Lockheed Martin Corporation

Daniel M Davenport

Rosemary DeSantis Paradis

Steven H Adachi

Maxwell P Henderson

David Menaker

Sarah M Taylor

Aspects of the disclosure provide a method for configuring a Quantum Annealing (QA) device. Then QA device has a plurality of qubits and a plurality of couplers at overlapping intersections of the qubits. The method includes mapping a node of a neural network that have a plurality of nodes and connections between the nodes to a qubit in the QA device, and mapping a connection of the neural network to a coupler at an intersection in the QA device where two qubits corresponding to two nodes connected by the connection intersect. The method further includes mapping a node of the neural network to a chain of qubits. In an embodiment, a coupling between qubits in the chain is configured to be a ferromagnetic coupling in order to map the node of the neural network to the chain of qubits.

Quantum-assisted training of neural networks

Diaculture of text can be determined or analyzed by tokenizing words of the text according to a rule set to generate tokenized text, the rule set defining: a first set of grammatical types of words, which are words that are replaced with tokens that respectively indicate a grammatical type of a respective word, and a second set of grammatical types of words, which are words that are passed as tokens without changing. Grams can be constructed from the tokenized text, each gram including one or more of consecutive tokens from the tokenized text. The grams can be compared to a training data set that corresponds to a known diaculture to obtain a comparison result that indicates how well the text matches the training data set for the known diaculture.

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Rustburg, VA, United States of America

Daniel M Davenport