Simulating electronic structure with quantum annealing devices and artificial neural networks

One or more non-transitory computer readable media storing a program of instructions that is executable by a device to perform a method for predicting electronic structural information of a molecule, the method comprising:

• generating quantum simulation results for the molecule based on a quantum simulation of an electronic structure of the molecule, wherein the quantum simulation of the electronic structure of the molecule is performed with one or more quantum processing units (QPUs) utilizing qubits;
• creating an input vector comprising data field values derived from the quantum simulation results for the molecule;
• and
• applying an electronic structural information prediction model to generate, based at least in part on the input vector, predicted electronic structural information for the molecule, wherein the electronic structural information prediction model is trained with training data instances corresponding to other types of molecules than said molecule, wherein the training data instances include one or more training instances corresponding to one or more di-atomic molecules.

A system, comprising:

• one or more computing processors;
• one or more non-transitory computer readable media storing a program of instructions that is executable by the one or more computing processors to perform a method for predicting electronic structural information of a molecule, the method comprising:
• generating quantum simulation results for the molecule based on a quantum simulation of an electronic structure of the molecule, wherein the quantum simulation of the electronic structure of the molecule is performed with one or more quantum processing units (QPUs) utilizing qubits;
• creating an input vector comprising data field values derived from the quantum simulation results for the molecule;
• and
• applying an electronic structural information prediction model to generate, based at least in part on the input vector, predicted electronic structural information for the molecule, wherein the electronic structural information prediction model is trained with training data instances corresponding to other types of molecules than said molecule, wherein the training data instances include one or more training instances corresponding to one or more di-atomic molecules.