Unraveling the rodeo algorithm through the Zeeman model

Abstract We unravel the rodeo algorithm to determine the eigenstates and eigenvalues spectrum for a Hamiltonian considering arbitrary initial pure states. By presenting a novel methodology, we detail the original method and show how to define all properties without having prior knowledge regarding the eigenstates. To this end, we exploit Pennylane and Qiskit platforms resources to analyze scenarios where the Hamiltonians are described by the Zeeman model for one and two spins. We also introduce strategies and techniques to improve the algorithm’s performance by adjusting its intrinsic parameters and reducing the fluctuations inherent to data distribution. First, we explore the dynamics of a single qubit on Xanadu simulators to set the parameters that optimize the method performance and select the best strategies to execute the algorithm. On the sequence, we extend the methodology for bipartite systems to discuss how the algorithm works when degeneracy and entanglement are taken into account. Finally, we compare the predictions with the results obtained on a real superconducting device provided by the IBM Q Experience program, and conclude presenting conditions to increase the protocol efficiency for multi-qubit systems and more complex Hamiltonians.

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Publication Details

Journal
Physica Scripta
Published
2025-05-07
DOI
https://doi.org/10.1088/1402-4896/add58c
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Unraveling the rodeo algorithm through the Zeeman model

Rodrigo Alves Dias, W. A. T. Nogueira, J. C. S. Rocha, Raphael Fortes Infante Gomes
Physica Scripta
Neural Networks and Applications
article

Unraveling the rodeo algorithm through the Zeeman model

Rodrigo Alves Dias, W. A. T. Nogueira, J. C. S. Rocha, Raphael Fortes Infante Gomes
article en

Abstract

Abstract We unravel the rodeo algorithm to determine the eigenstates and eigenvalues spectrum for a Hamiltonian considering arbitrary initial pure states. By presenting a novel methodology, we detail the original method and show how to define all properties without having prior knowledge regarding the eigenstates. To this end, we exploit Pennylane and Qiskit platforms resources to analyze scenarios where the Hamiltonians are described by the Zeeman model for one and two spins. We also introduce strategies and techniques to improve the algorithm’s performance by adjusting its intrinsic parameters and reducing the fluctuations inherent to data distribution. First, we explore the dynamics of a single qubit on Xanadu simulators to set the parameters that optimize the method performance and select the best strategies to execute the algorithm. On the sequence, we extend the methodology for bipartite systems to discuss how the algorithm works when degeneracy and entanglement are taken into account. Finally, we compare the predictions with the results obtained on a real superconducting device provided by the IBM Q Experience program, and conclude presenting conditions to increase the protocol efficiency for multi-qubit systems and more complex Hamiltonians.

Physica ScriptaVol. 100(6)
Universidade Federal de Juiz de Fora (BR), Universidade Federal de Ouro Preto (BR), Universidade Federal da Integração Latino-Americana (BR)
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Openalex Percentile: Top 96%
Neural Networks and Applications
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Unraveling the rodeo algorithm through the Zeeman model — Rodrigo Alves Dias, W. A. T. Nogueira, et al. · Physica Scripta (2025) | TGRS Research Map | TGRS