PhD Comprehensive Examination
Optimization Algorithms for Quantum Deep Learning
PhD Candidate: Guillaume Verdon-Akzam
PhD Candidate: Guillaume Verdon-Akzam
Master's Candidate: Jaron Huq
PhD Candidate: Muhammet Yurtalan
Supervisors: Adrian Lupascu and Zbigniew Wasilewski
Thesis on display in the Engineering graduate office, E7-7402.
Oral defence in EIT 3142.
PhD Candidate: Jean-Philippe MacLean
Supervisor: Kevin Resch
PhD thesis presentation in QNC 0101.
PhD Candidate: Matthew Amy
Supervisor: Michele Mosca
Oral defence in QNC B204.
The design and compilation of correct, efficient quantum circuits is integral to the future operation of quantum computers. This thesis makes contributions to the problems of optimizing and verifying quantum circuits, with an emphasis on the development of formal models for such purposes. We also present software implementations of these methods, which together form a full stack of tools for the design of optimized, formally verified quantum oracles.
Master's Candidate: Maria Papageorgiou
Much of the structure of quantum field theory (QFT) is predicated on the principle of locality. Adherence to locality is pursuant to convictions deduced from relativity, and is achieved in QFT by the association of regions of spacetime with algebras of observables. Although, by construction, the observables of QFT are local objects, one may also consider characterizing the spatial or spacetime features of a state.
Master's Candidate: Emma McKay
PhD Candidate: Olivia Di Matteo
Supervisor: Michele Mosca
Thesis available from the Science graduate office, PHY 2013.
Oral defence in QNC B204.
Candidate: Christopher Chamberland, Physics and Astronomy
Supervisor: Raymond Laflamme
Matthew Amy, PhD candidate
David R. Cheriton School of Computer Science