未找到相关数据
ANALYSIS OF QUANTUM MONTE CARLO DYNAMICS IN INFINITE-RANGE ISING SPIN SYSTEMS: THEORY AND ITS POSSIBLE APPLICATIONS
被引：0
|作者：
Inoue, Jun-ichi
[1
]
机构：
[1] Hokkaido Univ, Grad Sch Informat Sci & Technol, Kita Ku, Sapporo, Hokkaido 0600809, Japan
来源：
INTERFACE BETWEEN QUANTUM INFORMATION AND STATISTICAL PHYSICS
|
2013年
/
7卷
关键词：
Quantum dynamics;
Quantum Monte Carlo method;
Infinite-range model;
Probabilistic information processing;
Image restoration;
Neural networks;
Associative memories;
ERROR-CORRECTING CODES;
NEURAL-NETWORKS;
ASSOCIATIVE MEMORY;
IMAGE-RESTORATION;
HOPFIELD NETWORKS;
MODEL;
GLASS;
SIMULATIONS;
EVOLUTION;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In terms of the stochastic process of a quantum-mechanical variant of Markov chain Monte Carlo method based on the Suzuki-Trotter decomposition, we analytically derive deterministic flows of order parameters such as magnetization in infinite-range (a mean-field like) quantum spin systems. Under the static approximation, differential equations with respect to order parameters are explicitly obtained from the Master equation that describes the microscopic-law in the corresponding classical system. We discuss several possible applications of our approach to several research topics, say, image processing and neural networks. This paper is written as a self-review of two papers(1,2) for Symposium on Interface between Quantum Information and Statistical Physics at Kinki University in Osaka, Japan.
引用
收藏
页码：191 / 213
页数：23
相关论文