5 citations · 6 across the 6 of their papers we have counts for
5 papers · 1 filter
Snowmass White Paper: Quantum Computing Systems and Software for High-energy Physics Research
Travis S. Humble, Andrea Delgado, Raphael Pooser +23
Quantum computing offers a new paradigm for advancing high-energy physics research by enabling novel methods for representing and reasoning about fundamental quantum mechanical phe…
Mode connectivity in the QCBM loss landscape
Kathleen E. Hamilton, Emily Lynn, Vicente Leyton-Ortega +2
Quantum circuit Born machines (QCBMs) and training via variational quantum algorithms (VQAs) are key applications for near-term quantum hardware. QCBM ansätze designs are unique in…
Mode connectivity in the loss landscape of parameterized quantum circuits
Kathleen E. Hamilton, Emily Lynn, Raphael C. Pooser
Variational training of parameterized quantum circuits (PQCs) underpins many workflows employed on near-term noisy intermediate scale quantum (NISQ) devices. It is a hybrid quantum…
Scalable quantum processor noise characterization
Kathleen E. Hamilton, Tyler Kharazi, Titus Morris +3
Measurement fidelity matrices (MFMs) (also called error kernels) are a natural way to characterize state preparation and measurement errors in near-term quantum hardware. They can…
Generative model benchmarks for superconducting qubits
Kathleen E. Hamilton, Eugene F. Dumitrescu, Raphael C. Pooser
In this work we experimentally demonstrate how generative model training can be used as a benchmark for small ( qubits) quantum devices. Performance is quantified using three d…