Optimization of Quantum Cellular Automata Majority Gate Using Multiobjective Reinforcement Learning
نویسندگان
چکیده
منابع مشابه
Optimization of Quantum Cellular Automata Majority Gate Using Multiobjective Reinforcement Learning
The Quantum Cellular Automata (QCA) majority block gate, while more robust than the simple or classic version of the gate, is still affected by lithographic manufacturing errors that affect the polarization of each individual QCA and the block circuit. Analysis and correction of these errors has been done using Bayesian, Markovian, or neural network methodologies. The problem with learning an o...
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ژورنال
عنوان ژورنال: IOSR Journal of Computer Engineering
سال: 2016
ISSN: 2278-8727,2278-0661
DOI: 10.9790/0661-1804043345