Login for PhD students/staff at UCPH      Login for others
Diffusive and Stochastic Processes - PhD course
Provider: Faculty of Science

Activity no.: 5862-22-11-31
Enrollment deadline: 31/01/2022
Date and time25.04.2022, at: 00:00 - 26.06.2022, at: 16:00
Regular seats20
ECTS credits7.50
Contact personJulie Meier Hansen    E-mail address: juliemh@nbi.ku.dk
Enrolment Handling/Course OrganiserNamiko Mitarai    E-mail address: mitarai@nbi.ku.dk
Written languageEnglish
Teaching languageEnglish
Semester/BlockBlock 4
Scheme groupA (Tues 8-12 + Thurs 8-17)
Exam formWritten assignment
Exam formWritten examination, 4 hours under invigilation
Exam detailsNo preparation time
Exam aidsAll aids allowed
Grading scalePassed / Not passed
Censorship formSeveral internal examiners
Exam re-examinationSame as regular exam. It is possible to submit a new programming assignment (20%) until three weeks before the written re-exam (80%). Please contact the course responsible to arrange this. If there are 10 or fewer students signed up for the reexam, it will be changed to an oral exam, 25 minutes without aids and with no preparation time.
Course workload
Course workload categoryHours
Lectures24.00
Theory exercises35.00
Exam0.50
Preparation146.50

Sum206.00


Content
Stochastic descriptions offer powerful ways to understand fluctuating and noisy phenomena, and are widely used in many scientific discipline including physics, chemistry, and biology. In this course, basic analytical and numerical tools to analyze stochastic phenomena are introduced and will be demonstrated on several important natural examples. Students will learn to master stochastic descriptions for analyzing non-equilibrium complex phenomena.

Formel requirements
Academic qualifications:
Equilibrium statistical physics, physics bachelor level mathematics (Especially: differential and integral calculus, differential equations, Taylor expansions).

Learning outcome

 

Skills:
At the conclusion of the course students are expected to be able to:

  • Describe diffusion process using random walk, Langevin equation, and Fokker-Plank equation.
  • Explain the first passage time and Kramers escape problem
  • Explain the fluctuation-dissipation theorem.
  • Explain basic concepts in stochastic integrals.
  • Explain the Poisson process and the birth and death process. Use master equations to describe time evolution and steady state of the processes.
  • Explain the relationship between master equations and Fokker-Plank equations using Kramas-Moyal expansion and the linear noise approximation.
  • Explain asymmetric simple exclusion process and some related models to describe traffic flow and jamming transition in one-dimensional flows.
  • Apply the concepts and techniques to various examples from non-equilibrium complex phenomena.

Knowledge
In this course, first basic tools to analyse stochastic phenomena are introduced by using the diffusion process as one of the most useful examples of stochastic process. The topics include random walks, Langevin equations, Fokker-Planck equations, Kramars escape, and the fluctuation-dissipation theorem. Then selected stochastic models that have wide applications to various real phenomena are introduced and analysed. The topics are chosen from non-equilibrium stochastic phenomena, including birth and death process and Master equation, and asymmetric simple exclusion process. Throughout the course, exercises for analytical calculations and numerical simulations are provided to improve the students' skills.

Competences
This course will provide the students with mathematical tools that have application in range of fields within and beyond physics. Examples of the fields include non-equilibrium statistical physics, biophysics, soft-matter physics, complex systems, econophysics, social physics, chemistry, molecular biology, ecology, etc.  This course will provide the students with a competent background for further studies within the research field, i.e. a M.Sc. project.


Teaching and learning methods
Lectures and exercise sessions. Computer exercise included.

Remarks
To apply for the course:

If you are a PhD student, please apply as credit student at this link.

The course code to enter is NFYK10006U.

For support re. signing up, please contact Julie Meier Hansen: juliemh@nbi.ku.dk

Search
Click the search button to search Courses.


Course calendar
See which courses you can attend and when
JanFebMarApr
MayJunJulAug
SepOctNovDec



Publication of new courses
All planned PhD courses at the PhD School are visible in the course catalogue. Courses are published regularly.