Chapter 8 Quantum computing in automata theory
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G. Ignisha Rajathi
Abstract
In the contemporary era we dwell in, every now and then, new technologies are developed by master brains such as researchers and scientists. This also paves the way to discover replacements to classical computers. One such progression among the great inventions is the essence of quantum computing. They are brought to light for the purpose of solving problems and scenarios solved by classical computers but in a more effective way and in the least span of time. The study of quantum computing focuses on finding new ways to compute by using quantum physics phenomena. A qubit, in contrast to a typical computer bit, can be either 0 or 1, or it can be a superposition of both 0 and 1. Quantum theory commemorates with automata theory, thereby formulating quantum finite automata. Quantum finite automaton, or basically a deterministic finite automaton, is one of the simplest models of computation, which is an input-driven model, which takes an input, and according to the input, we just read the machine, and it changes its state. This proves that any quantum finite automata are completely capable of recognizing languages like Tally with given cut point too. Such languages recognized by a cut point, by quantum finite automata, are called stochastic languages. It further collaborates with the chemical industry with its qubit power over molecular collide, interactive models, and collaborative string processing using nonregular languages.
Abstract
In the contemporary era we dwell in, every now and then, new technologies are developed by master brains such as researchers and scientists. This also paves the way to discover replacements to classical computers. One such progression among the great inventions is the essence of quantum computing. They are brought to light for the purpose of solving problems and scenarios solved by classical computers but in a more effective way and in the least span of time. The study of quantum computing focuses on finding new ways to compute by using quantum physics phenomena. A qubit, in contrast to a typical computer bit, can be either 0 or 1, or it can be a superposition of both 0 and 1. Quantum theory commemorates with automata theory, thereby formulating quantum finite automata. Quantum finite automaton, or basically a deterministic finite automaton, is one of the simplest models of computation, which is an input-driven model, which takes an input, and according to the input, we just read the machine, and it changes its state. This proves that any quantum finite automata are completely capable of recognizing languages like Tally with given cut point too. Such languages recognized by a cut point, by quantum finite automata, are called stochastic languages. It further collaborates with the chemical industry with its qubit power over molecular collide, interactive models, and collaborative string processing using nonregular languages.
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- List of contributing authors IX
- Chapter 1 Digital transformation technology and tools: shaping the future of primary health care 1
- Chapter 2 Predictive maintenance of industrial machines using data collected through IoT sensors and analyzed by machine learning algorithms 27
- Chapter 3 A deep survey on quantum computing technologies 49
- Chapter 4 Machine learning and deep learning 71
- Chapter 5 From evolution to revolution: the contemporary development of quantum computing 85
- Chapter 6 Real-time big data analytics 107
- Chapter 7 Quantum processors/networks/sensors 129
- Chapter 8 Quantum computing in automata theory 147
- Chapter 9 Quantum computing: future of artificial intelligence and its applications 163
- Chapter 10 A leap among quantum ML and DL models: a review 185
- Chapter 11 A perspective study on quantum machine learning models for the areas of medicine, materials, sensing, and communication 205
- Chapter 12 Quantum computing: application-specific need of the hour 225
- Chapter 13 Industrial Internet of things and Industry 4.0: a learner’s perspectives toward quantum technologies 243
- Chapter 14 Applications of quantum AI for healthcare 271
- Biography 289
- Index 291
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- List of contributing authors IX
- Chapter 1 Digital transformation technology and tools: shaping the future of primary health care 1
- Chapter 2 Predictive maintenance of industrial machines using data collected through IoT sensors and analyzed by machine learning algorithms 27
- Chapter 3 A deep survey on quantum computing technologies 49
- Chapter 4 Machine learning and deep learning 71
- Chapter 5 From evolution to revolution: the contemporary development of quantum computing 85
- Chapter 6 Real-time big data analytics 107
- Chapter 7 Quantum processors/networks/sensors 129
- Chapter 8 Quantum computing in automata theory 147
- Chapter 9 Quantum computing: future of artificial intelligence and its applications 163
- Chapter 10 A leap among quantum ML and DL models: a review 185
- Chapter 11 A perspective study on quantum machine learning models for the areas of medicine, materials, sensing, and communication 205
- Chapter 12 Quantum computing: application-specific need of the hour 225
- Chapter 13 Industrial Internet of things and Industry 4.0: a learner’s perspectives toward quantum technologies 243
- Chapter 14 Applications of quantum AI for healthcare 271
- Biography 289
- Index 291
