Systems and methods for hybrid algorithms using cluster contraction

    公开(公告)号:US11537926B2

    公开(公告)日:2022-12-27

    申请号:US16741208

    申请日:2020-01-13

    IPC分类号: G06N10/00 G06F17/18 G06K9/62

    摘要: Systems and methods are described for operating a hybrid computing system using cluster contraction for converting large, dense input to reduced input that can be easily mapped into a quantum processor. The reduced input represents the global structure of the problem. Techniques involve partitioning the input variables into clusters and contracting each cluster. The input variables can be partitioned using an Unweighted Pair Group Method with Arithmetic Mean algorithm. The quantum processor returns samples based on the reduced input and the samples are expanded to correspond to the original input.

    SYSTEMS AND METHODS FOR SIMULATION OF DYNAMIC SYSTEMS

    公开(公告)号:US20200293331A1

    公开(公告)日:2020-09-17

    申请号:US16817210

    申请日:2020-03-12

    摘要: A highly parallelized parallel tempering technique for simulating dynamic systems, such as quantum processors, is provided. Replica exchange is facilitated by synchronizing grid-level memory. Particular implementations for simulating quantum processors by representing cells of qubits and couplers in grid-, block-, and thread-level memory are discussed. Parallel tempering of such dynamic systems can be assisted by modifying replicas based on isoenergetic cluster moves (ICMs). ICMs are generated via secondary replicas which are maintained alongside primary replicas and exchanged between blocks and/or generated dynamically by blocks without necessarily being exchanged. Certain refinements, such as exchanging energies and temperatures through grid-level memory, are also discussed.

    Systems and methods for simulation of dynamic systems

    公开(公告)号:US11567779B2

    公开(公告)日:2023-01-31

    申请号:US16817210

    申请日:2020-03-12

    摘要: A highly parallelized parallel tempering technique for simulating dynamic systems, such as quantum processors, is provided. Replica exchange is facilitated by synchronizing grid-level memory. Particular implementations for simulating quantum processors by representing cells of qubits and couplers in grid-, block-, and thread-level memory are discussed. Parallel tempering of such dynamic systems can be assisted by modifying replicas based on isoenergetic cluster moves (ICMs). ICMs are generated via secondary replicas which are maintained alongside primary replicas and exchanged between blocks and/or generated dynamically by blocks without necessarily being exchanged. Certain refinements, such as exchanging energies and temperatures through grid-level memory, are also discussed.

    SYSTEMS AND METHODS FOR HYBRID ANALOG AND DIGITAL PROCESSING OF A COMPUTATIONAL PROBLEM USING MEAN FIELD UPDATES

    公开(公告)号:US20200311591A1

    公开(公告)日:2020-10-01

    申请号:US16830650

    申请日:2020-03-26

    IPC分类号: G06N10/00 G06F17/18

    摘要: A hybrid computing system for solving a computational problem includes a digital processor, a quantum processor having qubits and coupling devices that together define a working graph of the quantum processor, and at least one nontransitory processor-readable medium communicatively coupleable to the digital processor which stores at least one of processor-executable instructions or data. The digital processor receives a computational problem, and programs the quantum processor with a first set of bias fields and a first set of coupling strengths. The quantum processor generates samples as potential solutions to an approximation of the problem. The digital processor updates the approximation by determining a second set of bias fields based at least in part on the first set of bias fields and a first set of mean fields that are based at least in part on the first set of samples and coupling strengths of one or more virtual coupling devices.

    SYSTEMS AND METHODS FOR HYBRID ALGORITHMS USING CLUSTER CONTRACTION

    公开(公告)号:US20200234172A1

    公开(公告)日:2020-07-23

    申请号:US16741208

    申请日:2020-01-13

    IPC分类号: G06N10/00 G06K9/62 G06F17/18

    摘要: Systems and methods are described for operating a hybrid computing system using cluster contraction for converting large, dense input to reduced input that can be easily mapped into a quantum processor. The reduced input represents the global structure of the problem. Techniques involve partitioning the input variables into clusters and contracting each cluster. The input variables can be partitioned using an Unweighted Pair Group Method with Arithmetic Mean algorithm. The quantum processor returns samples based on the reduced input and the samples are expanded to correspond to the original input.