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Basic concepts in computational physics / Benjamin A. Stickler and Ewald Schachinger.

By: Contributor(s): Material type: TextTextPublication details: Switzerland : Springer, 2014.Description: xvii, 377 p. : illustrations ; 25 cmISBN:
  • 9783319024349
Subject(s): DDC classification:
  • 530.1 23 St854
Contents:
1. Some basic remarks-- 2. Numerical differentiation -- 3. Numerical integration -- 4. The Kepler problem -- 5. Ordinary differential equations : initial value problems -- 6. The double pendulum -- 7. Molecular dynamics -- 8. Numerics of ordinary differential equations : boundary value problems -- 9. The one-dimensional stationary heat equation -- 10. The one-dimensional stationary Schrödinger equation -- 11.Partial differential equations -- 12.Pseudo random number generators -- 13.Random sampling methods-- 14. A Brief Introduction to Monte-Carlo Methods -- 15. The ISING Model -- 16. Some Basics of Stochastic Processes -- 17. The Random Walk and Diffusion Theory -- 18. MARKOV-Chain Monte Carlo and the POTTS Model -- 19. Data Analysis -- 20. Stochastic Optimization-- Appendices-- Index.
Summary: This book is divided into two main parts: Deterministic methods and stochastic methods. Based on concrete problems, the first part discusses numerical differentiation and integration, and the treatment of ordinary differential equations. This is augmented by notes on the numerics of partial differential equations. The second part discusses the generation of random numbers, summarizes the basics of stochastics which is then followed by the introduction of various Monte-Carlo (MC) methods. Specific emphasis is on MARKOV chain MC algorithms. All this is again augmented by numerous applications from physics. The final two chapters on Data Analysis and Stochastic Optimization share the two main topics as a common denominator. The book offers a number of appendices to provide the reader with more detailed information on various topics discussed in the main part. Nevertheless, the reader should be familiar with the most important concepts of statistics and probability theory albeit two appendices have been dedicated to provide a rudimentary discussion.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 530.1 St854 (Browse shelf(Opens below)) Available 136358
Total holds: 0

Includes bibliographical references and index.

1. Some basic remarks--
2. Numerical differentiation --
3. Numerical integration --
4. The Kepler problem --
5. Ordinary differential equations : initial value problems --
6. The double pendulum --
7. Molecular dynamics --
8. Numerics of ordinary differential equations : boundary value problems --
9. The one-dimensional stationary heat equation --
10. The one-dimensional stationary Schrödinger equation --
11.Partial differential equations --
12.Pseudo random number generators --
13.Random sampling methods--
14. A Brief Introduction to Monte-Carlo Methods --
15. The ISING Model --
16. Some Basics of Stochastic Processes --
17. The Random Walk and Diffusion Theory --
18. MARKOV-Chain Monte Carlo and the POTTS Model --
19. Data Analysis --
20. Stochastic Optimization--
Appendices--
Index.

This book is divided into two main parts: Deterministic methods and stochastic methods. Based on concrete problems, the first part discusses numerical differentiation and integration, and the treatment of ordinary differential equations. This is augmented by notes on the numerics of partial differential equations. The second part discusses the generation of random numbers, summarizes the basics of stochastics which is then followed by the introduction of various Monte-Carlo (MC) methods. Specific emphasis is on MARKOV chain MC algorithms. All this is again augmented by numerous applications from physics. The final two chapters on Data Analysis and Stochastic Optimization share the two main topics as a common denominator. The book offers a number of appendices to provide the reader with more detailed information on various topics discussed in the main part. Nevertheless, the reader should be familiar with the most important concepts of statistics and probability theory albeit two appendices have been dedicated to provide a rudimentary discussion.

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