• Boltzmann Law
• Boltzmann Machines
• Transition Matrix
• Quantum Boltzmann Law
• Quantum Gates

Week 1: Boltzmann Law

1.1 State Space

1.2 Boltzmann Law

1.3 Shannon Entropy

1.4 Free Energy

1.5 Self-consistent Field

1.6 Summary for Exam 1

Week 2: Boltzmann Machines

2.1. Sampling

2.2. Orchestrating Interactions

2.3. Optimization

2.4. Inference

2.5. Learning

Week 3: Transition Matrix

3.1. Markov Chain Monte Carlo

3.2. Gibbs Sampling

3.3. Sequential versus Simultaneous

3.4. Bayesian Networks

3.5. Feynman Paths

3.6 Summary for Exam 2

Week 4: Quantum Boltzmann Law

4.1. Quantum Spins

4.2. One q-bit Systems

4.3. Spin-spin Interactions

4.4. Two q-bit Systems

4.5. Quantum Annealing

Week 5: Quantum Transition Matrix

5.1. Adiabatic to Gated Computing

5.2. Hadamard Gates

5.3. Grover Search

5.4. Shor's Algorithm

5.5. Feynman Paths

5.6 Summary for Exam 3

Epilogue

"The way that this professor explains the material very well. All of this was very new to me but he explained it in a way that made the course interesting and engaging. I also enjoy the quizzes after every lecture video. It’s very helpful in ensuring that I learn the material properly. " - Student, Fall 2020 semester