COS 504: Simulations for Physical Systems
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Course Title |
Simulations for Physical Systems |
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Course Code |
COS 504 |
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Course Type |
Elective |
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Level |
PhD |
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Instructor’s Name |
Assoc. Prof. Giannis Koutsou (Lead Instructor), Dr. Simone Bachhio Prof. Constantia Alexandrou
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ECTS |
5 |
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Lectures / week |
2 (90 min. each) 4.5 weeks |
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Laboratories / week |
2 (90 min. each) 2.5 weeks |
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Course Purpose and Objectives |
The course aims at teaching students to apply high-performance computing and data analysis approaches to solve complex physical systems. Students will learn to handle a range of applications from condensed matter and biophysics to particle and nuclear physics. |
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Learning Outcomes |
Students will: - learn to describe and analyze non-linear systems and systems with many degrees of freedoms
- develop algorithms, optimize and implement them on large computers
- learn state-of-the-art simulations approaches such as Markov Chain Monte Carlo
- study phase transitions and critical behavior using simulations and deep learning approaches
- implement crowd simulation such as particle and agent based models for a range of self-organized dynamics of structures
- use a range of data analysis methods such as jackknife and bootstrap resampling, Bayesian statistical analysis,
- aquire a set of the High Performance Computing and data analysis skills and employ them for solving physical systems. These skills are applicable to a range of problems in chemistry, biology and engineering.
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Prerequisites |
None |
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Background Requirements |
Knowledge of a low-level programming languages such as Fortran, C, C++ and parallel programing including MPI |
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Course Content |
Week 1-2
Numerical solution of partial differential equations, such as the wave, diffusion and Schrödinger’s equations
Week 3 Introduction to minimization algorithms
Week 4 Data analysis of correlated data sets, resampling and Bayesian approaches
Week 5-6 Phase transitions in physical systems, critical behaviour, identification using deep learning methods
Week 7 Markov processes and Monte Carlo methods for many body systems
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Teaching Methodology |
- 9 x 1.5 h lectures |
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Bibliography |
- Course notes
- Monte Carlo Methods, Malvin H. Kalos and Paula A. Whitlock
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Assessment |
The following assessment methods will be combined for the final grade:
- Coursework
- A final project |
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Language |
English |
