© 2020

Molecular Dynamics Simulations in Statistical Physics: Theory and Applications


  • Introduces the basics multi-particle system dynamics, expounding the practical techniques and the implementation of the molecular dynamics

  • Describes the connection between the molecular dynamics and the information theory

  • Discusses the Bootstrapping Swarm Artificial Neural Network, an improved version of the artificial neural network


Part of the Scientific Computation book series (SCIENTCOMP)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Hiqmet Kamberaj
    Pages 1-55
  3. Hiqmet Kamberaj
    Pages 57-92
  4. Hiqmet Kamberaj
    Pages 93-116
  5. Hiqmet Kamberaj
    Pages 117-135
  6. Hiqmet Kamberaj
    Pages 281-312
  7. Hiqmet Kamberaj
    Pages 343-369
  8. Hiqmet Kamberaj
    Pages 397-422
  9. Hiqmet Kamberaj
    Pages 423-439
  10. Back Matter
    Pages 441-463

About this book


This book presents computer simulations using molecular dynamics techniques in statistical physics, with a focus on macromolecular systems. The numerical methods are introduced in the form of computer algorithms and can be implemented in computers using any desired computer programming language, such as Fortran 90, C/C++, and others. The book also explains how some of these numerical methods and their algorithms can be implemented in the existing computer programming software of macromolecular systems, such as the CHARMM program.

In addition, it examines a number of advanced concepts of computer simulation techniques used in statistical physics as well as biological and physical systems. Discussing the molecular dynamics approach in detail to enhance readers understanding of the use of this method in statistical physics problems, it also describes the equations of motion in various statistical ensembles to mimic real-world experimental conditions. 

Intended for graduate students and research scientists working in the field of theoretical and computational biophysics, physics and chemistry, the book can also be used by postgraduate students of other disciplines, such as applied mathematics, computer sciences, and bioinformatics. Further, offering insights into fundamental theory, it as a valuable resource for expert practitioners and programmers and those new to the field. 


Molecular Dynamics Techniques Information Theory Statistical Thermodynamics Liouville's formalism Trotter factorization scheme Swam Particle Intelligence Topological Data Analysis Effective Models for generation of model interaction potential

Authors and affiliations

  1. 1.Computer Engineering, International Balkan University, Skopje, Republic of North Macedonia, Advanced Computing Research CenterUniversity of New York TiranaTiranaAlbania

About the authors

Hiqmet Kamberaj is an Associate Professor at International Balkan University (Skopje, R. of North Macedonia) and Associate Professor at the University of New York Tirana (Tirana, Albania). He also was the Dean of the Faculty of Engineering at International Balkan University from January 2017 to September 2019. Hiqmet completed his Ph.D. (in Computational Physics) in 2005 from Manchester Metropolitan University and Post-Doctoral studies from University of Minnesota, Arizona State University and National Institute of Nanotechnology at University of Edmonton. He received his Bachelor of Science (in Physics) in 1996 from the University of Tirana and his Master of Science (in Physics) from the University of Siegen in 2000.

Hiqmet has published around 20 articles and book chapters in reputed journals and has been serving as editor-in-chief, editorial board member and ad-hoc reviewer of repute. His articles focus on understanding the structure, dynamics, and thermodynamics of macromolecular systems using the laws of physics and biochemistry, and applied mathematics.

Hiqmet loves teaching and preparing lecture notes for his students. He especially enjoys preparing resumes for his students who are taking the first steps of their careers.

Bibliographic information

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