IonQ and Kipu Quantum report record protein-folding and optimization results on Forte systems
On 2025-06-19 IonQ and Kipu Quantum announced they solved what they described as the largest known protein-folding problem run on quantum hardware to date, a 3D case of up to 12 amino acids, plus all-to-all-connected QUBO and HUBO optimization instances using up to 36 qubits. All instances ran on IonQ's Forte-generation trapped-ion systems using Kipu's non-variational BF-DCQO (Bias-Field Digitized Counterdiabatic Quantum Optimization) algorithm. The companies extended their collaboration with early access to IonQ's planned 64-qubit and 256-qubit systems.
A named-metric benchmark (12-amino-acid protein folding, up to 36 qubits via BF-DCQO) qualifies under the academic/benchmark filter and is relevant to the drug-discovery sub-domain, but lacks independent third-party verification and industry-wide implications, placing it at §8 band-5.
If the BF-DCQO advantage holds on IonQ's larger Forte/Tempo systems, it strengthens the case for near-term trapped-ion optimization workloads in pharma and logistics; absent peer review, the 'record' framing remains a vendor claim pending replication.