An optical system may include a target, a laser source, and an optical lens assembly. The optical lens assembly may include a mounting flange mounted adjacent the laser source, an objective lens aligned between the laser source and the target, and at least one adjustment stage coupled between the mounting flange and the objective lens. The adjustment stage may include a ball joint having a ball joint body, a ball receiver tube, and adjustable fasteners coupling the ball joint body to the ball receiver tube. The adjustment stage may include a translation tube having ramps thereon, and adjustable fasteners coupled between the mounting flange and the translation tube. In addition, the adjustment stage may include the mounting flange having a threaded surface thereon, and a focus ring rotatably coupled to the threaded surface of the mounting flange.

A device includes: a plurality of qubits arranged in a two-dimensional array and a plurality of readout resonators. Each readout resonator of a first readout resonator group is arranged to electromagnetically couple to a respective qubit of a first qubit group. Each readout resonator of a second readout resonator group is arranged to electromagnetically couple to a respective qubit of a second qubit group. A resonance frequency of each readout resonator of the first readout resonator group is within a first resonance frequency band, and a resonance frequency of each readout resonator of the second readout resonator group is within a second resonance frequency band that is different from the first resonance frequency band.

A device includes: a plurality of qubits arranged in a two-dimensional array and a plurality of readout resonators. Each readout resonator of a first readout resonator group is arranged to electromagnetically couple to a respective qubit of a first qubit group. Each readout resonator of a second readout resonator group is arranged to electromagnetically couple to a respective qubit of a second qubit group. A resonance frequency of each readout resonator of the first readout resonator group is within a first resonance frequency band, and a resonance frequency of each readout resonator of the second readout resonator group is within a second resonance frequency band that is different from the first resonance frequency band.

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 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.

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.

Quantum computing systems and methods are provided. In one example, a quantum computing system includes a quantum system having one or more quantum system qubits and one or more ancilla qubits. The quantum computing system includes one or more quantum gates implemented by the quantum computing system. The quantum gate(s) are operable to configure the one or more ancilla qubits into a known state. The quantum computing system includes a quantum measurement circuit operable to perform a plurality of measurements on the one or more quantum system qubits using the one or more ancilla qubits. The quantum computing system includes one or more processors operable to determine a reduced density matrix for a subset of the quantum system based on a set of the plurality of measurements that include a number of repeated measurements performed using the quantum measurement circuit.

Quantum computing systems and methods are provided. In one example, a quantum computing system includes a quantum system having one or more quantum system qubits and one or more ancilla qubits. The quantum computing system includes one or more quantum gates implemented by the quantum computing system. The quantum gate(s) are operable to configure the one or more ancilla qubits into a known state. The quantum computing system includes a quantum measurement circuit operable to perform a plurality of measurements on the one or more quantum system qubits using the one or more ancilla qubits. The quantum computing system includes one or more processors operable to determine a reduced density matrix for a subset of the quantum system based on a set of the plurality of measurements that include a number of repeated measurements performed using the quantum measurement circuit.

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.