3 citations · 6 across the 6 of their papers we have counts for
3 papers · 1 filter
Accelerating Quantum-Classical Auxiliary-Field Quantum Monte Carlo with Shadow-Trained Neural Quantum States
Justin Provazza, Oliver Knitter, Joshua Goings +4
Quantum-classical auxiliary-field quantum Monte Carlo (QC-AFQMC) uses a trial state prepared on a quantum computer to improve the accuracy of the classical AFQMC algorithm. State-o…
Orbital-Rotation Shadow Tomography Reduces the Classical Cost of Quantum-Classical Auxiliary-Field Quantum Monte Carlo
Luning Zhao, Joshua Goings, Evgeny Epifanovsky +1
Quantum-classical auxiliary-field quantum Monte Carlo (QC-AFQMC) is a promising route to using quantum computers for strongly correlated electronic structure problems, but its scal…
Measuring what matters: A scalable framework for application-level quantum benchmarking
Willie Aboumrad, Claudio Girotto, Joshua Goings +16
As quantum computing systems continue to mature, there is an increasing need for benchmarking methodologies that capture performance in terms of meaningful, application-level metri…