Abstract: In a general aspect, a quantum computing method is described. In some aspects, a control system in a quantum computing system assigns subsets of qubit devices in a quantum processor to respective cores. The control system identifies boundary qubit devices residing between the cores in the quantum processor and generates control sequences for each respective core. A signal delivery system in communication with the control system and the quantum processor receives control signals to execute the control sequences, and the control signals are applied to the respective cores in the quantum processor.

Abstract: In a general aspect, a gate is formed for a quantum processor. In some implementations, an arbitrary program is received. The arbitrary program includes a first sequence of quantum logic gates, which includes a parametric XY gate. A native gate set is identified, which includes a set of quantum logic gates associated with a quantum processing unit. A second sequence of quantum logic gates corresponding to the parametric XY gate is identified, which includes a parametric quantum logic gate. Each of the quantum logic gates in the second sequence is selected from the native gate set. A native program is generated. The native program includes a third sequence of quantum logic gates. The third sequence of quantum logic gates corresponds to the first sequence of quantum logic gates and includes the second sequence of quantum logic gates. The native program is provided for execution by the quantum processing unit.

Abstract: In a general aspect, a gate is formed for a quantum processor. In some implementations, an arbitrary program is received. The arbitrary program includes a first sequence of quantum logic gates, which includes a parametric XY gate. A native gate set is identified, which includes a set of quantum logic gates associated with a quantum processing unit. A second sequence of quantum logic gates corresponding to the parametric XY gate is identified, which includes a parametric quantum logic gate. Each of the quantum logic gates in the second sequence is selected from the native gate set. A native program is generated. The native program includes a third sequence of quantum logic gates. The third sequence of quantum logic gates corresponds to the first sequence of quantum logic gates and includes the second sequence of quantum logic gates. The native program is provided for execution by the quantum processing unit.

Abstract: In a general aspect, a quantum computing method is described. In some aspects, a control system in a quantum computing system assigns subsets of qubit devices in a quantum processor to respective cores. The control system identifies boundary qubit devices residing between the cores in the quantum processor and generates control sequences for each respective core. A signal delivery system in communication with the control system and the quantum processor receives control signals to execute the control sequences, and the control signals are applied to the respective cores in the quantum processor.

Abstract: In a general aspect, a computing system is configured to execute a quantum approximate optimization algorithm. In some aspects, a control system identifies a pair of qubit devices in a quantum processor. The quantum processor includes a connection that provides coupling between the pair of qubit devices. ZZ coupling between the pair of qubit devices is activated to execute a cost function defined in the quantum approximate optimization algorithm. The cost function is associated with a maximum cut problem, and the ZZ coupling is activated by allowing the pair of qubits to evolve under a natural Hamiltonian for a time period ?. One or more of the pair of qubit devices is measured to obtain an output from an execution of the quantum approximate optimization algorithm.

Abstract: In a general aspect, a quantum computing method is described. In some aspects, a control system in a quantum computing system assigns subsets of qubit devices in a quantum processor to respective cores. The control system identifies boundary qubit devices residing between the cores in the quantum processor and generates control sequences for each respective core. A signal delivery system in communication with the control system and the quantum processor receives control signals to execute the control sequences, and the control signals are applied to the respective cores in the quantum processor.

Abstract: In a general aspect, a quantum processor has a modular architecture. In some aspects, a modular quantum processor includes first and second quantum processor chips and a cap structure. The first quantum processor chip is supported on a substrate layer and includes a first plurality of qubit devices. The second quantum processor chip is supported on the substrate layer and includes a second plurality of qubit devices. The cap structure is supported on the first and second quantum processor chips and includes a coupler device that provides coupling between at least one of the first plurality of qubit devices with at least one of the second plurality of qubit devices. In some instances, the coupler device is an active coupler device that is configured to selectively couple at least one of the first plurality of qubit devices with at least one of the second plurality of qubit devices.

Abstract: In a general aspect, a computing system is configured to execute a quantum approximate optimization algorithm. In some aspects, a control system identifies a pair of qubit devices in a quantum processor. The quantum processor includes a connection that provides coupling between the pair of qubit devices. ZZ coupling between the pair of qubit devices is activated to execute a cost function defined in the quantum approximate optimization algorithm. The cost function is associated with a maximum cut problem, and the ZZ coupling is activated by allowing the pair of qubits to evolve under a natural Hamiltonian for a time period ?. One or more of the pair of qubit devices is measured to obtain an output from an execution of the quantum approximate optimization algorithm.

Abstract: In a general aspect, a superconducting quantum circuit system is modeled. In some aspects, a graph representing a quantum circuit system is generated. The graph includes vertices and edges; the edges represent circuit elements of the quantum circuit system, and the vertices represent physical connections between the circuit elements. Inverse inductances, conductances, capacitances, and junction inverse inductances are assigned to respective edges of the graph based on a lumped-element approximation of the quantum circuit system. A coordinate system is determined based on the graph, and a matrix representation of the system is determined based on the coordinate system. A Hamiltonian for the quantum circuit system is determined using the matrix representation, and the quantum circuit system is simulated based on the Hamiltonian.

Abstract: In a general aspect, a superconducting quantum circuit system is modeled. In some aspects, a graph representing a quantum circuit system is generated. The graph includes vertices and edges; the edges represent circuit elements of the quantum circuit system, and the vertices represent physical connections between the circuit elements. Inverse inductances, conductances, capacitances, and junction inverse inductances are assigned to respective edges of the graph based on a lumped-element approximation of the quantum circuit system. A coordinate system is determined based on the graph, and a matrix representation of the system is determined based on the coordinate system. A Hamiltonian for the quantum circuit system is determined using the matrix representation, and the quantum circuit system is simulated based on the Hamiltonian.

Abstract: In a general aspect, a superconducting quantum circuit system is modeled. In some aspects, a graph representing a quantum circuit system is generated. The graph includes vertices and edges; the edges represent circuit elements of the quantum circuit system, and the vertices represent physical connections between the circuit elements. Inverse inductances, conductances, capacitances, and junction inverse inductances are assigned to respective edges of the graph based on a lumped-element approximation of the quantum circuit system. A coordinate system is determined based on the graph, and a matrix representation of the system is determined based on the coordinate system. A Hamiltonian for the quantum circuit system is determined using the matrix representation, and the quantum circuit system is simulated based on the Hamiltonian.

Abstract: In a general aspect, a computing system is configured to execute a quantum approximate optimization algorithm. In some aspects, a control system identifies a pair of qubit devices in a quantum processor. The quantum processor includes a connection that provides coupling between the pair of qubit devices. ZZ coupling between the pair of qubit devices is activated to execute a cost function defined in the quantum approximate optimization algorithm. The cost function is associated with a maximum cut problem, and the ZZ coupling is activated by allowing the pair of qubits to evolve under a natural Hamiltonian for a time period ?. One or more of the pair of qubit devices is measured to obtain an output from an execution of the quantum approximate optimization algorithm.

Abstract: In a general aspect, a quantum computing method is described. In some aspects, a control system in a quantum computing system assigns subsets of qubit devices in a quantum processor to respective cores. The control system identifies boundary qubit devices residing between the cores in the quantum processor and generates control sequences for each respective core. A signal delivery system in communication with the control system and the quantum processor receives control signals to execute the control sequences, and the control signals are applied to the respective cores in the quantum processor.

Abstract: In a general aspect, a superconducting quantum circuit system is modeled. In some aspects, a graph representing a quantum circuit system is generated. The graph includes vertices and edges; the edges represent circuit elements of the quantum circuit system, and the vertices represent physical connections between the circuit elements. Inverse inductances, conductances, capacitances, and junction inverse inductances are assigned to respective edges of the graph based on a lumped-element approximation of the quantum circuit system. A coordinate system is determined based on the graph, and a matrix representation of the system is determined based on the coordinate system. A Hamiltonian for the quantum circuit system is determined using the matrix representation, and the quantum circuit system is simulated based on the Hamiltonian.