Non-adiabatic implementation of an iSWAP quantum logic gate

    公开(公告)号:US12124922B2

    公开(公告)日:2024-10-22

    申请号:US17433445

    申请日:2019-03-05

    Applicant: Google LLC

    CPC classification number: G06N10/00

    Abstract: Methods, systems and apparatus for generating plunge schedules for implementing iSWAP quantum logic gates between a first qubit and a second qubit. In one aspect, a plunge schedule that defines a trajectory of a detuning between a frequency of the first qubit and a frequency of the second qubit includes, during a first stage, non-adiabatically driving detuning between the frequency of the first qubit and the frequency of the second qubit through a first avoided crossing in a leakage channel, during a second stage, driving detuning between the frequency of the first qubit and the frequency of the second qubit through a second avoided crossing in a swap channel. during a third stage, allowing the first qubit and the second qubit to freely evolve and interact, during a fourth stage, implementing the second stage in reverse order, and during a fifth stage, implementing the first stage in reverse order.

    NONLINEAR CALIBRATION OF A QUANTUM COMPUTING APPARATUS

    公开(公告)号:US20230316117A1

    公开(公告)日:2023-10-05

    申请号:US18298576

    申请日:2023-04-11

    Applicant: Google LLC

    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.

    Nonlinear calibration of a quantum computing apparatus

    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

    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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