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Design of Reversible Quantum Logic Structures in CMOS Technology.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Design of Reversible Quantum Logic Structures in CMOS Technology.
Author:	Canga, Bahar.
Published:	Ann Arbor : ProQuest Dissertations & Theses, 2021
Description:	170 p.
Notes:	Source: Masters Abstracts International, Volume: 83-03.
Notes:	Advisor: Indovina, Mark A.
Contained By:	Masters Abstracts International83-03.
Subject:	Electrical engineering.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28717174
ISBN:	9798538110155

Design of Reversible Quantum Logic Structures in CMOS Technology.
Canga, Bahar.

Design of Reversible Quantum Logic Structures in CMOS Technology. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 170 p.

Source: Masters Abstracts International, Volume: 83-03.

Thesis (M.S.)--Rochester Institute of Technology, 2021.

This item must not be sold to any third party vendors.

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.

ISBN: 9798538110155Subjects--Topical Terms:

454503
Electrical engineering.
Subjects--Index Terms:

Carry-lookahead Adder

Design of Reversible Quantum Logic Structures in CMOS Technology.
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500 $a Source: Masters Abstracts International, Volume: 83-03.
500 $a Advisor: Indovina, Mark A.
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506 $a This item must not be sold to any third party vendors.
520 $a 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.
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653 $a Carry-lookahead Adder
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653 $a Logic gates
653 $a Reversible logic
653 $a Testing
653 $a Vedic
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