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Dynamics and resonance fluorescence from a superconducting artificial atom doubly driven by quantized and classical fields

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Physical Review Research 2024年第3期6卷 033064-033064页

作者： Xinhui Ruan Jia-Heng Wang Dong He Pengtao Song Shengyong Li Qianchuan Zhao L. M. Kuang Jaw-Shen Tsai Chang-Ling Zou Jing Zhang Dongning Zheng O. V. Astafiev Yu-xi Liu Zhihui Peng Department of Automation Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics and Synergetic Innovation Center of Quantum Effects and Applications School of Integrated Circuits School of Physical Sciences Center for Quantum Computing Graduate School of Science CAS Key Laboratory of Quantum Information Hefei National Laboratory Hefei 230088 China School of Automation Science and Engineering MOE Key Lab for Intelligent Networks and Network Security Nobel Street 3 143026 Moscow Russia Institutskiy Pereulok 9 141701 Dolgoprudny Russia Egham Surrey TW20 0EX United Kingdom

We report an experimental demonstration of resonance fluorescence in a two-level superconducting artificial atom under two driving fields coupled to a detuned cavity. One of the fields is classical and the other is varied from quantum (vacuum fluctuations) to classical by controlling the photon number inside the cavity. The device consists of a transmon qubit strongly coupled to a one-dimensional transmission line and a coplanar waveguide resonator. We observe a sideband anticrossing and asymmetry in the emission spectra of the system through a one-dimensional transmission line, which is fundamentally different from the weak-coupling case. By changing the photon number inside the cavity, the emission spectrum of our doubly driven system approaches the case when the atom is driven by two classical bichromatic fields. We also measure the dynamical evolution of the system through the transmission line and study the properties of the first-order correlation function, Rabi oscillations, and energy relaxation in the system. The study of resonance fluorescence from an atom driven by two fields promotes understanding decoherence in superconducting quantum circuits and may find applications in superconducting quantum computing and quantum networks.

关键词： Light-matter interaction Optical pumping Quantum circuits Quantum coherence & coherence measures Quantum-to-classical transition Strong electromagnetic field effects

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Customized Quantum Annealing Schedules

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Physical Review Applied 2022年第4期17卷 044005-044005页

作者： Mostafa Khezri Xi Dai Rui Yang Tameem Albash Adrian Lupascu Daniel A. Lidar Department of Electrical Engineering University of Southern California Los Angeles California 90089 USA Center for Quantum Information Science & Technology University of Southern California Los Angeles California 90089 USA Department of Physics and Astronomy University of Waterloo Waterloo Ontario Canada Institute for Quantum Computing University of Waterloo Waterloo Ontario Canada Department of Electrical and Computer Engineering University of New Mexico Albuquerque New Mexico 87131 USA Center for Quantum Information and Control CQuIC University of New Mexico Albuquerque New Mexico 87131 USA Department of Chemistry University of Southern California Los Angeles California 90089 USA Department of Physics University of Southern California Los Angeles California 90089 USA

In a typical quantum annealing protocol, the system starts with a transverse field Hamiltonian that is gradually turned off and replaced by a longitudinal Ising Hamiltonian. The ground state of the Ising Hamiltonian encodes the solution to the computational problem of interest, and the state overlap with this ground state gives the success probability of the annealing protocol. The form of the annealing schedule can have a significant impact on the ground-state overlap at the end of the anneal, so precise control over these annealing schedules can be a powerful tool for increasing success probabilities of annealing protocols. Here we show how superconducting circuits, in particular capacitively shunted flux qubits, can be used to construct quantum annealing systems by providing tools for mapping circuit flux biases to Pauli coefficients. We use this mapping to find customized annealing schedules: appropriate circuit control biases that yield a desired annealing schedule, while accounting for the physical limitations of the circuitry. We then provide examples and proposals that utilize this capability to improve quantum annealing performance.

关键词： Adiabatic quantum optimization Quantum control Quantum information with solid state qubits Quantum protocols Superconducting qubits

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FaSTrack: A modular framework for real-time motion planning and guaranteed safe tracking

arXiv

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arXiv 2021年

作者： Chen, Mo Herbert, Sylvia L. Hu, Haimin Pu, Ye Fisac, Jaime F. Bansal, Somil Han, SooJean Tomlin, Claire J. School of Computing Science Simon Fraser University Canada Department of Mechanical and Aerospace Engineering UC San Diego United States Department of Electrical Engineering Princeton University United States Department of Electrical and Electronic Engineering University of Melbourne Australia Department of Electrical Engineering and Computer Sciences UC Berkeley United States Control and Dynamical Systems Program California Institute of Technology United States

Real-time, guaranteed safe trajectory planning is vital for navigation in unknown environments. However, real-time navigation algorithms typically sacrifice robustness for computation speed. Alternatively, provably safe trajectory planning tends to be too computationally intensive for real-time replanning. We propose FaSTrack, Fast and Safe Tracking, a framework that achieves both real-time replanning and guaranteed safety. In this framework, real-time computation is achieved by allowing any trajectory planner to use a simplified planning model of the system. The plan is tracked by the system, represented by a more realistic, higher-dimensional tracking model. We precompute the tracking error bound (TEB) due to mismatch between the two models and due to external disturbances. We also obtain the corresponding tracking controller used to stay within the TEB. The precomputation does not require prior knowledge of the environment. We demonstrate FaSTrack using Hamilton-Jacobi reachability for precomputation and three different real-time trajectory planners with three different tracking-planning model pairs. Copyright © 2021, The Authors. All rights reserved.

关键词： Trajectories

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Tumor Detection, Segmentation and Classification Challenge on Automated 3D Breast Ultrasound: The TDSC-ABUS Challenge

arXiv

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arXiv 2025年

作者： Luo, Gongning Xu, Mingwang Chen, Hongyu Liang, Xinjie Tao, Xing Ni, Dong Jeong, Hyunsu Kim, Chulhong Stock, Raphael Baumgartner, Michael Kirchhoff, Yannick Rokuss, Maximilian Maier-Hein, Klaus Yang, Zhikai Fan, Tianyu Boutry, Nicolas Tereshchenko, Dmitry Moine, Arthur Charmetant, Maximilien Sauer, Jan Du, Hao Bai, Xiang-Hui Raikar, Vipul Pai Montoya-Del-Angel, Ricardo Martí, Robert Luna, Miguel Lee, Dongmin Qayyum, Abdul Mazher, Moona Guo, Qihui Wang, Changyan Awasthi, Navchetan Zhao, Qiaochu Wang, Wei Wang, Kuanquan Wang, Qiucheng Dong, Suyu School of Computer Science and Technology Harbin Institute of Technology Harbin150001 China Department of Mathematics Faculty of Science National University of Singapore Singapore National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Shenzhen University Medical School Shenzhen University Shenzhen China Laboratory Shenzhen University Shenzhen China School of Biomedical Engineering and Informatics Nanjing Medical University Nanjing China Pohang Korea Republic of Heidelberg Division of Medical Image Computing Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Germany Heidelberg Germany HIDSS4Health - Helmholtz Information and Data Science School for Health Karlsruhe Heidelberg Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Germany Department of Biomedical Engineering and Health KTH Royal Institute of Technology Stockholm Sweden France FathomX Singapore Saw Swee Hock School of Public Health National University of Singapore Singapore Philips Research University of Girona Spain Department of Robotics and Mechatronics Engineering DGIST Korea Republic of Department of Interdisciplinary Studies of Artificial Intelligence DGIST Korea Republic of National Heart and Lung Institute Faculty of Medicine Imperial College London London United Kingdom Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom Lab School of Communication and Information Engineering Shanghai University Shanghai China Faculty of Science Mathematics and Computer Science Informatics Institute University of Amsterdam Amsterdam1090 GH Netherlands Department of Biomedical Engineering and Physics Amsterdam UMC Amsterdam1081 HV Netherlands Xi’an Jiaotong-Liverpool University China Department of Ultrasound Harbin Medical University Cancer Hospital No. 150 Haping Road Nangang

Breast cancer is one of the most common causes of death among women worldwide. Early detection helps in reducing the number of deaths. Automated 3D Breast Ultrasound (ABUS) is a newer approach for breast screening, which has many advantages over handheld mammography such as safety, speed, and higher detection rate of breast cancer. Tumor detection, segmentation, and classification are key components in the analysis of medical images, especially challenging in the context of 3D ABUS due to the significant variability in tumor size and shape, unclear tumor boundaries, and a low signal-to-noise ratio. The lack of publicly accessible, well-labeled ABUS datasets further hinders the advancement of systems for breast tumor analysis. Addressing this gap, we have organized the inaugural Tumor Detection, Segmentation, and Classification Challenge on Automated 3D Breast Ultrasound 2023 (TDSC-ABUS2023). This initiative aims to spearhead research in this field and create a definitive benchmark for tasks associated with 3D ABUS image analysis. In this paper, we summarize the top-performing algorithms from the challenge and provide critical analysis for ABUS image examination. We offer the TDSC-ABUS challenge as an open-access platform at https://***/ to benchmark and inspire future developments in1algorithmic research. © 2025, CC BY.

关键词： Image segmentation

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Automatic identification of hypertension and assessment of its secondary effects using artificial intelligence: A systematic review (2013–2023)

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Computers in Biology and Medicine 2024年 172卷 108207-108207页

作者： Gudigar, Anjan Kadri, Nahrizul Adib Raghavendra, U. Samanth, Jyothi Maithri, M. Inamdar, Mahesh Anil Prabhu, Mukund A. Hegde, Ajay Salvi, Massimo Yeong, Chai Hong Barua, Prabal Datta Molinari, Filippo Acharya, U. Rajendra Department of Instrumentation and Control Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal576104 India Department of Biomedical Engineering Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia Department of Cardiovascular Technology Manipal College of Health Professions Manipal Academy of Higher Education Manipal576104 India Department of Mechatronics Manipal Institute of Technology Manipal Academy of Higher Education Manipal576104 India Department of Cardiology Kasturba Medical College Manipal Academy of Higher Education Manipal576104 India Manipal Hospitals Karnataka Bengaluru560102 India Biolab PolitoBIOMedLab Department of Electronics and Telecommunications Politecnicodi Torino Turin Italy School of Medicine Faculty of Health and Medical Sciences Taylor's University Subang Jaya47500 Malaysia Cogninet Brain Team Cogninet Australia SydneyNSW2010 Australia Faculty of Business Education Law & Arts University of Southern Queensland ToowoombaQLD4350 Australia Faculty of Engineering and Information Technology University of Technology Sydney SydneyNSW2007 Australia School of Mathematics Physics and Computing University of Southern Queensland SpringfieldQLD4300 Australia Centre for Health Research University of Southern Queensland ToowoombaQLD4350 Australia

Artificial Intelligence (AI) techniques are increasingly used in computer-aided diagnostic tools in medicine. These techniques can also help to identify Hypertension (HTN) in its early stage, as it is a global health issue. Automated HTN detection uses socio-demographic, clinical data, and physiological signals. Additionally, signs of secondary HTN can also be identified using various imaging modalities. This systematic review examines related work on automated HTN detection. We identify datasets, techniques, and classifiers used to develop AI models from clinical data, physiological signals, and fused data (a combination of both). Image-based models for assessing secondary HTN are also reviewed. The majority of the studies have primarily utilized single-modality approaches, such as biological signals (e.g., electrocardiography, photoplethysmography), and medical imaging (e.g., magnetic resonance angiography, ultrasound). Surprisingly, only a small portion of the studies (22 out of 122) utilized a multi-modal fusion approach combining data from different sources. Even fewer investigated integrating clinical data, physiological signals, and medical imaging to understand the intricate relationships between these factors. Future research directions are discussed that could build better healthcare systems for early HTN detection through more integrated modeling of multi-modal data sources. © 2024 The Authors

关键词： Medical imaging

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Exploring the etiology of auditory-verbal hallucinations through air- and bone-conducted self-other voice discrimination, a pilot study with preliminary results

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Neuroscience Applied 2024年 3卷

作者： I. Muselimović M. Bagarić J. Vukojević A. Savić P. Brečić L. Jelić P. Orepić University Psychiatric Hospital Vrapče Department for Diagnostics and Intensive care Zagreb Croatia University Psychiatric Hospital Vrapče Department for Affective disorders Zagreb Croatia Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Zagreb Croatia University of Geneva Campus Biotech Geneva Switzerland

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Influence of the variables describing brain signals on the performance of the Naive Bayesian Classifier

Influence of the variables describing brain signals on the p...

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Progress in Applied Electrical engineering (PAEE)

作者： Aleksandra Kawala-Sterniuk Jaroslaw Zygarlicki Adam Lysiak Barbara Grochowicz Mariusz Pelc Waldemar Bauer Dawid Baczkowicz Krzysztof Krecisz Katarzyna A. Dylag Wiktoria Wieczorek Radana Kahankova Radek Martinek Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland School of Computing and Mathematical Sciences University of Greenwich London UK Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland Faculty of Physical Education and Physiotherapy Opole University of Technology Opole Poland St. Louis Children Hospital Krakow Poland Department of Pathophysiology Jagiellonian University in Krakow–Collegium Medicum Krakow Poland Department of Bioinformatics and Telemedicine Jagiellonian University in Krakow–Collegium Medicum Krakow Poland Department of Cybernetics and Biomedical Engineering–FEECS VSB—Technical University Ostrava Ostrava–Poruba Czech Republic

ISBN: (数字)9781665455152

ISBN: (纸本)9781665455169

In this paper various variables describing brain signals such as near-infrared spectroscopy (NIRS) and electroencephalography (EEG) on the Naive Bayesian Classifier were presented. Analysis of biomedical signals is a very challenging task – therefore the authors of this work decided to analyse two types of brain signals – EEG and NIRS, which have different features, character, nature and are differently prone to various artifacts occurrence. The applied classifiers can be applied for various features extraction and pattern comparisons, which is useful in diagnostic processes.

关键词： Electrical engineering Feature extraction Electroencephalography Bayes methods Task analysis Functional near-infrared spectroscopy

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Numerical Simulation of Lowering a Payload into Waves with a Heave Compensation System Using Openfoam

SSRN

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SSRN 2022年

作者： Wang, Kai Ma, Xin Bai, Wei Qian, Ling Lin, Zaibin School of Control Science and Engineering Shandong University Shandong China Centre for Mathematical Modelling and Flow Analysis Department of Computing and Mathematics Manchester Metropolitan University ManchesterM1 5GD United Kingdom School of Engineering University of Aberdeen AberdeenAB24 3UE United Kingdom 17923 Jingshi Road. Shandong Jinan250061 China

In heavy lifting and lowering marine operations, heave compensation is wildly used to decouple the vessel heave motion from the payload and reduce the dynamic cable tension. This paper proposes a novel OpenFOAM-based numerical model to study the process of lowering payloads into waves by an offshore crane with a heave compensation system. First, an elastic cable module and electric winch system are established in a three-dimensional Numerical Wave Tank (NWT) model to achieve the crane vessel lifting and lowering operation. A correction method for the cable spring force is proposed to reduce the calculation error of the cable system. Second, a heave compensation is designed to compensate the vessel motion while taking hydrodynamic forces on payloads during the lowering operation into account. A physical experiment of lowering an aluminum cuboid into a water tank by the crane platform is conducted to verify the developed model. Finally, the process of lowering payloads into waves is simulated to analyze the dynamic character of the cable force and the payload motion using the developed numerical model. A PID controller is applied to stabilize the payload motion by controlling the winch velocity, reducing the dynamic cable tension and the risk of cable slack. © 2022, The Authors. All rights reserved.

关键词： Numerical models

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Asynchronous Activity Detection for Cell-Free Massive MIMO: From Centralized to Distributed Algorithms

arXiv

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arXiv 2022年

作者： Li, Yang Lin, Qingfeng Liu, Ya-Feng Ai, Bo Wu, Yik-Chung Shenzhen Research Institute of Big Data Shenzhen518172 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Peng Cheng Laboratory Shenzhen518055 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China

Device activity detection in the emerging cell-free massive multiple-input multiple-output (MIMO) systems has been recognized as a crucial task in machine-type communications, in which multiple access points (APs) jointly identify the active devices from a large number of potential devices based on the received signals. Most of the existing works addressing this problem rely on the impractical assumption that different active devices transmit signals synchronously. However, in practice, synchronization cannot be guaranteed due to the low-cost oscillators, which brings additional discontinuous and nonconvex constraints to the detection problem. To address this challenge, this paper reveals an equivalent reformulation to the asynchronous activity detection problem, which facilitates the development of a centralized algorithm and a distributed algorithm that satisfy the highly nonconvex constraints in a gentle fashion as the iteration number increases, so that the sequence generated by the proposed algorithms can get around bad stationary points. To reduce the capacity requirements of the fronthauls, we further design a communication-efficient accelerated distributed algorithm. Simulation results demonstrate that the proposed centralized and distributed algorithms outperform state-of-the-art approaches, and the proposed accelerated distributed algorithm achieves a close detection performance to that of the centralized algorithm but with a much smaller number of bits to be transmitted on the fronthaul links. Copyright © 2022, The Authors. All rights reserved.

关键词： Internet of things

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Non-Hermitian lattice fermions in the 2D Gross-Neveu-Yukawa model

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Physical Review D 2024年第3期110卷 034502-034502页

作者： Xingyu Guo Chen-Te Ma Hui Zhang Key Laboratory of Atomic and Subatomic Structure and Quantum Control (MOE) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter Institute of Quantum Matter South China Normal University Department of Physics and Astronomy Iowa State University Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Asia Pacific Center for Theoretical Physics Pohang University of Science and Technology School of Physics and Telecommunication Engineering South China Normal University The Laboratory for Quantum Gravity and Strings Department of Mathematics and Applied Mathematics University of Cape Town Physics Department Center for Exploration of Energy and Matter Indiana University

We work the lattice fermions and non-Hermitian formulation in the 2D Gross-Neveu-Yukawa (GNY) model and demonstrate the numerical implementation for two flavors by the hybrid Monte Carlo. Our approach has a notable advantage in dealing with chiral symmetry on a lattice by avoiding the Nielsen-Ninomiya theorem, due to the nonsymmetrized finite-difference operator. We restore the hypercubic symmetry by averaging over all possible orientations with the proper continuum limit. Our study is the first simulation for the interacting fermion formulated in a non-Hermitian way. We compare the numerical solution with the one-loop resummation. The resummation results matches with the numerical solution in ⟨ϕ⟩, ⟨ϕ2⟩, ⟨Tr(ψ¯1ψ1+ψ¯2ψ2)/2⟩, and ⟨Tr(ψ¯1ψ1+ψ¯2ψ2)ϕ/2⟩. We also used the one-loop resummation to provide the renormalization group flow and asymptotic safety in the 2D GNY model.

关键词： Nonperturbative effects in field theory Perturbation theory Chiral symmetry Hybrid Monte Carlo algorithm Lattice field theory

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