检索结果-内蒙古大学图书馆

36th Conference on Neural information processing Systems (NeurIPS)

作者： Jain, Rahul Piliouras, Georgios Sim, Ryann NUS Singapore Singapore SUTD Singapore Singapore

ISBN: (纸本)9781713871088

Recent advances in quantum computing and in particular, the introduction of quantum GANs, have led to increased interest in quantum zero-sum game theory, extending the scope of learning algorithms for classical games into the quantum realm. In this paper, we focus on learning in quantum zero-sum games under Matrix MultiplicativeWeights Update (a generalization of the multiplicative weights update method) and its continuous analogue, quantum Replicator Dynamics. When each player selects their state according to quantum replicator dynamics, we show that the system exhibits conservation laws in a quantum-information theoretic sense. Moreover, we show that the system exhibits Poincare recurrence, meaning that almost all orbits return arbitrarily close to their initial conditions infinitely often. Our analysis generalizes previous results in the case of classical games [48, 42].

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

ECO-BIKE: Bridging the Gap Between PQC BIKE and GPU Acceleration

引用

IEEE TRANSACTIONS ON information FORENSICS AND SECURITY 2024年 19卷 8952-8965页

作者： Dong, Jiankuo Fu, Yusheng Qin, Xusheng Dong, Zhenjiang Xiao, Fu Lin, Jingqiang Nanjing Univ Posts & Telecommun Sch Comp Sci Nanjing 210049 Peoples R China Univ Sci & Technol China Sch Cyber Secur Hefei 230026 Peoples R China

Advancements in quantum computing pose a threat to public-key cryptosystems, leading to the development of post-quantum cryptography. NIST is standardizing candidate algorithms, with BIKE, a code-based key encapsulation mechanism, among those under consideration. Performance is crucial in NIST PQC standardization process, and researchers have introduced a range of optimization techniques for BIKE across various platforms. To the best of our knowledge, our Efficient CryptOgraphy BIKE (ECO-BIKE) represents the first attempt at optimizing the implementation of BIKE on GPU architecture. In this paper, we introduce a comprehensive construction of a 3-threading parallel architecture tailored for the BIKE cryptosystem. This architecture covers a range of computational tasks, addressing operations from low-level to high-level computations. These include a parallel dense polynomial multiplication scheme with a better memory access pattern and a better XOR calculation, which forms the basis for a comprehensive parallel execution framework for the entire BIKE algorithm. Targeted optimizations are implemented for specific modules (KEYGEN, ENCAPS, DECAPS), which collectively enhance the overall efficiency of the algorithm. Our ECO-BIKE exhibits exceptional throughput performance on the NVIDIA GeForce RTX 4090. In the 3-thread mode, the throughput of the KEYGEN, ENCAPS, and DECAPS modules reaches 24.033 kops/s, 277.789 kops/s, and 5.817 kops/s, respectively. Our proposed optimal parallel multiplication scheme achieves a significantly higher overall throughput of 481.302 kops/s. These results highlight the substantial computational advantages our approach provides for cryptographic workloads.

关键词： Cryptography Graphics processing units Throughput Polynomials Encapsulation NIST Parallel processing GPU PQC BIKE CUDA Karatsuba

来源：评论

学校读者我要写书评

暂无评论

Approximate quantum gates compilation for superconducting transmon qubits with self-navigation algorithm

引用

quantum information processing 2023年第10期22卷 1-11页

作者： He, Run-Hong Ren, Feng-Hua Xie, Yang-Yang Ablimit, Arapat Wang, Zhao-Ming Ocean Univ China Coll Phys & Optoelect Engn Qingdao 266100 Peoples R China Qingdao Univ Technol Sch Informat & Control Engn Qingdao 266520 Peoples R China Chinese Acad Sci Inst Software State Key Lab Comp Sci Beijing 101408 Peoples R China

Precise and fast qubit control is crucial when compiling quantum gates for successful implementation of quantum algorithms. However, the presence of environmental noise and the nonzero bandwidth of control pulses pose challenges for the effective control, particularly for weakly anharmonic systems such as superconducting transmon qubits. To address these problems, in this work we propose a self-navigation algorithm to approximately compile single-qubit gates with high accuracy in the context of transmon qubit. By utilizing this algorithm, the overall rotation distance for the target gate operation is significantly shorter than that of the commonly used U3 gate technique. As a result, a shorter gate time can be obtained. The necessary number of pulses and the runtime of scheme designing scale up as O[Log(1/epsilon)]\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal {O}[\textrm{Log}(1/\epsilon )]$$\end{document} with a small prefactor, indicating a low overhead cost. Moreover, we investigate the trade-off between effectiveness and cost, and a balance point is identified. Our results demonstrate a reduction in both gate time and noise effects, but without an increase in leakage. Our work opens up a new avenue for efficient quantum algorithm implementations with contemporary superconducting quantum technology.

关键词： quantum gate Approximate compilation Superconducting transmon qubits

来源：评论

学校读者我要写书评

暂无评论

Exploring quantum Machine Learning algorithms for Enhanced Data Classification and Clustering in Complex Systems - Integration with Gradient Boosting and K-means for Improved Performance

Exploring Quantum Machine Learning Algorithms for Enhanced D...

引用

2024 International Conference on Cybernation and Computation, CYBERCOM 2024

作者： Babu, M. Arun, M. Pushparani, S. Muthukrishnan, A. Poongavanam, N. Rajalakshmi Engineering Çollege Department of Information Technology Thandalam Chennai India Panimalar Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Meenakshi College of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha University Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331542344

This research focuses on the implementation of quantum machine learning with the classical models such as Gradient Boosting and K-means clustering for efficient classification and clustering of most complex datasets in advanced systems. Taking advantage of the large datasets that are handled by the qc, this work examines quantum Support Vector Machines (QSVM), quantum Boosting, and quantum K-means. To compare the efficiency of these hybrid models three datasets - the healthcare, the financial, and the cyber-security datasets - are used. Our findings indicate that quantum optimization algorithms achieve better accuracy in clustering in comparison to the classical counterparts and are computationally faster. This work shows how quantum machine learning can lead to the enhancement of difficult data processing tasks, a major issue in the quantum computing domain, with specific reference to resources and high-dimensional data. The opportunity to integrate quantum and classical models successfully is the best basis for further developments in machine learning. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Invited: Leveraging Machine Learning for quantum Compilation Optimization 24

Invited: Leveraging Machine Learning for Quantum Compilation...

引用

61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Ren, Xiangyu Zhang, Tianyu Xu, Xiong Zheng, Yi-Cong Zhang, Shengyu University of Edinburgh Edinburgh United Kingdom Tencent Quantum Lab Guangdong Shenzhen China

ISBN: (纸本)9798400706011

The design of quantum algorithms typically assumes the availability of an ideal quantum computer, characterized by full connectivity, noiseless operation, and unlimited coherence time. However, Noisy Intermediate-Scale quantum (NISQ) devices present a stark contrast, with a limited number of qubits, non-negligible quantum operation errors, and stringent constraints on the connectivity of physical qubits within a quantum processing Unit (QPU). This necessitates the dynamic remapping of logical qubits to physical qubits within the compiler to facilitate the execution of two-qubit gates in the algorithm. However, this introduces additional operations, consequently reducing the fidelity of the algorithm. Therefore, minimizing the number of added gates becomes crucial. Finding such an optimal routing problem is NP-hard, and the task is conventionally addressed using human-crafted heuristics to search for SWAP sequences, but these lack performance guarantees. In this study, we employ a Seq2Seq machine learning model for the qubit routing task, incorporating a Transformer neural network to learn the routing information in the gate and SWAP sequence. Compared to heuristic search-based algorithms, our approach significantly reduces the overhead of quantum computing resources required to adapt logical circuits to physical circuits executable on specific quantum backend hardware. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Qubits

来源：评论

学校读者我要写书评

暂无评论

quantum image encryption based on hyper-chaotic system and double-random phase encoding 3

Quantum image encryption based on hyper-chaotic system and d...

引用

3rd International Conference on Advanced algorithms and Signal Image processing, AASIP 2023

作者： Wu, Lei Li, Meiju Jia, Jiyang Sun, Xiaofei School of Information Science and Engineering Zaozhuang University Shandong277160 China

ISBN: (纸本)9781510668522

In order to enhance the security of encrypted images, a new quantum image encryption algorithm is proposed. This algorithm combines Chen's hyper-chaotic system with Double-random Phase Encoding (DRPE). The pixel values of the original quantum image are diffused using DRPE, while the pixel positions are scrambled through Cyclic Translation (CT). The hyper-chaotic sequences generated by Chen's hyper-chaotic system control the scrambling and diffusion operations. Numerical simulations and theoretical analyses have shown that this algorithm is highly effective in resisting illegal attacks. The encrypted image generated by this algorithm exhibits lower pixel correlation and more evenly distributed histogram. Overall, the proposed algorithm represents a robust and secure approach for image encryption © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

SWAP test for an arbitrary number of quantum states

引用

quantum information processing 2022年第10期21卷 1-16页

作者： Gitiaux, Xavier Morris, Ian Emelianenko, Maria Tian, Mingzhen George Mason Univ Dept Comp Sci Fairfax VA 22030 USA George Mason Univ Dept Phys & Astron Fairfax VA 22030 USA George Mason Univ Dept Math Sci Fairfax VA 22030 USA George Mason Univ Quantum Sci & Engn Ctr Fairfax VA 22030 USA

We develop a recursive algorithm to generalize the quantum SWAP test for an arbitrary number m of quantum states requiring O(m) controlled-swap (CSWAP) gates and O(logm) ancillary qubits. We construct a quantum circuit able to simultaneously measure overlaps ||(2) of m arbitrary pure states |phi(1) . . . phi(m)>. Our construction relies on a pairing unitary that generates a superposition state where every pair of input states is labeled by a basis state formed by the ancillaries. By implementing a simple genetic algorithm, we give numerical evidence indicating that our method of labeling each pair of inputs using CSWAP gates is optimal up to m = 8. Potential applications of the new circuits in the context of quantum machine learning are discussed.

关键词： Swap test quantum circuits quantum algorithms

来源：评论

学校读者我要写书评

暂无评论

quantum activation functions for quantum neural networks

引用

quantum information processing 2022年第4期21卷 1-24页

作者： Maronese, Marco Destri, Claudio Prati, Enrico CNR Ist Foton & Nanotecnol Piazza Leonardo da Vinci 32 I-20133 Milan Italy Univ Milano Bicocca Dipartimento Fis Piazza Sci 3 I-20126 Milan Italy Univ Milan Dipartimento Fis Aldo Pontremoli Via Celoria 16 I-20133 Milan Italy

The field of artificial neural networks is expected to strongly benefit from recent developments of quantum computers. In particular, quantum machine learning, a class of quantum algorithms which exploit qubits for creating trainable neural networks, will provide more power to solve problems such as pattern recognition, clustering and machine learning in general. The building block of feed-forward neural networks consists of one layer of neurons connected to an output neuron that is activated according to an arbitrary activation function. The corresponding learning algorithm goes under the name of Rosenblatt perceptron. quantum perceptrons with specific activation functions are known, but a general method to realize arbitrary activation functions on a quantum computer is still lacking. Here, we fill this gap with a quantum algorithm which is capable to approximate any analytic activation functions to any given order of its power series. Unlike previous proposals providing irreversible measurement-based and simplified activation functions, here we show how to approximate any analytic function to any required accuracy without the need to measure the states encoding the information. Thanks to the generality of this construction, any feed-forward neural network may acquire the universal approximation properties according to Hornik's theorem. Our results recast the science of artificial neural networks in the architecture of gate-model quantum computers.

关键词： quantum perceptron quantum neural network quantum activation function Hornik's theorem

来源：评论

学校读者我要写书评

暂无评论

Optimized quantum leading zero detector circuits

引用

quantum information processing 2022年第1期22卷 1-17页

作者： Orts, Francisco Ortega, Gloria Combarro, Elias F. Rua, Ignacio F. Garzon, Ester M. Univ Almeria Informat Dept Carretera Sacramento La Canada De San Urbano 04120 Spain Univ Oviedo Informat Dept Oviedo Spain Univ Oviedo Math Dept Oviedo Spain

The algorithms that best demonstrate the potential of quantum computing are Shor's algorithm and Grover's algorithm. To this day, new evidence continues to emerge in the form of algorithms or ingenious applications that increase the field of application of this type of computing. However, given the limited number of qubits in current quantum computers, and also the noise problems they currently suffer from, implementing optimized circuits that allow us to take full advantage of the available resources, as well as detecting and correcting the errors caused by this noise, is a priority. In this work we present several leading zero detector circuits for quantum computers and simulators, optimized in terms of noise tolerance and number of qubits. These circuits are a fundamental part in major circuits that perform operations as important and basic in computation as addition and division.

关键词： quantum circuit quantum computing quantum arithmetic Leading zero detector LZD

来源：评论

学校读者我要写书评

暂无评论

A secure cross-chain transaction model based on quantum multi-signature

引用

quantum information processing 2022年第8期21卷 1-24页

作者： Wang, Zhuo Li, Jian Chen, Xiu-Bo Li, Chaoyang Beijing Univ Posts Telecommun Coll Artificial Intelligence Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Informat Secur Ctr State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Adv Cryptog & Syst Secur Key Lab Sichuan Prov Chengdu 610225 Peoples R China Zhengzhou Univ Light Ind Coll Software Engn Zhengzhou 450002 Peoples R China

There is an obvious demand for blockchain to break the "data island" by crossing chains. Notary signature is one of the common cross-chain methods, and its security depends on the security of the signature algorithm. However, with the development of quantum computing, classical authentication of blockchain based on mathematical cryptography algorithms is not secure enough to prevent quantum attacks. Designing a signature algorithm to ensure the security of blockchain transactions in the post-quantum era is a problem to be solved at present. In the existing quantum signature algorithms, there are some problems, such as the arbitrators are not completely trusted, the quantum measurement loss is not traceable, and the transaction efficiency is low. Hence, our main work is as follows: (i) A cross-chain transaction model is proposed, which includes a quantum multi-signature notary mechanism and an assets quantum-freeze algorithm. (ii) The quantum multi-signature scheme can not only prevent forgery and denial, but also trace back malicious notaries. Moreover, it has the advantages of low storage overhead, decentralization, and high efficiency. (iii) quantum freeze scheme can prevent messages from being tampered with when the system allocates transferred data or assets to the connector after transaction verification. It effectively improves system transaction security and ensures privacy.

关键词： Blockchain cross-chain certification quantum multi-signature Cross-chain transaction quantum-freeze

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：