課程資訊
課程名稱
 計算物理
Computational Physics 
開課學期
 106-1 
授課對象
 理學院  物理學研究所  
授課教師
 趙挺偉 
課號
 Phys7030 
課程識別碼
 222EM2710 
班次
  
學分
 3.0 
全/半年
 半年 
必/選修
 選修 
上課時間
 星期四2,3,4(9:10~12:10) 
上課地點
 新物517 
備註
 本課程以英語授課。
總人數上限：30人 
Ceiba 課程網頁
 http://ceiba.ntu.edu.tw/1061Phys7030_CP 
課程簡介影片
 
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課程概述

Computer simulations have become an integral part of contemporary basic and applied physics, and have been serving as a bridge between
theoretical and experimental physics. This course introduces computational
methods for solving problems in physical sciences whose complexity or
difficulty places them beyond analytic solution or human endurance. 

課程目標
 Fundamental programming techniques in C and FORTRAN;
Basic Mathematical Operations;
Integration and Differentiation;
System of Linear Equations;
Matrix Operations;
Differential and Integral Equations;
Probability and Statistics;
Monte Carlo Methods: from Ising model to Lattice QCD;
Partial Differential Equations. 
課程要求
  
預期每週課後學習時數
  
Office Hours
 每週四 14:20~16:20 
指定閱讀
  
參考書目
 J. Thijssen, ``Computational Physics", 2nd Ed.,
Cambridge (2007).

H. Gould, J. Tobochnik, W. Christian,
``An introduction to computer simulation methods", 3rd Ed.,
Addison-Wesley (2007)

R. Landau and M. Paez Mejia ``Computational Physics:
Problem Solving with Computers", John Wiley (1997).

P. DeVries, ``A First Course in Computational Physics",
John Wiley (1994).

Press, W.H., et. al., ``Numerical Recipes,
The Art of Scientific Computing", Cambridge (1992).

T. Degrand, C. DeTar,
``Lattice Methods for Quantum Chromodynamics", World
Scientific (2006).

H. Rothe, ``Lattice Gauge Theories, An Introduction",
3rd Ed., World Scientific (2005)

I. Montvay, G. Munster, ``Quantum Fields on a Lattice",
Cambridge (1994). 
評量方式
(僅供參考)
  
No.
項目
百分比
說明
1. 
 Homework Assignment 
80% 
  
2. 
 Term Project  
20% 
  
 
課程進度
週次
日期
單元主題
Week 1
 2017/09/14  Overview of computational physics.
Fundamental programming techniques in C and FORTRAN.
Basic Mathematical Operations.
Differentiation.
Integration. 
Week 2
 2017/09/21  Numerical Integration,
Introduction to Monte Carlo Simulation 
Week 3
 2017/09/28  Metropolis Algorithm,
Heat Bath Algorithm,
Error Estimate in Monte Carlo Simulation 
Week 4
 2017/10/05  Monte Carlo Simulation of Spin Models 
Week 5
 2017/10/12  Single Cluster Algorithm,
Pseudo-Random Number Generators 
Week 6
 2017/10/19  System of linear equations,
LU decomposition. 
Week 7
 2017/10/26  Iterative algorithms for linear system,
Conjugate Gradient (CG) algorithm  
Week 8
 2017/11/02  More discussions on the error estimation for Monte Carlo simulation;
LU decomposition,
Conjugate Gradient
 
Week 9
 2017/11/09  Conjugate Gradient with Mixed-Precision,
Ordinary Differential Equation  
Week 10
 2017/11/16  Partial Differential Equations,
Wave Equation,
Heat Diffusion,
Laplace Equation,
Successive Over-Relaxation,
Solving Poisson Equation with CG.  
Week 11
 2017/11/23  Introduction to Quantum Field Theory,
Path Integral Formulation of QFT,
Scalar Field 
Week 12
 2017/11/30  Hybrid Monte Carlo simulation,
Scalar field in one-dimension 
Week 13
 2017/12/07  Animation with OpenGL 
Week 14
 2017/12/14  Introduction to Dirac Fermion Field 
Week 15
 2017/12/21  Lattice Dirac Fermion,
Error Estimate by Jackknife with Binning 
Week 16
 2017/12/28  Monte Carlo Simulation of Lattice Fermion,
Introduction to QCD  
Week 17
 2018/01/05  Hybrid Monte Carlo Simulation of QCD,
Introduction to GPU computation,
Introduction to CUDA