QMetro++ -- Python optimization package for large scale quantum metrology with customized strategy structures
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866918321350246400 |
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| author | Dulian, Piotr Kurdziałek, Stanisław Demkowicz-Dobrzański, Rafał |
| author_facet | Dulian, Piotr Kurdziałek, Stanisław Demkowicz-Dobrzański, Rafał |
| contents | QMetro++ is a Python package that provides a set of tools for identifying optimal estimation protocols that maximize quantum Fisher information (QFI). Optimization can be performed for arbitrary configurations of input states, parameter-encoding channels, noise correlations, control operations, and measurements. The use of tensor networks and an iterative see-saw algorithm allows for an efficient optimization even in the regime of a large number of channel uses ($N\approx100$). Additionally, the package includes implementations of the recently developed methods for computing fundamental upper bounds on QFI, which serve as benchmarks for assessing the optimality of numerical optimization results. All functionalities are wrapped up in a user-friendly interface which enables the definition of strategies at various levels of detail. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_16524 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | QMetro++ -- Python optimization package for large scale quantum metrology with customized strategy structures Dulian, Piotr Kurdziałek, Stanisław Demkowicz-Dobrzański, Rafał Quantum Physics QMetro++ is a Python package that provides a set of tools for identifying optimal estimation protocols that maximize quantum Fisher information (QFI). Optimization can be performed for arbitrary configurations of input states, parameter-encoding channels, noise correlations, control operations, and measurements. The use of tensor networks and an iterative see-saw algorithm allows for an efficient optimization even in the regime of a large number of channel uses ($N\approx100$). Additionally, the package includes implementations of the recently developed methods for computing fundamental upper bounds on QFI, which serve as benchmarks for assessing the optimality of numerical optimization results. All functionalities are wrapped up in a user-friendly interface which enables the definition of strategies at various levels of detail. |
| title | QMetro++ -- Python optimization package for large scale quantum metrology with customized strategy structures |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2506.16524 |