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arXiv 0807.4738hep-th
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复作用量的随机量子化

Stochastic Quantization for Complex Actions

G. Menezes, N. F. Svaiter

摘要:

本文利用随机量子化方法研究了具有复值路径积分权的系统。我们假设一个朗之万方程的记忆核和爱因斯坦的关系与色噪声。分析了该非马尔可夫朗之万方程的平衡解。我们表明,对于一类大的椭圆非厄米算子的标量函数上的欧氏空间,定义不同的模型在量子场论,收敛到一个平衡态的渐近极限的马尔可夫参数。此外,正如我们所预期的,我们得到了该理论的Schwinger函数。

英文摘要:

We use the stochastic quantization method to study systems with complex valued path integral weights. We assume a Langevin equation with a memory kernel and Einstein's relations with colored noise. The equilibrium solution of this non-Markovian Langevin equation is analyzed. We show that for a large class of elliptic non-Hermitian operators acting on scalar functions on Euclidean space, which define different models in quantum field theory, converges to an equilibrium state in the asymptotic limit of the Markov parameter. Moreover, as we expected, we obtain the Schwinger functions of the theory.

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