检索结果-内蒙古大学图书馆

quantum algorithms for simulation of quantum chemistry problems by quantum computers: an appraisal

FOUNDATIONS OF CHEMISTRY 2022年第2期24卷 263-276页

作者： Sharma, Smriti Univ Delhi Dept Chem Miranda House New Delhi 110007 India

The ideas of quantum simulation and advances in quantum algorithms to solve quantum chemistry problems have been discussed. Theoretical proposals and experimental investigations both have been studied to gauge the extent to which quantum computation has been applied to solve quantum chemical problems till date. The distinctive features and limitations of the application of quantum simulation on chemical systems and current approaches to define and improve upon standard quantum algorithms have been studied in detail. The possibility and consequences of designing an efficient quantum computer that can address chemical problems have been assessed. The experimental realization of quantum supremacy defies the conventional belief of chemists, that millions of qubits would be required to solve fundamental chemistry problems. It is predicted that quantum simulation of quantum chemistry problems will radically revolutionize this field.

关键词： quantum chemistry Computational chemistry Molecular simulations quantum simulation quantum algorithms quantum supremacy

来源：评论

学校读者我要写书评

暂无评论

Computational Analysis: Unveiling the quantum algorithms for Protein Analysis and Predictions

引用

IEEE ACCESS 2023年 11卷 94023-94033页

作者： Bhuvaneswari, S. Deepakraj, R. Urooj, Shabana Sharma, Neelam Pathak, Nitish Easwari Engn Coll Dept Comp Sci & Engn Chennai 600089 India Princess Nourah Bint Abdulrahman Univ Coll Engn Dept Elect Engn Riyadh 11671 Saudi Arabia Guru Gobind Singh Indraprastha Univ GGSIPU Maharaja Agrasen Inst Technol MAIT Dept Artificial Intelligence & Machine Learning New Delhi 110078 India GGSIPU Bhagwan Parshuram Inst Technol BPIT Dept Informat Technol New Delhi 110078 India

The study of protein-protein interactions (PPIs) and predicting the protein structure plays a critical role in understanding cellular processes and designing therapeutic interventions. In this research, we explore the application of quantum algorithms, specifically Grover's algorithm, in improving the accuracy and efficiency of PPI prediction. By harnessing the inherent parallelism and quantum search capabilities of Grover's algorithm, we aim to enhance the identification of interacting protein pairs from large-scale datasets. We demonstrate the effectiveness of using this algorithm through an extensive approach, comparing the performance of Grover's algorithm with classical machine learning algorithms. Our results reveal that the quantum algorithm offers significant improvements in prediction accuracy, enabling the identification of previously undetected PPIs. Moreover, we discuss the advantages and limitations of using Grover's algorithm in PPI prediction and provide insights into its potential for accelerating research in protein interaction networks. This research highlights the potential of quantum algorithms in advancing the field of bioinformatics and protein interaction analysis.

关键词： Bioinformatics Grover's algorithm protein-protein interaction (PPI) protein structure quantum algorithms quantum simulation

来源：评论

学校读者我要写书评

暂无评论

quantum Meets Fine-Grained Complexity: Sublinear Time quantum algorithms for String Problems

引用

ALGORITHMICA 2023年第5期85卷 1251-1286页

作者： Le Gall, Francois Seddighin, Saeed Nagoya Univ Grad Sch Math Chikusa Ku Furocho Nagoya Aichi 4648602 Japan Toyota Technol Inst Chicago 6045 S Kenwood Ave Chicago IL 60637 USA

Longest common substring (LCS), longest palindrome substring (LPS), and Ulam distance (UL) are three fundamental string problems that can be classically solved in near linear time. In this work, we present sublinear time quantum algorithms for these problems along with quantum lower bounds. Our results shed light on a very surprising fact: Although the classic solutions for LCS and LPS are almost identical (via suffix trees), their quantum computational complexities are different. While we give an exact o (root n) time algoritham for LPS, we prove that LCS needs at least time omega(sic) (n(2/3 )) even for 0/1 strings.

关键词： String algorithms quantum algorithms Sublinear-time algorithms Fine-grained complexity

来源：评论

学校读者我要写书评

暂无评论

Introducing nega-Forrelation: quantum algorithms in analyzing nega-Hadamard and nega-crosscorrelation spectra

引用

DESIGNS CODES AND CRYPTOGRAPHY 2023年第3期92卷 863-883页

作者： Dutta, Suman Maitra, Subhamoy Indian Stat Inst Kolkata India

Aaronson defined Forrelation (2010) as a measure of correlation between a Boolean function f and the Walsh-Hadamard transform of another function g. In a recent work, we have studied different cryptographically important spectra of Boolean functions through the lens of Forrelation. In this paper, we explore a similar kind of correlation in terms of nega-Hadamard transform. We call it nega-Forrelation and obtain a more efficient sampling strategy for nega-Hadamard transform compared to the existing results. Moreover, we present an efficient sampling strategy for nega-crosscorrelation (and consequently nega-autocorrelation) spectra too, by tweaking the nega-Forrelation technique. Finally, we connect the hidden shift finding algorithm for bent functions (Rotteler, 2010) with the Forrelation algorithm and extend it for the negabent functions.

关键词： Boolean functions Cryptology Forrelation Hidden-shift problem nega-Forrelation nega-Hadamard transform quantum algorithms Walsh-Hadamard transform

来源：评论

学校读者我要写书评

暂无评论

Computing Classical Partition Functions: From Onsager and Kaufman to quantum algorithms 24

Computing Classical Partition Functions: From Onsager and Ka...

引用

Recent Advances in quantum Computing and Technology conference (ReAQCT)

作者： Gargiulo, Roberto Rizzi, Matteo Zeier, Robert Forschungszentrum Julich Peter Grunberg Inst Quantum Control PGI 8 D-52425 Julich Germany Univ Cologne Inst Theoret Phys THP D-50937 Cologne Germany

ISBN: (纸本)9798400717987

The computation of classical Ising partition functions, coming from statistical physics, is a natural generalization of binary optimization. This is a notoriously hard problem in general, which makes it an especially interesting task to consider in the search for practical quantum advantage in near term quantum computers. In this work we view classical Ising models (on certain graphs) as quantum imaginary time evolution, which is enabled by the use of the transfer matrix mapping. We study this mapping from two points of view: (1) following Onsager and Kaufman's original solution of the 2D Ising model, which serves as a starting point, we consider more general models and the possibility of a similar Lie-theoretic solution;(2) we consider quantum algorithms for the computation of partition functions and thermal averages via transfer matrices, which can be implemented either with block encodings inside larger unitaries or by approximating the state trajectories with unitary operators.

关键词： partition functions binary optimization quantum algorithms spin glasses imaginary time evolution Lie theory

来源：评论

学校读者我要写书评

暂无评论

Qubit-Efficient Variational quantum algorithms for Image Segmentation 5

Qubit-Efficient Variational Quantum Algorithms for Image Seg...

引用

2024 International Conference on quantum Computing and Engineering

作者： Venkatesh, Supreeth Mysore Macaluso, Antonio Nuske, Marlon Klusch, Matthias Dengel, Andreas Univ Kaiserslautern Landau RPTU Kaiserslautern Germany German Res Ctr Artificial Intelligence DFKI Saarbrucken Germany German Res Ctr Artificial Intelligence DFKI Kaiserslautern Germany

ISBN: (纸本)9798331541378

quantum computing is expected to transform a range of computational tasks beyond the reach of classical algorithms. In this work, we examine the application of variational quantum algorithms (VQAs) for unsupervised image segmentation to partition images into separate semantic regions. Specifically, we formulate the task as a graph cut optimization problem and employ two established qubit-efficient VQAs, which we refer to as Parametric Gate Encoding (PGE) and Ancilla Basis Encoding (ABE), to find the optimal segmentation mask. In addition, we propose Adaptive Cost Encoding (ACE), a new approach that leverages the same circuit architecture as ABE but adopts a problem-dependent cost function. We benchmark PGE, ABE and ACE on synthetically generated images, focusing on quality and trainability. ACE shows consistently faster convergence in training the parameterized quantum circuits in comparison to PGE and ABE. Furthermore, we provide a theoretical analysis of the scalability of these approaches against the quantum Approximate Optimization Algorithm (QAOA), showing a significant cutback in the quantum resources, especially in the number of qubits that logarithmically depends on the number of pixels. The results validate the strengths of ACE, while concurrently highlighting its inherent limitations and challenges. This paves way for further research in quantum-enhanced computer vision.

关键词： quantum algorithms variational circuits image segmentation combinatorial optimization

来源：评论

学校读者我要写书评

暂无评论

QuCode: A Novel Conceptual Description of quantum algorithms 54

QuCode: A Novel Conceptual Description of Quantum Algorithms

引用

54th IEEE International Symposium on Multiple-Valued Logic (ISMVL)

作者： Ketineni, Hrithik Perkowski, Marek Portland State Univ Dept Elect & Comp Engn Portland OR 97207 USA

ISBN: (纸本)9798350343090;9798350343083

Conventional presentations of quantum algorithms overwhelmingly rely on mathematical formalism, posing an unnecessary barrier to conceptual understanding. The growing influence of quantum computing across diverse domains necessitates more accessible education on the subject. To engage a broader audience in quantum computing, we introduce a new approach for teaching quantum algorithms: drawing parallels to classical pseudocode. This approach, which we call "QuCode," is demonstrated through its application to several black box quantum algorithms: Deutsch-Jozsa, Bernstein-Vazirani, and Simon's algorithm.

关键词： Bernstein-Vazirani algorithm Deutsch-Jozsa algorithm oracle pedagogy pseudocode Simon's algorithm quantum algorithms quantum computing

来源：评论

学校读者我要写书评

暂无评论

Discovery of quantum algorithms Using Genetic algorithms: Exponential Speedup via Random Sampling 5

Discovery of Quantum Algorithms Using Genetic Algorithms: Ex...

引用

2024 International Conference on quantum Computing and Engineering

作者： Almuqbil, Tarig Felemban, Muhamad KFUPM Dept Phys Dhahran Saudi Arabia KFUPM Dept Comp Engn Dhahran Saudi Arabia

ISBN: (纸本)9798331541378

The integration of classical machine learning with quantum computing is a promising frontier for solving complex problems more efficiently. This study focuses on discovering oracle-based quantum algorithms, specifically quantum search algorithms like Grover's algorithm, using genetic algorithms (Gas). By leveraging random sampling of oracle combinations, our method reduces the evaluation time complexity from O(2(n)) to O(n), enabling the efficient optimization of larger n-qubit circuits. The fitness evaluation of quantum circuits was based on a reduced number of random oracle combinations, significantly speeding up the process while maintaining optimization effectiveness. Our GA experiments, involving up to 8-qubit oracles, demonstrated the ability to identify the first iteration of Grover's algorithm and provided insights into the algorithm's performance across various circuit sizes. The results highlight the efficacy of our fast evaluation method in accelerating classical optimization techniques for discovering quantum algorithms, offering a scalable solution for larger qubit configurations. Limitations and potential improvements for handling even larger qubit sizes are also discussed.

关键词： quantum computing machine learning genetic algorithms quantum circuits quantum algorithms Grover's algorithm

来源：评论

学校读者我要写书评

暂无评论

quantum algorithms for Linear and Nonlinear Differential Equations

Quantum Algorithms for Linear and Nonlinear Differential Equ...

引用

作者： Liu, Jin-Peng University of Maryland College Park

学位级别：Ph.D., Doctor of Philosophy

quantum computers are expected to dramatically outperform classical computers for certain computational problems. Originally developed for simulating quantum physics, quantum algorithms have been subsequently developed to address diverse computational challenges. There has been extensive previous work for linear dynamics and discrete models, including Hamiltonian simulations and systems of linear equations. However, for more complex realistic problems characterized by differential equations, the capability of quantum computing is far from well understood. One fundamental challenge is the substantial difference between the linear dynamics of a system of qubits and real-world systems with continuum and nonlinear behaviors. My research is concerned with mathematical aspects of quantum computing. In this dissertation, I focus mainly on the design and analysis of quantum algorithms for differential equations. Systems of linear ordinary differential equations (ODEs) and linear elliptic partial differential equations (PDEs) appear ubiquitous in natural and social science, engineering, and medicine. I propose a variety of quantum algorithms based on finite difference methods and spectral methods for producing the quantum encoding of the solutions, with an exponential improvement in the precision over previous quantum algorithms. Nonlinear differential equations exhibit rich phenomena in many domains but are notoriously difficult to solve. Whereas previous quantum algorithms for general nonlinear equations have been severely limited due to the linearity of quantum mechanics, I give the first efficient quantum algorithm for nonlinear differential equations with sufficiently strong dissipation. I also establish a lower bound, showing that nonlinear differential equations with sufficiently weak dissipation have worst-case complexity exponential in time, giving an almost tight classification of the quantum complexity of simulating nonlinear dynamics. Overall, utilizing advanced

关键词： Differential equations quantum algorithms Linear and nonlinear

来源：评论

学校读者我要写书评

暂无评论

Memristor Crossbar Arrays Performing quantum algorithms

引用

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2022年第2期69卷 552-563页

作者： Fyrigos, Iosif-Angelos Ntinas, Vasileios Vasileiadis, Nikolaos Sirakoulis, Georgios Ch Dimitrakis, Panagiotis Zhang, Yue Karafyllidis, Ioannis G. Democritus Univ Thrace DUTh Dept Elect & Comp Engn Xanthi 67100 Greece Univ Politecn Cataluna Dept Elect Engn Barcelona 08028 Spain NCSR Demokritos Inst Nanosci & Nanotechnol Athens 15341 Greece Beihang Univ Beijing Adv Innovat Ctr Big Data & Brain Comp Sch Integrated Circuit Sci & Engn Fert Beijing Inst Beijing 100191 Peoples R China Hefei Innovat Res Inst Beihang Univ Nanoelect Sci & Technol Ctr Hefei 230013 Peoples R China

There is a growing interest in quantum computers and quantum algorithm development. It has been proved that ideal quantum computers, with zero error rates and large decoherence times, can solve problems that are intractable for today's classical computers. quantum computers use two resources, superposition and entanglement, that have no classical analog. Since quantum computer platforms that are currently available comprise only a few dozen of qubits, the use of quantum simulators is essential in developing and testing new quantum algorithms. We present a novel quantum simulator based on memristor crossbar circuits and use them to simulate well-known quantum algorithms, namely the Deutsch and Grover quantum algorithms. In quantum computing the dominant algebraic operations are matrix-vector multiplications. The execution time grows exponentially with the simulated number of qubits, causing an exponential slowdown in quantum algorithm execution using classical computers. In this work, we show that the inherent characteristics of memristor arrays can be used to overcome this problem and that memristor arrays can be used not only as independent quantum simulators but also as a part of a quantum computer stack where classical computers accelerators are connected. Our memristive crossbar circuits are re-configurable and can be programmed to simulate any quantum algorithm.

关键词： quantum computing Qubit Computers Memristors quantum algorithm Logic gates quantum entanglement Memristors memristor crossbars quantum algorithms quantum simulators

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：