Basic Statistical Mechanics

Overview

COURSE OUTLINE: In order to understand natural phenomena like phase transitions or nucleation or many biological reactions like protein folding, enzyme kinetics, we need to understand how many particles interact and behave together in a certain specified manner. For example, ice melts at 00 C and water boils at 1000 C, at low temperature the raindrops form in the upper atmosphere. Enzyme beta-galactosidase allows the breaking of the C-O bond that leads to the digestion of lactose . These are complex processes that involve many particles to behave in a collective fashion. This could happen because of the interaction among particles. However, these cannot be solved by Newton’s equations, because we cannot solve Newton’s equations even for three particles interacting system. So the forefathers of this field, Maxwell, Boltzmann and Gibbs introduced the probabilistic approach and combined it with mechanics to form the ‘Statistical Mechanics.’ This a branch of theoretical science that parallels Quantum Mechanics and these two together form the main tools at our disposal to understand why things happen and how they happen. The present course will address the basic postulates of Statistical Mechanics and then will show how starting from the basic postulates one builds a formidable framework that can be used to explain phenomena mentioned above.

Syllabus

Course Introduction Basic Statistical Mechanics.
Week 1: Lecture 1.
Week 1: Lecture 2.
Week 1: Lecture 3.
Week 1: Lecture 4.
Week 1: Lecture 5.
Week 2: Lecture 6.
Week 2: Lecture 7.
Week 2: Lecture 8.
Week 2: Lecture 9.
Week 2: Lecture 10.
Week 3: Lecture 11.
Week 3: Lecture 12.
Week 3: Lecture 13.
Week 3: Lecture 14.
Week 3: Lecture 15.
Week 4: Lecture 16.
Week 4: Lecture 17.
Week 4: Lecture 18.
Week 4: Lecture 19.
Week 4: Lecture 20.
Week 5: Lecture 21.
Week 5: Lecture 22.
Week 5: Lecture 23.
Week 5: Lecture 24.
Week 5: Lecture 25.
Week 6: Lecture 26.
Week 6: Lecture 27.
Week 6: Lecture 28.
Week 6: Lecture 29.
Week 6: Lecture 30.
Week 7: Lecture 31.
Week 7: Lecture 32.
Week 7: Lecture 33.
Week 7: Lecture 34.
Week 7: Lecture 35.
Week 8: Lecture 36.
Week 8: Lecture 37.
Week 8: Lecture 38.
Week 8: Lecture 39.
Week 8: Lecture 40.
Week 9: Lecture 41.
Week 9: Lecture 42.
Week 9: Lecture 43.
Week 9: Lecture 44.
Week 9: Lecture 45.
Week 10: Lecture 46.
Week 10: Lecture 47.
Week 10: Lecture 48.
Week 10: Lecture 49.
Week 10: Lecture 50.
Week 11: Lecture 51.
Week 11: Lecture 52.
Week 11: Lecture 53.
Week 11: Lecture 54.
Week 11: Lecture 55.
Week 12: Lecture 56.
Week 12: Lecture 57.
Week 12: Lecture 58.
Week 12: Lecture 59.
Week 12: Lecture 60.
Week 12: Lecture 61.