IonQ, in collaboration with Oak Ridge National Laboratory (ORNL), has launched a hybrid quantum algorithm that considerably enhances the effectivity of quantum optimization duties. Based mostly on Quantum Imaginary Time Evolution (QITE), the algorithm reduces the variety of two-qubit gates required by over 85% for a 28-qubit drawback in comparison with the Quantum Approximate Optimization Algorithm (QAOA). This enchancment was validated utilizing IonQ’s Aria and Forte quantum methods.
The brand new algorithm gives superior noise tolerance, making it notably efficient for fixing advanced combinatorial optimization issues. Its growth aligns with the rising demand for sensible quantum computing purposes in areas similar to power grid administration, logistics optimization, monetary danger evaluation, and pharmaceutical analysis. The strategy not solely optimizes computational sources but in addition lays the groundwork for scaling quantum options to bigger drawback sizes.
Highlighting the importance of this achievement, Dr. Martin Roetteler of IonQ famous that the development demonstrates quantum computing’s potential to deal with real-world industrial challenges. Dr. Travis Humble of ORNL emphasised the tactic’s sensible utility, bridging present quantum capabilities with business wants.
For an in depth technical overview, discuss with the preprint Performant near-term quantum combinatorial optimization here and the IonQ’s press launch here.
December 31, 2024
