Abstract:
Solving computational problems may include generating a logic circuit representation of the computational problem, encoding the logic circuit representation as a discrete optimization problem, and solving the discrete optimization problem using a quantum processor. Output(s) of the logic circuit representation may be clamped such that the solving involves effectively executing the logic circuit representation in reverse to determine input(s) that corresponds to the clamped output(s). The representation may be of a Boolean logic circuit. The discrete optimization problem may be composed of a set of miniature optimization problems, where each miniature optimization problem encodes a respective logic gate from the logic circuit representation. A quantum processor may include multiple sets of qubits, each set coupled to respective annealing signal lines such that dynamic evolution of each set of qubits is controlled independently from the dynamic evolutions of the other sets of qubits.
Abstract:
Various techniques and apparatus permit fabrication of superconductive circuits and structures, for instance Josephson junctions, which may, for example be useful in quantum computers. For instance, a low magnetic flux noise trilayer structure may be fabricated having a dielectric structure or layer interposed between two elements or layers capable of superconducting. A superconducting via may directly overlie a Josephson junction. A structure, for instance a Josephson junction, may be carried on a planarized dielectric layer. A fin may be employed to remove heat from the structure. A via capable of superconducting may have a width that is less than about 1 micrometer. The structure may be coupled to a resistor, for example by vias and/or a strap connector.
Abstract:
Solving computational problems may include generating a logic circuit representation of the computational problem, encoding the logic circuit representation as a discrete optimization problem, and solving the discrete optimization problem using a quantum processor. Output(s) of the logic circuit representation may be clamped such that the solving involves effectively executing the logic circuit representation in reverse to determine input(s) that corresponds to the clamped output(s). The representation may be of a Boolean logic circuit. The discrete optimization problem may be composed of a set of miniature optimization problems, where each miniature optimization problem encodes a respective logic gate from the logic circuit representation. A quantum processor may include multiple sets of qubits, each set coupled to respective annealing signal lines such that dynamic evolution of each set of qubits is controlled independently from the dynamic evolutions of the other sets of qubits.
Abstract:
Solving computational problems may include generating a logic circuit representation of the computational problem, encoding the logic circuit representation as a discrete optimization problem, and solving the discrete optimization problem using a quantum processor. Output(s) of the logic circuit representation may be clamped such that the solving involves effectively executing the logic circuit representation in reverse to determine input(s) that corresponds to the clamped output(s). The representation may be of a multiplication circuit. The discrete optimization problem may be composed of a set of miniature optimization problems, where each miniature optimization problem encodes a respective logic gate from the logic circuit representation. A multiplication circuit may employ binary representations of factors, and these binary representations may be decomposed to reduce the total number of variables required to represent the multiplication circuit.
Abstract:
Systems, methods and aspects, and embodiments thereof relate to unsupervised or semi-supervised features learning using a quantum processor. To achieve unsupervised or semi-supervised features learning, the quantum processor is programmed to achieve Hierarchal Deep Learning (referred to as HDL) over one or more data sets. Systems and methods search for, parse, and detect maximally repeating patterns in one or more data sets or across data or data sets. Embodiments and aspects regard using sparse coding to detect maximally repeating patterns in or across data. Examples of sparse coding include L0 and L1 sparse coding. Some implementations may involve appending, incorporating or attaching labels to dictionary elements, or constituent elements of one or more dictionaries. There may be a logical association between label and the element labeled such that the process of unsupervised or semi-supervised feature learning spans both the elements and the incorporated, attached or appended label.
Abstract:
Analog processors for solving various computational problems are provided. Such analog processors comprise a plurality of quantum devices, arranged in a lattice, together with a plurality of coupling devices. The analog processors further comprise bias control systems each configured to apply a local effective bias on a corresponding quantum device. A set of coupling devices in the plurality of coupling devices is configured to couple nearest-neighbor quantum devices in the lattice. Another set of coupling devices is configured to couple next-nearest neighbor quantum devices. The analog processors further comprise a plurality of coupling control systems each configured to tune the coupling value of a corresponding coupling device in the plurality of coupling devices to a coupling. Such quantum processors further comprise a set of readout devices each configured to measure the information from a corresponding quantum device in the plurality of quantum devices.
Abstract:
Analog processors for solving various computational problems are provided. Such analog processors comprise a plurality of quantum devices, arranged in a lattice, together with a plurality of coupling devices. The analog processors further comprise bias control systems each configured to apply a local effective bias on a corresponding quantum device. A set of coupling devices in the plurality of coupling devices is configured to couple nearest-neighbor quantum devices in the lattice. Another set of coupling devices is configured to couple next-nearest neighbor quantum devices. The analog processors further comprise a plurality of coupling control systems each configured to tune the coupling value of a corresponding coupling device in the plurality of coupling devices to a coupling. Such quantum processors further comprise a set of readout devices each configured to measure the information from a corresponding quantum device in the plurality of quantum devices.
Abstract:
Various techniques and apparatus permit fabrication of superconductive circuits and structures, for instance Josephson junctions, which may, for example be useful in quantum computers. For instance, a low magnetic flux noise trilayer structure may be fabricated having a dielectric structure or layer interposed between two elements or layers capable of superconducting. A superconducting via may directly overlie a Josephson junction. A structure, for instance a Josephson junction, may be carried on a planarized dielectric layer. A fin may be employed to remove heat from the structure. A via capable of superconducting may have a width that is less than about 1 micrometer. The structure may be coupled to a resistor, for example by vias and/or a strap connector.
Abstract:
Analog processors for solving various computational problems are provided. Such analog processors comprise a plurality of quantum devices, arranged in a lattice, together with a plurality of coupling devices. The analog processors further comprise bias control systems each configured to apply a local effective bias on a corresponding quantum device. A set of coupling devices in the plurality of coupling devices is configured to couple nearest-neighbor quantum devices in the lattice. Another set of coupling devices is configured to couple next-nearest neighbor quantum devices. The analog processors further comprise a plurality of coupling control systems each configured to tune the coupling value of a corresponding coupling device in the plurality of coupling devices to a coupling. Such quantum processors further comprise a set of readout devices each configured to measure the information from a corresponding quantum device in the plurality of quantum devices.
Abstract:
Various techniques and apparatus permit fabrication of superconductive circuits and structures, for instance Josephson junctions, which may, for example be useful in quantum computers. For instance, a low magnetic flux noise trilayer structure may be fabricated having a dielectric structure or layer interposed between two elements or layers capable of superconducting. A superconducting via may directly overlie a Josephson junction. A structure, for instance a Josephson junction, may be carried on a planarized dielectric layer. A fin may be employed to remove heat from the structure. A via capable of superconducting may have a width that is less than about 1 micrometer. The structure may be coupled to a resistor, for example by vias and/or a strap connector.