The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Peng Wang - One of the best experts on this subject based on the ideXlab platform.
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adaptive multi scale quantum Harmonic Oscillator algorithm based on evolutionary strategy
Congress on Evolutionary Computation, 2020Co-Authors: Peng WangAbstract:This paper proposes a novel adaptive multi-scale quantum Harmonic Oscillator algorithm based on evolutionary strategies (AMQHOA-ES) for global numerical optimization. Since the original Multi-scale Quantum Harmonic Oscillator Algorithm (MQHOA) utilizes a fixed contraction factor to narrow the search scale, the searching step decreases too fast at the later stage of the evolution and is more likely to suffer premature convergence and stagnation. To improve the convergence performance, an adaptive attenuation mechanism of scaling is proposed to dynamically adjust the exploration and exploitation properties. Evolutionary strategies such as selection, crossover and DE/rand/1 mutation are implemented in the proposed algorithm to enhance the exploration and exploitation abilities. Experimental results evaluated on several unimodal and multimodal benchmark functions indicate the significant improvement of the proposed algorithm to the original MQHOA. Meanwhile, the experimental results compared with several state-of-the-art optimizers show the superiority or competitiveness of the proposed algorithm.
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multi scale quantum Harmonic Oscillator algorithm for global numerical optimization
Applied Soft Computing, 2018Co-Authors: Peng Wang, Xinggui Ye, Bo Li, Kun ChengAbstract:Abstract This paper aims to provide a novel metaheuristic algorithm motivated from quantum motion entitled Multi-scale Quantum Harmonic Oscillator Algorithm (MQHOA). The calculation accuracy of MQHOA is adjustable. The physical model and mathematical analysis of the proposed algorithm are detailed and well interpreted in this paper. The structure of MQHOA is very simple, including merely two phases, the quantum Harmonic Oscillator process (QHO process) and multi-scale process (M process). Experiments are carried out to validate the effectiveness and efficiency of MQHOA by applying it to 30 well defined benchmark functions. We also compare MQHOA with several well-known metaheuristic algorithms, such as genetic algorithm (GA), simulated annealing (SA), particle swarm optimization (PSO) and quantum particle swarm optimization (QPSO). The comparative results indicate the competitive and superior performance of the proposed algorithm in both convergence speed and optimal solution accuracy.
Kun Cheng - One of the best experts on this subject based on the ideXlab platform.
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multi scale quantum Harmonic Oscillator algorithm for global numerical optimization
Applied Soft Computing, 2018Co-Authors: Peng Wang, Xinggui Ye, Bo Li, Kun ChengAbstract:Abstract This paper aims to provide a novel metaheuristic algorithm motivated from quantum motion entitled Multi-scale Quantum Harmonic Oscillator Algorithm (MQHOA). The calculation accuracy of MQHOA is adjustable. The physical model and mathematical analysis of the proposed algorithm are detailed and well interpreted in this paper. The structure of MQHOA is very simple, including merely two phases, the quantum Harmonic Oscillator process (QHO process) and multi-scale process (M process). Experiments are carried out to validate the effectiveness and efficiency of MQHOA by applying it to 30 well defined benchmark functions. We also compare MQHOA with several well-known metaheuristic algorithms, such as genetic algorithm (GA), simulated annealing (SA), particle swarm optimization (PSO) and quantum particle swarm optimization (QPSO). The comparative results indicate the competitive and superior performance of the proposed algorithm in both convergence speed and optimal solution accuracy.
Xinggui Ye - One of the best experts on this subject based on the ideXlab platform.
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multi scale quantum Harmonic Oscillator algorithm for global numerical optimization
Applied Soft Computing, 2018Co-Authors: Peng Wang, Xinggui Ye, Bo Li, Kun ChengAbstract:Abstract This paper aims to provide a novel metaheuristic algorithm motivated from quantum motion entitled Multi-scale Quantum Harmonic Oscillator Algorithm (MQHOA). The calculation accuracy of MQHOA is adjustable. The physical model and mathematical analysis of the proposed algorithm are detailed and well interpreted in this paper. The structure of MQHOA is very simple, including merely two phases, the quantum Harmonic Oscillator process (QHO process) and multi-scale process (M process). Experiments are carried out to validate the effectiveness and efficiency of MQHOA by applying it to 30 well defined benchmark functions. We also compare MQHOA with several well-known metaheuristic algorithms, such as genetic algorithm (GA), simulated annealing (SA), particle swarm optimization (PSO) and quantum particle swarm optimization (QPSO). The comparative results indicate the competitive and superior performance of the proposed algorithm in both convergence speed and optimal solution accuracy.
Jonas Keller - One of the best experts on this subject based on the ideXlab platform.
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quantum Harmonic Oscillator spectrum analyzers
Physical Review Letters, 2021Co-Authors: Jonas Keller, P Y Hou, Katherine C Mccormick, Daniel C Cole, Stephen Erickson, A C WilsonAbstract:Characterization and suppression of noise are essential for the control of Harmonic Oscillators in the quantum regime. We measure the noise spectrum of a quantum Harmonic Oscillator from low frequency to near the Oscillator resonance by sensing its response to amplitude modulated periodic drives with a qubit. Using the motion of a trapped ion, we experimentally demonstrate two different implementations with combined sensitivity to noise from 500 Hz to 600 kHz. We apply our method to measure the intrinsic noise spectrum of an ion trap potential in a previously unaccessed frequency range.
Ali Mostafazadeh - One of the best experts on this subject based on the ideXlab platform.
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inverting a time dependent Harmonic Oscillator potential by a unitary transformation and a class of exactly solvable Oscillators
Physical Review A, 1997Co-Authors: Ali MostafazadehAbstract:A time-dependent unitary (canonical) transformation is found which maps the Hamiltonian for a Harmonic Oscillator with time-dependent real mass and real frequency to that of a generalized Harmonic Oscillator with time-dependent real mass and imaginary frequency. The latter may be reduced to an ordinary Harmonic Oscillator by means of another unitary (canonical) transformation. A simple analysis of the resulting system leads to the identification of a previously unknown class of exactly solvable time-dependent Oscillators. Furthermore, it is shown how one can apply these results to establish a canonical equivalence between some real and imaginary frequency Oscillators. In particular it is shown that a Harmonic Oscillator whose frequency is constant and whose mass grows linearly in time is canonically equivalent with an Oscillator whose frequency changes from being real to imaginary and vice versa repeatedly.
