SYSTEM AND METHOD OF QUANTUM STOCHASTIC ROUNDING USING SILICON BASED QUANTUM DOT ARRAYS

    公开(公告)号:US20220147314A1

    公开(公告)日:2022-05-12

    申请号:US17522873

    申请日:2021-11-09

    申请人: equal1.labs Inc.

    摘要: A novel and useful system and method of quantum stochastic rounding using silicon based quantum dot arrays. Unitary noise is derived from a probability of detecting a particle within a quantum dot array structure comprising position based charge qubits with two time independent basis states |0> and |1>. A two level electron tunneling device such as an interface device, qubit or other quantum structure is used to generate quantum noise. The electron tunneling device includes a reservoir of particles, a quantum dot, and a barrier that is used to control tunneling between the reservoir and the quantum dot. A detector circuit connected to the device outputs a digital stream corresponding to the probability of a particle of being detected. Controlling the bias applied to the barrier controls the probability of detection. Thus, the probability density function (PDF) of the output unitary noise can be controlled to correspond to a desired probability. The unitary noise is used to perform stochastic rounding by controlling the bias applied to the barrier in accordance with a remainder of numbers to be rounded.

    SYSTEM AND METHOD OF GENERATING QUANTUM UNITARY NOISE USING SILICON BASED QUANTUM DOT ARRAYS

    公开(公告)号:US20220149823A1

    公开(公告)日:2022-05-12

    申请号:US17522835

    申请日:2021-11-09

    申请人: equal1.labs Inc.

    摘要: A novel and useful system and method of generating quantum unitary noise using silicon based quantum dot arrays. Unitary noise is derived from a probability of detecting a particle within a quantum dot array structure comprising position based charge qubits with two time independent basis states |0> and |1>. A two level electron tunneling device such as an interface device, qubit or other quantum structure is used to generate quantum noise. The electron tunneling device includes a reservoir of particles, a quantum dot, and a barrier that is used to control tunneling between the reservoir and the quantum dot. A detector circuit connected to the device outputs a digital stream corresponding to the probability of a particle of being detected. Controlling the bias applied to the barrier controls the probability of detection. Thus, the probability density function (PDF) of the output unitary noise can be controlled to correspond to a desired probability. The unitary noise can be used in stochastic rounding by controlling the bias applied to the barrier in accordance with a remainder of numbers to be rounded.

    Accelerated Learning In Neural Networks Incorporating Quantum Unitary Noise And Quantum Stochastic Rounding Using Silicon Based Quantum Dot Arrays

    公开(公告)号:US20220147824A1

    公开(公告)日:2022-05-12

    申请号:US17522888

    申请日:2021-11-09

    申请人: equal1.labs Inc.

    摘要: A novel and useful system and method of accelerated learning in neural networks using silicon based quantum dot arrays. Unitary noise is derived from a probability of detecting a particle within a quantum dot array structure comprising position based charge qubits with two time independent basis states |0> and |1>. A two level electron tunneling device such as an interface device, qubit or other quantum structure is used to generate quantum noise. The electron tunneling device includes a reservoir of particles, a quantum dot, and a barrier that is used to control tunneling between the reservoir and the quantum dot. Controlling the bias applied to the barrier controls the probability of detection. Thus, the probability density function (PDF) of the output unitary noise can be controlled to correspond to a desired probability. The quantum unitary noise is injected into one or more layers of an artificial neural network (ANN) to improve the learning and training process. The quantum noise source is also used to perform stochastic rounding in the ANN. The PDF of the quantum noise source output is set to a desired value in accordance with the remainder portion of input numbers within the layers of the ANN to be rounded.