this paper proposes a novel hybrid algorithm namely apso-bfo which combines merits of bacterial foraging optimization (bfo) algorithm and adaptive particle swarm optimization (apso) algorithm to determine the optimal pid parameters for control of nonlinear systems. to balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

Quantum Factoring and Search Algorithms Quantum Information Seminar Friday, Sep. 17, 1999 Ashok Muthukrishnan Rochester Center for Quantum Information (RCQI) ___________________________________________________________ § 1. Quantum Algorithm for Factorisation (1994) A. Factorising and cryptography p. 2 B. Relation of factorisation to period-finding p. 5 C. Quantum algorithm for period-finding p....

In this paper, we will use a quantum operator which performs the inversion about the mean operation only on a subspace of the system (Partial Diffusion Operator) to propose a quantum search algorithm runs in O( √ N/M ) for searching unstructured list of size N with M matches such that, 1 ≤ M ≤ N . We will show that the performance of the algorithm is more reliable than known quantum search algo...

We investigate the generalisation of quantum search of unstructured and totally ordered sets to search of partially ordered sets (posets). Two models for poset search are considered. In both models, we show that quantum algorithms can achieve at most a quadratic improvement in query complexity over classical algorithms, up to logarithmic factors; we also give quantum algorithms that almost achi...

The Grover search algorithm is one of the two key algorithms in the field of quantum computing, and hence it is desirable to represent it in the simplest and most intuitive formalism possible. We show firstly, that Clifford’s geometric algebra, provides a significantly simpler representation than the conventional bra-ket notation, and secondly, that the basis defined by the states of maximum an...

An SO(3) picture of the generalized Grover’s quantum searching algorithm,with arbitrary unitary transformation and with arbitrary phase rotations, is constructed. In this picture, any quantum search operation is a rotation in a 3 dimensional space. Exact formulas for the rotation angle and rotational axis are given. The probability of finding the marked state is just (z +1)/2, where z is the z-...

Abstract We use the mapping between two computation frameworks, Adiabatic Grover Search (AGS) and Quantum Computing (AQC), to translate search algorithm into AQC regime. then apply Trotterization on schedule-dependent Hamiltonian of AGS obtain values variational parameters in Approximate Optimization Algorithm (QAOA) framework. The goal is carry optimal behavior QAOA framework without iterative...