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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…
Hybrid Quantum-Classical Optimization Workflows for the Shipment Selection Problem
Miguel Angel Lopez-Ruiz, Daiwei Zhu, Jonas Hatzenbuhler +8
We present a quantum optimization framework for the Shipment Selection Problem (SSP) in electric freight logistics, developed jointly by IonQ and Einride. Idle gaps arising from st…
End-to-end performance of quantum-accelerated large-scale linear algebra workflows
Daiwei Zhu, Miguel Angel Lopez-Ruiz, François-Henry Rouet +5
Solving large-scale sparse linear systems is a challenging computational task due to the introduction of non-zero elements, or "fill-in". The Graph Partitioning Problem (GPP) arise…
Quantum Kernel Machine Learning for Autonomous Materials Science
Felix Adams, Daiwei Zhu, David W. Steuerman +2
Autonomous materials science, where active learning is used to navigate large compositional phase space, has emerged as a powerful vehicle to rapidly explore new materials. A cruci…