Using Quantum Computers to Study Random Close Packing of Granular Discs We reformulate the problem of granular random close packing of 2D discs as a Quadratic Unconstrained Binary Optimization in order to utilize the DWave 2000Q quantum annealing computer. The solution is a set of ground states corresponding to jammed configurations in which no single particle can be moved without creating a nonzero potential. The problem is adapted to the quantum computer by discretizing space and mapping each point onto physical quantumbits (qubits). An objective function is derived that defines the system energy for arbitrary particle locations, subject to constraints biasing solutions toward a predetermined number of particles. Uniquely, the quantum computer samples and returns minimum values of this function finding low energy states, a subset of which are physically realizable solutions we seek. While quantum computingu0027s technological infancy restricts our study to proofofconcept, our work still shows promise for efficient analysis of complex granular problems.

Solving Quantum Chemistry Problems with a DWave Quantum Annealer Quantum annealing devices have been subject to various analyses in order to classify their usefulness for practical applications. While it has been successfully proven that such systems can in general be used for solving combinatorial optimization problems, they have not been used to solve chemistry applications. In this paper we apply a mapping, put forward by Xia et al. (The Journal of Physical Chemistry B 122.13 (2017): 33843395.), from a quantum chemistry Hamiltonian to an Ising spin glass formulation and find the ground state energy with a quantum annealer. Additionally we investigate the scaling in terms of needed physical qubits on a quantum annealer with limited connectivity. To the best of our knowledge, this is the first experimental study of quantum chemistry problems on quantum annealing devices.