In this course you will learn a whole lot of modern physics (classical and quantum) from basic computer programs that you will download, generalize, or write from scratch, discuss, and then hand in. Join in if you are curious (but not necessarily knowledgeable) about algorithms, and about the deep insights into science that you can obtain by the algorithmic approach.
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Statistical Mechanics: Algorithms and Computations
École normale supérieureAcerca de este Curso
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École normale supérieure
L’École normale supérieure (ENS) est un établissement d'enseignement supérieur pour les études prédoctorales et doctorales (graduate school) et un haut lieu de la recherche française. L'ENS offre à 300 nouveaux étudiants et 200 doctorants chaque année une formation de haut niveau, largement pluridisciplinaire, des humanités et sciences sociales aux sciences dures. Régulièrement distinguée au niveau international, l'ENS a formé 10 médailles Fields et 13 prix Nobel.
Programa - Qué aprenderás en este curso
Monte Carlo algorithms (Direct sampling, Markov-chain sampling)
Dear students,
Hard disks: From Classical Mechanics to Statistical Mechanics
In Week 2, you will get in touch with the hard-disk model, which was first simulated by Molecular Dynamics in the 1950's. We will describe the difference between direct sampling and Markov-chain sampling, and also study the connection of Monte Carlo and Molecular Dynamics algorithms, that is, the interface between Newtonian mechanics and statistical mechanics. The tutorial includes classical concepts from statistical physics (partition function, virial expansion, ...), and the homework session will show that the equiprobability principle might be more subtle than expected.
Entropic interactions and phase transitions
After the hard disks of Week 2, in Week 3 we switch to clothe-pins aligned on a washing line. This is a great model to learn about the entropic interactions, coming only from statistical-mechanics considerations. In the tutorial you will see an example of a typical situation: Having an exact solution often corresponds to finding a perfect algorithm to sample configurations. Finally, in the homework session we will go back to hard disks, and get a simple evidence of the transition between a liquid and a solid, for a two-dimensional system.
Sampling and integration
In Week 4 we will deepen our understanding of sampling, and its connection with integration, and this will allow us to introduce another pillar of statistical mechanics (after the equiprobability principle): the Maxwell and Boltzmann distributions of velocities and energies. In the homework session, we will push the limits of sampling until we can compute the integral of a sphere... in 200 dimensions!
Reseñas
- 5 stars85,37 %
- 4 stars12,25 %
- 3 stars1,18 %
- 2 stars0,39 %
- 1 star0,79 %
Principales reseñas sobre STATISTICAL MECHANICS: ALGORITHMS AND COMPUTATIONS
The course is self-contained. Very good for people even if they are not physicist. They can still learn a lot about computational methods that are useful in many ways.
I learned a lot from all kinds of algorithms that I heard of, but never had the chance to get the clarifications.
Brilliant course, lots of advanced material, pretty much exceptional way of teaching. The difficulty is just right. Appreciate the effort of the team.
This course was awesome! Although, I can tell I'll need another pass at it to understand things more fully...
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