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Computer Simulation in Physics and Engineering

:	Martin Oliver Steinhauser
:	Computer Simulation in Physics and Engineering
:	Walter de Gruyter GmbH& Co.KG
:	9783110256062
:	1
:	CHF 180.80
:

:	Physik, Astronomie
:	English

:	529
:	Wasserzeichen
:	PC/MAC/eReader/Tablet
:	PDF

< >This work is a needed reference for widely used techniques and methods of computer simulation in physics and other disciplines, such as materials science. The work conveys both: the theoretical foundations of computer simulation as well as applications and 'tricks of the trade', that often are scattered across various papers. Thus it will meet a need and fill a gap for every scientist who needs computer simulations for his/her task at hand. In addition to being a reference, case studies and exercises for use as course reading are included.

< >Martin Oliver Steinhauser, Fraunhofer-Institute for High-Speed Dynamics, Ernst-Mach-Institute, EMI, Freiburg, Germany.

	Preface	5
	1 Introduction to computer simulation	21
	1.1 Physics and computational physics	21
	1.2 Choice of programming language	25
	1.3 Outfitting your PC for scientific computing	33
	1.4 History of computing in a nutshell	37
	1.5 Number representation: bits and bytes in computer memory	42
	1.5.1 Addition and subtraction of dual integer numbers	44
	1.5.2 Basic data types	49
	1.6 The role of algorithms in scientific computing	61
	1.6.1 Efficient and inefficient calculations	63
	1.6.2 Asymptotic analysis of algorithms	71
	1.6.3 Merge sort and divide-and-conquer	76
	1.7 Theory, modeling and computer simulation	79
	1.7.1 What is a theory?	79
	1.7.2 What is a model?	87
	1.7.3 Model systems: particles or fields?	92
	1.7.4 The linear chain as a model system	94
	1.7.5 From modeling to computer simulation	98
	1.8 Exercises	101
	1.8.1 Addition of bit patterns of 1 byte duals	101
	1.8.2 Subtracting dual numbers using two’s complement	101
	1.8.3 Comparison of running times	101
	1.8.4 Asymptotic notation	102
	1.9 Chapter literature	103
	2 Scientific Computing in C	104
	2.1 Introduction	104
	2.1.1 Basics of a UNIX/Linux programming environment	107
	2.2 First steps in C	119
	2.2.1 Variables in C	121
	2.2.2 Global variables	123
	2.2.3 Operators in C	124
	2.2.4 Control structures	128
	2.2.5 Scientific “Hello world!”	131
	2.2.6 Streams - input/output functionality	136
	2.2.7 The preprocessor and symbolic constants	139
	2.2.8 The function scanf()	142
	2.3 Programming examples of rounding errors and loss of precision	145
	2.3.1 Algorithms for calculating e-x	150
	2.3.2 Algorithm for summing 1/n	153
	2.4 Details on C-Arrays	157
	2.4.1 Direct initialization of certain array elements (C99)	161
	2.4.2 Arrays with variable length (C99)	161
	2.4.3 Arrays as function parameters	162
	2.4.4 Pointers	164
	2.4.5 Pointers as function parameters	172
	2.4.6 Pointers to functions as function parameters	174
	2.4.7 Strings	179
	2.5 Structures and their representation in computer memory	181
	2.5.1 Blending structs and arrays	183
	2.6 Numerical differentiation and integration	185
	2.6.1 Numerical differentiation	186
	2.6.2 Case study: the second derivative of ex	189
	2.6.3 Numerical integration	196
	2.7 Remarks on programming and software engineering	201
	2.7.1 Good software development practices	201
	2.7.2 Reduction of complexity	204
	2.7.3 Designing a program	208
	2.7.4 Readability of a program	209
	2.7.5 Focus your attention by using conventions	210
	2.8 Ways to improve your programs	211
	2.9 Exercises	213
	2.9.1 Questions	213
	2.9.2 Errors in programs	214
	2.9.3 printf()-statement	217
	2.9.4 Assignments	218
	2.9.5 Loops	219
	2.9.6 Recurrence	219
	2.9.7 Macros	220
	2.9.8 Strings	220
	2.9.9 Structs	221
	2.10 Projects	223
	2.10.1 Decimal and binary representation	223
	2.10.2 Nearest machine number	223
	2.10.3 Calculating e -x	223
	2.10.4 Loss of precision	224
	2.10.5 Summing series	224
	2.10.6 Recurrence in orthogonal functions	225
	2.10.7 The Towers of Hanoi	225
	2.10.8 Spherical harmonics and Legendre polynomials	227
	2.10.9 Memory diagram of a battle	228
	2.10.10 Computing derivatives numerically	228
	2.11 Chapter literature	230
	3 Fundamentals of statistical physics	231
	3.1 Introduction and basic ideas	232
	3.1.1 The macrostate	236
	3.1.2 The microstate	238
	3.1.3 Information conservation in statistical physics	239
	3.1.4 Equations of motion in classical mechanics	245
	3.1.5 Statistical physics in phase space	249
	3.2 Elementary statistics	255
	3.2.1 Random Walk	256
	3.2.2 Discrete and continuous probability distributions	261
	3.2.3 Reduced probability distributions	262
	3.2.4 Important distributions in physics and engineering	264
	3.3 Equilibrium distribution	269
	3.3.1 The most probable distribution	271
	3.3.2 A statistical definition of temperature	273
	3.3.3 The Boltzmann distribution and the partition function	275
	3.4 The canonical ensemble	278
	3.5 Exercises	281
	3.5.1 Trajectories of the one-dimensional harmonic oscillator in phase space	281
	3.5.2 Important integrals of statistical physics	281
	3.5.3 Probability, e