Summer Short Course on Monte Carlo methods and Applications


Dates: June 27 - July 2, 2016

Place: Conference room  I, 1st floor, CSRC Building

Objective: To provide a balanced course for graduate students new to MC methods on the basic techniques and current states of MC methods and applications for classical and quantum systems of high dimensions.

Organizer: Wei Cai (CSRC), Michael Mascagni (FSU), Wenjian Yu (Tsinghua)

Day 1: Basic MC Techniques lectures

            Lecturer: Prof. Wenjian Yu, Tsinghua University

            Basic idea of pseudo-random number * algorithms for generating uniform-

            distribution random number * algorithms for generating Gaussian-distribution

            random number * rand/randn in Matlab

            Lecturer: Prof. Dan Hu, Shanghai Jian Tong University

            Basic MC Integration * Random sampling with inverse method, rejection

            method * Reduction of variance, importance sampling * MC and statistical


Day 2-3: Metropolis–Hastings algorithm, MC in ensembles and methods of accelerated samplings

             Lecturer: Prof. Andrij Baumketner,  Ukraine Academy of Science

 Introduction to mathematical modeling of physical systems by particles   *

 heoretical formalism: energy function, Hamiltonian. Basics of stat mechanics

 (distributions) * MC as a simulation method. Metropolis sampling. Detailed

 balance.* Setting up a simulation: boundary conditions *  MC * simulations in

 various ensembles Canonical/ Microcanonical/sobaric-Isothermal/ Grand-

 Canonical * The Gibbs Ensemble * Problem of phase transitions *  MC simulations
 Methods of accelerated simulations for various systems in physics and

 chemistry * The extended ensemble idea * Algorithms for enhanced sampling

 *  Multicanonical *Tsallis * Wang-Landau * J-walking *Simulated tempering*

 Parallel tempering of Replica Exchange* Examples of applications

 Lecturer: Prof. Wei Cai ,  Stanford University

 Conventional methods for finding energy barrier * umbrella sampling for

 Computing free energy barrier at finite temperature.

             Lecturer:  Prof. Yuan Yao,  Peking University 

             A Dynamic Approach to Sparse Recovery in High Dimensional Statistics

Day 4: MC for carrier transport in semiconductors

             Lecturer: Prof. Gang Du, Peking University

 Basic theories of carrier transport simulation in semiconductor device by using

 Monte Carlo method * Fundamentals of charge transports in semiconductors *

 Monte Carlo simulation

 Monte Carlo method for nanoscale MOSFETs simulation * Review of

 nanoscale MOSFETs * Quantum effect simulation *Applications


             MC for Neutron transport

             Lecturer: Prof. Li Deng, Institute of Applied Physics and Computational Mathematics

 The Algorithms and Applications of the Independent Monte Carlo Particle

 Transport Software JMCT                 

Day 5: Quantum Monte Carlo methods

            Lecturer: Prof. Hai-Qing Lin, Beijing Computational Science Research

            Quantum Monte Carlo Simulation of Many-Body Systems

            Lecturer: Prof. David Ceperley, University of Illinois at Urbana

            Path Integral Monte Carlo (introduction) *How quantum statistics of particles

(bosons and fermions) enter into PIMC *Variational Monte Carlo for ground

state properties *Projector Monte Carlo.

Day 6: MC for other applications in 1 hour-research talks     

            Lecturer: Prof. David Ceperley, University of Illinois at Urbana

            Lecturer:  Prof. Michael Mascagni,  Florida State University 

            MC for solving PDEs

            Lecturer: Prof. Jinqiao Duan,  Illinois Institute of Technology

           Deterministic & Numerical Methods for Stochastic Dynamics

All participant group photo




1. 招生规模为60~80人。

2. 实行学生自由申请制。

3. 在读研究生或青年学者均具有申请资格,同时亦接受少量优秀的本科三、四年级学生。

4. 申报时间:即日至2016年6月20日

5. 申报者的入选资格由委员会审定,并及时通知申请者。


1. 教学时间:2016年6月27--7月2日

2. 授课地点:北京计算科学研究中心三层第二会议室

   地        址:北京市海淀区东北旺西路10号,中关村软件园二期


  1. 院内合影



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