9600-0008/01 – Particle Simulations (CAS)

Gurantor departmentIT4InnovationsCredits10
Subject guarantorprof. RNDr. René Kalus, Ph.D.Subject version guarantorprof. RNDr. René Kalus, Ph.D.
Study levelpostgraduateRequirementChoice-compulsory
YearSemesterwinter + summer
Study languageCzech
Year of introduction2015/2016Year of cancellation
Intended for the facultiesUSP, FEIIntended for study typesDoctoral
Instruction secured by
LoginNameTuitorTeacher giving lectures
KAL0063 prof. RNDr. René Kalus, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Examination 2+0
Part-time Examination 10+0

Subject aims expressed by acquired skills and competences

Upon the successful completion of the course, students will be able to actively use the concepts from the field of particle simulations, implement simulation models, perform numerical pseudoexperiments, and independently extend their acquired knowledge of this field.

Teaching methods

Lectures
Individual consultations

Summary

Students will acquire general knowledge of the most important methods for simulations of multiparticle systems and, according to their diploma thesis topic, they will focus on one of the four main areas: a) molecular dynamics methods (microcanonical and canonical ensembles, numerical integration of equations of motion), b) classical Monte Carlo methods (canonical, microcanonical, isothermal-isobaric, and grandcanonical MC methods), c) quantum Monte Carlo methods (variational, diffusion, and path-integral MC methods), and d) dynamical simulations (quasiclassical trajectory methods for adiabatic as well as non-adiabatic molecular dynamics, and quantum decoherence).

Compulsory literature:

• Allen, M.P., Tildesley, D.J. Computer Simulations of Liquids. Oxford Science Publications, Oxford 1989, ISBN 0-19-855645-4.

Recommended literature:

• Dimov, I.T. Monte Carlo Methods for Applied Scientists, World Scientific, Singapore 2008, ISBN 978-981-02-2329-8. • Hammond, B.L., et al. Monte Carlo Methods in Ab Initio Quantum Chemistry, World Scientific, Singapore 1994, ISBN 981-02-0322-5. • Grotendorst, J., et al. (Eds.) Quantum Simulations of Complex Many-Body Systems, NIC Series Vol. 10, Juelich 2002, ISBN 3-00-009057-6.

Way of continuous check of knowledge in the course of semester

Project elaboration and its presentation and defence, oral exam.

E-learning

Other requirements

Elaboration of a project as assigned at the beginning of the semester.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Students will acquire general knowledge of the most important methods for simulations of multiparticle systems and, according to their diploma thesis topic, they will focus on one of the four main areas: a) molecular dynamics methods (microcanonical and canonical ensembles, numerical integration of equations of motion), b) classical Monte Carlo methods (canonical, microcanonical, isothermal-isobaric, and grandcanonical MC methods), c) quantum Monte Carlo methods (variational, diffusion, and path-integral MC methods), and d) dynamical simulations (quasiclassical trajectory methods for adiabatic as well as non-adiabatic molecular dynamics, and quantum decoherence).

Conditions for subject completion

Full-time form (validity from: 2015/2016 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Examination Examination   3
Mandatory attendence participation:

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Conditions for subject completion and attendance at the exercises within ISP:

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Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2023/2024 (P2658) Computational Sciences (2612V078) Computational Sciences P Czech Ostrava Choice-compulsory study plan
2023/2024 (P2658) Computational Sciences (2612V078) Computational Sciences K Czech Ostrava Choice-compulsory study plan
2022/2023 (P2658) Computational Sciences (2612V078) Computational Sciences P Czech Ostrava Choice-compulsory study plan
2022/2023 (P2658) Computational Sciences (2612V078) Computational Sciences K Czech Ostrava Choice-compulsory study plan
2021/2022 (P2658) Computational Sciences (2612V078) Computational Sciences P Czech Ostrava Choice-compulsory study plan
2021/2022 (P2658) Computational Sciences (2612V078) Computational Sciences K Czech Ostrava Choice-compulsory study plan
2020/2021 (P2658) Computational Sciences (2612V078) Computational Sciences P Czech Ostrava Choice-compulsory study plan
2020/2021 (P2658) Computational Sciences (2612V078) Computational Sciences K Czech Ostrava Choice-compulsory study plan
2019/2020 (P2658) Computational Sciences (2612V078) Computational Sciences P Czech Ostrava Choice-compulsory study plan
2019/2020 (P2658) Computational Sciences (2612V078) Computational Sciences K Czech Ostrava Choice-compulsory study plan
2018/2019 (P2658) Computational Sciences (2612V078) Computational Sciences P Czech Ostrava Choice-compulsory study plan
2018/2019 (P2658) Computational Sciences (2612V078) Computational Sciences K Czech Ostrava Choice-compulsory study plan
2017/2018 (P2658) Computational Sciences (2612V078) Computational Sciences P Czech Ostrava Choice-compulsory study plan
2017/2018 (P2658) Computational Sciences (2612V078) Computational Sciences K Czech Ostrava Choice-compulsory study plan
2016/2017 (P2658) Computational Sciences (2612V078) Computational Sciences P Czech Ostrava Choice-compulsory study plan
2016/2017 (P2658) Computational Sciences (2612V078) Computational Sciences K Czech Ostrava Choice-compulsory study plan
2015/2016 (P2658) Computational Sciences (2612V078) Computational Sciences P Czech Ostrava Choice-compulsory study plan
2015/2016 (P2658) Computational Sciences (2612V078) Computational Sciences K Czech Ostrava Choice-compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

Assessment of instruction

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