Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Smart innovation, systems and technologies

An Efficient Quantum Circuit Design: Properties and Optimization Techniques

Mamtha Prajapati, Kalyan Babu Killana

Published Oct 17, 2024• 3 citations
Publisher
DOI
10.1007/978-981-97-2147-4_28

Related papers

Quantum Circuits: Design and Optimization

George A. Kevrekidis

•Aug 17, 2018•0 citations

基于自组织的量子电路的拓扑优化

Jincheng Zhang

This paper introduces a novel optimization algorithm based on self-organized quantum circuits, aiming to enhance the performance and efficiency of quantum circuits while minimizing their complexity. Traditional quantum circuit design often relies on manual manipulation, limiting flexibility and potential for optimization. We propose a new approach that leverages the inherent topological properties of quantum circuits to dynamically adjust their structure, leading to significant improvements. The core mechanism involves constructing a self-organized circuit that evolves through a series of transformations, guided by a topological mapping. We demonstrate the effectiveness of this algorithm through simulations and analysis of various quantum circuit designs, highlighting its ability to achieve superior performance compared to traditional optimization methods. The research explores the potential of this technique to address challenges in quantum circuit design and expansion, paving the way for more efficient and versatile quantum technologies.

•Aug 29, 2026•0 citations

Quantum circuits design and simulation

Fatma Hamzaoui, Roselyne Chotin-Avot, Mohsen Machhout +2 more

•Jun 1, 2011•0 citations

自组织量子态的量子电路优化

Jincheng Zhang

Quantum circuits, the fundamental building blocks of quantum computation, require careful design and optimization to achieve optimal performance. Traditional optimization methods often involve manual parameter adjustments, which can be time-consuming and limit the potential for efficient optimization. This paper introduces a novel quantum circuit optimization algorithm based on self-organized quantum states, aiming to significantly enhance the efficiency of quantum computation. The core mechanism of this algorithm leverages the inherent properties of quantum states to dynamically adjust circuit parameters, leading to improved performance metrics. We present a detailed explanation of the algorithm's design and implementation, along with a thorough analysis of its effectiveness through simulations and theoretical considerations. The results demonstrate a substantial improvement in circuit fidelity and computational speed compared to existing optimization techniques.

•Sep 7, 2026•0 citations

Automatic design of quantum circuits

Khaled Khalfaoui, Tahar Boudjedaa, Elhillali Kerkouche

Quantum Information Processing•Sep 1, 2021•8 citations

基于拓扑的量子计算的自适应量子电路布局

Jincheng Zhang

This paper introduces a novel approach to quantum circuit design leveraging topological properties to achieve adaptive quantum circuit layout. Traditional quantum circuit design relies on static layouts, often resulting in suboptimal performance. We propose a method that dynamically adjusts the structure of quantum circuits based on topological principles, optimizing for both computational efficiency and accuracy. This framework addresses limitations of current layout techniques by incorporating a self-organizing, topologically driven design process. The proposed method demonstrates improved results through a rigorous analysis of circuit performance across a variety of quantum algorithms.

•Sep 4, 2026•0 citations
This paper introduces a novel optimization algorithm based on self-organized quantum circuits, aiming to enhance the performance and efficiency of quantum circuits while minimizing their complexity. Traditional quantum circuit design often relies on manual manipulation, limiting flexibility and potential for optimization. We propose a new approach that leverages the inherent topological properties of quantum circuits to dynamically adjust their structure, leading to significant improvements. The core mechanism involves constructing a self-organized circuit that evolves through a series of transformations, guided by a topological mapping. We demonstrate the effectiveness of this algorithm through simulations and analysis of various quantum circuit designs, highlighting its ability to achieve superior performance compared to traditional optimization methods. The research explores the potential of this technique to address challenges in quantum circuit design and expansion, paving the way for more efficient and versatile quantum technologies.
Quantum circuits, the fundamental building blocks of quantum computation, require careful design and optimization to achieve optimal performance. Traditional optimization methods often involve manual parameter adjustments, which can be time-consuming and limit the potential for efficient optimization. This paper introduces a novel quantum circuit optimization algorithm based on self-organized quantum states, aiming to significantly enhance the efficiency of quantum computation. The core mechanism of this algorithm leverages the inherent properties of quantum states to dynamically adjust circuit parameters, leading to improved performance metrics. We present a detailed explanation of the algorithm's design and implementation, along with a thorough analysis of its effectiveness through simulations and theoretical considerations. The results demonstrate a substantial improvement in circuit fidelity and computational speed compared to existing optimization techniques.
This paper introduces a novel approach to quantum circuit design leveraging topological properties to achieve adaptive quantum circuit layout. Traditional quantum circuit design relies on static layouts, often resulting in suboptimal performance. We propose a method that dynamically adjusts the structure of quantum circuits based on topological principles, optimizing for both computational efficiency and accuracy. This framework addresses limitations of current layout techniques by incorporating a self-organizing, topologically driven design process. The proposed method demonstrates improved results through a rigorous analysis of circuit performance across a variety of quantum algorithms.