Kenneth Merz, PhD , of Cleveland Clinic's Center for Computational Life Sciences and a team are exploring how quantum computers can work with supercomputers to better simulate molecule behavior.
Simulating large molecule stability and behavior requires more time and power than is possible on even the most advanced supercomputer. Dr. Merz and his team developed a strategy for overcoming this barrier by combining the power of a quantum computer with the accuracy of a supercomputer in a study published in the Journal of Chemical Theory and Computation.
"Current state quantum computers are extremely powerful, but they do not yet have error correction capabilities," Dr. Merz says. "By combining the power of a quantum computer with the error correction capabilities of a supercomputer, we can start to simulate and predict how molecules behave enhancing our ability to understand and treat disease."
Supercomputers have millions of processors that can work on different parts of a problem at the same time. This capability is essential for a process known as high-performance computing, which runs multiple tasks simultaneously on multiple computers or processors. For this project, high-performance computing was used to perform an advanced technique known as Density Matrix Embedding Theory, which breaks down large, complex molecules into smaller, manageable pieces that researchers can study in detail.
Once the molecules are broken down into smaller pieces, the researchers can calculate the ground-state energy, or the lowest possible energy a molecule can reach. Ground-state energy predicts molecule stability and potential interactions with other substances.
Dr. Merz and his team used IBM Quantum System One located onsite at Cleveland Clinic's main campus for a technique called Sample-Based Quantum Diagonalization. To begin, the researchers use the quantum computer to complete the complex calculations required to determine the different possible electron configurations for the pieces of the molecule. The quantum computer then takes samples of the different possible configurations that are then sent back to the supercomputer to combine the results and complete the final analysis.
The team tested their hybrid computing method on a hydrogen ring of 18 atoms and cyclohexane. The model was not only able to correctly predict the relative stability of the molecules – it did so using fewer qubits than would be needed to do the whole simulation on a quantum computer alone.
"This is a groundbreaking step in computational research that demonstrates how near-term quantum computers can advance biomedical research," Dr. Merz says.
