Courses

In this seminar, we are interested in all aspects of research at the intersection between quantum information science and mathematics.  Goals for talks include:

  • Studying recent research results in quantum information from a mathematical angle;
  • Finding examples (old and new) in which existing tools from mathematics can be adapted for application in quantum information;
  • Studying quantum algorithms for mathematical problems.

https://quics.umd.edu/people/carl-miller

Designed for computer science, engineering and mathematics majors. Introduces basic concepts and techniques widely used in quantum information science.

An introduction to the field of quantum information processing. Students will be prepared to pursue further study in quantum computing, quantum information theory, and related areas.

Investigates the physical systems used to implement quantum computers. Covers basics of atomic clocks, laser interferometers, quantum key distribution, quantum networks, and three types of qubits (ion-based, superconductor-based, and semiconductor-based).

The aim of the course is to develop the theory of how to protect quantum computers from noise through active control, measurement, and feedback of quantum systems. Topics will include quantum coding theory, stabilizer codes, continuous variable codes, fault-tolerance, resource theories, magic states, threshold theorems, topological codes, decoding algorithms, noisy quantum circuits, and related aspects of quantum many-body physics.

This is an advanced graduate course on quantum algorithms for students with prior experience in quantum information. The course will cover algorithms that allow quantum computers to solve problems faster than classical computers.