Quantum technologies' processing capacity is built on quantum mechanics foundations, including superposition, the no-cloning theorem, and quantum entanglement. Quantum computing seeks to understand and embrace quantum effects, as well as techniques to improve and sustain them in order to achieve old computational goals in novel ways. It accomplishes this by utilising quintessentially quantum phenomena. We can't get equivalent findings using traditional computation because these processes don't have a classical analogue. There have been significant claims that quantum computers can surpass the Turing limit, however these assertions have been debunked. The Church-Turing thesis, which states that all realisable physical and dynamical systems cannot be more powerful than classical models of computation, has been the subject of numerous intensive attempts. However, quantum computing technologies' experimental insights have already been proved, and various studies are currently underway. In this article, the authors look at the most current quantum computation results and claims.
Quantum technologies' processing capacity is built on quantum mechanics foundations, including superposition, the no-cloning theorem, and quantum entanglement. Quantum computing seeks to understand and embrace quantum effects, as well as techniques to improve and sustain them in order to achieve old computational goals in novel ways. It accomplishes this by utilising quintessentially quantum phenomena. We can't get equivalent findings using traditional computation because these processes don't have a classical analogue. There have been significant claims that quantum computers can surpass the Turing limit, however these assertions have been debunked. The Church-Turing thesis, which states that all realisable physical and dynamical systems cannot be more powerful than classical models of computation, has been the subject of numerous intensive attempts. However, quantum computing technologies' experimental insights have already been proved, and various studies are currently underway. In this article, the authors look at the most current quantum computation results and claims.
There has been significant advancements in Quantum Computing research related to infrastructure and algorithmic complexity in recent years. Since the 1980s, the scientific community has been interested in the possibility of using quantum phenomena to tackle computer issues. Quantum computing systems get their power from the no-cloning theorem, quantum superposition, and quantum entanglement. Based on the fact that these events lack a classical equivalent, it is not possible to reach comparable conclusions using the framework of traditional computing. Already demonstrated are the experimental breakthroughs that can be made with quantum computing technology, and a number of investigations are currently being carried out. In this chapter, we analyze the most recent technological breakthroughs in the field of quantum computing and investigate some of the outstanding issues.
Quantum computing represents a revolutionary leap in computational power, leveraging the principles of quantum mechanics to process information in fundamentally new ways. Unlike classical computers, which use bits to represent data as 0s or 1s, quantum computers use quantum bits or qubits, enabling the phenomena of superposition and entanglement to perform complex calculations more efficiently (Nielsen & Chuang, 2010). This article explores the basic principles of quantum computing, the different models and algorithms that have been developed, and the current state of quantum hardware. The power of quantum computing lies in its ability to solve certain types of problems exponentially faster than classical computers. For instance, Shor's algorithm can factorize large integers in polynomial time, posing a significant threat to classical encryption methods (Shor, 1997). Similarly, Grover's algorithm provides a quadratic speedup for unstructured search problems, showcasing the potential for dramatic improvements in database search capabilities (Grover, 1996). These algorithms exemplify how quantum computing can revolutionize fields that rely on complex computations. Quantum hardware, however, is still in its nascent stage, with significant challenges to be overcome. Current quantum computers, such as those developed by IBM and Google, have demonstrated quantum supremacy but are limited by issues of qubit coherence and error rates (Arute et al., 2019). Quantum error correction and the development of more stable qubit technologies are critical areas of ongoing research (Preskill, 2018). Despite these challenges, recent advancements in quantum hardware and algorithms continue to drive the field forward, promising transformative impacts on industries such as cryptography, drug discovery, and artificial intelligence. As quantum computing continues to advance, it holds the promise of solving problems that are currently intractable for classical computers, paving the way for unprecedented technological and scientific advancements (Shor, 1997; Grover, 1996). This article provides a comprehensive overview of the current landscape of quantum computing, discussing its foundational principles, key algorithms, hardware challenges, and potential applications. By understanding these aspects, we can better appreciate the profound implications of quantum computing for the future of technology and science.
This manuscript is intended for readers who have a general interest in the subject of quantum computation and provides an overview of the most significant developments in the field. It begins by introducing foundational concepts from quantum mechanics—such as superposition, entanglement, and the no-cloning theorem—that underpin quantum computation. The primary computational models are discussed, including gate-based (circuit) quantum computing, adiabatic quantum computing, measurement-based quantum computing and the quantum Turing machine. A selection of significant quantum algorithms are reviewed, notably Grover’s search algorithm, Shor’s factoring algorithm, and Quantum Singular Value Transformation (QSVT), which enables efficient solutions to linear algebra problems on quantum devices. To assess practical performance, we compare quantum and classical implementations of support vector machines (SVMs) using several synthetic datasets. These experiments offer insight into the capabilities and limitations of near-term quantum classifiers relative to classical counterparts. Finally, we review leading quantum programming platforms—including Qiskit, PennyLane, and Cirq—and discuss their roles in bridging theoretical models with real-world quantum hardware. The paper aims to provide a concise yet comprehensive guide for those looking to understand both the theoretical foundations and applied aspects of quantum computing.
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.
Quantum theory and quantum computing in recent years, has raised more and more increasing interest within the scientific community because of various reasons. First, the highly interdisciplinary nature of the subject which involves diverse topics such as, on the theoretical side, information theory and foundational issues of quantum mechanics and on the experimental side, the physics of quantum, optical, atomic and solid state systems. Secondly, the field is extremely promising for revolutionary technological implications in the near future. It is now perfectly clear that one can use quantum mechanics to process and transmit information in a way which does not have a classical analogue, and that using quantum techniques one can implement fully secure cryptographic systems. Recent breakthroughs, such as quantum teleportation, have led to extremely rapid progresses in a fascinating new field and, as a consequence, have attracted the interest of many scientists from varied disciplines. The purpose of this article is to provide a comprehensive overview about the deep involvement of quantum theory in quantum computation to young researchers and newcomers in the field.
Quantum computing represents a transformative shift in computational technology, leveraging the principles of quantum mechanics to process information in ways that surpass the limits of classical systems.By exploiting qubits, superposition, entanglement, and quantum parallelism, quantum computers offer the potential to solve certain classes of problems-such as optimization, cryptography, molecular simulation, and complex machine learning tasks-significantly faster than classical algorithms.With rapid advancements in quantum hardware and the emergence of Noisy Intermediate-Scale Quantum (NISQ) devices, quantum computing has evolved from a theoretical concept to a practical field with growing industrial and scientific relevance.Although current systems face challenges related to error rates, decoherence, and scalability, ongoing developments in quantum error correction, hybrid quantum-classical algorithms, and software frameworks like Qiskit, Cirq, and PennyLane continue to push the field forward.This paper provides an introductory overview of quantum computing, outlining its foundational principles, current technological landscape, key algorithms, and future research directions.The goal is to offer a clear understanding of how quantum computing is poised to reshape the future of computation.