Probabilistic inference in machine learning using a quantum oracle

    公开(公告)号:US11030548B1

    公开(公告)日:2021-06-08

    申请号:US16413273

    申请日:2019-05-15

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using a quantum oracle to make inference in complex machine learning models that is capable of solving artificial intelligent problems. Input to the quantum oracle is derived from the training data and the model parameters, which maps at least part of the interactions of interconnected units of the model to the interactions of qubits in the quantum oracle. The output of the quantum oracle is used to determine values used to compute loss function values or loss function gradient values or both during a training process.

    NONLINEAR CALIBRATION OF A QUANTUM COMPUTING APPARATUS

    公开(公告)号:US20210035005A1

    公开(公告)日:2021-02-04

    申请号:US16624037

    申请日:2017-12-15

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus for nonlinear calibration of quantum computing apparatus. In one aspect, elements in a set of experimental data correspond to a respective configuration of control biases for the quantum computing apparatus. An initial physical model comprising one or more model parameters of the quantum computing apparatus is defined. The model is iteratively adjusted to determine a revised physical model, where at each iteration: a set of predictive data corresponding to the set of experimental data is generated, and elements in the predictive data represent a difference between the two smallest eigenvalues of a Hamiltonian characterizing the system qubits for the previous iteration, and are dependent on at least one model parameter of the physical model for the previous iteration; and the model for the previous iteration is adjusted using the obtained experimental data and the generated set of predictive data for the iteration.

    PROGRAMMABLE UNIVERSAL QUANTUM ANNEALING WITH CO-PLANAR WAVEGUIDE FLUX QUBITS

    公开(公告)号:US20200250570A1

    公开(公告)日:2020-08-06

    申请号:US16857955

    申请日:2020-04-24

    Applicant: Google LLC

    Abstract: A quantum computing device includes multiple co-planar waveguide flux qubits, at least one coupler element arranged such that each co-planar waveguide flux qubit, of the multiple co-planar waveguide flux qubits, is operatively couplable to each other co-planar waveguide flux qubit, of the multiple co-planar waveguide flux qubits, of the quantum computing device, and a tuning quantum device, in which the tuning quantum device is in electrical contact with a first co-planar waveguide flux qubit of the plurality of co-planar waveguide flux qubits and with a second co-planar waveguide flux qubit of the plurality of co-planar waveguide flux qubits.

    QUANTUM ASSISTED OPTIMIZATION
    18.
    发明申请

    公开(公告)号:US20190164059A1

    公开(公告)日:2019-05-30

    申请号:US16096237

    申请日:2016-12-30

    Applicant: Google LLC

    Abstract: Methods and apparatus for quantum assisted optimization. In one aspect, a method includes obtaining a set of initial input states, applying one or more of (i) dynamical thermal fluctuations and (ii) cluster update algorithms to the set of input states and subsequent input states when the states evolve within the classical information processors, applying dynamical quantum fluctuations to the set of input states and subsequent states when the states evolve within the quantum systems and repeating the application steps until a desirable output state is obtained.

    COUPLING ARCHITECTURES FOR SUPERCONDUCTING FLUX QUBITS

    公开(公告)号:US20190147359A1

    公开(公告)日:2019-05-16

    申请号:US16096110

    申请日:2016-12-30

    Applicant: Google LLC

    CPC classification number: G06N10/00 H01L39/025 H01P3/003 H01P7/086

    Abstract: A quantum computing device includes: a first array of qubits arranged along a first axis; and a second array of qubits arranged along a second axis different from the first axis so that the qubits of the second array intersect with the qubits of the first array to form a lattice structure, in which each qubit in the first array is offset along the second axis relative to a directly adjacent qubit in the first array, each qubit in the second array is offset along the first axis relative to a directly adjacent qubit in the second array, and each intersection between a qubit from the first array and a qubit from the second array in the lattice structure comprises a coupler arranged to inductively couple the qubit from the first array to the qubit from the second array.

    Training quantum evolutions using sublogical controls

    公开(公告)号:US10275717B2

    公开(公告)日:2019-04-30

    申请号:US15171778

    申请日:2016-06-02

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus for training quantum evolutions using sub-logical controls. In one aspect, a method includes the actions of accessing quantum hardware, wherein the quantum hardware includes a quantum system comprising one or more multi-level quantum subsystems; one or more control devices that operate on the one or more multi-level quantum subsystems according to one or more respective control parameters that relate to a parameter of a physical environment in which the multi-level quantum subsystems are located; initializing the quantum system in an initial quantum state, wherein an initial set of control parameters form a parameterization that defines the initial quantum state; obtaining one or more quantum system observables and one or more target quantum states; and iteratively training until an occurrence of a completion event.

Patent Agency Ranking