Syllabus

1. Information regarding the programme
1.1 Higher education institution	Babeş Bolyai University	
1.2 Faculty	Faculty of Mathematics and Computer Science	
1.3 Department	Department of Computer Science	
1.4  Field of Study	Computer Science	
1.5 Study Cycle	Master	
1.6 Study Programme/Qualifications	High Performance Computing  and Big Data Analytics	

2. Information regarding the discipline
2.1 Name of the discipline	Stochastic Simulation Methods with Interdisciplinary Applications	
2.2 Course coordinator	Prof. Dr. Zoltán Néda	
2.3 Seminar coordinator		
2.4 Laboratory coordinator	Prof. Dr. Zoltán Néda	
2.5 year of study	2	2.6 semester	4	2.7  Type of evaluation	E	2.8 Type of Discipline	Opt.	

3. Timpul total estimat (ore pe semestru al activităţilor didactice)
3.1 Hours per week		Of which:	
3.2 course	3	3.3 seminar		3.4 laboratory	2	
3.5 Total hours in the curriculum		Din care:	
3.6 course		3.7 seminar		3.8 laboratory		
Time allotment:	ore	
Learning using manual, course support, bibliography, course notes	42	
Additional documentation (in libraries, on electronic platforms, field documentation)	14	
Preparation for seminars/labs, homework, papers, portfolios and essays	42	
Tutorship	3	
Evaluations	4	
Other activities: 	– 	
3.9 Total individual study hours	105	
3.10 Total hours per semester	161	
3.11 Number of ECTS credits	7	

4. Prerequisities
4.1 curriculum	Statistical Physics, C Programming, Elements of Probability Theory and Mathematical Statistics 	
4.2 competencies	Logical thinking, interdisciplinay thinking, communication abilities in English, active participation at the courses and laboratories  	

5. Conditions
5.1 for the course	  Video projector, blackboard	
5.2 for the seminars	 	
5.3 for lab activities	 Computers with Linux operating system, Vidoe projector	

6. Specific competencies acquired 
Professional	C1. Capacities for analyzing and synthetizing physical data, capacities for modelling complex phenomena 

C2. Working and mastering with software packages for analyzing and processing experimental data. Using C , Python and Mathematica software for modelling complex phenomena. Capacities for using information technologies in describing complex phenomena from physics, biology, chemistry and social sciences. Advanced programming techniques.

C3. Trans- and Interdisciplinary thinking.

C4. Planning and Performing computer experiments for validating physical models. Abilities for making high performance computations in physics. Capacieties for writing computer codes and running them on modern supercomputers.  

C5. Communicating efficiently modern scientific ideas. Presenting in a professional manner results of a research or scientific projects. Capacities for writing scientific publications, to interact and have a scientific debate with Editors and Referees. omunicarea ideilor științifice complexe, a concluziilor experimentelor sau a rezultatelor unui proiect științific. Capacities for arguing and defeneding scientific views and ideas.
	
Transversal	CT1. To deal with professional duties efficiently and in a responsible manner, keeping in mind the laws and scientific ethics. Being responsible for the published scientific results and taking all actions for their proper use.   

CT2.  Working in an Interdisciplinar environment respecting the professional hierarchy. Having initiative, new ideas and approaches to classical problems. Promoting the dialogue, cooperation and positive attitude in a group. Respecting multicultural environment and helping the others. 

CT3. Efficient use of information tehnology tools and presentation methods in English.  Learning and applying autoevaluation methods, f or keeping the professional training up to date, in agreement with the deminds of the market.   	

7. Objectives of the discipline
7.1 General objective of the discipline	- a rigorous introduction in MC simulation methods, oriented on interdisciplinary applications. 	
7.2 Specific objective of the discipline	- mastering stohastic simulation methods and physical modelling
- learning to approach modern problems in an interdisciplinary manner
- using classical models of physics in approaching interdisciplinary problems.
- advance programming in C and C++
- an introduction to scientific research	

8. Content
8.1 Course	Teaching methods	Observations	
Computer simulation techniques – an overview	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	-role of Monte Carlo (MC) simulations in physics
- Monte Carlo simulations versus Molecular Dynamics  (MD) methods
- the interdisciplinar applicability of the MC methods	
Examples of MC simulations	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	- detailed discussion of two examples of MC simulations: simple random walk, phase transition in a sociological system, 	
Random number generators	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	-generating uniformly distributed random numbers
-generating random numbers distributed according to an arbitrary distribution
-generating random numbers with a normal distribution
-testing the random number genrators	
Elements of Statistical Physics, Stochastic Processes and Critical Phenomena	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	- overview of basic thermodynamics, statistical physics, stochastic processes and critical phenomena knowledge, needed for the course	
Brownian dynamics	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	-Langevin equation
-implementing Brownian dyanimcs
-examples	
Monte Carlo integration	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	- straightforward sampling
-reducing the error: important sampling
-advantages of important sampling for high dimensional integrals	
The Ising model	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	-history of the Ising model
-phase transition in the Ising model
-exact solution in 1D
-mean-field solution 
-critical behavior
-known and unknown issues	
Metropolis and Glauber MC for the Ising model	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	-important sampling and Markov chains for statistical physics integrals
-detailed balance
-Metropolis method
-Glauber method
-application for the ising model	
The BKL or kinetic MC method	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	- problems with the Metropolis and Glauber methods
- noniform time-update
- grain-growth
- kinetic MC techniques and interdisciplinary applications	
Cluster MC methods	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	-crtitical slowing down 
-dynamic exponent
-Swendsen and Wang algorithm
-Wolf algorithm
	
The histogram MC method and the microcanonical MC method	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	-fluctuation of the energy and magnetization
-determining relevant quantities at different temperatures
- the demon algorithm
- determining the temperature of the microcanonical simulation	
Quantum Monte Carlo methods	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	-elements of quantum statistics
-quantum statistical models
-the Trotter-Suzuki transformation
-QMC method for 1D interacting fermions	
MC simulation of Frustrated Systems	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	-spin-glasses
-NP hard and NP complete problems
-simulated annealing
-extremal optimization
-other heuristic methods	
Interdisciplinary application of the MC methods	Problem formulation
Presentation
Demonstartations
Software packages
Discutions
Movies 	-applications in materials science, biophysics, economics, sociology and 
biology.	
Bibliography
1. Z. Neda : Stochastic simulations in physics with interdisciplinary applications,  http://www.phys.ubbcluj.ro/~zneda/edu/mc.htm
2. Z. Neda: Stochasztikus szimulacios modszerek a fizikaban (Erdelyi Tankonyvtanacs, 1998).  accesibil in numar mare la biblioteca Facultăţii de Fizică
3. H. Gould and J. Tobochnik Introduction to Computer Simulation Methods  and applications in physics (Addison-Wesley, 1996). Accesibil pentru studenţi pe pagina de web a cursului în format PDF.
4.A. MacKinnon: Computational Physics online course (http://b.sst.ph.ic.ac.uk/~angus/Lectures/compphys/compphys.html)
5.F. Bagnoli: Introduction to Cellular Automata (cond-mat/9810012; http:arxiv.org, 1998)
6.David Landau and Kurt Binder: A guide to Monte Carlo Simulations in Statistical 
      Physics,  Cambridge Univ. Press, 2004 (disponibil la titular curs)
	
8.3 Laboratory	Teaching methods	Observations	
-    Organization aspects
-   The C programming language, some basic facts
-   Linux operational system, some basic facts	Explanations
Presentations
Discussions
Problem formulation
Individual work
Programming

	[1] coresponding links	
-  research projects
  - scientific papers that will be discussed
  - computational study of the random walk	Explanations
Presentations
Discussions
Problem formulation
Individual work
Programming
	[1] coresponding links and programs in C
	
-    programming the projects and presentations
  - computational study of phase transition in a two-state interacting systems	Explanations
Presentations
Discussions
Problem formulation
Individual work
Programming
	[1] coresponding links and programs in C

- working of pseudo-random number generators 
 -testing the pseudo-random number generators	Explanations
Presentations
Discussions
Problem formulation
Individual work
Programming
	[1] coresponding links and programs in C

  - generating random numbers with non-uniform distribution
 - discussing novel scientific works related to Monte Carlo methods	Explanations
Presentations
Discussions
Problem formulation
Individual work
Programming
	[1] coresponding links and programs in C
	
- studying the Brownian dynamics
 - studying stohastic resonance with molecular dynamics
- discussing novel scientific works related to Monte Carlo methods	Explanations
Presentations
Discussions
Problem formulation
Individual work
Programming
	[1] coresponding links and programs in C

- The Monte Carlo integration with straightforward  and important sampling
- calculating the number PI with MC methods. 
- individual discussions with the students on their chosen research projects.	Explanations
Presentations
Discussions
Problem formulation
Individual work
Programming
	[1] coresponding links and programs in C

  - computational study of the 2D and 3D Ising model.
- discussing novel scientific works related to Monte Carlo methods
- individual discussions with the students on their chosen research projects.	Explanations
Presentations
Discussions
Problem formulation
Individual work
Programming
	[1] coresponding links and programs in C

- finite size effects in the MC studies of the Ising model.
- discussing novel scientific works related to Monte Carlo methods.
- individual discussions with the students on their chosen research project. 	Explanations
Presentations
Discussions
Problem formulation
Individual work
Programming
	[1] coresponding links and programs in C

- simulating the Potts model with q states at low temperatures (the BKL Monte Carlo method)
 - simulationg the dynamics of atoms deposited on surfaces. 
- discussing novel scientific works related to Monte Carlo methods.
- individual discussions with the students on their chosen research project. 	Explanations
Presentations
Discussions
Problem formulation
Individual work
Programming
	[1] coresponding links and programs in C

- studying 2D and 3D Ising models with the Swendsen and Wang and Wolf dynamics. 
-discussing novel scientific works related to Monte Carlo methods.
- individual discussions with the students on their chosen research project. 	Explanations
Presentations
Discussions
Problem formulation
Individual work
Programming
	[1] coresponding links and programs in C

- Studying 2D and 3D Ising problems with the histogram MC method. The microcanonical MC method. 
- discussing novel scientific works related to Monte Carlo methods.
- individual discussions with the students on their chosen research project. 	Explanations
Presentations
Discussions
Problem formulation
Individual work
Programming
	[1] coresponding links and programs in C

Presentation of individual research projects (I)	Presentations		
Presentation of individual research projects(II)	Presentations		
References	
1. Z. Neda : Stochastic simulations in physics with interdisciplinary applications,  http://www.phys.ubbcluj.ro/~zneda/edu/mc.htm

9. Corroborating the content of the discipline with the expectations of the epistemic community,
professional associations and representative employers within the field of the program

The syllabus and the studied material is in agreement with  similar courses from other universities in Romania and abroad. For helping the integration with the deminds of the work-force market, the syllabus was harmonized with the deminds of the pre-university and university educations, of those of research institutes and the business sector.  	

10. Evaluation
Type of activity	10.1 Evaluation criteria	10.2 Evaluation method	10.3 Percent in the final grade	
10.4 Course	knowledge of the tought material	 Exam 	    55%	
	application of the tought material			
10.5 Seminar				
				
10.6 Laboratory	Solving the proposed exercises	 Colloquium	   25%	
	Realization degree and presentation of the research project 	Colloquium	   20%	
10.7 Minimal performance standard	
Understanding the methods presented at the course and laboratory. 
Addressing the laboratory requirements in proportion of at least 75%. 
Successful Developing a project of medium complexity.

Signature of course coordinator		Signature of seminar coordinator		Signature of laboratory coordinator	
Prof. Dr. Neda Zoltan				 Lect. Dr. Zsolt Lazar	

Date		Date of approval		Signature head of Department	
12.01.2014