**Graduate Quantum Mechanics 1**

**Fall 2020**

**Instructor:**

Prof: Jared Kaplan

TA: Utkarsh Sharma

Schedule: T&Th at 10:30 AM (Online)

This is a graduate level course on quantum mechanics.

**Course Materials:** We will use Weinberg’s Lectures on Quantum Mechanics as a textbook. Here’s a Syllabus outlining some of what we’ll cover in the course. Please feel encouraged to communicate with the professor & TA if you have any questions or concerns, as we’ll be online-only.

**Assignments: **Weekly problem sets: 1

**Quantum Gravity and AdS/CFT**** **

**Spring 2020**

**Instructor:**

Prof: Jared Kaplan

Schedule: M&W at Noon (Bloomberg 464)

This is a course on quantum gravity and AdS/CFT. The discussion of quantum gravity will emphasize why gravity differs from the other forces, requiring a radical “holographic” perspective to unite it with quantum mechanics. We approach AdS/CFT from the point of view of Effective Field Theory and the Conformal Bootstrap.

**Course Materials:** The course is based on my Quantum Gravity Lecture Notes and my AdS/CFT Course Notes. Lectures on the conformal bootstrap by Slava Rychkov and David Simmons-Duffin provide very useful background material on conformal field theory.

**Assignments: **Biweekly problem sets and student presentations at the end of the course.

**Contemporary Machine Learning for Physicists
**

**Spring 2019**

This was a graduate-level course on contemporary (post-2012, neural network based) machine learning, presented in a style targeted at physicists with no prior knowledge. The course aimed to be simultaneously highly pragmatic (ie focused on state-of-the-art methods) and fairly theoretical, and could not avoid this pitfall.

**Prerequisites: **An excellent understanding of linear algebra, and general mathematical/physical maturity. The pace of the course will be similar to that of other advanced graduate courses in physics (eg QFT).

**Course Materials:** My lecture notes were the primary reference. Additional resources may be recommended to those attending the course.

**Thermodynamics and Statistical Physics
**

**Fall 2018**

This was an advanced undergraduate course on thermodynamics and statistical physics. Topics included basics of temperature, heat, and work; entropy, state-counting, probability, and the second law; partition functions and the Boltzmann distribution; applications to engines, refrigerators, and computation; phase transitions; basics of quantum statistical mechanics.

**Prerequisites: **An excellent understanding of mechanics, and ideally some basic knowledge of quantum mechanics.

**Course Materials:** The main textbook for the course is Schroeder’s An Introduction to Thermal Physics (1999/2000). Here are rough, incomplete lecture notes.

**Assignments: **Weekly problem sets (typically due on Fridays): 1 2 3 4 5 6 8 9 10 11 12 13

**Quantum Field Theory**** **

**Fall 2016 & Spring 2017**

This was a graduate QFT course. The first semester covers basic lattice phonon models and their continuum field theory limit, canonical quantization, implications of Lorentz invariance, effective field theory, quantization and Feynman rules for scalars, renormalization and RG flows, and the basics of scalar and spinor QED. In the second semester we will have further discussions of QED, Wilsonian renormalization, continuous global and gauge symmetries, Nambu-Goldstone bosons and the spontaneous breaking of global symmetries, the Higgs mechanism, the standard model, deep inelastic scattering, and anomalies.

**Prerequisites: **An excellent understanding of undergraduate physics, especially Quantum Mechanics.

**Course Materials:** The Course Notes also include some discussion of background and other references. The main textbook was Schwartz’s Quantum Field Theory and the Standard Model.

**Assignments: **There were biweekly problem sets and a take home final / problem set at the end of the course.