Details zur Lehrveranstaltung
| Collective processes in non-equilibrium systems | |
| Modul: | Phy-Ma-Vert: Physikalische Vertiefung |
| Lecture language | English |
| Summary of Lecture: | Suppose someone gave you a terabyte of data on an epidemic. What are the theoretical concepts you need to know in order to understand collective behaviour in such a system? Technological breakthroughs in biology and the social sciences now give unprecedented access to microscopic states of non-equilibrium systems. These emerging technologies demand a rethinking about our approaches to understanding collective degrees of freedom in complex systems. In this lecture, we will take an interdisciplinary perspective on the concepts necessary to identify and understand collective order in space and time in non-equilibrium systems. We will begin by introducing core concepts from non-equilibrium statistical physics, such as field theory, renormalisation group theory and non-equilibrium phase transitions, and complement these tools with approaches from data science and machine learning that allow identifying collective degrees of freedom in high-dimensional measurements. We will synthetise these lessons using examples from current research. |
| data set up-to-date | |
| Scope: | lecture: 2 hours/week |
| Time/location: | DI(6) MPIPKS, SR3(Hybrid s. Kommentar) |
| Audience: | Vertiefung Bachelor (PV) und Master (alle) |
| Specialization area: | |
| Previous knowledge: | Statistical physics | Certificate: |
| Enrolment: | |
| Web-reference: | http://www.rulands.net/teaching/collective-processes-in-non-equilibrium-systems/ |
| The lecture will start on Nov 3. If possible, this will be a hybrid lecture with limited attendance in the seminar room and parallel steaming over Zoom. Please check the website for further information. | |