Speaker
Description
Quantum phase estimation (QPE) is a leading route to chemically accurate ground-state energies, but its practicality hinges on quantum resource costs. In this talk I present concrete strategies to lower those costs. First, I show how orbital optimization improves initial-state overlap with the exact ground state, boosting QPE's success probability. Second, I detail how the Hamiltonian one-norm can be lowered using symmetry-compressed double factorization. Finally, I discuss how dynamic correlation can be included by enlarging the active space while controlling growth of the one-norm through careful basis-set selection. Together, these techniques (and follow-on methods) yield substantially lower resource estimates for running QPE on fault-tolerant hardware.
