most citedProtein folding with an all-to-all trapped-ion quantum computer

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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

Quantum Feature Selection with Higher-Order Binary Optimization on Trapped-Ion Hardware

Carlos Flores-Garrigós, Anton Simen, Qi Zhang +6

We present a quantum feature-selection framework based on a higher-order unconstrained binary optimization (HUBO) formulation that explicitly incorporates multivariate dependencies…

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-ph20251 cited

Protein folding with an all-to-all trapped-ion quantum computer

Sebastián V. Romero, Alejandro Gomez Cadavid, Pavle Nikačević +8

We experimentally demonstrate that the bias-field digitized counterdiabatic quantum optimization (BF-DCQO) algorithm, implemented on IonQ's fully connected trapped-ion quantum proc…

quant-ph2025

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…