This paper proposes a new artificial bee colony algorithm with quantum theory and the chaotic local search strategy (QCABC), and uses it to solve the optimal power flow (OPF) problem. Under the quantum computing theory, the QCABC algorithm encodes each individual with quantum bits to form a corresponding quantum bit string. By determining each quantum bits value, we can get the value of the ind...

In this paper we will present a quantum algorithm which works very efficiently in case of multiple matches within the search space and in the case of few matches, the algorithm performs classically. This allows us to propose a hybrid quantum search engine that integrates Grover’s algorithm and the proposed algorithm here to have general performance better that any pure classical or quantum sear...

An alternative quantum algorithm for the discrete logarithm problem is presented. The algorithm uses two quantum registers and two Fourier transforms whereas Shor’s algorithm requires three registers and four Fourier transforms. A crucial ingredient of the algorithm is a quantum state that needs to be constructed before we can perform the computation. After one copy of this state is created, th...

We study the quantum walk search algorithm of Shenvi, Kempe, and Whaley [PRA 67 052307 (2003)] on data structures of one to two spatial dimensions, on which the algorithm is less efficient than in three or more spatial dimensions. Our aim is to understand why the quantum algorithm is dimension dependent whereas the best classical algorithm is not, and to find in more detail how the efficiency o...

Laplacian eigenmap algorithm is a typical nonlinear model for dimensionality reduction in classical machine learning. We propose an efficient quantum Laplacian eigenmap algorithm to exponentially speed up the original counterparts. In our work, we demonstrate that the Hermitian chain product proposed in quantum linear discriminant analysis (arXiv:1510.00113,2015) can be applied to implement qua...

Learning with Errors is one of the fundamental problems in computational learning theory and has in the last years become the cornerstone of post-quantum cryptography. In this work, we study the quantum sample complexity of Learning with Errors and show that there exists an efficient quantum learning algorithm (with polynomial sample and time complexity) for the Learning with Errors problem whe...

The identification of an unknown quantum gate is a significant issue in quantum technology. In this paper, we propose a quantum gate identification method within the framework of quantum process tomography. In this method, a series of pure states are inputted to the gate and then a fast state tomography on the output states is performed and the data are used to reconstruct the quantum gate. Our...

Quantum algorithm acts as an important role in quantum computation science, not only for providing a great vision for solving classically unsolvable problems, but also due to the fact that it gives a potential way of understanding quantum physics. We experimentally realize a quantum speed-up algorithm with a single qudit via linear optics and prove that even a single qudit is enough for designi...

In this paper we describe a quantum algorithm to solve sparse systems of nonlinear differential equations whose nonlinear terms are polynomials. The algorithm is nondeterministic and its expected resource requirements are polylogarithmic in the number of variables and exponential in the integration time. The best classical algorithm runs in a time scaling linearly with the number of variables, ...

In Round-Robin Scheduling, the quantum time is static and tasks are scheduled such that no process uses CPU time more than one slice time each cycle. If quantum time is too large, the response time of the processes will not be tolerated in an interactive environment. If quantum the time is too small, unnecessary frequent context switch may occur. Consequently, overheads result in fewer throughp...