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.
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.
Quantum computing is a modern way of computing that is based on the science of quantum mechanics and its unbelievable phenomena. It is a beautiful combination of physics, mathematics, computer science and information theory. It provides high computational power, less energy consumption and exponential speed over classical computers by controlling the behavior of small physical objects i.e. microscopic particles like atoms, electrons, photons, etc. Here, we present an introduction to the fundamental concepts and some ideas of quantum computing. This paper starts with the origin of traditional computing and discusses all the improvements and transformations that have been done due to their limitations until now. Then it moves on to the basic working of quantum computing and the quantum properties it follows like superposition, entanglement and interference. To understand the full potentials and challenges of a practical quantum computer that can be launched commercially, the paper covers the architecture, hardware, software, design, types and algorithms that are specifically required by the quantum computers. It uncovers the capability of quantum computers that can impact our lives in various viewpoints like cyber security, traffic optimization, medicines, artificial intelligence and many more. At last, we concluded all the importance, advantages and disadvantages of quantum computers. Small-scale quantum computers are being developed recently. This development is heading towards a great future due to their high potential capabilities and advancements in ongoing research. Before focusing on the significances of a general-purpose quantum computer and exploring the power of the new arising technology, it is better to review the origin, potentials, and limitations of the existing traditional computing. This information helps us in understanding the possible challenges in developing exotic and competitive technology. It will also give us an insight into the ongoing progress in this field.
To overcome the scaling limitations of conventional semiconductor chips, quantum computing has emerged and experienced significant growth in recent years. Quantum computing utilizes resources such as quantum superposition and quantum entanglement to encode and process information. Compared to classical computing, this technology can provide exponential acceleration in the field of ultra-large-scale parallel computing. Consequently, its practical application is anticipated to have profound impacts on information and related technologies. The paper employs a comparative analysis approach to systematically examine the research progress of quantum computer technology. Specifically, the study emphasizes the analysis and consolidation of various quantum computing technology routes, critically evaluates their advantages and disadvantages, and provides a foresight into their future development trends. Currently, research on quantum computing technology is in its early stages and is evolving rapidly. Multiple technical paths are being pursued, resulting in a diverse and competitive landscape that is expected to persist in the short term, as it will take some time before the practical application of quantum computers becomes feasible.
Quantum computing has evolved from a largely theoretical discipline into a field of growing interest for commercial and industrial applications. Recent advances in quantum hardware, algorithms, and cloud-based access have enabled early experimentation outside academic environments, raising questions about its potential impact on real-world decision-making and operational problems. This paper provides an overview of the current state of quantum computing with a focus on its emerging relevance in commercial contexts. It examines the categories of problems that have attracted attention from industry, particularly those involving high combinatorial complexity such as optimization, scheduling, logistics, and resource allocation. The analysis also reviews the global landscape of companies and initiatives engaged in quantum computing, highlighting different technological approaches, maturity levels, and regional characteristics. In parallel, the paper discusses the principal challenges and limitations that constrain widespread adoption, including hardware immaturity, algorithmic readiness, cost factors, and organizational requirements. By considering both opportunities and risks, this study aims to present a balanced and realistic perspective on the role quantum computing may play in business environments. The objective is to clarify the current position of quantum computing within the broader technological landscape and to support informed interpretation of its potential, limitations, and future trajectory in commercial applications.
Quantum computing is a transformative paradigm based on the principles of quantum mechanics such as superposition and entanglement to outperform classical computers in solving complex problems. This paper presents a comprehensive overview of quantum computing, detailing its foundational concepts, advancements, applications, platforms, limitations, and future scope. Key research contributions from organizations such as IBM, AWS, and Microsoft, as well as government initiatives, are discussed. Applications are explored across cryptography, pharmaceuticals, healthcare, finance, manufacturing, simulation, and AI. Quantum platforms such as Qiskit, Azure Quantum, and D-Wave Ocean SDK are also reviewed. Although still in its development stages and facing challenges, quantum computing faces difficulties related to error correction and the environment may entirely change modern computing. The article concludes by stressing the need for continuous research, education, strategic planning, and development to utilize the disruptive abilities of quantum technologies.
Quantum Computing (QC) and Artificial Intelligence (AI) have emerged as key technologies in the evolution of Industry 6.0, driving advancements in automation and advanced analytics, and process optimization. Their integration holds the potential to revolutionize sectors such as data science, healthcare, finance, and cybersecurity by enabling faster and more efficient computations through qubits, superposition, and quantum entanglement. However, the lack of structured knowledge regarding specific QC methodologies and applications in AI hinders its optimal implementation and development. Consequently, this study aims to identify the applications and variables associated with QC-AI integration. To this end, a systematic literature review was conducted following the PRISMA 2020 methodology, drawing on studies from Scopus and Web of Science databases. This enabled the analysis of trends, limitations, and opportunities in this technological convergence. This study aims to systematically examine the intersection of quantum computing and artificial intelligence by identifying the key technological features, integration requirements, and sectoral applications that define the current state of the field. The review contributes by mapping existing research, highlighting methodological approaches, and revealing gaps that may guide targeted advancements in hybrid quantum AI systems. The insights generated have the potential to accelerate innovation in high-impact domains such as healthcare, finance, energy, and cybersecurity. The findings indicate that the main advances in QC applied to AI focus on quantum optimization, Quantum Machine Learning (QML), and post-quantum cryptography. Notably, sectors such as energy, healthcare, and finance have shown significant progress in adopting these technologies. For example, in healthcare, QML has been applied to simulate molecular interactions to accelerate drug discovery, and in finance, it enhances predictive models for market behavior. The study concludes that although QC demonstrates substantial potential to enhance AI, its broader adoption remains constrained by reliance on NISQ hardware, the need for effective error correction, and the limited scalability of hybrid quantum classical algorithms. Addressing these challenges will be essential to establishing QML as a cornerstone of technological innovation and digital transformation. Additionally, this review introduces an integrative framework that categorizes key AI QC convergence dimensions and proposes a classification of application areas based on technical requirements and algorithmic capabilities. These contributions aim to guide future experimental validations and hybrid model development.
Quantum computing has emerged as a groundbreaking paradigm in computational science, offering unprecedented capabilities to tackle complex problems that are beyond the reach of classical computing. This paper provides a comprehensive overview of quantum computing technologies and their uses across various domains. We begin by elucidating the fundamental principles of quantum mechanics that underpin quantum computing, including superposition, entanglement, and quantum interference. Subsequently, we delve into the key components of quantum computing architectures, such as qubits, quantum gates, and quantum circuits, highlighting the advancements in hardware implementations, including superconducting qubits, trapped ions, and photonic systems. Finally, we survey a wide array uses of quantum computing across fields such as cryptography, optimization, machine learning, chemistry, and finance, showcasing the transformative potential of this revolutionary technology. Through this survey, we aim to provide researchers, practitioners, and enthusiasts with a comprehensive understanding of the state-of-the-art in quantum computing technologies and their burgeoning applications, thereby fostering further advancements and innovations in this rapidly evolving field.