Abstract: A computer implemented method includes receiving, by a control system, an optimization problem expressed as a MWIS on a problem graph. Then encoding the MWIS problem into an energy spectrum of a problem Hamiltonian. Also, determining an XX-driver graph based on an identified independent-cliques (IC), where the edges in the XX-driver graph are the edges between partites in each clique of the IC. Also, determining XX-coupler strengths associated with the XX-driver graph, and specifying a non-stoquastic driver Hamiltonian based on the XX-driver graph and the associated XX-coupler strengths. Also, initializing and programming a time-dependent non-stoquastic system Hamiltonian of the quantum annealing hardware using determined values of parameters included in the problem Hamiltonian and determined values of parameters included in the non-stoquastic driver Hamiltonian.

Abstract: Various adaptations to adiabatic quantum computation and quantum annealing are described. These adaptations generally involve tailoring an initial Hamiltonian so that a local minimum is avoided when a quantum processor is evolved from the initial Hamiltonian to a problem Hamiltonian. The initial Hamiltonian may represent a mixed Hamiltonian that includes both diagonal and off-diagonal terms, where the diagonal terms at least partially define a center point of a first computation space that is at least partially contained within a second computation space. A problem Hamiltonian may be evolved into a low energy state by inhomogeneously inducing disorder in the qubits of the quantum processor. A higher degree of disorder may be induced in a subset of qubits predicted to contribute to a local minimum of the problem Hamiltonian.

Abstract: Various adaptations to adiabatic quantum computation and quantum annealing are described. These adaptations generally involve tailoring an initial Hamiltonian so that a local minimum is avoided when a quantum processor is evolved from the initial Hamiltonian to a problem Hamiltonian. The initial Hamiltonian may represent a mixed Hamiltonian that includes both diagonal and off-diagonal terms, where the diagonal terms at least partially define a center point of a first computation space that is at least partially contained within a second computation space. A problem Hamiltonian may be evolved into a low energy state by inhomogeneously inducing disorder in the qubits of the quantum processor. A higher degree of disorder may be induced in a subset of qubits predicted to contribute to a local minimum of the problem Hamiltonian.

Abstract: Various adaptations to adiabatic quantum computation and quantum annealing are described. These adaptations generally involve tailoring an initial Hamiltonian so that a local minimum is avoided when a quantum processor is evolved from the initial Hamiltonian to a problem Hamiltonian. The initial Hamiltonian may represent a mixed Hamiltonian that includes both diagonal and off-diagonal terms, where the diagonal terms at least partially define a center point of a first computation space that is at least partially contained within a second computation space. A problem Hamiltonian may be evolved into a low energy state by inhomogeneously inducing disorder in the qubits of the quantum processor. A higher degree of disorder may be induced in a subset of qubits predicted to contribute to a local minimum of the problem Hamiltonian.

Abstract: An analog processor, for example a quantum processor may include a plurality of elongated qubits that are disposed with respect to one another such that each qubit may selectively be directly coupled to each of the other qubits via a single coupling device. Such may provide a fully interconnected topology.

Abstract: A system employs a plurality of physical qubits, each having a respective bias operable to up to six differentiable inputs to solve a Quadratic Unconstrained Binary Optimization problem. Some physical qubit couplers are operated as intra-logical qubit couplers to ferromagnetically couple respective pairs of the physical qubits as a logical qubit, where each logical qubit represents a variable from the Quadratic Unconstrained Binary Optimization problem. The logical qubits may include two or more physical qubits.

Abstract: Various adaptations to adiabatic quantum computation and quantum annealing are described. These adaptations generally involve tailoring an initial Hamiltonian so that a local minimum is avoided when a quantum processor is evolved from the initial Hamiltonian to a problem Hamiltonian. The initial Hamiltonian may represent a mixed Hamiltonian that includes both diagonal and off-diagonal terms, where the diagonal terms at least partially define a center point of a first computation space that is at least partially contained within a second computation space. A problem Hamiltonian may be evolved into a low energy state by inhomogeneously inducing disorder in the qubits of the quantum processor. A higher degree of disorder may be induced in a subset of qubits predicted to contribute to a local minimum of the problem Hamiltonian.

Abstract: A system employs a plurality of physical qubits, each having a respective bias operable to up to six differentiable inputs to solve a Quadratic Unconstrained Binary Optimization problem. Some physical qubit couplers are operated as intra-logical qubit couplers to ferromagnetically couple respective pairs of the physical qubits as a logical qubit, where each logical qubit represents a variable from the Quadratic Unconstrained Binary Optimization problem.

Abstract: An analog processor, for example a quantum processor may include a plurality of elongated qubits that are disposed with respect to one another such that each qubit may selectively be directly coupled to each of the other qubits via a single coupling device. Such may provide a fully interconnected topology.