Part 1 On the theory of near-term quantum advantage | Bill Fefferman (The University of Chicago)
Computational complexity of near-term quantum experiments Part 1 On the theory of near-term quantum advantage Lecture 1 notes https://www.ias.edu/sites/defau...
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Computational complexity of near-term quantum experiments
Part 1 On the theory of near-term quantum advantage
Lecture 1 notes
https://www.ias.edu/sites/default/files/billfefferman-lectures-pcmi-out.pdf
Problem set 1
https://www.ias.edu/sites/default/files/problems-fefferman.pdf
A critical goal for the field of quantum computation is experimental quantum advantage -- a demonstration of any quantum computation that is prohibitively hard for classical computers. Quantum advantage is both a necessary milestone on the path to useful, fault-tolerant quantum computers as well as a test of quantum theory in the realm of
high complexity. In these lectures I will discuss the theory of near-term experimental quantum advantage. I will highlight the current evidence for believing that near-term quantum experiments can solve problems that are classically intractable as well as give an overview of the state of classical simulation algorithms for these experiments.
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The 2023 Program: Quantum Computation
Organizers: David Gosset, University of Waterloo; Aram Harrow, MIT; Stacey Jeffery, CWI and QuSoft; Ryan O'Donnell, Carnegie Mellon University; and Thomas Vidick, Caltech
Very recently we have seen experiments at the boundary of the "quantum computing advantage", where quantum computers can massively outperform classical ones at certain tasks. These advances highlight the need for further mathematical understanding of the computational power of near-term quantum devices. The goal of the 2023 GSS is to dive deeply into the mathematics relevant for building near-term quantum computers, analyzing their power, and putting them to use. Minicourses will include: overviews of quantum learning, information theory, and linear-algebraic algorithms; recent advances in quantum error-correcting codes; and, the complexity theory of random circuits and Hamiltonians.
Structure:
The Graduate Summer School at PCMI consists of a series of several interwoven minicourses on different aspects of the main research theme of that summer. These courses are taught by leading experts in the field, chosen not only for their stature in the field but their pedagogical abilities. Each minicourse comprises three to five lectures. Each course is accompanied by a daily problem session, structured to help students develop facility with the material.
2023 Schedule
Week 1
 Andras: Quantum Fourier transform beyond Shor's algorithm
 Omar: Quantum information theory
 Srinivasan: Overview of quantum learning theory
Week 2
 Ewin: Quantum and quantum-inspired linear algebra
 Nicolas: Quantum LDPC codes
 Yassine: Quantum query complexity
Week 3
 Bill: Computational complexity of near-term quantum experiments
 Jeongwan: Topological aspects of quantum codes
 Sandy: Quantum Hamiltonian complexity
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The GSS takes place within the broader structure of PCMI, so there are many researchers at all levels in the field in attendance, as well as participants in the other PCMI programs.
ias.edu/PCMI
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