检索结果-内蒙古大学图书馆

quantum algorithm for Solving the Continuous Hidden Symmetry Subgroup Problem

IEEE ACCESS 2021年 9卷 93248-93254页

作者： Bae, Eunok Lee, Soojoon Kyung Hee Univ Dept Math Seoul 02447 South Korea Kyung Hee Univ Res Inst Basic Sci Seoul 02447 South Korea

quantum computers are expected to be able to outperform classical computers. In fact, some computational problems such as integer factorization can be solved on quantum computers substantially faster than classical computers. Interestingly, these problems can be cast in a framework of the hidden symmetry subgroup problem. However, only a few of quantum algorithms for effciently solving this problem have been known, and the approaches used in all previous results can be applied to particular groups with specific group actions. In this paper, we introduce new technique for solving the hidden symmetry subgroup problem which can be applicable for any groups and any group actions with a certain condition. In addition, we define the continuous hidden symmetry subgroup problem on a group by employing a continuous oracle function, and prove that if the group is a metric space and the group action satisfies some condition, then the continuous hidden symmetry subgroup problem can be efficiently reduced to the continuous hidden subgroup problem. In particular, we show that there exists an efficient quantum algorithm to solve the continuous hidden symmetry subgroup problem on R-n, while it has not yet been shown that the original hidden symmetry subgroup problem on R-n can be efficiently solved by a quantum computer.

关键词： quantum algorithm continuous hidden symmetry subgroup problem hidden symmetry subgroup problem

来源：评论

学校读者我要写书评

暂无评论

quantum algorithm for learning secret strings and its experimental demonstration

引用

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2023年 609卷

作者： Xu, Yongzhen Zhang, Shihao Li, Lvzhou Sun Yat Sen Univ Inst Quantum Comp & Comp Theory Sch Comp Sci & Engn Guangzhou 510006 Peoples R China

In this paper, we consider the secret-string-learning problem in the teacher-student setting: the teacher has a secret string s is an element of {0, 1}n, and the student wants to learn the secret s by question-answer interactions with the teacher, where at each time, the student can ask the teacher with a pair (x, q) is an element of {0, 1}n x {0, 1, ... , n-1} and the teacher returns a bit given by the oracle fs(x, q) that indicates whether the length of the longest common prefix of s and x is greater than q or not. Our contributions are as follows.(i) We prove that any classical deterministic algorithm needs at least n queries to the oracle fsto learn the n-bit secret string s in both the worst case and the average case, and also present an optimal classical deterministic algorithm learning any s using n queries.(ii) We propose a quantum algorithm learning the n-bit secret string s with certainty using left ceiling n/2 right ceiling queries to the oracle fs, thus proving a double speedup over classical counterparts.(iii) Experimental demonstrations of our quantum algorithm on the IBM cloud quantum computer are presented, with the average success probabilities of 85.3% and 82.5% for all cases with n = 2 and n = 3, respectively.(c) 2022 Elsevier B.V. All rights reserved.

关键词： quantum computing String learning quantum algorithm Query complexity

来源：评论

学校读者我要写书评

暂无评论

quantum algorithm for unsupervised anomaly detection

引用

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2023年 625卷

作者： Guo, Mingchao Pan, Shijie Li, Wenmin Gao, Fei Qin, Sujuan Yu, XiaoLing Zhang, Xuanwen Wen, Qiaoyan Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Comprehens Res Ctr Elect Informat Technol MIIT Weihai 264200 Shandong Peoples R China

Anomaly detection, an important branch of machine learning, plays a critical role in fraud detection, health care, intrusion detection, military surveillance, etc. As one of the most commonly used unsupervised anomaly detection algorithms, the Local Outlier Factor algorithm (LOF algorithm) has been extensively studied. This algorithm contains three steps, i.e., determining the k-distance neighborhood for each data point x, computing the local reachability density of x, and calculating the local outlier factor of x to judge whether x is abnormal. The LOF algorithm is computationally expensive when processing big data sets. Here we present a quantum LOF algorithm consisting of three parts corresponding to the classical algorithm. Specifically, the k-distance neighborhood of x is determined by amplitude estimation and minimum search;the local reachability density of each data point is calculated in parallel based on the quantum multiply-adder;the local outlier factor of each data point is obtained in parallel using amplitude estimation. It is shown that our quantum algorithm achieves exponential speedup on the dimension of the data points and polynomial speedup on the number of data points compared to its classical counterpart. This work demonstrates the advantage of quantum computing in unsupervised anomaly detection.(c) 2023 Elsevier B.V. All rights reserved.

关键词： quantum algorithm Unsupervised anomaly detection k-distance neighborhood Exponential speedup Polynomial speedup

来源：评论

学校读者我要写书评

暂无评论

A novel quantum algorithm for ant colony optimisation

IET QUANTUM COMMUNICATION

引用

IET quantum COMMUNICATION 2022年第1期3卷 13-29页

作者： Ghosh, Mrityunjay Dey, Nivedita Mitra, Debdeep Chakrabarti, Amlan HCL Technol Noida Uttar Pradesh India Univ Calcutta Kolkata India QRDLab North Dumdum W Bengal India

Ant colony optimisation (ACO) is a commonly used meta-heuristic to solve complex combinatorial optimisation problems like the travelling salesman problem (TSP), vehicle routing problem (VRP) etc. However, classical ACO algorithms provide better optimal solutions but do not reduce computation time overhead to a significant extent. algorithmic speed-up can be achieved by using parallelism offered by quantum computing. Existing quantum algorithms to solve ACO are either quantum-inspired classical algorithms or hybrid quantum-classical algorithms. Since all these algorithms need the intervention of classical computing, leveraging the true potential of quantum computing on real quantum hardware remains a challenge. This study's main contribution is to propose a fully quantum algorithm to solve ACO, enhancing the quantum information processing toolbox in the fault-tolerant quantum computing (FTQC) era. We have solved the single source single destination (SSSD) shortest-path problem using our proposed adaptive quantum circuit for representing the dynamic pheromone-updating strategy in real IBMQ devices. Our quantum ACO technique can be further used as a quantum ORACLE to solve complex optimisation problems in a fully quantum setup with significant speed up upon the availability of more qubits.

关键词： ant colony optimisation QACO quantum algorithm quantum ant quantum circuit synthesis quantum computing

来源：评论

学校读者我要写书评

暂无评论

quantum algorithm for Density Peak Anomaly Detection Based on KNN

Quantum Algorithm for Density Peak Anomaly Detection Based o...

引用

Computing, Communication, Perception and quantum Technology (CCPQT), International Conference on

作者： Chengkang Pan Shuai Hou Chunfeng Cui China Mobile Research Institute Beijing China

ISBN: (数字)9798331528386

ISBN: (纸本)9798331528393

The density peak anomaly detection algorithm based on KNN, one of the most frequently utilized classical algorithms, is widely applied in communication fields, such as network fault detection, network traffic detection, user behavior detection, and network intrusion detection. In this algorithm, the local density value and KNN distance of all data points must be calculated, which faces enormous computational cost and computational delay challenges when the data set is processed as the network scale increases. To address this trouble, we introduce quantum computing into the algorithm and propose a quantum version of the density peak anomaly detection algorithm based on KNN. The proposed quantum algorithm first utilizes the inner product estimate algorithm and the quantum minimum search algorithm to accelerate the determination of the K nearest neighbor set of each data point and the calculation of KNN distance. Then, it performs amplitude estimation to concurrently obtain the local density of all data points. Our quantum algorithm is shown to be exponentially faster than its classical counterpart in the dimensionality of the data points and polynomially faster than the classical algorithm in the number of data points.

关键词： quantum algorithm Fault detection Network intrusion detection Telecommunication traffic Nearest neighbor methods Delays Computational efficiency Amplitude estimation Anomaly detection Faces

来源：评论

学校读者我要写书评

暂无评论

quantum algorithm for Copula-Based Risk Aggregation using Orthogonal Series Density Estimation

Quantum Algorithm for Copula-Based Risk Aggregation using Or...

引用

quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Hitomi Mori Koichi Miyamoto Graduate School of Engineering Science Osaka University Toyonaka Osaka Japan Center for Quantum Information and Quantum Biology Osaka University Toyonaka Osaka Japan

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

quantum Monte Carlo integration (QMCI) provides a quadratic speed-up over its classical counterpart, and its applications have been investigated in various fields, including finance. This paper considers its application to risk aggregation, one of the most important numerical tasks in financial risk management. Risk aggregation combines several risk variables and quantifies the total amount of risk, taking into account the correlation among them. For this task, there exists a useful tool called copula, with which the joint distribution can be generated from marginal distributions with a flexible correlation structure. Classically, the copula-based method utilizes sampling of risk variables. However, this procedure is not directly applicable to the quantum setting, where sampled values are not stored as classical data, and thus no efficient quantum algorithm is known. In this paper, we introduce a quantum algorithm for copula-based risk aggregation that is compatible with QMCI. In our algorithm, we first estimate each marginal distribution as a series of orthogonal functions, where the coefficients can be calculated with QMCI. Then, by plugging the marginal distributions into the copula and obtaining the joint distribution, we estimate risk measures using QMCI again. With this algorithm, nearly quadratic quantum speed-up can be obtained for sufficiently smooth marginal distributions.

关键词： quantum algorithm Correlation Monte Carlo methods Finance Estimation Probability density function Particle measurements Risk management Standards Plugs

来源：评论

学校读者我要写书评

暂无评论

quantum algorithm for the Analysis of Temporal Sequences of Satellite Images

Quantum Algorithm for the Analysis of Temporal Sequences of ...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Henri Painchart Matthijs Van Waveren Brice Mora Guillaume Pasero CS Group Toulouse France

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

This article describes the first published quantum algorithm for the analysis of temporal sequences of satellite images. This algorithm can be used for the purpose of detecting deforestation in tropical forests. We achieved a reasonable accuracy on a quantum simulator even though we had a relatively small number of parameters. The algorithm we propose opens promising avenues for the remote sensing community when quantum computing technologies will become widely available.

关键词： Computers Deforestation Sequential analysis quantum algorithm Accuracy Forests Qubit

来源：评论

学校读者我要写书评

暂无评论

quantum algorithm for Searching Resonant Frequency Based on Frequency Response Encoding

Quantum Algorithm for Searching Resonant Frequency Based on ...

引用

quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Kyoung Keun Park Beomgeun Cho Kwangyeul Choi Taehyun Kim Dept. of Computer Scienc and Engineering Seoul National University Seoul Republic of Korea

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Frequency response and resonant frequency are crucial aspects of system analysis and design. quantum computers offer efficient algorithms for solving linear differential equations and performing discrete Fourier transforms. This paper introduces a quantum algorithm that encodes the quantum frequency response state to represent a system's frequency response. We also propose a condition to probabilistically determine resonant frequency of the system with higher-order derivatives. This condition has been validated through computer simulations.

关键词： Linear systems quantum algorithm Computer simulation Resonant frequency Search problems Probabilistic logic Frequency response Encoding Frequency measurement System analysis and design

来源：评论

学校读者我要写书评

暂无评论

quantum algorithm for the Set Splitting Problem

Quantum Algorithm for the Set Splitting Problem

引用

quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Sean Borneman Bloomington High School South Bloomington IN United States

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

We present a novel use of quantum annealing to solve the Set Splitting Problem using (QUBO) problem formulation. The contribution of the work is in formulating penalty functions that ensure the ground state of the QUBO Hamiltonian corresponds to valid solutions that split the input subsets. This approach scales linearly in terms of the number of logical qubits relative to problem size. Empirical tests of the proposed solution show convergence to globally optimal solutions, with high accuracy rates over repeated trials.

关键词： Annealing quantum algorithm Accuracy Stationary state Qubit quantum annealing Convergence

来源：评论

学校读者我要写书评

暂无评论

quantum algorithm and experimental demonstration for the subset sum problem

引用

Science China(Information Sciences) 2022年第8期65卷 261-274页

作者： Qilin ZHENG Pingyu ZHU Shichuan XUE Yang WANG Chao WU Xinyao YU Miaomiao YU Yingwen LIU Mingtang DENG Junjie WU Ping XU Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense Technology

To solve the subset sum problem, a well-known nondeterministic polynomial-time complete problem that is widely used in encryption and resource scheduling, we propose a feasible quantum algorithm that utilizes fewer qubits to encode and achieves quadratic speedup. Specifically, this algorithm combines an amplitude amplification algorithm with quantum phase estimation, and requires n + t + 1 qubits and O(2(0.5+o(1))n) operations to obtain the solution, where n is the number of elements, and t is the number of qubits used to store the eigenvalues. To verify the performance of the algorithm, we simulate the algorithm with the online quantum simulator of IBM named ibmq simulator using Qiskit and then run it on two IBM quantum computers called ibmq santiago and ibmq bogota. The experimental results indicate that compared with the brute force algorithm, the proposed algorithm results in quadratic acceleration for the problem of a set S with four elements and two subsets whose sum equals target w. Using the iterator twice, we obtain success probabilities of 0.940 ± 0.004, 0.751 ± 0.040, and 0.665 ± 0.060 on the simulator, ibmq santiago, and ibmq bogota, respectively, and the fidelity between the theoretical and experimental quantum states is calculated to be 0.944 ± 0.002, 0.753 ± 0.017, and 0.657 ± 0.028, respectively. If the error rates of the experimental quantum logic gates can be reduced, the success probabilities of the proposed algorithm on real quantum devices can be further improved.

关键词： quantum algorithm subset sum quadratic speedup encryption algorithm complexity

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：