Quantum Complexity Theory
CSE 291 / Math 277A - Fall 2025
Place and Time: | PCYNH 120, TTh 2:00pm-3:20pm |
Instructor: | Daniel Grier (dgrier@ucsd.edu) |
Resources: | Canvas, Piazza |
Daniel's office hours: | Thursday after class and by appointment in CSE 4218 |
Jacks's office hours: | Friday 11-12pm in CSE BA250 |
- Homework 1 - due October 3rd at 11:59pm
- Homework 2 - due October 17th at 11:59pm
These lecture notes are intended to be a comprehensive reflection of the course material. They will be updated throughout the quarter (last updated: 9/24/25).
Lecture 1 | Foundations of quantum mechanics | 1.1-1.2 |
Lecture 2 | Multi-qubit states, tensor products | 1.2 |
Lecture 3 | Partial measurements, Dirac notation, inner products | 1.3 |
Lecture 4 | Quantum circuits, Deutsch's problem | 2.1-2.2 |
This is a graduate-level course that will use tools from complexity theory to understand the fundamental differences between quantum and classical computers. After an introduction to the basics of quantum computation, the course will explore several settings in which quantum computers provably outperform their classical counterparts. This will take us to the forefront of quantum computing research, where we'll look at the complexity-theoretic foundations of recent quantum computing experiments.
Prerequisites: A previous course in complexity theory (CSE 200 or equivalent) is highly recommended. No prerequisite knowledge of physics or quantum computation is required. That said, this is an advanced research-level course and will go far beyond a simple introduction to quantum computation and information.
- Quantum foundations: states, operations, measurements
- Quantum algorithms: Deutsch-Jozsa, Simon, Grover
- Lower bounds from query complexity: polynomial method, adversary method
- Classical vs. quantum complexity classes: P vs. BQP, NP vs. QMA
- Quantum satisfiability and the local Hamiltonian problem
- Classical simulation: Clifford circuits, tensor networks
- Near-term computational advantage: Shallow circuits, BosonSampling
- Homework (55%): There will be 6 homework assignments throughout the course.
- Project (30%): Written report of a topic related to quantum complexity theory.
- Peer Grading (15%): Each student will be required to help grade one homework assignment.
- Complexity Zoo Largest unified collection of complexity classes and their relationships
- SciRate Popular voting for recent quantum papers on the arXiv
- Quantum Computation and Quantum Information The canonical introductory textbook on the foundations of quantum information theory
- Ronald de Wolf's Quantum Computing Lecture Notes Published freely on the web
- Quantikz LaTex package for drawing quantum circuits