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SSRN 2024年

作者： Li, Ruizhi He, Jintao Yin, Minghao Hu, Shuli Ding, Nan Jilin University of Finance and Economics Changchun130117 China Northeast Normal University Changchun130117 China Business Big Data Research Center of Jilin Province Changchun130117 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China

The minimum weighted connected dominating set problem is a classical NP-hard problem with wide applications in practice. In this paper, an efficient local search algorithm is proposed to solve this problem. In this algorithm, firstly, an initial solution construction method based on greedy randomized adaptive strategy is adopted, which can balance the quality and the diversity of the initial solutions. Second, two new scoring functions, Ascore and Cscore, are proposed to increase the diversity of deleted vertices. Third, a new connectivity method is proposed so that the algorithm no longer relies on the shortest path between two connected components. Fourth, a vertex penalty mechanism is introduced, which helps the algorithm to jump out of the local optimum effectively. Fifth, two scoring functions, Ascore and Cscore, are combined with the vertex penalty mechanism to propose an effective vertex selection method, which helps the algorithm to select suitable vertices to be added to or removed from the current candidate solution. Finally, the propsoed local search algorithm is compared with seven state-of-the-art algorithms on three types of benchmark instances. The experimental results show that the algorithm exhibits better performance on these three types of classical benchmark instances. © 2024, The Authors. All rights reserved.

关键词： Learning algorithms

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Association of coffee consumption and caffeine metabolism with arrhythmias and cardiac morphology: An observational, genetic, and Mendelian randomization study

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Heart Rhythm 2025年

作者： Zheng, Jiazhen Chen, Haowen Yang, Quan Zhou, Zhen Yang, Chuang Huang, Jinghan Tu, Qiang Wu, Haisheng Qiu, Peng Huang, Wenbo Shi, Wenming Chen, Mifen Liu, Huamin Shen, Junchun Tang, Shaojun Bioscience and Biomedical Engineering Thrust Systems Hub The Hong Kong University of Science and Technology (Guangzhou) Guangdong Guangzhou China Department of Epidemiology School of Public Health (Guangdong Provincial Key Laboratory of Tropical Disease Research) Southern Medical University Guangdong Guangzhou China Cardiac and Vascular Center The University of Hong Kong-Shenzhen Hospital Shenzhen China School of Public Health and Preventive Medicine Monash University Melbourne VIC Australia Medical Faculty University of Leipzig Leipzig Germany Biomedical Genetics Section School of Medicine Boston University One Silber Way Boston MA United States Department of Chemical Pathology Faculty of Medicine The Chinese University of Hong Kong Hong Kong Faculty of Medicine and Health The University of Sydney Sydney NSW Australia School of Public Health LKS Faculty of Medicine The University of Hong Kong Hong Kong Department of Vascular Surgery Shanghai Ninth People's Hospital Shanghai Jiao Tong University School of Medicine Shanghai China Department of Clinical Epidemiology & Health Economics The University of Tokyo Tokyo Japan School of Public Health Fudan University Shanghai China Department of Oncology The First Affiliated Hospital Sun Yat-sen University Guangdong Guangzhou China Department of Anesthesiology Nanfang Hospital Southern Medical University Guangdong Guangzhou China Division of Emerging Interdisciplinary Areas The Hong Kong University of Science and Technology Clear Water Bay Hong Kong

Background: The association of coffee intake and caffeine metabolism with arrhythmias and cardiac structure is not fully understood. Objective: We aim to explore the associations of coffee intake and caffeine metabolism with the risk of certain types of arrhythmias, a broad range of cardiovascular imaging phenotypes, and a potential gene-coffee interaction. Methods: On the basis of the UK Biobank imaging study, heart metrics were extracted via cardiovascular magnetic resonance using machine learning. Caffeine metabolism was determined by cytochrome P4501A2 gene (CYP1A2) or a polygenetic score of different genetic variants influencing caffeine metabolism. Genome-wide association data for 2-sample Mendelian randomization originated predominantly from individuals of European descent. Results: A total of 34,992 individuals (mean age 63.5 ± 7.5 years;18,506 [52.9%] female) were assessed in the principal imaging analysis. Higher daily consumption of coffee was independently associated with higher left ventricular mass, larger global ventricular volume, higher ventricular stroke volume, and larger atrial volume. The results were further supported by Mendelian randomization analysis. CYP1A2 and genetic score for caffeine metabolism were not associated with cardiovascular measurements (P>.053 for all tests). Coffee consumption was associated with a lower risk of sinus rhythm with a short PR interval (per cup increase: odds ratio 0.90;95% confidence interval 0.82–0.99) and atrial fibrillation (odds ratio 0.89;95% confidence interval 0.84–0.93). Conclusion: Coffee consumption was associated with a lower risk of atrial fibrillation, increased left ventricular mass, elevated ventricular volume, and larger atrial volume. Caffeine metabolism did not significantly alter the association. Our results suggest that customary caffeine consumption limitations aimed at arrhythmia risk reduction might be unnecessary. © 2024 Heart Rhythm Society

关键词： Arrhythmias Caffeine metabolism Cardiac structure Coffee consumption Mendelian randomization

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A Bicriterion Concentration Inequality and Prophet Inequalities for k-Fold Matroid Unions

arXiv

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arXiv 2024年

作者： Alon, Noga Gravin, Nick Pollner, Tristan Rubinstein, Aviad Wang, Hongao Weinberg, S. Matthew Zhang, Qianfan Department of Mathematics Princeton University Princeton United States Schools of Mathematics and Computer Science Tel Aviv University Tel Aviv Israel Key Laboratory of Interdisciplinary Research of Computation and Economics Shanghai University of Finance and Economics Shanghai China Department of Management Science and Engineering Stanford University Stanford United States Department of Computer Science Stanford University Stanford United States Department of Computer Science Purdue University West Lafayette United States Department of Computer Science Princeton University Princeton United States

We investigate prophet inequalities with competitive ratios approaching 1, seeking to generalize k-uniform matroids. We first show that large girth does not suffice: for all k, there exists a matroid of girth ≥ k and a prophet inequality instance on that matroid whose optimal competitive ratio is 1/2 . Next, we show k-fold matroid unions do suffice: we provide a prophet inequality with competitive ratio (formula presented) for any k-fold matroid union. Our prophet inequality follows from an online contention resolution scheme. The key technical ingredient in our online contention resolution scheme is a novel bicriterion concentration inequality for arbitrary monotone 1-Lipschitz functions over independent items which may be of independent interest. Applied to our particular setting, our bicriterion concentration inequality yields "Chernoff-strength" concentration for a 1-Lipschitz function that is not (approximately) self-bounding. Copyright © 2024, The Authors. All rights reserved.

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Promoting subjective preferences in simple economic choices during nap

Promoting subjective preferences in simple economic choices ...

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中国睡眠研究会第十一届全国学术年会

作者： Sizhi Ai Yunlu Yin Yu Chen Cong Wang Yan Sun Xiangdong Tang Lin Lu Lusha Zhu Jie Shi National Institute on Drug Dependence Peking University Department of Cardiology Henan Key Laboratory of Neurorestoratology The First Affiliated Hospital of Xinxiang Medical University School of Psychological and Cognitive Sciences Peking University Faculty of Business and Economics The University of Hong Kong Peking-Tsinghua Center for Life Sciences Peking University Academy for Advanced Interdisciplinary Studies Peking University IDG/McGovern Institute for Brain Research Peking University Sleep Medicine Center State Key Laboratory of Biotherapy West China Hospital Sichuan University Institute of Mental Health National Clinical Research Center for Mental Disorders Key Laboratory of Mental Health and Peking University Sixth Hospital Peking University Key Laboratory of Machine Perception Ministry of Education Beijing Key Laboratory of Behavior and Mental Health Peking University Beijing Key Laboratory on Drug Dependence Research The Key Laboratory for Neuroscience of the Ministry of Education and Health The State Key Laboratory of Natural and Biomimetic Drugs

Sleep is known to benefit consolidation of memories, especially those of motivational relevance. Yet, it remains largely unknown the extent to which sleep influences reward-associated behavior, in particular, whether and how sleep modulates reward evaluation that critically underlies value-based decisions. Here, we show that neural processing during sleep can selectively bias preferences in simple economic choices when the sleeper is stimulated by covert, reward-associated cues. Specifically, presenting the spoken name of a familiar, valued snack item during midday nap significantly improves the preference for that item relative to items not externally cued. The cueing-specific preference enhancement is sleep-dependent and can be predicted by cue-induced neurophysiological signals at the subject and item level. computational modeling further suggests that sleep cueing accelerates evidence accumulation for cued options during the post-sleep choice process in a manner consistent with the preference shift. These findings suggest that neurocognitive processing during sleep contributes to the fine-tuning of subjective preferences in a flexible, selective manner. Summary: Sleep complements wakefulness by supporting an array of cognitive functions. Yet its role in complex behavior such as value-based decision-making remains to be explored. Substantial evidence suggests that the storage of reward-related information does not stay sedentary during sleep. It remains to be explored, however, whether neural activity during sleep directly supports or modulates cognitive processes related to reward processing in ways that affect goal-directed behaviors, despite potential implications of such research for understanding the nature of mechanisms underlying sleep and reward processing and for clinical interventions aiming at modifying human behavior, such as overeating or smoking, to prevent diseases. We first examined whether TMR modifies behavior and whether such modification is sl

关键词： Promoting subjective preferences in simple economic choices during nap

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DL2G: Anatomical Landmark Detection with Deep Local Features and Geometric Global Constraint

DL2G: Anatomical Landmark Detection with Deep Local Features...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Rui Wang Wanli Yang Kuntao Xiao Yi Sun Shurong Sheng Zhao Lv Jiahong Gao Auhui University Hefei China Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China Anhui Province Key Laboratory of Multimodal Cognitive Computation Hefei China Center for MRI Research Academy for Advanced Interdisciplinary Studies Peking University Beijing China Beijing City Key Lab for Medical Physics and Engineering Institute of Heavy Ion PhysicsSchool of Physics Peking University Beijing China McGovern Institute for BrainResearch Peking University Beijing China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Anatomical landmark detection, a pivotal research area in medical image processing, holds immense value in surgical navigation, image registration, and related fields. Traditional machine learning methods struggle with generalization and robustness. Current supervised end-to-end approaches lacks in-terpretability in capturing global information, and GPU memory constraints restrict their application to extensive 3D medical image datasets. Moreover, existing methods overlook intrinsic geometric cues within images and point sets. Herein, we introduce a novel anatomical landmark detection framework that integrates deep learning’s representation capabilities with global geometric information derived from images and point sets (DL2G). This approach facilitates anatomical landmark localization in a local-to-global fashion. Initially, we train a deep feature descriptor based on self-supervised contrastive learning, which is further used to screen candidate points for the target one by comparing local patch embeddings. Subsequently, geometric constraints constructed from labeled template point sets enable the selection of geometrically consistent matching point sets. Ultimately, the framework utilizes the global mutual information of images to perform landmark localization through iterative optimization. Adhering to the AFID data annotation protocol, we evaluated our method on two public MRI head datasets, OASIS and HCP, for detecting 32 anatomical landmarks. The results convincingly demonstrate the superiority of our method over current state-of-the-art approaches in terms of both accuracy and computational efficiency.

关键词： Location awareness Three-dimensional displays Protocols Navigation Memory management Surgery Feature extraction Robustness Optimization Mutual information

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Metrological Characterization of Non-Gaussian Entangled States of Superconducting Qubits

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Physical Review Letters 2022年第15期128卷 150501-150501页

作者： Kai Xu Yu-Ran Zhang Zheng-Hang Sun Hekang Li Pengtao Song Zhongcheng Xiang Kaixuan Huang Hao Li Yun-Hao Shi Chi-Tong Chen Xiaohui Song Dongning Zheng Franco Nori H. Wang Heng Fan Institute of Physics Chinese Academy of Sciences Beijing 100190 China Theoretical Quantum Physics Laboratory RIKEN Cluster for Pioneering Research Wako-shi Saitama 351-0198 Japan RIKEN Center for Quantum Computing (RQC) Wako-shi Saitama 351-0198 Japan Physics Department University of Michigan Ann Arbor Michigan 48109-1040 USA Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation and Zhejiang Province Key Laboratory of Quantum Technology and Device Department of Physics Zhejiang University Hangzhou 310027 China Beijing Academy of Quantum Information Sciences and CAS Center for Excellence in Topological Quantum Computation University of Chinese Academy of Sciences Beijing 100190 China

Multipartite entangled states are significant resources for both quantum information processing and quantum metrology. In particular, non-Gaussian entangled states are predicted to achieve a higher sensitivity of precision measurements than Gaussian states. On the basis of metrological sensitivity, the conventional linear Ramsey squeezing parameter (RSP) efficiently characterizes the Gaussian entangled atomic states but fails for much wider classes of highly sensitive non-Gaussian states. These complex non-Gaussian entangled states can be classified by the nonlinear squeezing parameter (NLSP), as a generalization of the RSP with respect to nonlinear observables and identified via the Fisher information. However, the NLSP has never been measured experimentally. Using a 19-qubit programmable superconducting processor, we report the characterization of multiparticle entangled states generated during its nonlinear dynamics. First, selecting ten qubits, we measure the RSP and the NLSP by single-shot readouts of collective spin operators in several different directions. Then, by extracting the Fisher information of the time-evolved state of all 19 qubits, we observe a large metrological gain of 9.89−0.29+0.28 dB over the standard quantum limit, indicating a high level of multiparticle entanglement for quantum-enhanced phase sensitivity. Benefiting from high-fidelity full controls and addressable single-shot readouts, the superconducting processor with interconnected qubits provides an ideal platform for engineering and benchmarking non-Gaussian entangled states that are useful for quantum-enhanced metrology.

关键词： Quantum entanglement Quantum information with solid state qubits Quantum metrology Quantum parameter estimation Quantum simulation Superconducting qubits

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Metrological characterisation of non-Gaussian entangled states of superconducting qubits

arXiv

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arXiv 2021年

作者： Xu, Kai Zhang, Yu-Ran Sun, Zheng-Hang Li, Hekang Song, Pengtao Xiang, Zhongcheng Huang, Kaixuan Li, Hao Shi, Yun-Hao Chen, Chi-Tong Song, Xiaohui Zheng, Dongning Nori, Franco Wang, H. Fan, Heng Institute of Physics Chinese Academy of Sciences Beijing100190 China Theoretical Quantum Physics Laboratory RIKEN Cluster for Pioneering Research Wako-shi Saitama351-0198 Japan Physics Department University of Michigan Ann ArborMI48109-1040 United States Interdisciplinary Centre for Quantum Information State Key Laboratory of Modern Optical Instrumentation Zhejiang Province Key Laboratory of Quantum Technology and Device Department of Physics Zhejiang University Hangzhou310027 China CAS Centre for Excellence in Topological Quantum Computation UCAS Beijing100190 China

Multipartite entangled states are significant resources for both quantum information processing and quantum metrology [1]. In particular, non-Gaussian entangled states are predicted to achieve a higher sensitivity of precision measurements than Gaussian states [2]. On the basis of metrological sensitivity, the conventional linear Ramsey squeezing parameter (RSP) [3, 4] efficiently characterises the Gaussian entangled atomic states but fails for much wider classes of highly sensitive non-Gaussian states. These complex non-Gaussian entangled states can be classified by the nonlinear squeezing parameter (NLSP), as a generalisation of the RSP with respect to nonlinear observables [5], and identified via the Fisher information [6]. However, the NLSP has never been measured experimentally. Using a 19-qubit programmable superconducting processor, here we report the characterisation of multiparticle entangled states generated during its nonlinear dynamics. First, selecting 10 qubits, we measure the RSP and the NLSP by single-shot readouts of collective spin operators in several different directions. Then, by extracting the Fisher information of the time-evolved state of all 19 qubits, we observe a large metrological gain of 9.89+0−02829 dB over the standard quantum limit [1], indicating a high level of multiparticle entanglement for quantum-enhanced phase sensitivity. Benefiting from high-fidelity full controls and addressable single-shot readouts, the superconducting processor with interconnected qubits provides an ideal platform for engineering and benchmarking non-Gaussian entangled states that are useful for quantum-enhanced metrology. Copyright © 2021, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

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Changing life expectancy in European countries 1990–2021: a subanalysis of causes and risk factors from the Global Burden of Disease Study 2021

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The Lancet Public Health 2025年第3期10卷 e172-e188页

作者： Steel, Nicholas Bauer-Staeb, Clarissa Maria Mercedes Ford, John A. Abbafati, Cristiana Abdalla, Mohammed Altigani Abdelkader, Atef Abdi, Parsa Zuñiga, Roberto Ariel Abeldaño Abiodun, Olugbenga Olusola Abolhassani, Hassan Abu-Gharbieh, Eman Abukhadijah, Hana J. Abu-Zaid, Ahmed Addo, Isaac Yeboah Addolorato, Giovanni Adekanmbi, Victor Adetunji, Juliana Bunmi Adeyeoluwa, Temitayo Esther Agardh, Emilie E. Agyemang-Duah, Williams Ahmad, Danish Ahmed, Ayman Ahmed, Syed Anees Akinosoglou, Karolina Akkaif, Mohammed Ahmed Al Awaidy, Salah Al Hasan, Syed Mahfuz Al Zaabi, Omar Ali Mohammed Aldridge, Robert W. Algammal, Abdelazeem M. Al-Gheethi, Adel Ali Saeed Ali, Abid Ali, Mohammed Usman Ali, Syed Shujait Ali, Waad Alicandro, Gianfranco Alif, Sheikh Mohammad Al-Jumaily, Adel Allebeck, Peter Alrawashdeh, Ahmad Al-Rifai, Rami H. Alsabri, Mohammed A. Alshahrani, Najim Z. Aluh, Deborah Oyine Al-Wardat, Mohammad Al-Zyoud, Walid A. Amiri, Sohrab Anderlini, Deanna Andrei, Catalina Liliana Anil, Abhishek Anvari, Saeid Anyasodor, Anayochukwu Edward Appiah, Seth Christopher Yaw Aquilano, Michele Arabloo, Jalal Arafat, Mosab Areda, Demelash Aremu, Abdulfatai Armani, Keivan Armocida, Benedetta Ärnlöv, Johan Asaduzzaman, Muhammad Astell-Burt, Thomas Aujayeb, Avinash Ausloos, Marcel Azadnajafabad, Sina Aziz, Shahkaar Azzam, Ahmed Y. Babu, Giridhara Rathnaiah Badache, Andreea Corina Badiye, Ashish D. Bahramian, Saeed Baig, Atif Amin Baker, Jennifer L. Bansal, Hansi Bärnighausen, Till Winfried Barone, Mark Thomaz Ugliara Barrow, Amadou Barteit, Sandra Bashir, Shahid Bashiru, Hameed Akande Basso, João Diogo Bastan, Mohammad-Mahdi Basu, Sanjay Batra, Kavita Bauckneht, Matteo Baune, Bernhard T. Beghi, Massimiliano Beiranvand, Maryam Béjot, Yannick Bell, Michelle L. Bello, Olorunjuwon Omolaja Belo, Luis Beloukas, Apostolos Beneke, Alice A. Bettencourt, Paulo J.G. Bhagavathula, Akshaya Srikanth Bhala, Neeraj Bhaskar, Sonu Bisulli, Francesca Bjørge, Tone Bodunrin, Aadam Olalekan Carvajal, Alejandro Botero Bouaoud, Souad Brayne, Carol Brenner, H Department of Primary Care and Public Health University of East Anglia Norwich United Kingdom Office for Health Improvement and Disparities Department of Health and Social Care London United Kingdom Department of Legal and Economic Studies La Sapienza University Rome Italy Rome Italy Hull York Medical School University of Hull Hull United Kingdom Department of Mathematics and Sciences Ajman University Ajman United Arab Emirates Department of Medicine Memorial University St. John's NL Canada Postgraduate Department University of Sierra Sur Miahuatlan de Porfirio Diaz Mexico Yhteiskuntadatatieteen keskus (Centre for Social Data Science) Helsinki Finland Department of Internal Medicine Federal Medical Centre Abuja Nigeria Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Medical Biochemistry and Biophysics Karolinska Institutet (Karolinska Institute) Stockholm Sweden Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Department of Biopharmaceutics and Clinical Pharmacy University of Jordan Amman Jordan Medical Research Center Hamad Medical Corporation Doha Qatar Department of Biochemistry and Molecular Medicine Alfaisal University Riyadh Saudi Arabia College of Graduate Health Sciences University of Tennessee Memphis TN United States School of Medicine Sydney NSW Australia Centre for Social Research in Health University of New South Wales Sydney NSW Australia Internal Medicine and Alcohol Related Disease Unit Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy Department of Medical and Surgical Sciences Università Cattolica di Roma (Catholic University of Rome) Rome Italy Department of Obstetrics and Gynecology University of Texas Medical Branch Galveston TX United States Department of Biochemistry Osun State University Osogbo Nigeria Department of Pharmacology and Therapeutics University of Medical Sciences Ondo Ondo Nigeria Department of Veteri

Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic. Methods: We used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy. Findings: All countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy a

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Automated Detection of Epileptic Spikes and Seizures Incorporating a Novel Spatial Clustering Prior

Automated Detection of Epileptic Spikes and Seizures Incorpo...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Hanyang Dong Shurong Sheng Xiongfei Wang Jia-Hong Gao Yi Sun Wanli Yang Kuntao Xiao Pengfei Teng Guoming Luan Zhao Lv School of Artificial Intelligence Anhui University Hefei China Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China Department of Neurosurgery Beijing Key Laboratory of Epilepsy Sanbo Brain Hospital Capital Medical University Beijing China McGovern Institute for Brain Research Peking University Beijing China Center for MRI Research Academy for Advanced Interdisciplinary Studies Peking University Beijing China Beijing City Key Lab for Medical Physics and Engineering Institute of Heavy Ion Physics School of Physics Peking University Beijing China Anhui Province Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

A Magnetoencephalography (MEG) time-series recording consists of multi-channel signals collected by superconducting sensors, with each signal’s intensity reflecting magnetic field changes over time at the sensor location. Automating epileptic MEG spike detection significantly reduces manual assessment time and effort, yielding substantial clinical benefits. Existing research addresses MEG spike detection by encoding neural network inputs with signals from all channel within a time segment, followed by classification. However, these methods overlook simultaneous spiking occurred from nearby sensors. We introduce a simple yet effective paradigm that first clusters MEG channels based on their sensor’s spatial position. Next, a novel convolutional input module is designed to integrate the spatial clustering and temporal changes of the signals. This module is fed into a custom MEEG-ResNet3D developed by the authors, which learns to extract relevant features and classify the input as a spike clip or not. Our method achieves an F1 score of 94.73% on a large real-world MEG dataset Sanbo-CMR collected from two centers, outperforming state-of-the-art approaches by 1.85%. Moreover, it demonstrates efficacy and stability in the Electroencephalographic (EEG) seizure detection task, yielding an improved weighted F1 score of 1.4% compared to current state-of-the-art techniques evaluated on TUSZ, whch is the largest EEG seizure dataset.

关键词： Convolution Magnetic sensors Neural networks Magnetoencephalography Manuals Feature extraction Electroencephalography Encoding Recording Magnetic fields

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Observation of a Superradiant Phase Transition with Emergent Cat States

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Physical Review Letters 2023年第11期131卷 113601-113601页

作者： Ri-Hua Zheng Wen Ning Ye-Hong Chen Jia-Hao Lü Li-Tuo Shen Kai Xu Yu-Ran Zhang Da Xu Hekang Li Yan Xia Fan Wu Zhen-Biao Yang Adam Miranowicz Neill Lambert Dongning Zheng Heng Fan Franco Nori Shi-Biao Zheng Fujian Key Laboratory of Quantum Information and Quantum Optics College of Physics and Information Engineering Fuzhou University Fuzhou Fujian 350108 China Theoretical Quantum Physics Laboratory RIKEN Cluster for Pioneering Research Wako-shi Saitama 351-0198 Japan Quantum Information Physics Theory Research Team RIKEN Center for Quantum Computing (RQC) Wako-shi Saitama 351-0198 Japan Institute of Physics and Beijing National Laboratory for Condensed Matter Physics Chinese Academy of Sciences Beijing 100190 China CAS Center for Excellence in Topological Quantum Computation University of Chinese Academy of Sciences Beijing 100190 China School of Physics and Optoelectronics South China University of Technology Guangzhou 510640 China Interdisciplinary Center of Quantum Information State Key Laboratory of Modern Optical Instrumentation and Zhejiang Province Key Laboratory of Quantum Technology and Device School of Physics Zhejiang University Hangzhou 310027 China Institute of Spintronics and Quantum Information Faculty of Physics Adam Mickiewicz University 61-614 Poznań Poland Department of Physics University of Michigan Ann Arbor Michigan 48109-1040 USA

Superradiant phase transitions (SPTs) are important for understanding light-matter interactions at the quantum level, and play a central role in criticality-enhanced quantum sensing. So far, SPTs have been observed in driven-dissipative systems, but the emergent light fields did not show any nonclassical characteristic due to the presence of strong dissipation. Here we report an experimental demonstration of the SPT featuring the emergence of a highly nonclassical photonic field, realized with a resonator coupled to a superconducting qubit, implementing the quantum Rabi model. We fully characterize the light-matter state by Wigner matrix tomography. The measured matrix elements exhibit quantum interference intrinsic of a photonic mesoscopic superposition, and reveal light-matter entanglement.

关键词： Quantum entanglement Quantum foundations Quantum phase transitions Superradiance & subradiance

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