Python implementation of the classical and quantum-inspired Single-Thread Monte Carlo algorithm for estimating ground state energies, using a transformation matrix to improve convergence.

What are Machine learning algorithms in Python? Which guide should I choose?"- This guide explains explicitly the operation of Machine Learning methods and how to implement them in Python. Whether you ...

Abstract: Metropolis-Hastings algorithm (MH) is the most popular Markov Chain Monte Carlo (MCMC) method. Essentially, the MH algorithm generates a sample, accepts or rejects the sample based on an ...

我们将研究两种对分布进行抽样的方法：拒绝抽样和使用 Metropolis Hastings 算法的马尔可夫链蒙特卡洛方法 (MCMC)。像往常一样，我将提供直观的解释、理论和一些带有代码的示例。 背景 在我们进入主题之前，让我们将马尔可夫链蒙特卡罗（MCMC）这个术语分解为它 ...

Abstract: We will study the class of first-order locally-balanced Metropolis-Hastings algorithms. Popular choices within the class are the Metropolis-adjusted Langevin algorithm (MALA) andthe recently ...

Abstract: The paper studies the features of the Metropolis-Hastings algorithm and its applications in Bayesian data analysis problems. The application of the Monte-Carlo Markov chains (MCMC) methods ...

We develop an Evolutionary Markov Chain Monte Carlo (EMCMC) algorithm for sampling spatial partitions that lie within a large, complex, and constrained spatial state space. Our algorithm combines the ...

Python code that performs that Feynman path integral for a specified potential. Demonstrated by approximating the average energy of the quantum harmonic oscillator for various temperatures.

1 School of Mathematical Sciences, Guizhou Normal University, Guiyang, China. 2 School of Mathematical Sciences, Xiamen University, Xiamen, China. This paper mainly talks about a popular approach of ...