An IonQ collaboration with Oak Ridge National Laboratory (ORNL) has demonstrated a new approach to scalable quantum computing.
The collaboration combined IonQ’s enterprise-grade trapped-ion technology with ORNL’s world-class quantum technologies expertise to develop a novel hybrid quantum algorithm based on the Quantum Imaginary Time Evolution principle (QITE).
This noise-tolerant method enables near-optimal and optimal solutions for complex combinatorial optimization problems on IonQ’s commercially available hardware.
The results showed that QITE can significantly outperform other quantum optimization algorithms such as QAOA (Quantum Approximate Optimization Algorithm) in both time-to-solution and circuit depth – paving the way for tackling large optimization problems on near-term quantum computers.
By using this hybrid quantum algorithm, IonQ and ORNL were able to reduce the number of two-qubit gates by over 85% for a 28 qubit problem compared to a QAOA solution, improving over the state of the art.
The hybrid quantum algorithm was proved out on IonQ’s Aria and Forte systems which were used inside the optimization loop, paving the way for scaling to larger problem sizes.
Dr. Martin Roetteler, Senior Director, Quantum Solutions, IonQ, said: “This work is an important step forward in scaling quantum computing systems for practical commercial applications – we’re excited about the potential this has for industries ranging from logistics to energy systems, finance and life sciences.” Dr. Travis Humble, Director, Quantum Science Center, ORNL, said: “The development of quantum imaginary time evolution-based methods demonstrates our commitment to leveraging near-term quantum computers for real-world, industrial challenges.”
