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
mechanics
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
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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
招生计划
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。
教学计划
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
附件
院内合影
