This paper assesses the current state of the quantum computing field with reference to the varied hardware approaches to quantum computing to project the most cost-effective, practical, and long-term solution to quantum computing hardware. While companies and research labs have proven the viability of quantum computing through the construction and operation of intermediate-scale quantum computers, attempts have been unsuccessful at creating scalable, long-term quantum computers with significant capacity to be used in practical applications. While quantum algorithms and applications have already been developed, current quantum computers do not have the necessary hardware capabilities to support running such algorithms. Additionally, the construction of these quantum computers varies drastically, making it difficult to compare and measure quantum computing progress across different hardware architectures. This paper performs a comparative analysis on the four predominant quantum computing hardware architectures to reveal the most sustainable and practical solution based on the criteria of scalability, ease of manufacturing, and energy consumption. These comparisons, along with the shortcomings of each quantum design are discussed to guide further research and development in the field of quantum computing.
This paper assesses the current state of the quantum computing field with reference to the varied hardware approaches to quantum computing to project the most cost-effective, practical, and long-term solution to quantum computing hardware. While companies and research labs have proven the viability of quantum computing through the construction and operation of intermediate-scale quantum computers, attempts have been unsuccessful at creating scalable, long-term quantum computers with significant capacity to be used in practical applications. While quantum algorithms and applications have already been developed, current quantum computers do not have the necessary hardware capabilities to support running such algorithms. Additionally, the construction of these quantum computers varies drastically, making it difficult to compare and measure quantum computing progress across different hardware architectures. This paper performs a comparative analysis on the four predominant quantum computing hardware architectures to reveal the most sustainable and practical solution based on the criteria of scalability, ease of manufacturing, and energy consumption. These comparisons, along with the shortcomings of each quantum design are discussed to guide further research and development in the field of quantum computing.
This paper assesses the current state of the quantum computing field with reference to the varied hardware approaches to quantum computing to project the most cost-effective, practical, and long-term solution to quantum computing hardware. While companies and research labs have proven the viability of quantum computing through the construction and operation of intermediate-scale quantum computers, attempts have been unsuccessful at creating scalable, long-term quantum computers with significant capacity to be used in practical applications. While quantum algorithms and applications have already been developed, current quantum computers do not have the necessary hardware capabilities to support running such algorithms. Additionally, the construction of these quantum computers varies drastically, making it difficult to compare and measure quantum computing progress across different hardware architectures. This paper performs a comparative analysis on the four predominant quantum computing hardware architectures to reveal the most sustainable and practical solution based on the criteria of scalability, ease of manufacturing, and energy consumption. These comparisons, along with the shortcomings of each quantum design are discussed to guide further research and development in the field 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.
This paper presents a comprehensive review of quantum computing and the technological foundations of quantum processors. Quantum computing represents a transformative computational paradigm that leverages the fundamental principles of quantum mechanics—such as superposition, entanglement, and quantum interference—to solve complex problems that are intractable for classical computers. At the core of this paradigm lies the quantum processor, a specialized hardware system designed to initialize, control, and measure quantum bits (qubits) through precise gate operations and coherent interactions. The survey examines the essential theoretical concepts underlying quantum computation and provides a structured comparison of leading quantum processor platforms. Prominent architectures, including superconducting circuits, trapped-ion systems, and photonic implementations, are analyzed in terms of their physical mechanisms, scalability, coherence properties, and engineering challenges. Each platform offers distinct advantages and faces specific technical limitations related to noise, error correction, and fabrication complexity. In addition to reviewing hardware developments, this study highlights key obstacles in advancing quantum processors toward large-scale, fault-tolerant systems. Issues such as qubit stability, error mitigation, thermal management, and system integration are discussed to present a realistic perspective on current progress. Performance indicators including gate fidelity, coherence time, connectivity, and scalability are used to compare architectural approaches. The objective of this paper is to provide a clear and organized synthesis of recent advancements in quantum computing hardware, thereby offering researchers and practitioners a foundational reference to support continued innovation and development in this rapidly evolving field.
Quantum computing, built on the principles of quantum mechanics, has emerged as a transformative paradigm with the potential to revolutionize computational capabilities, enabling solutions to problems that are currently intractable for classical systems. Quantum computing integrates hardware, architectures, and software for improved applications while utilizing superposition, entanglement, and interference to promote materials science, cryptography, optimization, and artificial intelligence. Sections introduce and describe the model components needed in order to create quantum processors, including qubits, quantum gates and control electronics, as well as a review of new developments in quantum software frameworks and programming tools. Notable examples, such as Shor’s algorithm for cryptographic caveat, Grover’s algorithm for inefficient search processes, and quantum-enhanced optimization, illuminate the position of quantum computing as a means of tackling tough problems that span disciplines, such as pharmaceuticals, predictors of climate, and finance modeling. However, the field continues to face significant challenges, like limited scalability, quantum gate error rates, qubit coherence times, and difficulties integrating with classical systems. Future efforts will focus on developing hybrid quantum-classical systems, scalable architectures, and industry- specific applications to transition quantum computing from exploration to practical deployment. This review provides a comprehensive analysis of quantum computing, covering its potential, trends, and challenges, while exploring hardware-software integration, classicalquantum comparisons, and insights to guide research and industry in unlocking its revolutionary possibility.
The paper provides an exploration of quantum computing, emphasizing its potential and challenges. It begins with the fundamentals of quantum mechanics and differentiates between classical and quantum computing, focusing on concepts like qubits, superposition, and entanglement. The authors identify the existing limitations in practical quantum applications, particularly within the Noisy Intermediate-Scale Quantum (NISQ) era, where issues like noise in quantum circuits hinder scalability and reliability. The paper addresses the need for advancements in hardware, error correction techniques, and practical algorithms tailored for current technological constraints. Additionally, it discusses the implications of quantum computing on cryptography, underscoring the vulnerability of traditional cryptographic methods and the urgency for postquantum cryptographic solutions. The methodology involves literature review, expert consultations, and bibliometric analysis to gauge global research trends in quantum computing. The paper highlights crucial research gaps, particularly in the development of scalable quantum algorithms suitable for near-future applications.
Quantum computing, grounded in the principles of superposition and entanglement, has emerged as a revolutionary paradigm with the potential to outperform classical systems in specific computational tasks. This paper presents a comprehensive survey of the foundational concepts, algorithmic developments, hardware architectures, and programming ecosystems in quantum computing. We analyze the current progress in key application areas such as cryptography, machine learning, optimization, and quantum chemistry. Furthermore, we review recent advances between 2023 and 2025, including developments in fault-tolerant architectures and quantum error correction. The paper also discusses the significant technical challenges that hinder large-scale practical deployment, including qubit scalability, decoherence, and programming limitations. By synthesizing literature across disciplines, this review aims to provide a holistic understanding of the quantum computing landscape and outline critical directions for future research and integration with classical systems.