After the emergence of quantum mechanics and realising its need for an accurate understanding of physical systems, numerical methods were being used to undergo quantum mechanical treatment. With increasing system correlations and size, numerical methods fell rather inefficient, and there was a need to simulate quantum mechanical phenomena on actual quantum computing hardware. Now, with noisy quantum computing machines that have been built and made available to use, realising quantum simulations are edging towards a practical reality. In this paper, we talk about the progress that has been made in the field of quantum simulations by actual quantum computing hardware and talk about some very fascinating fields where it has expanded its branches, too. Not only that, but we also review different software tool-sets available to date, which are to lay the foundation for realising quantum simulations in a much more comprehensive manner.
After the emergence of quantum mechanics and realising its need for an accurate understanding of physical systems, numerical methods were being used to undergo quantum mechanical treatment. With increasing system correlations and size, numerical methods fell rather inefficient, and there was a need to simulate quantum mechanical phenomena on actual quantum computing hardware. Now, with noisy quantum computing machines that have been built and made available to use, realising quantum simulations are edging towards a practical reality. In this paper, we talk about the progress that has been made in the field of quantum simulations by actual quantum computing hardware and talk about some very fascinating fields where it has expanded its branches, too. Not only that, but we also review different software tool-sets available to date, which are to lay the foundation for realising quantum simulations in a much more comprehensive manner.
In the contemporary era of scientific and technical innovations, we are witnessing remarkable progress in the realm of quantum computing. Today’s phase is referred to as the second quantum revolution, characterized by ongoing research and progress in the hardware, software, and applications of quantum computers. While the theoretical foundations of quantum computing have been in place for decades, the practical tools and technologies that have emerged in recent years have catapulted this field from theory into reality. This paper provides a brief overview of the fundamental principles of quantum computing and explores the various technologies that support them. From quantum programming languages and simulators to quantum hardware platforms and software development kits, these tools have paved the way for groundbreaking research, experimentation, and the exploration of quantum’s boundless potential. Furthermore, it addresses the current developments, existing challenges, ongoing improvements, and future prospects in this dynamic field.
Quantum computing represents a groundbreaking technological advancement that can tackle problems beyond traditional computers’ reach. This innovative approach leverages quantum mechanical principles to execute computations in ways that surpass the capabilities of conventional computing systems. In theory, certain computation tasks can be completed exponentially quicker on quantum machines compared to their classical counterparts. This article provides a comprehensive examination of the rapidly advancing quantum computing approaches, encompassing recent developments in quantum hardware, programming languages, algorithmic methods, error mitigation techniques, and practical applications across various fields, including cryptography, sensing, and simulation. The study examines how quantum computers may potentially drive breakthroughs in various fields, including medicine, materials science, and artificial intelligence. Additionally, it addresses the obstacles that must be overcome to fully realise the transformative potential of this cutting-edge computing paradigm.
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.
In the effort to develop useful quantum computers, simulating quantum machines with conventional classical computing resources is a key capability. Such simulations will always face limits, preventing the emulation of quantum computers at substantial scale; however, by pushing the envelope through optimal choices of algorithms and hardware, the value of simulator tools can be maximized. This work reviews state-of-the-art numerical simulation methods, i.e., classical algorithms that emulate quantum computer evolution under specific operations. We focus on the mainstream state-vector and tensor-network paradigms, while briefly mentioning alternative methods. Moreover, we review the diverse applications of simulation across different facets of quantum computer development, including understanding the fundamental differences between quantum and classical computations, exploring algorithmic design for quantum advantage, predicting quantum processor performance at the design stage, and efficiently characterizing fabricated devices for rapid iterations. This review complements recent surveys of current tools and implementations; here, we aim to provide readers with an essential understanding of the theoretical basis of classical simulation methods, a detailed discussion of their advantages and limitations, and an overview of the demands and challenges arising from practical use cases.
Quantum computing represents a transformative shift in computational paradigms by leveraging quantum mechanical phenomena such as superposition, entanglement, and quantum interference. Unlike classical computers, which rely on binary logic, quantum systems exploit these principles to solve certain problems more efficiently. This survey presents a comprehensive overview of the field, drawing from extensive literature spanning foundational quantum principles through key quantum algorithms, hardware platforms, and programming tools. The analysis bridges theoretical foundations with practical engineering challenges, examining both current capabilities and fundamental limitations of quantum systems. The paper also explores applications in cryptography, optimization, and quantum simulation, while addressing the ethical implications and long-term prospects of quantum technologies. Distinct from prior surveys, this work provides a unified perspective that connects quantum theory to practical implementation, supporting researchers and students in navigating the evolving landscape of quantum computing.
Quantum network research, is exploring new networking protocols, physics-based hardware and novel experiments to demonstrate how quantum distribution will work over large distances. Current work explores much of these concepts in simulations, that are developed to understand how quantum networking will be set up and researchers can experiment virtually. Exposing flaws in network designs, like unsustainable topologies, or develop protocols that efficiently utilize network resources, simulators can also help assess whether workloads are balanced across virtual machines in the network. However, much of these simulation models come without reliable verification methods, for testing performance in real deployments. In this paper, we present a review of, to the best of our knowledge, currently used toolkits for modeling quantum networks. With these toolkits and standardized validation techniques, we can lay down the foundations for more accurate and reliable quantum network simulators.