Quantum-inspired method and system for clustering of data
OwnerRomán Oscar Orús Lacort, Pablo Bermejoinventors
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Abstract
A computer-implemented method for establishing clusters for a set of data points in a data set is described. The method comprises in a first step a building of a cost function for the data points in the form of a Hamiltonian, followed by creating from the cost function a tensor network comprising a plurality of tensors. The tensor network is subsequently passed to a processor for performing algebraic operations on the tensors in the tensor network using the processor to update iteratively the tensors in the tensor network. Finally, the method comprises outputting the updated tensors. The cluster into which the data points are clustered and be determined from the parameters of the updated tensors in the tensor network.
Claims10
A computer-implemented method for establishing clusters for a set of data points in a data set, the method comprising:
- building a cost function for the data points in the form of a Hamiltonian;
- creating from the cost function a tensor network comprising a plurality of tensors;
- passing the tensor network to a processor;
- performing algebraic operations on the tensors in the tensor network using the processor to update iteratively the tensors in the tensor network;
- and
- outputting the updated tensors.
A system for establishing clusters for a set of data points in a data set, the system comprising:
- a data storage unit for storing the data set;
- a central processing unit for calculating the Euclidean distances between the data points in the data set and constructing a cost function from the Euclidean distances;
- a quantum processor for receiving the cost function from the central processing unit and solving the cost function to identify a minimum in the cost function.
Dependencies are inferred from the claim text.