Quantum computing

Application-wise we mostly focus on life science problems, where the group has a long history. For implementation and verification, we employ the D-Wave quantum annealer at the Jülich Supercomputing Centre for QA and gate-based quantum hardware from IBM for QAOA.

We have tested using quantum computing for folding and design of lattice proteins. Folding lattice protein chains, through energy minimization, is a hard discrete optimization problem for long chains. At the same time, exact results are available for short chains. This makes lattice protein folding a useful test case for quantum optimization algorithms. To this end, we developed a novel mapping of lattice protein folding onto a quadratic unconstrained binary optimization (QUBO) problem, valid for arbitrary chain lengths. Using this QUBO representation, we swiftly and consistently folded 64 units long chains on the hybrid quantum-classical annealer offered by D-Wave. With pure QA, one is restricted to shorter chains. In ongoing research, we explore using QAOA to solve lattice protein problems.

While our interest in quantum computing applications is new, we have many years of experience in complex systems and computational biomolecular physics. In the latter area, we have investigated, and are still interested in, topics such as protein aggregation and phase separation.

The group is part of COSHE, the Computational Science for Health and Environment theme at CEC.