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IonQ and Kipu Quantum Set New Records for Protein Folding and Optimization Problems
ByAinvest
Saturday, Jun 21, 2025 4:36 am ET1min read
IonQ and Kipu Quantum have achieved a groundbreaking solution for protein folding on a quantum computer, setting new records in solving complex quantum optimization problems. The collaboration used IonQ's Forte generation systems and Kipu Quantum's BF-DCQO algorithm to solve a 12-amino acid protein folding problem, as well as all-to-all connected spin-glass problems and MAX-4-SAT problems using up to 36 qubits. Future plans involve using 64-qubit and 256-qubit chips to tackle industrial challenges in fields like drug discovery and logistics.
IonQ and Kipu Quantum have achieved a significant milestone in quantum computing by solving the most complex known protein folding problem ever executed on a quantum computer. The collaboration, announced on June 19, 2025, leveraged IonQ's Forte generation systems and Kipu Quantum's Bias-Field Digitized Counterdiabatic Quantum Optimization (BF-DCQO) algorithm to tackle a 12-amino acid protein folding problem, as well as all-to-all connected spin-glass problems and MAX-4-SAT problems using up to 36 qubits [1].This breakthrough marks the largest known quantum computation of its kind to date, demonstrating the synergy between Kipu's innovative algorithmic framework and IonQ's state-of-the-art hardware [2]. The results have significant implications for biology and drug development, showcasing the potential of quantum computing in addressing complex industrial challenges.
Future plans include extending the collaboration to gain early access to IonQ's upcoming 64-qubit and 256-qubit chips, which could unlock the potential to address even larger, industrially relevant challenges in fields such as drug discovery, logistics, and material design [1].
References:
[1] https://finance.yahoo.com/news/ionq-kipu-quantum-break-protein-111508624.html
[2] https://www.morningstar.com/news/business-wire/20250619505324/ionq-and-kipu-quantum-break-new-performance-records-for-protein-folding-and-optimization-problems
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