+++ title = "Curriculum" +++
Four 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.
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.
In the extended sessions we will cover many of the following topics:
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<h3>Confirmed Lecturers</h3>
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: Scientist at the Flatiron Institute, senior developer of the ITensor framework, the most widespread tensor networks software
Nathan Shammah: CTO of Unitary Fund. The Unitary Fund will run a workshop on error mitigation and related technologies during the summer school