collaborators

11 papers

quant-ph2026

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…

quant-ph2026

Protein folding on a 64 qubit trapped-ion hardware via counterdiabatic quantum optimization

Alejandro Gomez Cadavid, Pavle Nikačević, Pranav Chandarana +11

We report the largest trapped-ion hardware demonstration of lattice protein-folding optimization to date, using bias-field digitized counterdiabatic quantum optimization (BF-DCQO)…

quant-ph2026

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…

quant-ph2026

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…

quant-ph2026

Large-scale portfolio optimization on a trapped-ion quantum computer

Alejandro Gomez Cadavid, Ananth Kaushik, Pranav Chandarana +10

We present an end-to-end pipeline for large-scale portfolio selection with cardinality constraints and experimentally demonstrate it on trapped-ion quantum processors using hardwar…

quant-ph2026

Pathfinding Quantum Simulations of Neutrinoless Double-Beta Decay

Ivan A. Chernyshev, Roland C. Farrell, Marc Illa +10

We present results from co-designed quantum simulations of the neutrinoless double-beta decay of a simple nucleus in 1+1D quantum chromodynamics using IonQ's Forte-generation trapp…