Abstract: The present disclosure describes a system with a boson sampler that generates an output bosonic state by performing a transformation on an input bosonic state and produces measurement outcomes indicating the presence or absence of bosons in output modes. A controller of the system receives these measurement outcomes, generates binary sequences based on the presence or absence of bosons, and determines a solution to a binary optimization problem.

Abstract: A system may include a boson sampler configured to generate an output bosonic state by performing a parametrized unitary transformation on an input bosonic state. The system may include a controller coupled to the boson sampler. The controller may be configured to: (i) determine a set of one or more parameter values that defines the parametrized unitary transformation performed by the boson sampler, (ii) operate the boson sampler multiple times with the boson sampler tuned to the determined set of parameter values, (iii) record one or more responses of the boson sampler for the multiple operations (iv) generate binary sequences based on the responses, (v) calculate values of an objective function of a binary optimization problem, and (vi) determine a solution to the binary optimization problem based on the calculated values.

Abstract: A generative system for producing one or more conformers of a selected molecule includes a processor, and a memory coupled to the processor, wherein machine-readable instructions are stored in the memory, and wherein the machine-readable instructions, when executed on the processor, configure the processor to receive by a generative model both a training dataset and an input dataset, and generate by the generative model one or more synthetic conformers of the selected molecule using the input dataset associated with the selected molecule.

Abstract: Methods are provided for generating a dataset (e.g., an image). According to an example, the method comprises controlling a boson sampler to produce one or more integer sequences, each of the one or more integer sequences representative of a measurement outcome of one or more photodetectors of the boson sampler; determining, from the one or more integer sequences, one or more latent vectors; providing the determined one or more latent vectors to a trained artificial neural network (ANN) configured to convert one or more latent vectors to a generated dataset; and outputting the generated dataset. Methods for training an ANN are also provided. Systems and computer-readable storage media are also described.

Abstract: Methods and systems are described herein for determining a solution to a binary optimization problem. In examples, a system described herein comprises a controller and a boson sampler which together implement a hybrid quantum-classical process. Computer-readable media are also described herein.

Abstract: Methods and systems are described herein for determining a solution to a binary optimization problem. In examples, a system described herein comprises a controller and a boson sampler which together implement a hybrid quantum-classical process. Computer-readable media are also described herein.