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quantum algorithm design using dynamic learning

quantum INFORMATION & COMPUTATION 2008年第1-2期8卷 12-29页

作者： Behrman, E. C. Steck, J. E. Kumar, P. Walsh, K. A. Wichita State Univ Dept Phys Wichita KS 67260 USA Wichita State Univ Dept Elect & Comp Engn Wichita KS 67260 USA Wichita State Univ Dept Aerosp Engn Wichita KS 67260 USA Wichita State Univ Dept Phys Wichita KS 67260 USA

We present a dynamic learning paradigm for "programming" a general quantum computer. A learning algorithm is used to find the control parameters for a coupled qubit system, such that the system at an initial time evolves to a state in which a given measurement corresponds to the desired operation. This can be thought of as a quantum neural network. We first apply the method to a system of two coupled superconducting quantum interference devices (SQUIDs), and demonstrate learning of both the classical gates XOR and XNOR. Training of the phase produces a gate congruent to the CNOT modulo a phase shift. Striking out for somewhat more interesting territory, we attempt learning of an entanglement witness for a two qubit system. Simulation shows a reasonably successful mapping of the entanglement at the initial time onto the correlation function at the final time for both pure and mixed states. For pure states this mapping requires knowledge of the phase relation between the two parts;however, given that knowledge, this method can be used to measure the entanglement of an otherwise unknown state. The method is easily extended to multiple qubits or to quNits.

关键词： quantum algorithm entanglement dynamic learning

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Study of Error Propagation and Generation in Harrow-Hassidim-Lloyd (HHL) quantum algorithm

Study of Error Propagation and Generation in Harrow-Hassidim...

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IEEE Latin American Electron Devices Conference (LAEDC)

作者： Zaman, Anika Wong, Hiu Yung San Jose State Univ Elect Engn San Jose CA 95192 USA

ISBN: (数字)9781665497671

ISBN: (纸本)9781665497671

In this paper, we study the error propagation and generation in the Harrow-Hassidim-Lloyd (HHL) quantum algorithm runs on IBM-Q hardware with the help of a MATLAB simulator. HHL is a quantum algorithm that can provide exponential speedup over the fastest classical algorithm ( conjugate gradient method) in solving systems of linear equations (SLE). However, without error correction, it cannot give correct results even in a 2-variable system due to its complexity. In this study, an HHL quantum circuit for a 2-variable SLE is implemented in IBM-Q and the error is extracted after each stage of the circuit and compared to a MATLAB simulator. We identified three major sources of errors, namely single-qubit flipping, gate infidelity, and error propagation. We also found that at the ancillary bit rotation stage, the error becomes large but the encoded solution still has high fidelity. However, the solution is mostly lost after the inverse quantum phase estimation which is necessary to extract the solution efficiently. Therefore, it is suggested that error correction resources, if limited, should be added to the second half of the circuit.

关键词： Error HHL quantum algorithm quantum Computing Qubit Flipping

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quantum algorithm for quantum state discrimination via partial negation and weak measurement

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quantum INFORMATION PROCESSING 2021年第9期20卷 307-307页

作者： Rizk, Doha A. Younes, Ahmed Alexandria Univ Dept Math & Comp Sci Fac Sci Alexandria Egypt Univ Birmingham Sch Comp Sci Birmingham B15 2TT W Midlands England

The quantum state discrimination problem is to distinguish between non-orthogonal quantum states. This problem has many applications in quantum information theory, quantum communication and quantum cryptography. In this paper, a quantum algorithm using weak measurement and partial negation will be proposed to solve the quantum state discrimination problem using a single copy of an unknown qubit. The usage of weak measurement makes it possible to reconstruct the qubit after measurement since the superposition will not be destroyed due to measurement. The proposed algorithm will be able to determine, with high probability of success, the state of the unknown qubit and whether it is encoded in the Hadamard or the computational basis by counting the outcome of the successive measurements on an auxiliary qubit.

关键词： quantum state discrimination quantum algorithm Weak measurement Partial negation Computational basis Hadamard basis

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quantum algorithm of Imperfect KB Self-organization. Pt II: Robotic Control with Remote Knowledge Base Exchange

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Artificial Intelligence Advances 2021年第2期3卷 44-70页

作者： A.G.Reshetnikov S.V.Ulyanov Plekhanov Russian University of Economics Laboratory of cloud technologies and Big Data analyticsRussia State University Dubna Russia

The technology of knowledge base remote design of the smart fuzzy controllers with the application of the"Soft/quantum computing optimizer"toolkit software *** possibility of the transmission and communication the knowledge base using remote connection to the control object *** and communication of the fuzzy controller’s knowledge bases implemented through the remote connection with the control object in the online mode apply the Bluetooth or WiFi *** transmission of knowledge bases allows designing many different built-in intelligent controllers to implement a variety of control strategies under conditions of uncertainty and *** examples,two different models of robots described(mobile manipulator and(“cart-pole”system)inverted pendulum).A comparison of the control quality between fuzzy controllers and quantum fuzzy controller in various control modes is *** ability to connect and work with a physical model of control object without using than mathematical model *** implemented technology of knowledge base design sharing in a swarm of intelligent robots with quantum *** allows to achieve the goal of control and to gain additional knowledge by creating a new quantum hidden information source based on the synergetic effect of combining ***ment and implementation of intelligent robust controller’s prototype for the intelligent quantum control system of mega-science project NICA(at the first stage for the cooling system of superconducted magnets)is *** results of the experiments demonstrate the possibility of the ensured achievement of the control goal of a group of robots using soft/quantum computing technologies in the design of knowledge bases of smart fuzzy controllers in quantum intelligent control *** developed software toolkit allows to design and setup complex ill-defined and weakly formalized technical systems on line.

关键词： quantum software engineering quantum algorithm Group of intelligent robots Multi-agent system Intelligent control Fuzzy controller Remote transmission of knowledge Knowledge synergetic

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quantum algorithm for solving matrix equations of the form AX = B

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LASER PHYSICS LETTERS 2022年第5期19卷 055202-055202页

作者： Xu, Li Liu, Xiao-qi Liang, Jin-min Wang, Jing Li, Ming Shen, Shu-qian China Univ Petr Coll Sci Qingdao 266580 Peoples R China Capital Normal Univ Sch Math Sci Beijing 10048 Peoples R China Max Planck Inst Math Sci D-04103 Leipzig Germany

Solving linear systems of equations is of vital importance in various fields of science. With the scale of calculation soaring, classical computers are intractable, and the advantage of quantum computing is reflected. quantum algorithm has exponential acceleration in solving the linear systems Ax' = (b) over right arrow for sparse and well-conditioned coefficient matrix A with dimension N xN. In this paper, we present a quantum algorithm to solve matrix equations of the form AX = B, where X = ((x) over right arrow1,.(x) over right arrow2, xn), B = ((x) over right arrow1, (b) over right arrow (2), (b) over right arrow (n)),(x) over right arrow (k) and.(b) over right arrow (k) are unit vectors. The problem can be intuitively treated as solving n linear systems simultaneously, which will needs O(n log N) complexity by the famous HHL algorithm. We demonstrate that in our algorithm the scale of complexity is O(log nN). In the error analysis part, phase estimation is discussed in details.

关键词： quantum algorithm quantum computation quantum information

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quantum algorithm for the Choice for the Site of the Public Transport Station Problem in Cloud Computing Environment

Quantum Algorithm for the Choice for the Site of the Public ...

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2013 3rd International Conference on Advanced Measurement and Test(AMT 2013)

作者： Guiying Mai Yueguang Li Gansu Normal University for Nationalities

In this paper,according to the characteristics and influence factors of the site of the public transport station problem,a mathematical model of the urban public transport station problem was *** computing and quantum algorithm was used to solve the model,with Hezuo city of Gansu Province as example,the algorithm was experimented and the experimental results show that the algorithm can acquire the optimal solution that is accord with the practice,moreover,the algorithm has much more practical.

关键词： quantum algorithm The site of the urban public transport station Lanzhou city Mathematical model

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quantum algorithm for Density Peak Anomaly Detection Based on KNN

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

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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

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quantum algorithm for the Simulation of Squamous Cell Lung Carcinoma tested through IBM quantum Composer

Quantum Algorithm for the Simulation of Squamous Cell Lung C...

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IEEE MIT Undergraduate Research Technology Conference (URTC)

作者： Akshita Tiwari Academy of Science Academies of Loudoun Leesburg United States

Classical algorithms for lung cancer exist based on immunotherapy but are quite prone to error. Non-small cell is a major type of lung cancer, frequently caused by smoking. A classical algorithm to treat non-small-cell lung cancer is compared to a quantum algorithm created. Using superposition of qubits, Born’s rule, and the general qubit rule, an algorithm simulates the pathway of certain driver genes, by finding the angle required of the qubit to be able to result in the probability needed to simulate the pathway, tested in IBM quantum Composer.

关键词： quantum algorithm Computational modeling Qubit Lung cancer Lung Immunotherapy

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

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

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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

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quantum algorithm for the Analysis of Temporal Sequences of Satellite Images

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

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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

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