SYSTEMS AND METHODS FOR IMPROVING COMPUTATIONAL EFFICIENCY OF PROCESSOR-BASED DEVICES IN SOLVING CONSTRAINED QUADRATIC MODELS

    公开(公告)号:US20240248947A1

    公开(公告)日:2024-07-25

    申请号:US18286624

    申请日:2022-03-30

    CPC classification number: G06F17/11

    Abstract: Systems and methods for optimization algorithms, updating samples, and penalizing constraint violations are discussed. A method for updating samples includes receiving a problem definition with an objective function and constraint functions, an initial sample, and a value for a progress parameter. For each variable a total energy change is determined based on an objective energy change based on the sample value for the variable and one or more terms of the objective function that include the variable and a constraint energy change based on the sample value for the variable and each of the constraint functions defined by the variable. A sampling distribution is selected based on the variable type and an updated value is sampled based on the total energy change and the progress parameter. An updated sample is returned with an updated value for each variable of the set of variables. Such may improve operation of processor-based systems.

    SYSTEMS AND METHODS FOR INCREASING DIVERSITY OF SAMPLES

    公开(公告)号:US20240176842A1

    公开(公告)日:2024-05-30

    申请号:US18142374

    申请日:2023-05-02

    Inventor: Alex Zucca

    CPC classification number: G06F17/11

    Abstract: Systems and methods for operating a computer system to generate samples having improved diversity are discussed. A processor receives a problem definition with a problem Hamiltonian defined over a set of variables and samples one or more values for the set of variables from the problem Hamiltonian, the one or more values for the set of variables comprising a first set of samples. At least a subset of the first set of samples is selected, and a diversity Hamiltonian based on the at least a subset of the first set of samples is generated. The problem Hamiltonian and the diversity Hamiltonian are combined to generate a combined Hamiltonian, and one or more values for the set of variables are sampled from the combined Hamiltonian, the one or more values for the set of variables comprising a second set of samples.

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