Details zur Lehrveranstaltung
Stochastic Processes (with programming exercises) | |||||||
Modul: | Phy-Ma-Vert: Physikalische Vertiefung | ||||||
Lecture language | English | ||||||
Summary of Lecture: | Thermal fluctuations, Brownian motion, or fluctuating stock prices are examples of stochastic dynamics. We introduce Markov chains and Langevin equations to model the time-evolution of stochastic systems, and discuss their link to statistical physics. Selected programming exercises in Python will accompany the lecture (no previous knowledge of Python required). | ||||||
data set up-to-date | |||||||
Scope: | lecture: 2 hours/week tutorials: 2 hours/week | ||||||
Time/location: | DO(4) BZW/A120 | ||||||
Tutorials: |
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Audience: | Vertiefung Bachelor (PV) und Master (alle) | ||||||
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Previous knowledge: | Multivariate calculus, Elementary probability theory, Ordinary and partial differential equations | Certificate: | Ersatzprüfung für Rigorosum möglich | ||||
Enrolment: | |||||||
Web-reference: | https://cfaed.tu-dresden.de/friedrich-group-teaching | ||||||
Target audience: Physics students at the Master’s level; Mathematics students interested in applications of stochastic processes; Bioengineering students with strong background in quantitative methods |