Quantum algorithms promise up to a superpolynomial factor speedup in computational tasks compared to their classical counterparts. Quantum computers are now approaching sizes where quantum algorithms can be demonstrated. As a result, the implementation of algorithms as quantum circuits has become an important research topic. In this work, we provide an overview of quantum computation and the design of quantum circuits. Properties unique to quantum computation are outlined. We introduce how a quantum algorithm is translated into a circuit and show measures used to assess the performance of quantum circuits.
Quantum algorithms promise up to a superpolynomial factor speedup in computational tasks compared to their classical counterparts. Quantum computers are now approaching sizes where quantum algorithms can be demonstrated. As a result, the implementation of algorithms as quantum circuits has become an important research topic. In this work, we provide an overview of quantum computation and the design of quantum circuits. Properties unique to quantum computation are outlined. We introduce how a quantum algorithm is translated into a circuit and show measures used to assess the performance of quantum circuits.
Quantum computers offer the potential to extend our abilities to tackle computational problems in fields such as number theory, encryption, search and scientific computation.Up to a superpolynomial speedup has been reported for quantum algorithms in these areas.Motivated by the promise of faster computations, the development of quantum machines has caught the attention of both academics and industry researchers.Quantum machines are now at sizes where implementations of quantum algorithms or their components are now becoming possible.In order to implement quantum algorithms on quantum machines, resource efficient circuits and functional blocks must be designed.This tutorial will cover the following:
In recent decades, the field of quantum computing has experienced remarkable progress. This progress is marked by the superior performance of many quantum algorithms compared with their classical counterparts, with Shor's algorithm serving as a prominent illustration. Quantum arithmetic circuits, which are the fundamental building blocks in numerous quantum algorithms, have attracted much attention. Despite extensive exploration of various designs in the existing literature, researchers remain keen to develop novel designs and improve existing ones. In this review article, we aim to provide a systematically organized and easily comprehensible overview of the current state of the art in quantum arithmetic circuits. Specifically, this study covers fundamental operations such as addition, subtraction, multiplication, division and modular exponentiation. We delve into the detailed quantum implementations of these prominent designs and evaluate their efficiency considering various objectives. We also discuss potential applications of the presented arithmetic circuits and suggest future research directions.This article is part of the theme issue 'Emerging technologies for future secure computing platforms'.
Quantum computing has been attracting increasing attention in recent years because of the rapid advancements that have been made in quantum algorithms and quantum system design. Quantum algorithms are implemented with the help of quantum circuits. These circuits are inherently reversible in nature and often contain a sizeable Boolean part that needs to be synthesized. The logic design of such quantum circuits constitutes a non-trivial task and, hence, have heavily been investigated by researchers in the recent past. This paper provides a brief overview of these research. We review the major steps to be conducted in the logic design of quantum circuits and provide a sketch for each single step. These descriptions are enriched with discussions as well as references to the respective related work.
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.
With its potential to completely change computation, quantum computing—a groundbreaking discipline that sprung from computer science and quantum mechanics—has attracted a lot of interest. This essay attempts to cover the foundations of quantum computing and offer a thorough manual for readers who are not specialists in the subject. We start by going over the basic ideas of quantum computing and then take readers through the concepts of qubits, superposition, entanglement, interference, and noise. We study quantum gates, quantum hardware, and fundamental quantum circuits. This paper provides an overview of the present state of quantum computing, focusing on the noisy intermediate-scale quantum (NISQ) era and its possible applications to practical issues. delve into the creation of quantum algorithms and their uses, emphasizing well-known algorithms like as Grover's and Shor's. We also discuss how several fields, like material science, machine learning, encryption, and optimization, are affected by quantum computing. Upon finishing this paper, readers will possess a firm grasp of the fundamentals, practical uses, and procedures of quantum circuit development. Our objective is to offer an invaluable resource for scholars hoping to keep current on this quickly developing topic as well as for those ready to start their adventure with quantum computing
This paper presents the design of a novel hardware accelerator leveraging fundamental principles of quantum mechanics. The core concept involves translating specific computational algorithms into quantum circuits and executing them on quantum hardware platforms such as superconducting qubits or ion traps. This approach aims to achieve significant speedup compared to classical algorithms. The design focuses on optimizing the quantum circuit for targeted algorithms, considering factors like qubit connectivity, gate fidelity, and measurement schemes. This work outlines the theoretical framework, key design considerations, and potential performance gains anticipated from utilizing quantum mechanical phenomena like superposition and entanglement for hardware acceleration. The primary goal is to demonstrate the feasibility and potential of quantum-inspired hardware accelerators for solving computationally intensive problems. ---