Optically coupled nitrogen vacancy-defect system for scalable qubit arrays

    公开(公告)号:US11972318B2

    公开(公告)日:2024-04-30

    申请号:US16388312

    申请日:2019-04-18

    发明人: Michele Reilly

    IPC分类号: G06N10/00 G06E1/00

    CPC分类号: G06N10/00 G06E1/00

    摘要: Described herein are systems and methods for coupling Nitrogen Vacancy (NV)-defects in a quantum computing architecture. A diamond wafer comprises separated implantation sites, at least a portion of which comprise a single NV-defect. An optical cavity system comprises cavity sites aligned to the implantation sites. An integrated optics system includes a first chip module comprising optical waveguides and associated switchable elements, photon sources, photon detectors, and fiber optic connections. A first switchable element couples a first pair of NV-defects by splitting a beam emitted by a photon source, via a first optical waveguide, to the cavity sites aligned to the implantation sites of the first pair of NV-defects. A second switchable element couples a second pair of NV-defects by splitting a beam emitted by a photon source, via a second optical waveguide, to the cavity sites aligned to the implantation sites of the second pair of NV-defects.

    OPTICAL COMPUTING SYSTEM WITH DISAGGREGATED MEMORY

    公开(公告)号:US20240045464A1

    公开(公告)日:2024-02-08

    申请号:US18364983

    申请日:2023-08-03

    申请人: Lightmatter, Inc.

    IPC分类号: G06E1/00

    CPC分类号: G06E1/00

    摘要: Described herein are embodiments of a photonic computing system comprising one or more processors in communication with disaggregated memory through one or more optical channels. The disaggregated memory comprises multiple memory units placed on a photonic substrate that includes a photonic network that can be programmed to configure which of the memory units can be accessed by each of the processor(s).

    System and method for scalable optical interconnect for quantum computing

    公开(公告)号:US11768340B2

    公开(公告)日:2023-09-26

    申请号:US17466581

    申请日:2021-09-03

    IPC分类号: G02B6/42 G06E1/00 G06N10/00

    摘要: The present disclosure relates to an interconnect system for interfacing an electronic subsystem to a qubit package, wherein the qubit package has a plurality of independent qubits. The system makes use of an optical fiber cable having a plurality of optical fibers, which is interfaced to the electronic subsystem. A 3D optical structure is used which has a plurality of internal waveguides, and which is configured to interface the optical fiber cable to the qubit package. The 3D optical structure further has at least one subsystem for using the plurality of waveguides to receive signals of a first type from at least one of the qubits package or the optical fiber cable, to convert the signals from the first type to a second type, and to transmit the signals in the second type to the other one of the fiber optic cable or the qubit package.

    Optical control of atomic quantum bits for phase control of operation

    公开(公告)号:US11710061B2

    公开(公告)日:2023-07-25

    申请号:US17313450

    申请日:2021-05-06

    IPC分类号: G06N10/00 G06E1/00 B82Y10/00

    CPC分类号: G06N10/00 G06E1/00 B82Y10/00

    摘要: The disclosure describes various aspects of optical control of atomic quantum bits (qubits) for phase control operations. More specifically, the disclosure describes methods for coherently controlling quantum phases on atomic qubits mediated by optical control fields, applying to quantum logic gates, and generalized interactions between qubits. Various attributes and settings of optical/qubit interactions (e.g., atomic energy structure, laser beam geometry, polarization, spectrum, phase, background magnetic field) are identified for imprinting and storing phase in qubits. The disclosure further describes how these control attributes are best matched in order to control and stabilize qubit interactions and allow extended phase-stable quantum gate sequences.

    Neural network data processing apparatus and method

    公开(公告)号:US11687775B2

    公开(公告)日:2023-06-27

    申请号:US16579665

    申请日:2019-09-23

    发明人: Jacek Konieczny

    IPC分类号: G06E1/00 G06N3/08 G06N3/04

    CPC分类号: G06N3/08 G06N3/04

    摘要: Embodiments of the invention relates to a data processing apparatus comprising a processor configured to provide a neural network, wherein the neural network comprises a neural network layer being configured to generate from an array of input data values an array of output data values based on a plurality of position dependent kernels and a plurality of input data values of the array of input data values. Moreover, embodiments of the invention relates to a corresponding data processing method.

    Neural network method and apparatus

    公开(公告)号:US11681915B2

    公开(公告)日:2023-06-20

    申请号:US16897461

    申请日:2020-06-10

    IPC分类号: G06E1/00 G06N3/08 G06N20/10

    CPC分类号: G06N3/08 G06N20/10

    摘要: A processor-implemented method of performing a convolution operation is provided. The method includes obtaining input feature map data and kernel data, determine the kernel data based on a number of input channels of the input feature map, a number of output channels of an output feature map, and a number of groups of the input feature map data and a number of groups of the kernel data related to the convolution operation, and performing the convolution operation based on the input feature map data and the determined kernel data.

    SOLVING OPTIMIZATION PROBLEMS WITH PHOTONIC CROSSBARS

    公开(公告)号:US20230176606A1

    公开(公告)日:2023-06-08

    申请号:US17643256

    申请日:2021-12-08

    IPC分类号: G06E1/00

    CPC分类号: G06E1/00

    摘要: The invention is directed to solving an optimization problem. The method operates a photonic crossbar array structure including N input lines and M output lines, which are interconnected at junctions via N×M photonic memory devices, where N≥2 and M≥2. The photonic memory devices are programmed to store respective weights in accordance with the optimization problem. The photonic crossbar array structure is operated as follows. First, the method determines values of L input vectors of N components each, where L≥2. Second, based on the determined values, N electromagnetic signals are generated, where each of the generated signals multiplexes L input signals encoded at respective wavelengths, so as for the N electromagnetic signals to map the L input vectors of N components each. Third, the N electromagnetic signals generated are applied to the N input lines of the photonic crossbar array structure.

    Dynamic processing element array expansion

    公开(公告)号:US11568238B2

    公开(公告)日:2023-01-31

    申请号:US16456414

    申请日:2019-06-28

    摘要: A computer-implemented method includes receiving a neural network model that includes a tensor operation, and dividing the tensor operation into sub-operations. The sub-operations includes at least two sub-operations that have no data dependency between the two sub-operations. The computer-implemented method further includes assigning a first sub-operation in the two sub-operations to a first computing engine, assigning a second sub-operation in the two sub-operations to a second computing engine, and generating instructions for performing, in parallel, the first sub-operation by the first computing engine and the second sub-operation by the second computing engine. An inference is then made based on a result of the first sub-operation, a result of the second sub-operation, or both. The first computing engine and the second computing engine are in a same integrated circuit device or in two different integrated circuit devices.