A method includes causing activation, at a first time, of a first set of squeezed light sources from a plurality of squeezed light sources of a Gaussian boson sampling (GBS) circuit. At a second time after the first time, a first photon statistic is detected at a first output port from a plurality of output ports of the GBS circuit. At a third time after the first time, a second set of squeezed light sources from the plurality of squeezed light sources of the GBS circuit is activated, the second set of squeezed light sources being different from the first set of squeezed light sources. At a fourth time after the third time, a second photon statistic is detected at a second output port from the plurality of output ports of the GBS circuit. At least one transformation matrix is estimated that represents a linear optical interferometer of the GBS circuit based on the first photon statistic and the second photon statistic.

A quantum contextual measurement is generated from a quantum device capable of performing continuous time evolution, by generating a first measurement result and a second measurement result and combining the first measurement result and the second measurement result to generate the quantum contextual measurement. The first measurement result may be generated by initializing the quantum device to a first initial quantum state, applying a first continuous time evolution to the first initial state to generate a first evolved state, and measuring the first evolved state to generate the first measurement result. A similar process may be applied to generate a second evolved state which is at least approximately equal to the first evolved state, and then applying another continuous time evolution to the second evolved state to generate a third evolved state, and measuring the third evolved state to generate the second measurement result.

Aspects of the present disclosure describe a method including compressing and uncompressing redundant quantum information encoded in quantum computers; processing quantum information in the compressed space; and computing, in response to determining the ansatz terms, a set of optimal transformations.

Using a classical data model executing on a classical processor, a set of classical features is scored. A classical feature comprises a first attribute of a resource, and a score of the classical feature comprises an evaluation of a utility of the classical feature in predicting a result involving the resource. Using a quantum data model executing on a quantum processor and the scored set of classical features, a set of quantum features is scored. The scored set of classical features and the scored set of quantum features are correlated, forming a combined set of scored features. Using the combined set of scored features and a first set of input data of a resource, a valuation of the resource is calculated.

Using a classical data model executing on a classical processor, a set of classical features is scored. A score of a classical feature comprises an evaluation of a utility of the classical feature in predicting a result involving a resource. Using a quantum data model executing on a quantum processor and the scored set of classical features, a set of quantum features is scored. The quantum data model is executed a number of times previously determined using a set of results of executing the quantum data model on a set of annotated training data. The scored set of classical features and the scored set of quantum features are correlated, forming a combined set of scored features. Using the combined set of scored features and a first set of input data of a resource, a valuation of the resource is calculated.

In a general aspect, input data for a computer process are preprocessed by a preprocessor unit that includes a quantum processor. In some aspects, a preprocessor unit obtains input data for a computer process that is configured to run on a computer processing unit. Randomized parameter values are computed for variable parameters of a quantum logic circuit based on the input data. A classical processor in the preprocessor unit computes the randomized parameter values from the input data and a set of random numbers. A quantum processor in the preprocessor unit produces quantum processor output data by executing the quantum logic circuit having the randomized parameter values assigned to the variable parameters. Preprocessed data generated based on the quantum processor output data are then provided as the input for the computer process configured to run on the computer processing unit.

A quantum chemistry method includes causing display, via a processor, of a representation of a plurality of controlled single-excitation quantum gates. A selection of a subset of controlled single-excitation quantum gates from the plurality of controlled single-excitation quantum gates is received at the processor. A particle-preserving unitary for a quantum chemistry simulation is identified based on the selected subset of controlled single-excitation quantum gates. At least one controlled single-excitation quantum gate from the plurality of controlled single-excitation quantum gates can be configured to apply a Givens rotation.

A quantum chemistry method includes causing display, via a processor, of a representation of a plurality of controlled single-excitation quantum gates. A selection of a subset of controlled single-excitation quantum gates from the plurality of controlled single-excitation quantum gates is received at the processor. A particle-preserving unitary for a quantum chemistry simulation is identified based on the selected subset of controlled single-excitation quantum gates. At least one controlled single-excitation quantum gate from the plurality of controlled single-excitation quantum gates can be configured to apply a Givens rotation.

Disclosed is a minimum searching method for searching a minimum in N (N is a natural number) data by a computing device including at least one processor. The method for searching the minimum may include: determining a threshold; initializing Qubits to include indexes representing addresses in which the N data are recorded, respectively, and the threshold in a superposition state; returning, from a superposition-state index, superposition-state data corresponding to the superposition-state index through a quantum memory; comparing the superposition-state data with the threshold in parallel through a quantum comparator (Q-comp); and searching the minimum based on the comparison result.

Disclosed is a minimum searching method for searching a minimum in N (N is a natural number) data by a computing device including at least one processor. The method for searching the minimum may include: determining a threshold; initializing Qubits to include indexes representing addresses in which the N data are recorded, respectively, and the threshold in a superposition state; returning, from a superposition-state index, superposition-state data corresponding to the superposition-state index through a quantum memory; comparing the superposition-state data with the threshold in parallel through a quantum comparator (Q-comp); and searching the minimum based on the comparison result.