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This is the official page for the year 2023-2024 of Disordered Systems course. | |||
== | == Course description == | ||
One of the | |||
* [https:// | |||
* [// | |||
* | Modern physics is characterized by an increasing complexity of systems under investigation, in | ||
domains as diverse as condensed matter, astrophysics, biophysics, etc. Establishing adequate | |||
models to describe these systems and being able to make quantitative predictions from those models | |||
is extremely challenging. The goal of the course is to provide the tools and concepts necessary to tackle those systems. | |||
We will first cover many algorithms used in many-body problems and complex systems, with special emphasis on Monte Carlo methods, molecular dynamics, and optimization in complex landscapes. | |||
Second, we will provide statistical inference and machine learning tools to harness the growing availability of experimental data to design accurate models of the underlying, complex, strongly non-homogeneous and interacting systems. | |||
Each theoretical lecture will be followed by a tutorial illustrating the concepts with practical applications | |||
borrowed from various domains of physics. We will focus on methods and algorithms and physics, not | |||
on programming and heavy numerics! You will have to hand in 3 homeworks. | |||
== The Team == | |||
* [https://vale1925.wixsite.com/vros Valentina Ros] | |||
* [http://lptms.u-psud.fr/alberto_rosso/ Alberto Rosso] | |||
== Where and When == | |||
* Lectures on Monday: xx | |||
* Tutorials on Monday: xx | |||
Revision as of 16:30, 7 October 2023
This is the official page for the year 2023-2024 of Disordered Systems course.
Course description
One of the
Modern physics is characterized by an increasing complexity of systems under investigation, in
domains as diverse as condensed matter, astrophysics, biophysics, etc. Establishing adequate
models to describe these systems and being able to make quantitative predictions from those models
is extremely challenging. The goal of the course is to provide the tools and concepts necessary to tackle those systems.
We will first cover many algorithms used in many-body problems and complex systems, with special emphasis on Monte Carlo methods, molecular dynamics, and optimization in complex landscapes.
Second, we will provide statistical inference and machine learning tools to harness the growing availability of experimental data to design accurate models of the underlying, complex, strongly non-homogeneous and interacting systems.
Each theoretical lecture will be followed by a tutorial illustrating the concepts with practical applications borrowed from various domains of physics. We will focus on methods and algorithms and physics, not on programming and heavy numerics! You will have to hand in 3 homeworks.
The Team
Where and When
- Lectures on Monday: xx
- Tutorials on Monday: xx