Learning, Optimizing, and Simulating Fermions with Quantum Computers

Understand

Fermions are fundamental particles which obey seemingly bizarre quantum-mechanical principles, yet constitute all the ordinary matter that we inhabit.

• As such, their study is heavily motivated from both fundamental and practical incentives.
• In this dissertation, we will explore how the tools of quantum information and computation can assist us on both of these fronts.
• We primarily do so through the task of partial state learning: tomographic protocols for acquiring a reduced, but sufficient, classical description of a quantum system.