Note on Monte Carlo methods without necessary detailed balance

Simple criteria for convergence of Monte Carlo algorithms not necessarily requiring detailed balance for any specified transition probability are derived and it is shown that it is possible to view the algorithm as a superimposition of a Brownian motion on configurational space coupled to the transition probabilities. As such, the error contributions due to a particular Monte Carlo algorithm and the integration limits in configuration space must be distinguished from those due to the nonuniform sampling of the Brownian motion, and criteria related to the number of steps required to distinguish these errors are provided for the simplest cases involving one dimension and symmetrical probability distributions.     

Quantum Monte Carlo Study of Frustrated Spin Chain under External Field

In this paper a stochastic series expansion quantum Monte Carlo algorithm is used to study a frustrated spin chain with diagonal next-nearest-neighbor interactions. The detailed balance conditions are carefully analyzed to improve the efficiency of simulation process. As an application of this algothrim, the total magnetization, the static structure factor and spin-stiffness are calculated for a certain set of system parameters as a function of external field strength.     

Quantum Monte Carlo Study of Frustrated Spin Chain Under External Field

In this paper a stochastic series expansion quantum Monte Carlo algorithm is used to study a frustrated spin chain with diagonal next-nearest-neighbor interactions. The detailed balance conditions are carefully analyzed to improve the efficiency of simulation process. As an application of this algothrim, the total magnetization, the static structure factor and spin-stiffness arecalculated for a certain set of system parameters as a function of external field strength.     

Effective model for rare-earth Kitaev materials and its classical Monte Carlo simulation

Recently, the family of rare-earth chalcohalides were proposed as candidate compounds to realize the Kitaev spin liquid (KSL) [Chin. Phys. Lett. 38 047502 (2021)]. In the present work, we firstly propose an effective spin Hamiltonian consistent with the symmetry group of the crystal structure. Then we apply classical Monte Carlo simulations to preliminarily study the model and establish a phase diagram. When approaching to the low temperature limit, several magnetic long range orders are observed, including the stripe, the zigzag, the antiferromagnetic (AFM), the ferromagnetic (FM), the incommensurate spiral (IS), the multi-Q, and the 120° ones. We further calculate the thermodynamic properties of the system, such as the temperature dependence of the magnetic susceptibility and the heat capacity. The ordering transition temperatures reflected in the two quantities agree with each other. For most interaction regions, the system is magnetically more susceptible in the ab-plane than in the c-direction. The stripe phase is special, where the susceptibility is fairly isotropic in the whole temperature region. These features provide useful information to understand the magnetic properties of related materials.     

Hierarchical Monte Carlo methods for fractal random fields

Two hierarchical Monte Carlo methods for the generation of self-similar fractal random fields are compared and contrasted. The first technique, successive random addition (SRA), is currently popular in the physics community. Despite the intuitive appeal of SRA, rigorous mathematical reasoning reveals that SRA cannot be consistent with any stationary power-law Gaussian random field for any Hurst exponent; furthermore, there is an inherent ratio of largest to smallest putative scaling constant necessarily exceeding a factor of 2 for a wide range of Hurst exponentsH, with 0.30<H<0.85. Thus, SRA is inconsistent with a stationary power-law fractal random field and would not be useful for problems that do not utilize additional spatial averaging of the velocity field. The second hierarchical method for fractal random fields has recently been introduced by two of the authors and relies on a suitable explicit multiwavelet expansion (MWE) with high-moment cancellation. This method is described briefly, including a demonstration that, unlike SRA, MWE is consistent with a stationary power-law random field over many decades of scaling and has low variance.     

Solving quantum rotor model with different Monte Carlo techniques

We systematically test the performance of several Monte Carlo update schemes for the (2+1)d XY phase transition of quantum rotor model. By comparing the local Metropolis (LM), LM plus over-relaxation (OR), Wolff-cluster (WC), hybrid Monte Carlo (HM), hybrid Monte Carlo with Fourier acceleration (FA) schemes, it is clear that among the five different update schemes, at the quantum critical point, the WC and FA schemes acquire the smallest autocorrelation time and cost the least amount of CPU hours in achieving the same level of relative error, and FA enjoys a further advantage of easily implementable for more complicated interactions such as the long-range ones. These results bestow one with the necessary knowledge of extending the quantum rotor model, which plays the role of ferromagnetic/antiferromagnetic critical bosons or Z₂ topological order, to more realistic and yet challenging models such as Fermi surface Yukawa-coupled to quantum rotor models.     

Monte Carlo Hamiltonian: Linear Potentials

We further study the validity of the Monte Carlo Hamiltonian method. The advantage of the method,in comparison with the standard Monte Carlo Lagrangian approach, is its capability to study the excited states. Weconsider two quantum mechanical models: a symmetric one V(x) = |x|/2; and an asymmetric one V(x) = ∞, forx ＜ 0 and V(x) = x, for x ≥ 0. The results for the spectrum, wave functions and thermodynamical observables are inagreement with the analytical or Runge-Kutta calculations.     

Monte Carlo Hamiltonian:Inverse Potential

The Monte Carlo Hamiltonian method developed recently allows to investigate the ground state and low-lying excited states of a quantum system, using Monte Carlo (MC) algorithm with importance sampling. However, conventional MC algorithm has some difficulties when applied to inverse potentials. We propose to use effective potential and extrapolation method to solve the problem. We present examples from the hydrogen system.     

Monte Carlo study of the critical behavior of pure and site-diluted Ising ferro-and ferrimagnets

Monte Carlo simulations are performed for pure and site-diluted Ising ferro- and ferrimagnets on a simple cubic lattice with up to 40³ sites and with impurity concentrationx. For the diluted ferromagnet (x=0.2) the exponent= 0.392±0.03 is definitely larger than the pure model value of=0.304±0.03. In contrast, for ferrimagnetic systems (x=0, 0.1, 0.2) the values appear to be independent ofx and within the error limits consistent with the value for the pure ferromagnet, possibly because the width of the asymptotic random critical regime (or of the crossover regime) is even smaller than in the case of ferromagnets.     

Quiet Monte Carlo radiation transport

We model radiation transport by advancing computational photons through phase space with solutions to a set of stochastic differential equations of motion. Random numbers that appear in the equations of motion are sampled with deterministically chosen Gaussian quadrature weights and abscissas. In this way, the advantages of particle Monte Carlo are realized without generating statistical noise. We demonstrate this technique by performing one- and two-dimensional test problems in which gray radiation is energetically coupled to stationary material. Scattering is accomplished with a Fokker-Planck scattering operator. Free streaming, diffusion and Marshak waves are recovered in appropriate limits.     

Configuration Path Integral Monte Carlo

A novel path integral Monte Carlo (PIMC) approach for correlated many‐particle systems with arbitrary pair interaction in continuous space at low temperatures is presented. It is based on a representation of the N ‐particle density operator in a basis of (anti‐)symmetrized N ‐particle states (configurations of occupation numbers). The path integral is transformed into a sum over trajectories with the same topology and, finally, the limit of M → ∞, where M is the number of high‐temperature factors, is analytically performed. This yields exact expressions for the thermodynamic quantities and allows to perform efficient simulations for fermions at low temperature and weak to moderate coupling. Our method is expected to be applicable to dense quantum plasmas in the regime of strong degeneracy where conventional PIMC fails due to the fermion sign problem (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

The Convergence of Markov Chain Monte Carlo Methods: From the Metropolis Method to Hamiltonian Monte Carlo

From its inception in the 1950s to the modern frontiers of applied statistics, Markov chain Monte Carlo has been one of the most ubiquitous and successful methods in statistical computing. The development of the method in that time has been fueled by not only increasingly difficult problems but also novel techniques adopted from physics. Here, the history of Markov chain Monte Carlo is reviewed from its inception with the Metropolis method to the contemporary state‐of‐the‐art in Hamiltonian Monte Carlo, focusing on the evolving interplay between the statistical and physical perspectives of the method.     

一维亚铁磁混合自旋链的磁特性的Monte Carlo模拟

基于一维自旋链模型,采用Monte Carlo方法对具有反铁磁相互作用的自旋一I和自旋-3／2交替混合的亚铁磁系统进行模拟计算,研究单离子各向异性对系统磁特性的影响．模拟结果发现：基态时系统的磁化强度在外加磁场作用下呈现出阶梯状,并获得了自旋-1和自旋-3／2交替混合的亚铁磁系统相图．最后,通过对系统能量和自旋组态的研究,解释了该系统中出现的阶梯效应和相图．     

Monte Carlo methods in radiative transfer and electron-beam processing

Monte Carlo methods (MCMs) are the most versatile approaches in solving the integro-differential equations. They are statistical in nature and can be easily adapted for simulation of the propagation of ensembles of quantum particles within absorbing, emitting, and scattering media. In this paper, we use MCM for the solution of the Boltzmann transport equation, which is the governing equation for both radiative transfer and electron-beam processing. We briefly outline the methodology for the solution of MCMs, and discuss the similarities and differences between the two different application areas. The focus of this paper is primarily on the treatment of different scattering phase functions.     

Permutation blocking path integral Monte Carlo simulations of degenerate electrons at finite temperature

We analyse the simulation of strongly degenerate electrons at finite temperature using the recently introduced permutation blocking path integral Monte Carlo (PB‐PIMC) method [T. Dornheim et al., New J. Phys. 17 , 073017 (2015)]. As a representative example, we consider electrons in a harmonic confinement and carry out simulations for up to P = 2000 so‐called imaginary‐time propagators – an important convergence parameter within the PIMC formalism. This allows us to study the P‐dependence of different observables of the configuration space in the Monte Carlo simulations and of the fermion sign problem. We find a surprisingly persisting effect of the permutation blocking for large P, which is explained by comparing different length scales. Finally, we touch upon the uniform electron gas in the warm dense matter regime.     

Monte Carlo方法在B样条函数分频理论中的应用

针对弹道参数的B样条表示问题,运用Monte Carlo方法对B样条函数分频理论进行仿真论证,得到B样条延拓节点的补充方法,并验证B样条函数逼近空间相容性定理的正确性.比较Monte Carlo方法和B样条分频算法的计算结果,说明分频算法合理.将该算法应用于外弹道跟踪测量数据的处理中,可以确定出表示弹道所需要的样条节点个数及样条节点序列的排布,有效减少待估参数个数.     

Random walk on distant mesh points Monte Carlo methods

A new technique for obtaining Monte Carlo algorithms based on the Markov chains with a finite number of states is suggested. Instead of the classical random walk on neighboring mesh points, a general way of constructing Monte Carlo algorithms that could be called random walk on distant mesh points is considered. It is applied to solve boundary value problems. The numerical examples indicate that the new methods are less laborious and therefore more efficient.In conclusion, we mention that all Monte Carlo algorithms are parallel and could be easily realized on parallel computers.     

热辐射输运问题的高效蒙特卡罗模拟方法

惯性约束聚变研究中,热辐射光子在介质中的输运以及热辐射光子与介质的相互作用是重要研究课题,蒙特卡罗方法是该类问题的重要研究手段之一.隐式蒙特卡罗方法虽然能正确地模拟热辐射在介质中的输运过程,但当模拟重介质(材料的吸收系数大)问题时,该方法花费的计算时间将变得很长,导致模拟效率很低.本文以离散扩散蒙特卡罗方法为基础,开发了"离散扩散蒙特卡罗方法辐射输运模拟程序",可以较好地解决重介质区的计算效率问题,但是离散扩散蒙卡罗方法在模拟轻介质区时精度不够高.辐射输运问题中通常既有轻介质也有重介质,为了能同时解决蒙特卡罗方法模拟的效率和精度问题,本文研究了离散扩散蒙特卡罗方法与隐式蒙特卡罗方法相结合的模拟方法,并提出了新的扩散区与输运区界面处理方法,研制了混合蒙特卡罗方法的辐射输运模拟程序.典型辐射输运问题模拟显示:在模拟重介质问题时,该程序能大幅缩短模拟时间,且能取得与隐式蒙特卡罗方法一致的结果;在模拟轻重介质均存在的问题时,与隐式蒙特卡罗方法相比,混合蒙特卡罗方法的模拟精度与其相当且计算效率同样能够得到显著提升.