Quantum science and quantum technology are of great current interest in multiple frontiers of many scientific fields ranging from computer science to physics and chemistry, and from engineering to mathematics and statistics. Their developments will likely lead to a new wave of scientific revolutions and technological innovations in a wide range of scientific studies and applications. This paper provides a brief review on quantum communication, quantum information, quantum computation, quantum simulation, and quantum metrology. We present essential quantum properties, illustrate relevant concepts of quantum science and quantum technology, and discuss their scientific developments. We point out the need for statistical analysis in their developments, as well as their potential applications to and impacts on statistics and data science.
Quantum science and quantum technology are of great current interest in multiple frontiers of many scientific fields ranging from computer science to physics and chemistry, and from engineering to mathematics and statistics. Their developments will likely lead to a new wave of scientific revolutions and technological innovations in a wide range of scientific studies and applications. This paper provides a brief review on quantum communication, quantum information, quantum computation, quantum simulation, and quantum metrology. We present essential quantum properties, illustrate relevant concepts of quantum science and quantum technology, and discuss their scientific developments. We point out the need for statistical analysis in their developments, as well as their potential applications to and impacts on statistics and data science.
Quantum computation and quantum information are of great current interest in computer science, mathematics, physical sciences and engineering. They will likely lead to a new wave of technological innovations in communication, computation and cryptography. As the theory of quantum physics is fundamentally stochastic, randomness and uncertainty are deeply rooted in quantum computation, quantum simulation and quantum information. Consequently quantum algorithms are random in nature, and quantum simulation utilizes Monte Carlo techniques extensively. Thus statistics can play an important role in quantum computation and quantum simulation, which in turn offer great potential to revolutionize computational statistics. While only pseudo-random numbers can be generated by classical computers, quantum computers are able to produce genuine random numbers; quantum computers can exponentially or quadratically speed up median evaluation, Monte Carlo integration and Markov chain simulation. This paper gives a brief review on quantum computation, quantum simulation and quantum information. We introduce the basic concepts of quantum computation and quantum simulation and present quantum algorithms that are known to be much faster than the available classic algorithms. We provide a statistical framework for the analysis of quantum algorithms and quantum simulation.
Quantum computation and quantum information are of great current interest in computer science, mathematics, physical sciences and engineering. They will likely lead to a new wave of technological innovations in communication, computation and cryptography. As the theory of quantum physics is fundamentally stochastic, randomness and uncertainty are deeply rooted in quantum computation, quantum simulation and quantum information. Consequently quantum algorithms are random in nature, and quantum simulation utilizes Monte Carlo techniques extensively. Thus statistics can play an important role in quantum computation and quantum simulation, which in turn offer great potential to revolutionize computational statistics. While only pseudo-random numbers can be generated by classical computers, quantum computers are able to produce genuine random numbers; quantum computers can exponentially or quadratically speed up median evaluation, Monte Carlo integration and Markov chain simulation. This paper gives a brief review on quantum computation, quantum simulation and quantum information. We introduce the basic concepts of quantum computation and quantum simulation and present quantum algorithms that are known to be much faster than the available classic algorithms. We provide a statistical framework for the analysis of quantum algorithms and quantum simulation.
Over the past century, quantum theory has taken flight from conceptual breakthroughs, such as wave–particle duality, quantisation of energy, and the uncertainty principle, to practical tools that are the backbone of modern electronics, lasers, semiconductors, and precision measurement systems. In the twenty-first century, this progress under the regime of the second quantum revolution has acquired the ability to directly control, manipulate, and engineer individual quantum systems. Quantum technologies found their pillars in quantum properties, such as superposition, entanglement, and coherence and have exceeded the boundaries of classical physics. The steady theoretical advances, combined with experimental progress, have brought quantum concepts closer to real-life use. Significant progress has made in filed of computation, communication, sensing, navigation, medicine, cyber security, and national defense undr the guidance of quantum technology. This book chapter presents a comprehensive and pedagogical overview of quantum technologies. It highlights quantum computing, quantum communication, and quantum sensing and metrology. The shift of quantum mechanics into practical applications is discussed. Current research trends are reviewed alongside the technological and engineering challenges. The critical issues, such as decoherence, scalability, error correction, standardisation, and workforce development, are discussed, which further highlights the need for global collaboration. Both National governments and the private sector are investing heavily in quantum research. This will act as a booster for quantum technologies to revolutionise information processing, secure communications, and precision measurements. Consequently and will significantly impact the scientific and technological landscape.
Quantum computation and quantum information have attracted considerable attention on multiple frontiers of scientific fields ranging from physics to chemistry and engineering, as well as from computer science to mathematics and statistics. Data science combines statistical methods, computational algorithms, and domain science information to extract knowledge and insights from big data, and to solve complex real-world problems. While it is well-known that quantum computation has the potential to revolutionize data science, much less has been said about the potential of data science to advance quantum computation. Yet because the stochasticity of quantum physics renders quantum computation random, data science can play an important role in the development of quantum computation and quantum information. This article gives an overview of quantum computation and promotes interplay between quantum science and data science. Overall, it advocates for the development of quantum data science for advancing quantum computation and quantum information.
Quantum computing is widely considered a frontier of interdisciplinary research and involves fields ranging from computer science to physics and from chemistry to engineering. On the one hand, the stochastic essence of quantum physics results in the random nature of quantum computing; thus, there is an important role for statistics to play in the development of quantum computing. On the other hand, quantum computing has great potential to revolutionize computational statistics and data science. This article provides an overview of the statistical aspect of quantum computing. We review the basic concepts of quantum computing and introduce quantum research topics such as quantum annealing and quantum machine learning, which require statistics to be understood.
Over the past century, quantum theory has taken flight from conceptual breakthroughs, such as wave–particle duality, quantisation of energy, and the uncertainty principle, to practical tools that are the backbone of modern electronics, lasers, semiconductors, and precision measurement systems. In the twenty-first century, this progress under the regime of the second quantum revolution has acquired the ability to directly control, manipulate, and engineer individual quantum systems.Quantum technologies found their pillars in quantum properties, such as superposition, entanglement, and coherence and have exceeded the boundaries of classical physics. The steady theoretical advances, combined with experimental progress, have brought quantum concepts closer to real-life use. Significant progress has made in filed of computation, communication, sensing, navigation, medicine, cyber security, and national defense undr the guidance of quantum technology.This book chapter presents a comprehensive and pedagogical overview of quantum technologies. It highlights quantum computing, quantum communication, and quantum sensing and metrology. The shift of quantum mechanics into practical applications is discussed. Current research trends are reviewed alongside the technological and engineering challenges. The critical issues, such as decoherence, scalability, error correction, standardisation, and workforce development, are discussed, which further highlights the need for global collaboration. Both National governments and the private sector are investing heavily in quantum research. This will act as a booster for quantum technologies to revolutionise information processing, secure communications, and precision measurements. Consequently and will significantly impact the scientific and technological landscape.