This review offers the first available overview of progress in the field of quantum computer simulation. As research interest in quantum computation grows, together with the number of field researchers, it seems certain that quantum computer simulators will play a major role in this research. The review discusses quantum computer simulators and their role in the study of quantum computation. Currently available simulators are described and compared and recommendations are offered as to the most appropriate uses for specific purposes. An awareness of the functions and features of existing simulators is essential for researchers in the field, to avoid duplication of effort and build on the foundations of previous work. This document is an ongoing project, the latest version will always be available at http://www.dcs.exeter.ac.uk/~jwallace A shorter version of this review is available as Department of Computer Science Technical Report 387. Comments, criticisms and suggestions a...
This review offers the first available overview of progress in the field of quantum computer simulation. As research interest in quantum computation grows, together with the number of field researchers, it seems certain that quantum computer simulators will play a major role in this research. The review discusses quantum computer simulators and their role in the study of quantum computation. Currently available simulators are described and compared and recommendations are offered as to the most appropriate uses for specific purposes. An awareness of the functions and features of existing simulators is essential for researchers in the field, to avoid duplication of effort and build on the foundations of previous work. This document is an ongoing project, the latest version will always be available at http://www.dcs.exeter.ac.uk/~jwallace A shorter version of this review is available as Department of Computer Science Technical Report 387. Comments, criticisms and suggestions a...
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.
With high density and high performance applications, classical CMOS technology's drawbacks may be addressed via a method called quantum computing. This research is attracting more and more scholarly/technically focused on core area of QC and attention on its challenges because to its potential to revolutionize the current computing environment. This paper looks/finds at the many technologies that support quantum computing and provides a brief overview of its fundamental concepts. The resources, which include quantum programming languages, simulators, hardware platforms, and software development kits, have made it possible to conduct cutting-edge research and explore the seemingly endless potential of quantum computing. It also covers the most recent developments, challenges that persist, ongoing progress, and possible futures applications and challenges in this quickly changing field.
Simulating quantum many-body systems is a key application for emerging quantum processors. While analog quantum simulation has already demonstrated quantum advantage, its digital counterpart has recently become the focus of intense research interest due to the availability of devices that aim to realize general-purpose quantum computers. In this perspective, we give a selective overview of the currently pursued approaches, review the advances in digital quantum simulation by comparing non-variational with variational approaches and identify hardware and algorithmic challenges. Based on this review, the question arises: What are the most promising problems that can be tackled with digital quantum simulation? We argue that problems of a qualitative nature are much more suitable for near-term devices then approaches aiming purely for a quantitative accuracy improvement.
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.
Abstract Advances in quantum technologies have prompted renewed interest in computational models that extend beyond the capabilities of classical systems. Quantum computing, grounded in the principles of quantum mechanics, introduces novel mechanisms for information processing that challenge conventional assumptions in computer science. This paper critically examines the role of quantum computing across core computer science domains by integrating foundational theory with application-oriented research. Existing studies in cryptography, optimization, artificial intelligence, database search, and system simulation are analyzed to assess both demonstrated capabilities and practical constraints. The discussion emphasizes the increasing relevance of hybrid quantum–classical approaches in the current technological landscape, while identifying key limitations related to scalability, noise, and algorithmic feasibility. By consolidating theoretical insights with applied perspectives, this work provides a realistic assessment of the present state of quantum computing and outlines research directions essential for its effective integration into future computational systems.
Abstract Advances in quantum technologies have prompted renewed interest in computational models that extend beyond the capabilities of classical systems. Quantum computing, grounded in the principles of quantum mechanics, introduces novel mechanisms for information processing that challenge conventional assumptions in computer science. This paper critically examines the role of quantum computing across core computer science domains by integrating foundational theory with application-oriented research. Existing studies in cryptography, optimization, artificial intelligence, database search, and system simulation are analyzed to assess both demonstrated capabilities and practical constraints. The discussion emphasizes the increasing relevance of hybrid quantum–classical approaches in the current technological landscape, while identifying key limitations related to scalability, noise, and algorithmic feasibility. By consolidating theoretical insights with applied perspectives, this work provides a realistic assessment of the present state of quantum computing and outlines research directions essential for its effective integration into future computational systems.