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

Nature Computational Science

Quantum algorithms for quantum dynamics

Alexander Miessen, Pauline J. Ollitrault, Francesco Tacchino, Ivano Tavernelli

Published Dec 30, 2022• 77 citations
Publisher
DOI
10.1038/s43588-022-00374-2

Related papers

On quantum computational algorithms

이수준

•Jan 1, 2002•0 citations

Dynamic Topological Quantum Algorithm (DTQA)

Jincheng Zhang

This paper presents the Dynamic Topological Quantum Algorithm (DTQA), a novel quantum algorithm designed to dynamically adapt quantum operations based on the system's inherent topological properties. Traditional quantum algorithms often require pre-defined parameters, limiting their flexibility and hindering optimal performance. DTQA addresses this limitation by incorporating a dynamic topology feature, allowing the algorithm to dynamically adjust quantum operations in response to the system's evolving topological structure. The core mechanism involves characterizing the system's topology and then employing a mapping to dynamically modify the quantum state, resulting in enhanced computational capabilities. This paper details the theoretical framework, implementation details, and preliminary results demonstrating the effectiveness of DTQA.

•Sep 6, 2026•0 citations

Algorithms for Quantum Computers

Jamie Smith, Michele Mosca

arXiv:1001.0767•Springer eBooks•Jan 1, 2012•23 citations

Dynamic Quantum State Prediction Algorithm (DQPA)

Jincheng Zhang

This paper introduces the Dynamic Quantum State Prediction Algorithm (DQPA), a novel approach to quantum state prediction that leverages the inherent dynamism of quantum states. Traditional methods often rely on static models, while DQPA dynamically analyzes and predicts quantum system evolution, ultimately aiming for more precise control and optimization within quantum computation. We detail the core mechanisms of DQPA, emphasizing its ability to mitigate error and computational complexity through the observation of quantum state transitions. This research explores the potential of DQPA to significantly advance the capabilities of quantum algorithms.

•Aug 31, 2026•0 citations

Dynamic-Graph Quantum Algorithm

Jincheng Zhang

This paper introduces a novel quantum algorithm, the Dynamic-Graph Quantum Algorithm, designed to enhance the efficiency of quantum computations by leveraging the unique properties of dynamic graphs. Traditional quantum algorithms often rely on static representations, limiting their potential for optimization. The Dynamic-Graph Quantum Algorithm utilizes dynamic graph structures to guide the optimization process, offering a fundamentally new approach to quantum circuit design and execution. This work explores the potential of dynamic graph structure in quantum computing and proposes a method for improving the performance and scalability of quantum algorithms.

•Sep 3, 2026•0 citations

Algorithms of quantum computation

Shinil Cho

Institute of Physics eBooks•Jul 1, 2022•7 citations
This paper presents the Dynamic Topological Quantum Algorithm (DTQA), a novel quantum algorithm designed to dynamically adapt quantum operations based on the system's inherent topological properties. Traditional quantum algorithms often require pre-defined parameters, limiting their flexibility and hindering optimal performance. DTQA addresses this limitation by incorporating a dynamic topology feature, allowing the algorithm to dynamically adjust quantum operations in response to the system's evolving topological structure. The core mechanism involves characterizing the system's topology and then employing a mapping to dynamically modify the quantum state, resulting in enhanced computational capabilities. This paper details the theoretical framework, implementation details, and preliminary results demonstrating the effectiveness of DTQA.
This paper introduces the Dynamic Quantum State Prediction Algorithm (DQPA), a novel approach to quantum state prediction that leverages the inherent dynamism of quantum states. Traditional methods often rely on static models, while DQPA dynamically analyzes and predicts quantum system evolution, ultimately aiming for more precise control and optimization within quantum computation. We detail the core mechanisms of DQPA, emphasizing its ability to mitigate error and computational complexity through the observation of quantum state transitions. This research explores the potential of DQPA to significantly advance the capabilities of quantum algorithms.
This paper introduces a novel quantum algorithm, the Dynamic-Graph Quantum Algorithm, designed to enhance the efficiency of quantum computations by leveraging the unique properties of dynamic graphs. Traditional quantum algorithms often rely on static representations, limiting their potential for optimization. The Dynamic-Graph Quantum Algorithm utilizes dynamic graph structures to guide the optimization process, offering a fundamentally new approach to quantum circuit design and execution. This work explores the potential of dynamic graph structure in quantum computing and proposes a method for improving the performance and scalability of quantum algorithms.