Keywords
quantum computation, associative memory
Abstract
Quantum computation uses microscopic quantum level effects to perrform computational tasks and has produced results that in some cases are exponentially faster than their classical counterparts by taking advantage of quantum parallelism. The unique characteristics of quantum theory may also be used to create a quantum associative memory with a capacity exponential in the number of neurons. This paper covers necessary high-level quantum mechanical ideas and introduces a simple quantum associative memory. Further, it provides discussion, empirical results and directions for future work.
Original Publication Citation
Ventura, D. and Martinez, T. R., "Quantum Associative Memory with Exponential Capacity", Proceedings of the IEEE International Joint Conference on Neural Networks IJCNN'98, pp. 59-513, 1998.
BYU ScholarsArchive Citation
Martinez, Tony R. and Ventura, Dan A., "Quantum Associative Memory with Exponential Capacity" (1998). Faculty Publications. 1133.
https://scholarsarchive.byu.edu/facpub/1133
Document Type
Peer-Reviewed Article
Publication Date
1998-05-09
Permanent URL
http://hdl.lib.byu.edu/1877/2436
Publisher
IEEE
Language
English
College
Physical and Mathematical Sciences
Department
Computer Science
Copyright Status
© 1998 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Copyright Use Information
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