Curriculum
Five main topics will be covered: general engineering principles behind high performance numerical computing (including the use of accelerators like GPUs); state-vector simulation techniques; tensor network theory and practice; fast simulation of Clifford circuits and error correcting codes; quantum error mitigation with Mitiq.
Most of the practice will be in the Julia programming language due to the ease with which one can introduce low-level high-performance constructs in it, without losing the dynamic nature and ease of prototyping available in languages like Python. However, practical tips and guides will be provided for programming in Python, Rust, and C/C++, as well.
Multiple hackathons, will be available in the evenings, providing opportunities to work on personal research projects with the help of the instructors, and with bounties available for work on open source projects.
The summer school will end with multiple showcases, workshops, and hackathons from academic and industry partners, demonstrating how the techniques discussed during the summer school are currently applied at the cutting edge of science.
On Saturday August 17th, members of the Unitary Fund technical team will host a workshop on quantum error mitigation (QEM) with the software package Mitiq. We will cover QEM core concepts and techniques and the Mitiq structure and interface, with a deep dive into the techniques of Zero Noise Extrapolation and Digital Dynamical Decoupling. In the later part of the session, we will explore QEM on simulated noisy backends with benchmarks and calibration. The workshop will conclude in the evening with a Mitiq hackathon.
In the extended sessions we will cover many of the following topics:
General software engineering practices and cluster computing tools
Advanced general scientific programming (ODEs, optimization, autodifferentiation)
GPU programming
Fast general purpose wavefunction simulation
Tensor networks for faster approximate quantum simulations
Stabilizer formalism for quantum ECC
Discrete event simulations (e.g. for networking)
Quantum chemistry
Symbolic computer algebra basics
Optimal control of quantum hardware
APIs for control of commercial quantum hardware
Quantum error mitigation
Confirmed Lecturers
Stefan Krastanov: CS and Physics professor at University of Massachusetts Amherst, lead of the QuantumClifford.jl project and of the NSF Center for Quantum Networks virtual testbed
Katharine Hyatt: Scientist at AWS quantum information science division and past member of the Flatiron institute
Roger Luo: Scientific Software Developer at QuEra Computing, PhD from Perimeter Institute Quantum Intelligence Lab (PIQuL) and University of Waterloo, lead of the Yao.jl and related projects.
Miles Stoudenmire and Karl Pierce: Miles is a scientist at the Flatiron Institute, senior developer of the ITensor framework, the most widespread tensor networks software.
Aaron Trowbridge and Andy Goldschmidt: Aaron is a staff research scientist with the Robotics Institute at Carnegie Mellon University, and Andy is a quantum computing postdoc in Computer Science at the University of Chicago. They are the developers of Piccolo.jl, a modern trajectory optimization framework for quantum optimal control.
Nathan Shammah: CTO of Unitary Fund, with Unitary Fund Members of Technical Staff Misty Wahl, Nate Stemen, and Jordan Sullivan. The Unitary Fund will run a workshop on error mitigation with Mitiq and related technologies during the summer school.
Brian Doolittle: Quantum Physicist and Simulation Tech Lead at Aliro Technologies. PhD in Quantum Information Theory from the University of Illinois Urbana-Champaign.
Di Luo： MIT fellow at NSF AI Institute for Artificial Intelligence and Fundamental Interactions, UCLA ECE assistant professor.