Abstract: A user interface (UI), data structures and algorithms facilitate programming, analyzing, debugging, embedding, and/or modifying problems that are embedded or to be embedded on an analog processor (e.g., quantum processor), increasing computational efficiency and/or accuracy of problem solutions. The UI provides graph representations (e.g., source graph, target graph and correspondence therebetween) with nodes and edges which may map to hardware components (e.g., qubits, couplers) of the analog processor. Characteristics of solutions are advantageously represented spatially associated (e.g., overlaid or nested) with characteristics of a problem. Characteristics (e.g., bias state) may be represented by color, pattern, values, icons. Issues (e.g., broken chains) may be detected and alerts provided.

Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples.

Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples.

Abstract: A user interface (UI), data structures and algorithms facilitate programming, analyzing, debugging, embedding, and/or modifying problems that are embedded or to be embedded on an analog processor (e.g., quantum processor), increasing computational efficiency and/or accuracy of problem solutions. The UI provides graph representations (e.g., source graph, target graph and correspondence therebetween) with nodes and edges which may map to hardware components (e.g., qubits, couplers) of the analog processor. Characteristics of solutions are advantageously represented spatially associated (e.g., overlaid or nested) with characteristics of a problem. Characteristics (e.g., bias state) may be represented by color, pattern, values, icons. Issues (e.g., broken chains) may be detected and alerts provided.

Abstract: A user interface (UI), data structures and algorithms facilitate programming, analyzing, debugging, embedding, and/or modifying problems that are embedded or to be embedded on an analog processor (e.g., quantum processor), increasing computational efficiency and/or accuracy of problem solutions. The UI provides graph representations (e.g., source graph, target graph and correspondence therebetween) with nodes and edges which may map to hardware components (e.g., qubits, couplers) of the analog processor. Characteristics of solutions are advantageously represented spatially associated (e.g., overlaid or nested) with characteristics of a problem. Characteristics (e.g., bias state) may be represented by color, pattern, values, icons. Issues (e.g., broken chains) may be detected and alerts provided.

Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples.

Abstract: A user interface (UI), data structures and algorithms facilitate programming, analyzing, debugging, embedding, and/or modifying problems that are embedded or to be embedded on an analog processor (e.g., quantum processor), increasing computational efficiency and/or accuracy of problem solutions. The UI provides graph representations (e.g., source graph, target graph and correspondence therebetween) with nodes and edges which may map to hardware components (e.g., qubits, couplers) of the analog processor. Characteristics of solutions are advantageously represented spatially associated (e.g., overlaid or nested) with characteristics of a problem. Characteristics (e.g., bias state) may be represented by color, pattern, values, icons. Issues (e.g., broken chains) may be detected and alerts provided.

Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples.

Abstract: A user interface (UI), data structures and algorithms facilitate programming, analyzing, debugging, embedding, and/or modifying problems that are embedded or to be embedded on an analog processor (e.g., quantum processor), increasing computational efficiency and/or accuracy of problem solutions. The UI provides graph representations (e.g., source graph, target graph and correspondence therebetween) with nodes and edges which may map to hardware components (e.g., qubits, couplers) of the analog processor. Characteristics of solutions are advantageously represented spatially associated (e.g., overlaid or nested) with characteristics of a problem. Characteristics (e.g., bias state) may be represented by color, pattern, values, icons. Issues (e.g., broken chains) may be detected and alerts provided.

Abstract: Generate an automorphism of the problem graph, determine an embedding of the automorphism to the hardware graph and modify the embedding of the problem graph into the hardware graph to correspond to the embedding of the automorphism to the hardware graph. Determine an upper-bound on the required chain strength. Calibrate and record properties of the component of a quantum processor with a digital processor, query the digital processor for a range of properties. Generate a bit mask and change the sign of the bias of individual qubits according to the bit mask before submitting a problem to a quantum processor, apply the same bit mask to the bit result. Generate a second set of parameters of a quantum processor from a first set of parameters via a genetic algorithm.

Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples.

Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples.

Abstract: Generate an automorphism of the problem graph, determine an embedding of the automorphism to the hardware graph and modify the embedding of the problem graph into the hardware graph to correspond to the embedding of the automorphism to the hardware graph. Determine an upper-bound on the required chain strength. Calibrate and record properties of the component of a quantum processor with a digital processor, query the digital processor for a range of properties. Generate a bit mask and change the sign of the bias of individual qubits according to the bit mask before submitting a problem to a quantum processor, apply the same bit mask to the bit result. Generate a second set of parameters of a quantum processor from a first set of parameters via a genetic algorithm.

Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples.