Search

Your search keyword '"Liao, Zhiqiang"' showing total 3 results
Start Over Author "Liao, Zhiqiang" Topic combinatorial optimization
3 results on '"Liao, Zhiqiang"'

2. Quantum Analog Annealing of Gain‐Dissipative Ising Machine Driven by Colored Gaussian Noise.

Author

Liao, Zhiqiang, Ma, Kaijie, Sarker, Md Shamim, Tang, Siyi, Yamahara, Hiroyasu, Seki, Munetoshi, and Tabata, Hitoshi

Subjects
*QUANTUM annealing, *RANDOM noise theory, *WHITE noise, *COMBINATORIAL optimization, *CLUSTER analysis (Statistics), *WIENER processes
Abstract

Gain‐dissipative Ising machines (GIMs) are a type of quantum analog equipment that can rapidly determine the optimal solution for combinatorial optimization problems. When the noise intensity is significantly lower than the fixed point of the system, the performance of a GIM is not influenced by the fluctuation of the noise intensity. However, the noise in this study is limited to Gaussian white noise. The influence of prevalent colored noise on GIMs has not been researched. In this study, the influence of common‐colored noise on the performance of GIMs is numerically investigated. The results of a domain clustering dynamics analysis reveal that red noise can better suppress the generation of the noise‐induced irregular temporary domain. Furthermore, several prevalent MAXCUT problem topologies, including the Moebius ladder, random Moebius ladder, and 2D random lattice, are adopted as test benchmarks. The results reveal that GIMs influenced by white, blue, and violet noise perform better at low‐intensity noise condition. In contrast, pink and red noise‐injected GIMs demonstrate higher performances when applied to MAXCUT topologies with both ferromagnetic and antiferromagnetic connections under larger noise intensity conditions. This indicates that the noise dispersion can be used as an additional hyperparameter to optimize the performance of GIMs. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

3. Nonbistable rectified linear unit-based gain-dissipative Ising spin network with stochastic resonance effect.

Author

Liao, Zhiqiang, Ma, Kaijie, Tang, Siyi, Yamahara, Hiroyasu, Seki, Munetoshi, and Tabata, Hitoshi

Subjects
RESONANCE effect, STOCHASTIC resonance, COMBINATORIAL optimization, NONLINEAR functions, TRANSFER functions, PROBLEM solving
Abstract

The gain-dissipative Ising machine (GIM), comprising a nonlinear transfer function and spin interaction feedback, is one of the most promising quantum analog annealers. However, previous GIM constructions have been limited to only bistable nonlinear transfer functions with low noise intensity condition. To provide a new insight and broaden the potential design of GIMs, we construct a nonbistable rectified linear unit-based gain-dissipative Ising spin network (RISN). In contrast to the traditional GIM, spin dynamics analysis in the uncoupled state proves that RISN is nonbistable. Furthermore, it is demonstrated that the proposed RISN can effectively solve combinatorial optimization problems with a high noise level, which can be regarded as a stochastic resonance phenomenon. The proposed configuration, which does not comply with known conclusions, can become a stepping-stone for new GIM designs. • Gain-dissipative Ising spin network based on a nonbistable ReLU function (RISN) proposed. • Spin dynamics analysis prove that RISN completely differs from traditional gain-dissipative Ising machines (GIMs). • RISN can effectively solve MAXCUT problems under appropriate noise intensity (SR). • Proposed configuration can be a stepping-stone for new GIM design. • The SR phenomenon in RISN can offer new insight on noise implementation in GIMs. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results