Previously taught courses

Spring 2024

APh 138b: Quantum Hardware and Techniques

This class covers multiple quantum technology platforms and related theoretical techniques, and will provide students with broad knowledge in quantum science and engineering. It will be split into three-week modules covering: applications of near-term quantum computers, superconducting qubits, trapped atoms and ions, topological quantum matter, solid state quantum bits, tensorproduct states.

Fall 2023

APh 105a: States of Matter

Thermodynamics and statistical mechanics, with emphasis on gases, liquids, materials, and condensed matter. Effects of heat, pressure, and fields on states of matter are presented with both classical thermodynamics and with statistical mechanics. Conditions of equilibrium in systems with multiple degrees of freedom. Applications include ordered states of matter and phase transitions.

Fall 2022

APh 138b: Quantum Hardware and Techniques

This class covers multiple quantum technology platforms and related theoretical techniques, and will provide students with broad knowledge in quantum science and engineering. It will be split into three-week modules covering: applications of near-term quantum computers, superconducting qubits, trapped atoms and ions, topological quantum matter, solid state quantum bits, tensorproduct states.

Fall 2021

APh 105a: States of Matter

Thermodynamics and statistical mechanics, with emphasis on gases, liquids, materials, and condensed matter. Effects of heat, pressure, and fields on states of matter are presented with both classical thermodynamics and with statistical mechanics. Conditions of equilibrium in systems with multiple degrees of freedom. Applications include ordered states of matter and phase transitions.

Winter 2021

Ae/ME 118: Classical Thermodynamics

Fundamentals of classical thermodynamics. Basic postulates and laws of thermodynamics, work and heat, entropy and available work, equations of state, thermodynamic potentials, chemical and phase equilibrium, phase transitions, and thermodynamic properties of solids, liquids, and gases. The course will end with various advanced topics TBD.

Fall 2020

ME 11a: Thermal Science

This term of ME 11 is an introduction to classical thermodynamics. We will emphasize the first and second laws of thermodynamics for closed and open systems, and introduce the relations between thermodynamic properties.

Spring 2020

APh 250/ME 201: Microwave noise in semiconductor electronic devices

Course description: What do radio telescopes, quantum computers, and deep space communication have in common? The transistor microwave amplifier! Low noise amplifiers are a key technology that allow weak signals to be processed and analyzed. The noise above the standard quantum limit added by these amplifiers thus represents a basic limit to the accuracy of a measurement.

This course will provide a comprehensive overview of the physical origin of noise mechanisms in transistor amplifiers and how they may be mitigated. Specific topics to be covered include:

Mathematical description of stochastic processes and fundamental noise sources
Equivalent circuit noise model of field-effect and bipolar junction transistors
Non-equilibrium noise mechanisms including hot electron noise

Prerequisites: Basic knowledge of circuits and semiconductor physics.

Class notes

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Fall 2019

APh 250/ME 201: A numerical introduction to tensor networks for quantum simulation

Tensor networks have emerged as a powerful tool for the numerical simulation of quantum many-body systems. This course will cover the fundamentals of tensor networks and recent algorithmic developments from a numerical perspective. Emphasis will be placed on both the theoretical foundation and practical numerical implementation of a variety of 1D and 2D tensor network algorithms. Specific topics to be covered include:

Fundamentals of matrix product states, canonical forms, computation of expectation values, matrix product operators, and other basics
Numerical renormalization group for impurity problems
Algorithms to find ground states, including phase estimation, variational methods, imaginary time evolution, and quantum annealing
Density matrix renormalization group, including time-dependent and imaginary-time algorithms, and tangent space methods
Pair-entangled projected states (PEPS), tensor network renormalization (TNR), 2D canonical forms, isometric PEPS, and fermionic PEPS.

Prerequisites: PH 125, CH 125 or equivalent graduate quantum mechanics course. ACM 104 or equivalent linear algebra course.

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Spring 2019

APh 250/ME 201:Physics on near-term quantum computers

Quantum computers with tens of physical qubits and high gate fidelities will become available in the next few years. This class will explore how this new type of computing device could be used to address research questions in physics. Specific topics to be covered include:

Fundamentals of quantum computing and key algorithms
Translating states and Hamiltonians to qubits and Pauli gates
Algorithms to find ground states, including phase estimation, variational methods, imaginary time evolution, and quantum annealing
Algorithms for quantum dynamics
Noise and error mitigation strategies on near-term devices

Prerequisites: PH 125, CH 125 or equivalent graduate quantum mechanics course. ACM 104 or equivalent linear algebra course. Some familiarity with fundamental concepts of quantum computing is beneficial.

Class notes

Lecture 1: Quantum Simulation 04/01/2019

Lecture 2: Efficient Quantum Simulations 04/03/2019

Lecture 3: Overview of Computational Complexity 04/05/2019

Lecture 4: Review of Linear Algebra and Quantum Mechanics 04/08/2019

Lecture 5: Review of Quantum Computing 04/12/2019

Lecture 6: Second quantization 04/22/2019

Lecture 7: Jordan-Wigner transform 04/26/2019

Lecture 8: Brayvi-Kitaev transform 05/01/2019

Lecture 9: Iterative Phase Estimation 05/03/2019

Lecture 10: Variational Quantum Eigensolver 05/06/2019

Lecture 11: Variational imaginary time evolution 05/08/2019