Identifying Gamma Radiation Anomaly Signals Using Quantum Computation Methods

Date

2022-07-28

Authors

Foate, Joshua
Valdez, Luis
Alamaniotis, Miltos

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Abstract

Collected data using a radiation detector to identify anomalies in the presence of naturally occurring radioactive material. Samples of the anomaly signals were put into a Hopfield neural network to train the network to identify whether data from the detector was an anomaly or background radiation. Converting our data into a 3SAT (3- Satisfiability) problem and use Grover's algorithm to find the solutions for Hopfield Artificial Neural Network memory

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undergraduate student works

Citation

Department

Electrical and Computer Engineering