检索结果-内蒙古大学图书馆

Light cone distribution amplitude for the Λ baryon from lattice QCD

学校读者我要写书评

暂无评论

Physical Review D 2025年第3期111卷 034510-034510页

作者： Min-Huan Chu Haoyang Bai Jun Hua Jian Liang Xiangdong Ji Andreas Schäfer Yushan Su Wei Wang Xiaonu Xiong INPAC Key Laboratory for Particle Astrophysics and Cosmology (MOE) Shanghai Key Laboratory for Particle Physics and Cosmology School of Physics and Astronomy Shanghai Jiao Tong University Shanghai 200240 China Yang Yuanqing Scientific Computering Center Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai 200240 China Faculty of Physics Adam Mickiewicz University ulica Uniwersytetu Poznańskiego 2 61-614 Poznań Poland Institute of High Energy Physics CAS Beijing 100049 China School of Physics University of Chinese Academy of Sciences Beijing 100049 China 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 Guangzhou 510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Guangdong Provincial Key Laboratory of Nuclear Science Southern Nuclear Science Computing Center South China Normal University Guangzhou 510006 China Department of Physics University of Maryland College Park Maryland 20742 USA Institut für Theoretische Physik Universität Regensburg D-93040 Regensburg Germany Southern Center for Nuclear-Science Theory (SCNT) Institute of Modern Physics Chinese Academy of Sciences Huizhou 516000 Guangdong Province China School of Physics Central South University Changsha 418003 China

We calculate the leading-twist light cone distribution amplitudes of the Λ(uds) baryon using lattice QCD methods within the framework of large-momentum effective theory. Our numerical computations are carried out with Nf=2+1 stout smeared clover fermions and a Symanzik gauge action on a lattice with spacing a=0.077 fm and a pion mass of 303 MeV. To approach the large-momentum region, we simulate the equal-time correlations with the hadron momentum Pz={2.52,3.02,3.52} GeV. We investigate the analytic properties of the baryon quasidistribution amplitude in coordinate space and validate them through our lattice calculations. After renormalization and extrapolation, we present results for the three-dimensional distribution in momentum fractions of the two light quarks. Based on these findings, we briefly discuss the phenomenological impact on weak decays of Λb and outline potential systematic uncertainties that can be improved in the future. This work lays the theoretical foundation for accessing baryon light cone distribution amplitudes from lattice QCD.

关键词：

Entanglement in quantum field theory via wavelet representations

学校读者我要写书评

暂无评论

Physical Review D 2022年第3期106卷 036025-036025页

作者： Daniel J. George Yuval R. Sanders Mohsen Bagherimehrab Barry C. Sanders Gavin K. Brennen Department of Physics and Astronomy Macquarie University Sydney NSW 2109 Australia Sydney Quantum Academy Sydney NSW 2000 Australia ARC Centre of Excellence in Engineered Quantum Systems Macquarie University Sydney NSW 2109 Australia Centre for Quantum Software and Information University of Technology Sydney Sydney NSW 2007 Australia Institute for Quantum Science and Technology University of Calgary Calgary Alberta T2N 1N4 Canada Chemical Physics Theory Group Department of Chemistry University of Toronto Toronto Ontario M5G 1Z8 Canada Department of Computer Science University of Toronto Toronto Ontario M5S 2E4 Canada

quantum field theory (QFT) describes nature using continuous fields, but physical properties of QFT are usually revealed in terms of measurements of observables at a finite resolution. We describe a multiscale representation of free scalar bosonic and Ising model fermionic QFTs using wavelets. Making use of the orthogonality and self-similarity of the wavelet basis functions, we demonstrate some well-known relations such as scale-dependent subsystem entanglement entropy and renormalization of correlations in the ground state. We also find some new applications of the wavelet transform as a compressed representation of ground states of QFTs which can be used to illustrate quantum phase transitions via fidelity overlap and holographic entanglement of purification.

关键词： quantum entanglement quantum information theory quantum simulation Lattice field theory

MotionTrack: Learning Motion Predictor for Multiple Object Tracking

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Xiao, Changcheng Cao, Qiong Zhong, Yujie Lan, Long Zhang, Xiang Luo, Zhigang Tao, Dacheng School of Computer Science National University of Defense Technology Hunan Changsha410073 China JD Explore Academy Beijing102628 China Meituan Inc. Beijing100000 China Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Hunan Changsha410073 China Institute for Quantum State Key Laboratory of High Performance Computing National University of Defense Technology Hunan Changsha410073 China

Significant progress has been achieved in multi-object tracking (MOT) through the evolution of detection and re-identification (ReID) techniques. Despite these advancements, accurately tracking objects in scenarios with homogeneous appearance and heterogeneous motion remains a challenge. This challenge arises from two main factors: the insufficient discriminability of ReID features and the predominant utilization of linear motion models in MOT. In this context, we introduce a novel motion-based tracker, MotionTrack, centered around a learnable motion predictor that relies solely on object trajectory information. This predictor comprehensively integrates two levels of granularity in motion features to enhance the modeling of temporal dynamics and facilitate precise future motion prediction for individual objects. Specifically, the proposed approach adopts a self-attention mechanism to capture token-level information and a Dynamic MLP layer to model channel-level features. MotionTrack is a simple, online tracking approach. Our experimental results demonstrate that MotionTrack yields state-of-the-art performance on datasets such as Dancetrack and SportsMOT, characterized by highly complex object motion. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion estimation

Disentangling quantum neural networks for unified estimation of quantum entropies and distance measures

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Shin, Myeongjin Lee, Seungwoo Lee, Junseo Lee, Mingyu Ji, Donghwa Yeo, Hyeonjun Jeong, Kabgyun School of Computing KAIST Daejeon34141 Korea Republic of Quantum AI Team Norma Inc. Seoul04799 Korea Republic of Department of Computer Science and Engineering Seoul National University Seoul08826 Korea Republic of College of Liberal Studies Seoul National University Seoul08826 Korea Republic of Department of Physics and Astronomy Seoul National University Seoul08826 Korea Republic of Research Institute of Mathematics Seoul National University Seoul08826 Korea Republic of School of Computational Sciences Korea Institute for Advanced Study Seoul02455 Korea Republic of

The estimation of quantum entropies and distance measures, such as von Neumann entropy, Rényi entropy, Tsallis entropy, trace distance, and fidelity-induced distances such as the Bures distance, has been a key area of research in quantum information science. In our study, we introduce the disentangling quantum neural network (DEQNN), designed to efficiently estimate various physical quantities in quantum information. Estimation algorithms for these quantities are generally tied to the size of the Hilbert space of the quantum state to be estimated. Our proposed DEQNN offers a unified dimensionality reduction methodology that can significantly reduce the size of the Hilbert space while preserving the values of diverse physical quantities. We provide an in-depth discussion of the physical scenarios and limitations in which our algorithm is applicable, as well as the learnability of the proposed quantum neural network. Copyright © 2024, The Authors. All rights reserved.

关键词： Hilbert spaces

The Basics of quantum computing for Chemists

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Claudino, Daniel Quantum Computing Institute Oak Ridge National Laboratory Oak RidgeTN37831 United States Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Computer Science and Mathematics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States

The rapid and successful strides in quantum chemistry in the past decades can be largely credited to a conspicuous synergy between theoretical and computational advancements. However, the architectural computer archetype that enabled such a progress is approaching a state of more stagnant development. One of the most promising technological avenues for the continuing progress of quantum chemistry is the emerging quantum computing paradigm. This revolutionary proposal comes with several challenges, which span a wide array of disciplines. In chemistry, it implies, among other things, a need to reformulate some of its long established cornerstones in order to adjust to the operational demands and constraints of quantum computers. Due to its relatively recent emergence, much of quantum computing may still seem fairly nebulous and largely unknown to most chemists. It is in this context that here we review and illustrate the basic aspects of quantum information and their relation to quantum computing insofar as enabling simulations of quantum chemistry. We consider some of the most relevant developments in light of these aspects and discuss the current landscape when of relevance to quantum chemical simulations in quantum computers. © 2022, CC BY.

关键词： quantum optics

Large-Scale Simulation of quantum Computational Chemistry on a New Sunway Supercomputer

学校读者我要写书评

暂无评论

Large-Scale Simulation of Quantum Computational Chemistry on...

Supercomputing Conference

作者： Honghui Shang Li Shen Yi Fan Zhiqian Xu Chu Guo Jie Liu Wenhao Zhou Huan Ma Rongfen Lin Yuling Yang Fang Li Zhuoya Wang Yunquan Zhang Zhenyu Li Chinese Academy of Sciences Institute of Computing Technology Beijing China School of Computer Science and Technology University of Science and Technology of China Hefei China Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of China Hefei China Shanghai Research Center for Quantum Sciences Shanghai China Hefei National Laboratory University of Science and Technology of China Hefei China National Supercomputing Center in Wuxi Wuxi China Department of Computer Science and Technology Tsinghua University Beijing China Pilot National Laboratory for Marine Science and Technology (Qingdao) Qingdao China

ISBN: (纸本)9781665454452

quantum computational chemistry (QCC) is the use of quantum computers to solve problems in computational quantum chemistry. We develop a high performance variational quantum eigensolver (VQE) simulator for simulating quantum computational chemistry problems on a new Sunway supercomputer. The major innovations include: (1) a Matrix Product State (MPS) based VQE simulator to reduce the amount of memory needed and increase the simulation efficiency; (2) a combination of the Density Matrix Embedding theory with the MPS-based VQE simulator to further extend the simulation range; (3) A three-level parallelization scheme to scale up to 20 million cores; (4) Usage of the Julia script language as the main programming language, which both makes the programming easier and enables cutting edge performance as native C or Fortran; (5) Study of real chemistry systems based on the VQE simulator, achieving nearly linearly strong and weak scaling. Our simulation demonstrates the power of VQE for large quantum chemistry systems, thus paves the way for large-scale VQE experiments on near-term quantum computers.

关键词： Technological innovation quantum computing Computational modeling quantum chemistry Qubit quantum mechanics Programming

quantum information and beyond - With quantum candies

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Lin, Junan Mor, Tal Shapira, Roman Institute for Quantum Computing Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Computer Science Department Technion - Israel Institute of Technology Technion city Haifa3200003 Israel

The field of quantum information is becoming more known to the general public. However, effectively demonstrating the concepts underneath quantum science and technology to the general public can be a challenging job. We investigate, extend, and greatly expand here "quantum candies" (invented by Jacobs), a pedagogical model for intuitively describing some basic concepts in quantum information, including quantum bits, complementarity, the no-cloning principle, and entanglement. Following Jacob's quantum candies description of the well-known quantum key distribution protocol BB84, we explicitly demonstrate additional quantum cryptography protocols and quantum communication protocols, using generalized quantum candies (including correlated pairs of qandies). These demonstrations are done in an approachable manner, that can be explained to high-school students, without using the hard-to-grasp concept of superpositions and its mathematics. The intuitive model we investigate has a fascinating overlap with some of the most basic features of quantum theory. Hence, it can be a valuable tool for science and engineering educators who would like to help the general public to gain more insights into quantum science and technology. For the experts, the model we present, due to not employing quantum superpositions, enables - in some sense - extending far beyond quantum theory. Most remarkably, "quantum" candies of some unique type can be defined, such that non-local boxes (of the Popescu-Rohrlich type) as well as regular (correlated) quantum candies can be generated by a single "quantum" candies machine. Copyright © 2021, The Authors. All rights reserved.

关键词： quantum optics

quantum architecture search with meta-learning

学校读者我要写书评

暂无评论

arXiv 2021年

作者： He, Zhimin Chen, Chuangtao Li, Lvzhou Zheng, Shenggen Situ, Haozhen School of Electronic and Information Engineering Foshan University Foshan528000 China School of Mechatronic Engineering and Automation Foshan University Foshan528000 China Institute of Quantum Computing and Computer Science Theory School of Computer Science and Engineering Sun Yat-Sen University Guangzhou510006 China Peng Cheng Laboratory Shenzhen518055 China College of Mathematics and Informatics South China Agricultural University Guangzhou510642 China

Variational quantum algorithms (VQAs) have been successfully applied to quantum approximate optimization algorithms, variational quantum compiling and quantum machine learning models. The performances of VQAs largely depend on the architecture of parameterized quantum circuits (PQCs). quantum architecture search (QAS) aims to automate the design of PQCs in different VQAs with classical optimization algorithms. However, current QAS algorithms do not use prior experiences and search the quantum architecture from scratch for each new task, which is inefficient and time consuming. In this paper, we propose a meta quantum architecture search (MetaQAS) algorithm, which learns good initialization heuristics of the architecture (i.e., meta-architecture), along with the meta-parameters of quantum gates from a number of training tasks such that they can adapt to new tasks with a small number of gradient updates, which leads to fast learning on new tasks. The proposed MetaQAS can be used with arbitrary gradient-based QAS algorithms. Simulation results of variational quantum compiling on three- and four-qubit circuits show that the architectures optimized by MetaQAS converge much faster than a state-of-the-art gradient-based QAS algorithm, namely DQAS. MetaQAS also achieves a better solution than DQAS after fine-tuning of gate parameters. Copyright © 2021, The Authors. All rights reserved.

关键词： Learning algorithms

Variational quantum compiling with double Q-learning

学校读者我要写书评

暂无评论

arXiv 2021年

作者： He, Zhimin Li, Lvzhou Zheng, Shenggen Li, Yongyao Situ, Haozhen School of Electronic and Information Engineering Foshan University Foshan528000 China Peng Cheng Laboratory Shenzhen518055 China Institute of Quantum Computing and Computer Science Theory School of Computer Science and Engineering Sun Yat-Sen University Guangzhou510006 China School of Physics and Optoelectronic Engineering Foshan University Foshan528000 China College of Mathematics and Informatics South China Agricultural University Guangzhou510642 China

quantum compiling aims to construct a quantum circuit V by quantum gates drawn from a native gate alphabet, which is functionally equivalent to the target unitary U. It is a crucial stage for the running of quantum algorithms on noisy intermediate-scale quantum (NISQ) devices. However, the space for structure exploration of quantum circuit is enormous, resulting in the requirement of human expertise, hundreds of experimentations or modifications from existing quantum circuits. In this paper, we propose a variational quantum compiling (VQC) algorithm based on reinforcement learning (RL), in order to automatically design the structure of quantum circuit for VQC with no human intervention. An agent is trained to sequentially select quantum gates from the native gate alphabet and the qubits they act on by double Q-learning with Ε-greedy exploration strategy and experience replay. At first, the agent randomly explores a number of quantum circuits with different structures, and then iteratively discovers structures with higher performance on the learning task. Simulation results show that the proposed method can make exact compilations with less quantum gates compared to previous VQC algorithms. It can reduce the errors of quantum algorithms due to decoherence process and gate noise in NISQ devices, and enable quantum algorithms especially for complex algorithms to be executed within coherence time. © 2021, CC BY.

关键词： Reinforcement learning