Boltzmann Law: Physics to Computing
This course is intended to be broadly accessible to students in any branch of science or engineering who would like to learn about the conceptual framework for equilibrium statistical mechanics and its application to modern machine learning. Weekly topics: 1) Boltzmann Law; 2) Boltzmann Machines; 3) Transition Matrix; 4) Quantum Boltzmann Law; 5) Quantum Transition Matrix
ECE50633
Credit Hours:
1Learning Objective:
- Explain the law of equilibrium and entropy
- Understand the operation of Boltzmann machines
- Understand the operation of quantum circuits
Description:
This course is intended to be broadly accessible to students in any branch of science or engineering who would like to learn about the conceptual framework for equilibrium statistical mechanics and its application to modern machine learning.
Weekly topics: 1) Boltzmann Law; 2) Boltzmann Machines; 3) Transition Matrix; 4) Quantum Boltzmann Law; 5) Quantum Transition Matrix