arXiv - PHYS - Quantum Physics最新文献_第10页

Quantum hacking: Induced-photorefraction attack on a practical continuous-variable quantum key distribution system 量子黑客：对实用连续可变量子密钥分发系统的诱导光分攻击

arXiv - PHYS - Quantum Physics Pub Date : 2024-09-12 DOI: arxiv-2409.08017

Yiliang Wang, Yi Zheng, Chenlei Fang, Haobin Shi, Wei Pan

{"title":"Quantum hacking: Induced-photorefraction attack on a practical continuous-variable quantum key distribution system","authors":"Yiliang Wang, Yi Zheng, Chenlei Fang, Haobin Shi, Wei Pan","doi":"arxiv-2409.08017","DOIUrl":"https://doi.org/arxiv-2409.08017","url":null,"abstract":"We explore a new security loophole in a practical continuous-variable quantum\u0000key distribution (CVQKD) system, which is opened by the photorefractive effect\u0000of lithium niobate-based (LN-based) modulators. By exploiting this loophole, we\u0000propose a quantum hacking strategy, i.e., the induced-photorefraction attack,\u0000which utilizes the induced photorefraction on the LN-based modulators to hide\u0000the classical intercept-resend attack. Specifically, we show that the induced\u0000photorefraction can bias the response curve of the LN-based modulator, which\u0000will affect the intensity of the modulated signal. Based on the investigation\u0000of the channel parameter estimation under above influence, we further analyze\u0000the secret key rate of the practical CVQKD system. The simulation results\u0000indicate that the communication parties will overestimate the secret key rate,\u0000which reveals that Eve can actively open the above loophole by launching the\u0000induced-photorefraction attack to successfully obtain the secret key\u0000information. To defend against this attack, we can use a random monitoring\u0000scheme for modulation variance to determine this attack, and use an improving\u0000optical power limiter to effectively mitigate the irradiation beam. Apart from\u0000these countermeasures, we also propose using the Sagnac-based IM to stabilize\u0000the practical CVQKD system, which can minimize the above effects.","PeriodicalId":501226,"journal":{"name":"arXiv - PHYS - Quantum Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Emergent Liouvillian exceptional points from exact principles 从精确原理出发的新兴刘维尔超常点

arXiv - PHYS - Quantum Physics Pub Date : 2024-09-12 DOI: arxiv-2409.08100

Shishir Khandelwal, Gianmichele Blasi

引用次数: 0

Silicon Spin Qubit Control and Readout Circuits in 22nm FDSOI CMOS 采用 22 纳米 FDSOI CMOS 的硅自旋质子控制和读出电路

arXiv - PHYS - Quantum Physics Pub Date : 2024-09-12 DOI: arxiv-2409.08182

Raffaele R. Severino, Michele Spasaro, Domenico Zito

引用次数: 0

Collaboration Encouraging Quantum Secret Sharing Scheme with Seal Property 鼓励合作的量子秘密共享计划与印章属性

arXiv - PHYS - Quantum Physics Pub Date : 2024-09-12 DOI: arxiv-2409.07863

Xiaogang Cheng, Ren Guo

引用次数: 0

A Riemannian Approach to the Lindbladian Dynamics of a Locally Purified Tensor Network 局部纯化张量网络的林德布拉德动力学黎曼方法

arXiv - PHYS - Quantum Physics Pub Date : 2024-09-12 DOI: arxiv-2409.08127

Emiliano Godinez-Ramirez, Richard Milbradt, Christian B. Mendl

{"title":"A Riemannian Approach to the Lindbladian Dynamics of a Locally Purified Tensor Network","authors":"Emiliano Godinez-Ramirez, Richard Milbradt, Christian B. Mendl","doi":"arxiv-2409.08127","DOIUrl":"https://doi.org/arxiv-2409.08127","url":null,"abstract":"Tensor networks offer a valuable framework for implementing Lindbladian\u0000dynamics in many-body open quantum systems with nearest-neighbor couplings. In\u0000particular, a tensor network ansatz known as the Locally Purified Density\u0000Operator employs the local purification of the density matrix to guarantee the\u0000positivity of the state at all times. Within this framework, the dissipative\u0000evolution utilizes the Trotter-Suzuki splitting, yielding a second-order\u0000approximation error. However, due to the Lindbladian dynamics' nature,\u0000employing higher-order schemes results in non-physical quantum channels. In\u0000this work, we leverage the gauge freedom inherent in the Kraus representation\u0000of quantum channels to improve the splitting error. To this end, we formulate\u0000an optimization problem on the Riemannian manifold of isometries and find a\u0000solution via the second-order trust-region algorithm. We validate our approach\u0000using two nearest-neighbor noise models and achieve an improvement of orders of\u0000magnitude compared to other positivity-preserving schemes. In addition, we\u0000demonstrate the usefulness of our method as a compression scheme, helping to\u0000control the exponential growth of computational resources, which thus far has\u0000limited the use of the locally purified ansatz.","PeriodicalId":501226,"journal":{"name":"arXiv - PHYS - Quantum Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamical Structure Factor from Weak Measurements 从弱测量得出的动态结构因子

arXiv - PHYS - Quantum Physics Pub Date : 2024-09-11 DOI: arxiv-2409.07030

E. Altuntas, R. G. Lena, S. Flannigan, A. J. Daley, I. B. Spielman

{"title":"Dynamical Structure Factor from Weak Measurements","authors":"E. Altuntas, R. G. Lena, S. Flannigan, A. J. Daley, I. B. Spielman","doi":"arxiv-2409.07030","DOIUrl":"https://doi.org/arxiv-2409.07030","url":null,"abstract":"Much of our knowledge of quantum systems is encapsulated in the expectation\u0000value of Hermitian operators, experimentally obtained by averaging projective\u0000measurements. However, dynamical properties are often described by products of\u0000operators evaluated at different times; such observables cannot be measured by\u0000individual projective measurements, which occur at a single time. For example,\u0000the dynamical structure factor describes the propagation of density\u0000excitations, such as phonons, and is derived from the spatial density operator\u0000evaluated at different times. Conventionally, this is measured by first\u0000exciting the system at a specific wavevector and frequency, then measuring the\u0000response. Here, we describe an alternative approach using a pair of\u0000time-separated weak measurements, and analytically show that their\u0000cross-correlation function directly recovers the dynamical structure factor. We\u0000provide numerical confirmation of this technique with a matrix product states\u0000simulation of the one-dimensional Bose-Hubbard model, weakly measured by phase\u0000contrast imaging. We explore the limits of the method and demonstrate its\u0000applicability to real experiments with limited imaging resolution.","PeriodicalId":501226,"journal":{"name":"arXiv - PHYS - Quantum Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Learning Robust Observable to Address Noise in Quantum Machine Learning 在量子机器学习中学习鲁棒可观测数据以解决噪声问题

arXiv - PHYS - Quantum Physics Pub Date : 2024-09-11 DOI: arxiv-2409.07632

Bikram Khanal, Pablo Rivas

{"title":"Learning Robust Observable to Address Noise in Quantum Machine Learning","authors":"Bikram Khanal, Pablo Rivas","doi":"arxiv-2409.07632","DOIUrl":"https://doi.org/arxiv-2409.07632","url":null,"abstract":"Quantum Machine Learning (QML) has emerged as a promising field that combines\u0000the power of quantum computing with the principles of machine learning. One of\u0000the significant challenges in QML is dealing with noise in quantum systems,\u0000especially in the Noisy Intermediate-Scale Quantum (NISQ) era. Noise in quantum\u0000systems can introduce errors in quantum computations and degrade the\u0000performance of quantum algorithms. In this paper, we propose a framework for\u0000learning observables that are robust against noisy channels in quantum systems.\u0000We demonstrate that it is possible to learn observables that remain invariant\u0000under the effects of noise and show that this can be achieved through a\u0000machine-learning approach. We present a toy example using a Bell state under a\u0000depolarization channel to illustrate the concept of robust observables. We then\u0000describe a machine-learning framework for learning such observables across six\u0000two-qubit quantum circuits and five noisy channels. Our results show that it is\u0000possible to learn observables that are more robust to noise than conventional\u0000observables. We discuss the implications of this finding for quantum machine\u0000learning, including potential applications in enhancing the stability of QML\u0000models in noisy environments. By developing techniques for learning robust\u0000observables, we can improve the performance and reliability of quantum machine\u0000learning models in the presence of noise, contributing to the advancement of\u0000practical QML applications in the NISQ era.","PeriodicalId":501226,"journal":{"name":"arXiv - PHYS - Quantum Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generalization Error Bound for Quantum Machine Learning in NISQ Era -- A Survey NISQ 时代量子机器学习的泛化误差约束 -- 综述

arXiv - PHYS - Quantum Physics Pub Date : 2024-09-11 DOI: arxiv-2409.07626

Bikram Khanal, Pablo Rivas, Arun Sanjel, Korn Sooksatra, Ernesto Quevedo, Alejandro Rodriguez

{"title":"Generalization Error Bound for Quantum Machine Learning in NISQ Era -- A Survey","authors":"Bikram Khanal, Pablo Rivas, Arun Sanjel, Korn Sooksatra, Ernesto Quevedo, Alejandro Rodriguez","doi":"arxiv-2409.07626","DOIUrl":"https://doi.org/arxiv-2409.07626","url":null,"abstract":"Despite the mounting anticipation for the quantum revolution, the success of\u0000Quantum Machine Learning (QML) in the Noisy Intermediate-Scale Quantum (NISQ)\u0000era hinges on a largely unexplored factor: the generalization error bound, a\u0000cornerstone of robust and reliable machine learning models. Current QML\u0000research, while exploring novel algorithms and applications extensively, is\u0000predominantly situated in the context of noise-free, ideal quantum computers.\u0000However, Quantum Circuit (QC) operations in NISQ-era devices are susceptible to\u0000various noise sources and errors. In this article, we conduct a Systematic\u0000Mapping Study (SMS) to explore the state-of-the-art generalization bound for\u0000supervised QML in NISQ-era and analyze the latest practices in the field. Our\u0000study systematically summarizes the existing computational platforms with\u0000quantum hardware, datasets, optimization techniques, and the common properties\u0000of the bounds found in the literature. We further present the performance\u0000accuracy of various approaches in classical benchmark datasets like the MNIST\u0000and IRIS datasets. The SMS also highlights the limitations and challenges in\u0000QML in the NISQ era and discusses future research directions to advance the\u0000field. Using a detailed Boolean operators query in five reliable indexers, we\u0000collected 544 papers and filtered them to a small set of 37 relevant articles.\u0000This filtration was done following the best practice of SMS with well-defined\u0000research questions and inclusion and exclusion criteria.","PeriodicalId":501226,"journal":{"name":"arXiv - PHYS - Quantum Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantum-Train with Tensor Network Mapping Model and Distributed Circuit Ansatz 带有张量网络映射模型和分布式电路解析的量子列车

arXiv - PHYS - Quantum Physics Pub Date : 2024-09-11 DOI: arxiv-2409.06992

Chen-Yu Liu, Chu-Hsuan Abraham Lin, Kuan-Cheng Chen

{"title":"Quantum-Train with Tensor Network Mapping Model and Distributed Circuit Ansatz","authors":"Chen-Yu Liu, Chu-Hsuan Abraham Lin, Kuan-Cheng Chen","doi":"arxiv-2409.06992","DOIUrl":"https://doi.org/arxiv-2409.06992","url":null,"abstract":"In the Quantum-Train (QT) framework, mapping quantum state measurements to\u0000classical neural network weights is a critical challenge that affects the\u0000scalability and efficiency of hybrid quantum-classical models. The traditional\u0000QT framework employs a multi-layer perceptron (MLP) for this task, but it\u0000struggles with scalability and interpretability. To address these issues, we\u0000propose replacing the MLP with a tensor network-based model and introducing a\u0000distributed circuit ansatz designed for large-scale quantum machine learning\u0000with multiple small quantum processing unit nodes. This approach enhances\u0000scalability, efficiently represents high-dimensional data, and maintains a\u0000compact model structure. Our enhanced QT framework retains the benefits of\u0000reduced parameter count and independence from quantum resources during\u0000inference. Experimental results on benchmark datasets demonstrate that the\u0000tensor network-based QT framework achieves competitive performance with\u0000improved efficiency and generalization, offering a practical solution for\u0000scalable hybrid quantum-classical machine learning.","PeriodicalId":501226,"journal":{"name":"arXiv - PHYS - Quantum Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulations 量子哈密顿模拟性能基准的综合跨模型框架

arXiv - PHYS - Quantum Physics Pub Date : 2024-09-11 DOI: arxiv-2409.06919

Avimita Chatterjee, Sonny Rappaport, Anish Giri, Sonika Johri, Timothy Proctor, David E. Bernal Neira, Pratik Sathe, Thomas Lubinski

{"title":"A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulations","authors":"Avimita Chatterjee, Sonny Rappaport, Anish Giri, Sonika Johri, Timothy Proctor, David E. Bernal Neira, Pratik Sathe, Thomas Lubinski","doi":"arxiv-2409.06919","DOIUrl":"https://doi.org/arxiv-2409.06919","url":null,"abstract":"Quantum Hamiltonian simulation is one of the most promising applications of\u0000quantum computing and forms the basis for many quantum algorithms. Benchmarking\u0000them is an important gauge of progress in quantum computing technology. We\u0000present a methodology and software framework to evaluate various facets of the\u0000performance of gate-based quantum computers on Trotterized quantum Hamiltonian\u0000evolution. We propose three distinct modes for benchmarking: (i) comparing\u0000simulation on a real device to that on a noiseless classical simulator, (ii)\u0000comparing simulation on a real device with exact diagonalization results, and\u0000(iii) using scalable mirror circuit techniques to assess hardware performance\u0000in scenarios beyond classical simulation methods. We demonstrate this framework\u0000on five Hamiltonian models from the HamLib library: the Fermi and Bose-Hubbard\u0000models, the transverse field Ising model, the Heisenberg model, and the Max3SAT\u0000problem. Experiments were conducted using Qiskit's Aer simulator, BlueQubit's\u0000CPU cluster and GPU simulators, and IBM's quantum hardware. Our framework,\u0000extendable to other Hamiltonians, provides comprehensive performance profiles\u0000that reveal hardware and algorithmic limitations and measure both fidelity and\u0000execution times, identifying crossover points where quantum hardware\u0000outperforms CPU/GPU simulators.","PeriodicalId":501226,"journal":{"name":"arXiv - PHYS - Quantum Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0