Abstract
Reversible logic gates have an equal number of inputs and outputs, which also makes it possible to reverse calculate and reconstruct the inputs from the outputs. Quantum logic elements are inherently reversible and requires very little energy to operate. Some of the most common uses of Quantum Computers are in the design of Convolutional Neural Networks (CNN), Deep Neural Networks (DNN) and for machine learning (ML) purposes. In this research, the reversible logic gates were designed with 45ηm CMOS technology modeled after reversible quantum logic gates. As a proof of concept, hardware that provided Sigmoid Neuron Functionality was carried out by processing the MNIST Dataset, a handwritten digit database for number recognition.
Library of Congress Subject Headings
Quantum computing; Reversible computing; Metal oxide semiconductors, Complementary--Design and construction
Publication Date
8-2021
Document Type
Thesis
Student Type
Graduate
Degree Name
Electrical Engineering (MS)
Department, Program, or Center
Electrical Engineering (KGCOE)
Advisor
Mark A. Indovina
Advisor/Committee Member
Dan Phillips
Advisor/Committee Member
Carlos Barrios
Recommended Citation
Canga, Bahar, "Design of Reversible Quantum Logic Structures in CMOS Technology" (2021). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/10872
Campus
RIT – Main Campus
Plan Codes
EEEE-MS
