Faster algorithms, novel cryptographic mechanisms, and alternative methods of communication become possible when the model underlying information and computation changes from a classical mechanical model to a quantum mechanical one. Quantum algorithms perform a select set of tasks vastly more efficiently than any classical algorithm, but for many tasks it has been proved that quantum algorithms provide no advantage. The breadth of quantum computing applications is still being explored. Major application areas include security and the many fields that would benefit from efficient quantum simulation. The quantum information processing viewpoint provides insight into classical algorithmic issues as well as a deeper understanding of entanglement and other non-classical aspects of quantum physics. This overview is aimed at technology managers who wish to gain a high level understanding of quantum information processing, particularly quantum computing.
Faster algorithms, novel cryptographic mechanisms, and alternative methods of communication become possible when the model underlying information and computation changes from a classical mechanical model to a quantum mechanical one. Quantum algorithms perform a select set of tasks vastly more efficiently than any classical algorithm, but for many tasks it has been proved that quantum algorithms provide no advantage. The breadth of quantum computing applications is still being explored. Major application areas include security and the many fields that would benefit from efficient quantum simulation. The quantum information processing viewpoint provides insight into classical algorithmic issues as well as a deeper understanding of entanglement and other non-classical aspects of quantum physics. This overview is aimed at technology managers who wish to gain a high level understanding of quantum information processing, particularly quantum computing.
Advancements in computer technologies have been evolving in order to provide new services or to improve recent computing performance. Applications of computer technologies to several real-world domains are becoming more realistic and efficient. Two challenges are taken into consideration when applying such technologies including more complicated user requirements and exponential growth of data. In the real world, which is driven by business, achieving user requirements is one promising way of yielding competitive advantages. Moreover, time constraints are also crucial for corporate users. Apart from structured data, unstructured data have been significantly generated via several platforms. Such aspects make data processing more demanding. Quantum technology, which is instantiated in physics, has been utilized in various fields including computer science. Even the real quantum computer is still in its early development, but other concepts such as quantum information and quantum computing are making progress. Furthermore, some quantum-based algorithms have been analytically proven to have higher performance compared to the traditional ones. According to such important milestones, quantum computing has been regarded as one of the key infrastructures of future computing. This paper aims to focus on the main aspects of quantum computing including its backgrounds and recent advancement to provide a clearer picture. Its recent applications to intelligent system enhancement, cybersecurity and cryptography empowerment, and finance are addressed. Several key ideas, and opportunities of quantum computing utilization are also outlined based upon systematic reviews of existing works and case studies. Moreover, comparative analysis between classical and quantum computing in terms of core principles, computational efficiency, and practical feasibility is given. Better understanding and proper preparation of applying quantum computing are thus achieved.
The topic of these lectures lies in the new and rapidly growing field of quantum computing,which explores connections between physics and computing in general. Quantum informa-tion processing is a cross-disciplinary field and is of great importance from both a funda-mental, as well as technological perspective [27]. From the fundamental perspective we havedeepened our understanding of the relationship between physics, information and computa-tion in general, and have also gained a deeper understanding of the fundamental aspects ofquantum theory - non-locality and entanglement in particular [31]. From the technologicalperspective we have manipulated larger and larger quantum systems and obtained power-ful practical applications in the domain of communication and cryptography such as theunconditionally secure quantum cryptography (key exchange) and quantum teleportation[7, 14, 5].Historically, the greater potential of the quantum computer was first realised by Feyn-man, who noted that quantum systems appear to be exponentially hard to simulate withclassical computers [15]. He speculated that, therefore, quantum computers could poten-tially be much more powerful than their classical counterparts. This intuition has beenproven to be correct for some tasks, such as factoring large numbers and searching unstruc-tured databases. Every computer is fundamentally a physical system, and any computationis just a physical process undergone by this system. Quantum physics is the most accurateway of describing physical systems and their behaviour in general. Encoding informationinto quantum systems and processing it according to the laws of quantum physics results innew features which do not exist in the classical computation.Large scale quantum computation is still hypothetical. However, Moore’s law
Quantum computing is a potential technological revolution that will transform the entire field of information processing. However, quantum computing like classical bits in classical computers is operated using quantum bits principle physics based on quantum mechanics. Quantum computing explores many solution spaces simultaneously because of a fundamental difference from the classical computation paradigms, leading to the possibility of exponential speed-up on some computational plant tasks. This paper discusses quantum computing with essential concepts like quantum superposition, entanglement, and applications such as cryptography, optimization, and drug discovery and machine learning. Quantum computing will enable numerous groundbreaking discoveries that were previously unattainable and will bequeath a lasting legacy in the digital innovation era. Quantum computing is an information processing technique that harnesses the laws of quantum mechanics to conduct calculations far faster circumvented by traditional digital computers. Digital computers utilize bits, which may take one of two forms: 0 or 1. This superposition of quantum superposition and entanglement yielded qubits unique qualities that can’t be expected in classical systems. Indeed, superposition enables qubits to take numerous forms simultaneously, while entanglement enables qubits to be connected such their properties are connected. In cryptography, quantum computers can decrypt existing cryptographic keys or develop new, more secure quantum encryption using qubits. Quantum computers can dramatically accelerate materials science and drug design by allowing scientists to simulate how molecules interact more accurately. In conclusion, quantum computing represents a unique information processing change and has a future impact on science, technology, and society.
Quantum computing represents a transformative approach to computation leveraging fundamental principles of quantum mechanics such as superposition, entanglement and interference to store and process information in ways that classical computers cannot achieve.This paper attempts to provide a bona fide bibliographic overview of the principles, computational models, hardware technologies, and potential applications of quantum computing.It analyses how quantum algorithms could outperform classical algorithms in cryptographic analysis, optimization, and big data analysis.The survey integrates viewpoints from recent works; it presents system architectures, software development challenges, and quantum-assisted applications in healthcare, artificial intelligence, cybersecurity, and industrial optimization.Meanwhile, it examines hybrid quantum-classical systems that would allow quantum technologies to be deployed in the near term skirted by the limitations currently posed by quantum hardware.Moreover, the paper discusses foremost hurdles in scaling, error-correction, and maintaining coherence.From reviewing the recent developments and whether possible, this present review work informs researchers, engineers, and practitioners alike on the current state, as well as on the long-run viability, of quantum computing.
The success of the abstract model of computation, in terms of bits, logical operations, programming language constructs, and the like, makes it easy to forget that computation is a physical process. Our cherished notions of computation and information are grounded in classical mechanics, but the physics underlying our world is quantum. In the early 80s researchers began to ask how computation would change if we adopted a quantum mechanical, instead of a classical mechanical, view of computation. Slowly, a new picture of computation arose, one that gave rise to a variety of faster algorithms, novel cryptographic mechanisms, and alternative methods of communication. Small quantum information processing devices have been built, and efforts are underway to build larger ones. Even apart from the existence of these devices, the quantum view on information processing has provided significant insight into the nature of computation and information, and a deeper understanding of the physics of our universe and its connections with computation. We start by describing aspects of quantum mechanics that are at the heart of a quantum view of information processing. We give our own idiosyncratic view of a number of these topics in the hopes of correcting common misconceptions and highlighting aspects that are often overlooked. A number of the phenomena described were initially viewed as oddities of quantum mechanics. It was quantum information processing, first quantum cryptography and then, more dramatically, quantum computing, that turned the tables and showed that these oddities could be put to practical effect. It is these application we describe next. We conclude with a section describing some of the many questions left for future work, especially the mysteries surrounding where the power of quantum information ultimately comes from.
Introduction Any technology that functions at the quantum level must face the issues of measurement and control. We have good reasons to believe that quantum physics enables communication and computation tasks that are either impossible or intractable in a classical world [NC00]. The security of widely used classical cryptographic systems relies upon the difficulty of certain computational tasks, such as breaking large semi-prime numbers into their two prime factors in the case of RSA encryption. By contrast, quantum cryptography can be absolutely secure, and is already a commercial reality. At the same time, the prospect of a quantum computer vastly faster than any classical computer at certain tasks is driving an international research programme to implement quantum information processing. Shor's factoring algorithm would enable a quantum computer to find factors exponentially faster than any known algorithm for classical computers, making classical encryption insecure. In this chapter, we investigate how issues of measurement and control arise in this most challenging quantum technology of all, quantum computation. The subjects of information theory and computational theory at first sight appear to belong to mathematics rather than physics. For example, communication was thought to have been captured by Shannon's abstract theory of information [SW49, Sha49]. However, physics must impact on such fundamental concepts once we acknowledge the fact that information requires a physical medium to support it.