing macroscopic fluctuations. To deal with these problems, the corresponding methods for feature extraction and modeling are proposed. From the viewpoint of macroscopic facial expression, action unit (AU) is applied for describing the temporal transformation of muscles. Then, modulation spectrum is used for extracting short-term variation of AU. The multilayer perceptron (MLP)-based disorder prediction model is then applied to obtain the prediction results. For evaluation of the proposed method, 12 subjects for three group are included in the K-fold (K=12) cross validation experiments. The experiment results reached 61.1% classification accuracy, and outperformed the other baseline methods.

关键词： Mood Gold Fluctuations Databases Feature extraction Modulation Predictive models

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Combined effects of hydrometeorological hazards and urbanisation on dengue risk in Brazil: a spatiotemporal modelling study

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The Lancet Planetary Health 2021年第4期5卷 e209-e219页

作者： Lowe, Rachel Lee, Sophie A Brady, Oliver J Bastos, Leonardo Carrasco-Escobar, Gabriel de Castro Catão, Rafael Colón-González, Felipe J Barcellos, Christovam Carvalho, Marilia Sá Blangiardo, Marta Rue, Håvard Gasparrini, Antonio Centre for Mathematical Modelling of Infectious Diseases London School of Hygiene & Tropical Medicine London United Kingdom Centre on Climate Change and Planetary Health London School of Hygiene & Tropical Medicine London United Kingdom Department of Infectious Disease Epidemiology London School of Hygiene & Tropical Medicine London United Kingdom Department of Public Health Environments and Society London School of Hygiene & Tropical Medicine London United Kingdom Centre for Statistical Modelling London School of Hygiene & Tropical Medicine London United Kingdom Scientific Computing Program Oswaldo Cruz Foundation Rio de Janeiro Brazil Health Information and Communication Institute Oswaldo Cruz Foundation Rio de Janeiro Brazil Scripps Institution of Oceanography University of California San Diego San Diego CA United States Health Innovation Laboratory Institute of Tropical Medicine Alexander von Humboldt Universidad Peruana Cayetano Heredia Lima Peru Department of Geography Federal University of Espírito Santo Vitória Brazil MRC Centre for Environment and Health Department of Epidemiology and Biostatistics Imperial College London London United Kingdom Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia

Background: Temperature and rainfall patterns are known to influence seasonal patterns of dengue transmission. However, the effect of severe drought and extremely wet conditions on the timing and intensity of dengue epidemics is poorly understood. In this study, we aimed to quantify the non-linear and delayed effects of extreme hydrometeorological hazards on dengue risk by level of urbanisation in Brazil using a spatiotemporal model. Methods: We combined distributed lag non-linear models with a spatiotemporal Bayesian hierarchical model framework to determine the exposure-lag-response association between the relative risk (RR) of dengue and a drought severity index. We fit the model to monthly dengue case data for the 558 microregions of Brazil between January, 2001, and January, 2019, accounting for unobserved confounding factors, spatial autocorrelation, seasonality, and interannual variability. We assessed the variation in RR by level of urbanisation through an interaction between the drought severity index and urbanisation. We also assessed the effect of hydrometeorological hazards on dengue risk in areas with a high frequency of water supply shortages. Findings: The dataset included 12 895 293 dengue cases reported between 2001 and 2019 in Brazil. Overall, the risk of dengue increased between 0–3 months after extremely wet conditions (maximum RR at 1 month lag 1·56 [95% CI 1·41–1·73]) and 3–5 months after drought conditions (maximum RR at 4 months lag 1·43 [1·22–1·67]). Including a linear interaction between the drought severity index and level of urbanisation improved the model fit and showed the risk of dengue was higher in more rural areas than highly urbanised areas during extremely wet conditions (maximum RR 1·77 [1·32–2·37] at 0 months lag vs maximum RR 1·58 [1·39–1·81] at 2 months lag), but higher in highly urbanised areas than rural areas after extreme drought (maximum RR 1·60 [1·33–1·92] vs 1·15 [1·08–1·22], both at 4 months lag). We also found the den

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Spin-orbit Interactions for Singlet-Triplet Qubits in Silicon

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Physical Review Letters 2019年第21期122卷 217702-217702页

作者： Patrick Harvey-Collard N. Tobias Jacobson Chloé Bureau-Oxton Ryan M. Jock Vanita Srinivasa Andrew M. Mounce Daniel R. Ward John M. Anderson Ronald P. Manginell Joel R. Wendt Tammy Pluym Michael P. Lilly Dwight R. Luhman Michel Pioro-Ladrière Malcolm S. Carroll Département de physique et Institut quantique Université de Sherbrooke Sherbrooke (Québec) J1K 2R1 Canada Sandia National Laboratories Albuquerque New Mexico 87185 USA Center for Computing Research Sandia National Laboratories Albuquerque New Mexico 87185 USA Center for Integrated Nanotechnologies Sandia National Laboratories Albuquerque New Mexico 87185 USA Quantum Information Science Program Canadian Institute for Advanced Research Toronto (Ontario) M5G 1Z8 Canada

Spin-orbit coupling is relatively weak for electrons in bulk silicon, but enhanced interactions are reported in nanostructures such as the quantum dots used for spin qubits. These interactions have been attributed to various dissimilar interface effects, including disorder or broken crystal symmetries. In this Letter, we use a double-quantum-dot qubit to probe these interactions by comparing the spins of separated singlet-triplet electron pairs. We observe both intravalley and intervalley mechanisms, each dominant for [110] and [100] magnetic field orientations, respectively, that are consistent with a broken crystal symmetry model. We also observe a third spin-flip mechanism caused by tunneling between the quantum dots. This improved understanding is important for qubit uniformity, spin control and decoherence, and two-qubit gates.

关键词： Coulomb blockade Quantum control Quantum gates Quantum information with solid state qubits Spin blockade Spin-orbit coupling Double quantum dots Elemental semiconductors MOSFET Nanostructures Bloch wave theory Dilution refrigerator Electrical techniques

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AIRR community curation and standardised representation for immunoglobulin and T cell receptor germline sets

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Immunoinformatics (Amsterdam, Netherlands) 2023年 10卷 100025页

作者： William D Lees Scott Christley Ayelet Peres Justin T Kos Brian Corrie Duncan Ralph Felix Breden Lindsay G Cowell Gur Yaari Martin Corcoran Gunilla B Karlsson Hedestam Mats Ohlin Andrew M Collins Corey T Watson Christian E Busse Institute of Structural and Molecular Biology Birkbeck College London England. Human-Centered Computing and Information Science Institute for Systems and Computer Engineering Technology and Science Porto Portugal. Peter O'Donnell Jr. School of Public Health UT Southwestern Medical Center Dallas TX USA. Bioengineering Program Faculty of Engineering Bar-Ilan University Ramat Gan Israel. Department of Biochemistry and Molecular Genetics School of Medicine University of Louisville KY USA. Department of Biological Sciences Simon Fraser University Burnaby BC Canada. Fred Hutchinson Cancer Research Center Seattle WA USA. Peter O'Donnell Jr. School of Public Health Department of Immunology School of Biomedical Sciences UT Southwestern Medical Center Dallas TX USA. Department of Microbiology Tumor and Cell Biology Karolinska Institutet Stockholm Swede. Department of Immunotechnology and SciLifeLab Lund University Lund Sweden. School of Biotechnology and Biomolecular Sciences University of New South Wales Sydney NSW Australia. Division of B Cell Immunology German Cancer Research Center Heidelberg Germany.

Analysis of an individual's immunoglobulin or T cell receptor gene repertoire can provide important insights into immune function. High-quality analysis of adaptive immune receptor repertoire sequencing data depends upon accurate and relatively complete germline sets, but current sets are known to be incomplete. Established processes for the review and systematic naming of receptor germline genes and alleles require specific evidence and data types, but the discovery landscape is rapidly changing. To exploit the potential of emerging data, and to provide the field with improved state-of-the-art germline sets, an intermediate approach is needed that will allow the rapid publication of consolidated sets derived from these emerging sources. These sets must use a consistent naming scheme and allow refinement and consolidation into genes as new information emerges. Name changes should be minimised, but, where changes occur, the naming history of a sequence must be traceable. Here we outline the current issues and opportunities for the curation of germline IG/TR genes and present a forward-looking data model for building out more robust germline sets that can dovetail with current established processes. We describe interoperability standards for germline sets, and an approach to transparency based on principles of findability, accessibility, interoperability, and reusability.

关键词： AIRR-seq Immune receptor Immune receptor germline Immune receptor repertoire Rep-seq

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Author Correction: The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci

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Nature computational science 2023年第7期3卷 658页

作者： Gengjie Jia Yu Li Xue Zhong Kanix Wang Milton Pividori Rabab Alomairy Aniello Esposito Hatem Ltaief Chikashi Terao Masato Akiyama Koichi Matsuda David E Keyes Hae Kyung Im Takashi Gojobori Yoichiro Kamatani Michiaki Kubo Nancy J Cox James Evans Xin Gao Andrey Rzhetsky Shenzhen Branch Guangdong Laboratory of Lingnan Modern Agriculture Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China. jiagengjie@***. Computational Bioscience Research Center King Abdullah University of Science and Technology Thuwal Saudi Arabia. Computer Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong People's Republic of China. Department of Medicine and Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville TN US. Department of Medicine Institute of Genomics and Systems Biology Committee on Genomics Genetics and Systems Biology University of Chicago Chicago IL US. Department of Operations Business Analytics and Information Systems University of Cincinnati Cincinnati OH US. Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania Philadelphia PA US. Extreme Computing Research Center Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia. HPE HPC/AI EMEA Research Laboratory Bristol UK. RIKEN Center for Integrative Medical Sciences Yokohama Japan. Clinical Research Center Shizuoka General Hospital Shizuoka Japan. Department of Applied Genetics The School of Pharmaceutical Sciences University of Shizuoka Shizuoka Japan. Department of Ophthalmology Graduate School of Medical Sciences Kyushu University Fukuoka Japan. Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences The University of Tokyo Tokyo Japan. Biological and Environmenta

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Lithium-Ion Batteries: Operando Magnetometry Probing the Charge Storage Mechanism of CoO Lithium-Ion Batteries (Adv. Mater. 12/2021)

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Advanced Materials 2021年第12期33卷

作者： Hongsen Li Zhengqiang Hu Qingtao Xia Hao Zhang Zhaohui Li Huaizhi Wang Xiangkun Li Fengkai Zuo Fengling Zhang Xiaoxiong Wang Wanneng Ye Qinghao Li Yunze Long Qiang Li Shishen Yan Xiaosong Liu Xiaogang Zhang Guihua Yu Guo-Xing Miao College of Physics Center for Marine Observation and Communications Qingdao University Qingdao 266071 China School of Physics State Key Laboratory of Crystal Materials Shandong University Jinan 250100 China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology (SIMIT) Chinese Academy of Sciences Shanghai 200050 China College of Material Science and Engineering Nanjing University of Aeronautics and Astronautics Nanjing 210016 China Materials Science and Engineering Program and Department of Mechanical Engineering The University of Texas at Austin Austin TX 78712 USA Department of Electrical and Computer Engineering & Institute for Quantum Computing University of Waterloo Waterloo ON N2L 3G1 Canada

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Eavesdropper's ability to attack a free-space quantum-key-distribution receiver in atmospheric turbulence

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Physical Review A 2019年第6期99卷 062315-062315页

作者： Poompong Chaiwongkhot Katanya B. Kuntz Yanbao Zhang Anqi Huang Jean-Philippe Bourgoin Shihan Sajeed Norbert Lütkenhaus Thomas Jennewein Vadim Makarov Institute for Quantum Computing University of Waterloo Waterloo ON Canada N2L 3G1 Department of Physics and Astronomy University of Waterloo Waterloo ON Canada N2L 3G1 NTT Basic Research Laboratories NTT Corporation Atsugi Kanagawa 243-0198 Japan NTT Research Center for Theoretical Quantum Physics NTT Corporation Atsugi Kanagawa 243-0198 Japan Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha 410073 People's Republic of China Department of Electrical and Computer Engineering University of Waterloo Waterloo ON Canada N2L 3G1 Aegis Quantum Waterloo ON Canada Department of Electrical and Computer Engineering University of Toronto Toronto Canada M5S 3G4 Quantum Information Science Program Canadian Institute for Advanced Research Toronto ON Canada M5G 1Z8 Russian Quantum Center Skolkovo Moscow 143025 Russia Shanghai Branch National Laboratory for Physical Sciences at Microscale and CAS Center for Excellence in Quantum Information University of Science and Technology of China Shanghai 201315 People's Republic of China NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow 119049 Russia

The ability of an eavesdropper (Eve) to perform an intercept-resend attack on a free-space quantum-key-distribution (QKD) receiver by precisely controlling the incidence angle of an attack laser has been previously demonstrated. However, such an attack could be ineffective in the presence of atmospheric turbulence due to beam wander and spatial mode aberrations induced by the air's varying index of refraction. We experimentally investigate the impact turbulence has on Eve's attack on a free-space polarization-encoding QKD receiver by emulating atmospheric turbulence with a spatial light modulator. Our results identify how well Eve would need to compensate for turbulence to perform a successful attack by either reducing her distance to the receiver or using beam wavefront correction via adaptive optics. Furthermore, we use an entanglement-breaking scheme to find a theoretical limit on the turbulence strength that hinders Eve's attack.

关键词： Quantum cryptography

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