Вернуться к Статистическая механика: алгоритмы и вычисления

4.8

Оценки: 191

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Рецензии: 63

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....

Sep 23, 2017

Excellent and enthusiastic lectures and tutorials covering a number of topics. Much of the learning took place in the assignments where the concepts were applied and various points were illustrated.

Mar 18, 2017

I really like this course also I am only confused by my knowledge in computing because this course is very high rated in sense of detailed explanation and easy to follow through difficult themes.

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автор: Jianfei X

•Aug 21, 2016

a great course!

автор: Xu H

•Sep 15, 2017

It helps deepen my understanding about Mont Carlo. I had a lot of fun in programing and reading codes or opinions from other students. Our lovely teachers are humorous. They even prepared a big Party at the end of this course XD. hf gl

автор: Ning A

•Jan 10, 2017

I learned a lot from all kinds of algorithms that I heard of, but never had the chance to get the clarifications.

автор: Le Y

•Mar 30, 2016

Deepen my trust in Monte-Carlo and Markov Chain Monte-Carlo simulation --- exact mimic their analytical counterpart.

Also get the chance to touch the spirit of Quantum Mechanics.

автор: Sirui L

•Sep 12, 2016

Perfect Course!

автор: Gavin C

•Aug 16, 2016

An exceptionally brilliant course.

Exceptionnel. Nutzlich. Speciale.

автор: Philippe S

•Apr 29, 2017

I learned a bunch of things, thank you very much.

автор: Jiting T (

•Sep 09, 2017

This is a graduate or advanced undergraduate level class on statistical physics, focusing on the computational tools (MC and MD). The materials are organized very well and the concepts are illustrated in a clear way. A lot of Python examples are provided to help students master the contents. The homework and exam is not hard, as most of the code is already present by the teachers, and students only need to fill the blank or do a little changes. It's not difficult to go through this course and pass the exam, but it's truly difficult to deeply understand all the materials. Although, for the guys who love statistical mechanics, this course deserve your effects.

автор: Yessimzhan R

•Mar 18, 2017

I really like this course also I am only confused by my knowledge in computing because this course is very high rated in sense of detailed explanation and easy to follow through difficult themes.

автор: Efren S

•Mar 09, 2018

Most useful course I've had a quite some time. Thank you Monsieur Krauth!

автор: Tim B

•Oct 24, 2017

Some of the lessons are very difficult, but if you persevere, it's very rewarding.

автор: Nicolas B

•Mar 23, 2016

Not one of the easiest courses, but extremely interesting!

автор: Ji T

•Jul 28, 2016

这门课非常有趣！很注重动（码）手（代）实（码）践！

автор: Wenting T

•Mar 23, 2016

great course and clever instruction!

автор: José J B d M

•Apr 08, 2018

It was a very interesting course, both for having a look on Statistical Mechanic

автор: Monika K

•Aug 02, 2016

Way over my head but hope to keep working at it.

автор: Robert F

•May 27, 2016

Material is very interesting and the courser work provides great opportunities to try out and build different statistical algorithms. You don't need a background in physics but I think it would help to fully grasp the materials.

автор: Marcelo S

•Aug 23, 2016

The course is excellent. Great quality of supplied material, teachers and assignments. I rate it on the fact that I was able to follow it and learn quite a lot on a subject that is far from easy, and I'm pleased with the results.

The only issue / recommendation I can point out : The course is not very specific on the needed background. As an example, I took this course being an engineer with a decent understanding of maths, a less-decent understanding of physics (almost no quantum physics background), and experience with python programming: in my case, it required a lot of effort in order to follow some of the chapters (specially the ones focused in quantum physics), and normally always more than the normal 8 hs/week. I recommend the student to have some background on probability theory / functions and python programming so as to follow easier, and expect some difficulty in fully understanding some of the subjects. I still rate it 5 stars.

автор: Simon C

•Jun 27, 2017

A great introduction to the ideas of statistical mechanics and Monte Carlo methods. I also like Dr. Krauth's sense of humour. He begins by imagining children on the beach in Monte Carlo, computing pi by throwing pebbles.

If you're looking for a nice set of lectures followed by easy multiple choice questions, this course isn't for you. The lectures and tutorials are very professional, Dr. Krauth & his students have done a great job, but the assignments are where you will learn the most. They are hard work, and I found I had to think hard. Don't leave them until the last minute: start early, and break for a walk outside when you get stuck. They really teach the ideas.

I started this course to support other coursework as was doing, as I felt my command of thermodynamics was a bit shaky. I've found it enjoyable in its own right. I've learned to appreciate Monte Carlo methods, and apply them to my own work on Molecular Diagnosis.

автор: 王富强

•Nov 01, 2016

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автор: Bingyu Z

•May 29, 2016

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.

автор: César A L

•Dec 22, 2017

You will learn not only the theory about how to solve differente many body problems, but you will laso will adquire the hability to ptogram the solutions for any incoming value in almost any related problem

the best statiscal mechanics course i've taken in my whole live. I also bought the book by Werner, it's very well written

автор: RLee

•Aug 28, 2017

Engage students with the world of Statistical Mechanics by making hands dirty. One needs to have some basics in Quantum Mechanics or Thermodynamics in order to make sense of what have been done. Not sufficient mathematical proof and intuition could be found in Professor's textbook, although it is good to have it free. The solutions to Newton's packing problem is a kind of surprise. Not sufficient conclusions to problems like with and without boundaries; one-half rules; violation of tabula rasa rules; rejection-free direct sampling to avoid Metropolis Algorithm; simulated annealing. These gaps need to be filled in order to make it more self-sufficient. But still it is a very sincere effort to promote this branch of Physics to the world. It is very transferable to Mathematical Finance and Artificial Intelligence.

автор: Erik P

•Aug 20, 2017

Very clear and very interesting! The exercises are a bit difficult (especially for me that I'm only a beginner in Python) but it's a powerful introduction to computational condensed matter physics!

I suggest it for people that already has the rudiments of Mechanics, Statistical Mechanics and algorithmic approach to every-day problems

автор: Uwe K

•Feb 06, 2017

All is said. Strongly recommended

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