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公开(公告)号：US20230299951A1
公开(公告)日：2023-09-21
申请号：US18117232
申请日：2023-03-03
Applicant: Google LLC
Inventor： Hartmut Neven , Edward Henry Farhi
CPC classification number: H04L9/0852 , B82Y10/00 , G06N3/063 , G06N3/08 , G06N10/00 , G06N20/00 , H04L2209/34
Abstract: A quantum neural network architecture. In one aspect, a quantum neural network trained to perform a machine learning task includes: an input quantum neural network layer comprising (i) multiple qubits prepared in an initial quantum state encoding a machine learning task data input, and (ii) a target qubit, a sequence of intermediate quantum neural network layers, each intermediate quantum neural network layer comprising multiple quantum logic gates that operate on the multiple qubits and target qubit; and an output quantum neural network layer comprising a measurement quantum gate that operates on the target qubit and provides as output data representing a solution to the machine learning task.
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公开(公告)号：US11657315B2
公开(公告)日：2023-05-23
申请号：US17339276
申请日：2021-06-04
Applicant: Google LLC
Inventor： Yuezhen Niu , Hartmut Neven , Vadim Smelyanskiy , Sergio Boixo Castrillo
Abstract: Methods, systems, and apparatus for implementing a unitary quantum gate on one or more qubits. In one aspect, a method includes the actions designing a control pulse for the unitary quantum gate, comprising: defining a universal quantum control cost function, wherein the control cost function comprises a qubit leakage penalty term representing i) coherent qubit leakage, and ii) incoherent qubit leakage across all frequency components during a time dependent Hamiltonian evolution that realizes the unitary quantum gate; adjusting parameters of the time dependent Hamiltonian evolution to vary a control cost according to the control cost function such that leakage errors are reduced; generating the control pulse using the adjusted parameters; and applying the control pulse to the one or more qubits to implement the unitary quantum gate.
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公开(公告)号：US11651263B2
公开(公告)日：2023-05-16
申请号：US16624037
申请日：2017-12-15
Applicant: Google LLC
Inventor： John Martinis , Yu Chen , Hartmut Neven , Dvir Kafri
IPC: G06N10/00 , G06F30/25 , G06K9/62 , G06F18/214
CPC classification number: G06N10/00 , G06F18/214 , G06F30/25
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.
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公开(公告)号：US11562285B2
公开(公告)日：2023-01-24
申请号：US17339125
申请日：2021-06-04
Applicant: Google LLC
Inventor： Ryan Babbush , Hartmut Neven
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.
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公开(公告)号：US11449760B2
公开(公告)日：2022-09-20
申请号：US16096237
申请日：2016-12-30
Applicant: Google LLC
Inventor： Vasil S. Denchev , Masoud Mohseni , Hartmut Neven
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.
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Patent Agency Ranking
公开(公告)号：US20220180238A1
公开(公告)日：2022-06-09
申请号：US17678897
申请日：2022-02-23
Applicant: Google LLC
Inventor： Masoud Mohseni , Hartmut Neven
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for constructing and programming quantum hardware for machine learning processes. A Quantum Statistic Machine (QSM) is described, consisting of three distinct classes of strongly interacting degrees of freedom including visible, hidden and control quantum subspaces or subsystems. The QSM is defined with a programmable non-equilibrium ergodic open quantum Markov chain with a unique attracting steady state in the space of density operators. The solution of an information processing task, such as a statistical inference or optimization task, can be encoded into the quantum statistics of an attracting steady state, where quantum inference is performed by minimizing the energy of a real or fictitious quantum Hamiltonian. The couplings of the QSM between the visible and hidden nodes may be trained to solve hard optimization or inference tasks.
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公开(公告)号：US11244240B2
公开(公告)日：2022-02-08
申请号：US16301863
申请日：2016-05-17
Applicant: Google LLC
Inventor： John Martinis , Nan Ding , Ryan Babbush , Sergei V. Isakov , Hartmut Neven , Vadim Smelyanskiy , Sergio Boixo Castrillo
IPC: G06N10/00
Abstract: Methods and apparatus for estimating the fidelity of quantum hardware. In one aspect, a method includes accessing a set of quantum gates; sampling a subset of quantum gates from the set of quantum gates, wherein the subset of quantum gates defines a quantum circuit; applying the quantum circuit to a quantum system and performing measurements on the quantum system to determine output information of the quantum system; calculating output information of the quantum system based on application of the quantum circuit to the quantum system; and estimating a fidelity of the quantum circuit based on the determined output information and the calculated output information of the quantum system.
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公开(公告)号：US11113620B2
公开(公告)日：2021-09-07
申请号：US16067338
申请日：2016-12-22
Applicant: GOOGLE LLC
Inventor： Hartmut Neven
IPC: G06N10/00 , G06N7/00 , G06F15/163
Abstract: Methods and apparatus for enhancing simulated annealing with quantum fluctuations. In one aspect, a method includes obtaining an input state; performing simulated annealing on the input state with a temperature reduction schedule until a decrease in energy is below a first minimum value; terminating the simulated annealing in response to determining that the decrease in energy is below the first minimum level; outputting a first evolved state and first temperature value; reducing the temperature to a minimum temperature value; performing quantum annealing on the first evolved state with a transversal field increase schedule until a completion of a second event occurs; terminating the quantum annealing in response to determining that a completion of the second event has occurred; outputting a second evolved state as a subsequent input state for the simulated annealing, and determining that the completion of the first event has occurred.
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公开(公告)号：US11055626B2
公开(公告)日：2021-07-06
申请号：US16355293
申请日：2019-03-15
Applicant: Google LLC
Inventor： Ryan Babbush , Hartmut Neven
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.
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公开(公告)号：US10657455B2
公开(公告)日：2020-05-19
申请号：US16062076
申请日：2015-12-16
Applicant: Google LLC , Alireza Shabani Barzegar , Pedram Roushan , Yu Chen , Hartmut Neven
Inventor： Alireza Shabani Barzegar , Pedram Roushan , Yu Chen , Hartmut Neven
IPC: G06N10/00 , G01R33/035 , H01P3/00
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.
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