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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.19272 |
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| _version_ | 1866911332243079168 |
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| author | Mannone, Maria Itaborai, Paulo Vitor Hamido, Omar Costa Goldack, Miriam Marwan, Norbert Fazio, Peppino Ribino, Patrizia |
| author_facet | Mannone, Maria Itaborai, Paulo Vitor Hamido, Omar Costa Goldack, Miriam Marwan, Norbert Fazio, Peppino Ribino, Patrizia |
| contents | We apply sonification strategies and quantum computing to the analysis of an episode of seizure. We first sonify the signal from a selection of channels (from real ECoG data), obtaining a polyphonic sequence. Then, we propose two quantum approaches to simulate a similar episode of seizure, and we sonify the results. The comparison of sonifications can give hints on similarities and discrepancies between real data and simulations, helping refine the \textit{in silico} model. This is a pioneering approach, showing how the combination of quantum computing and sonification can broaden the perspective of real-data investigation, and helping define a new test bench for analysis and prediction of seizures. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_19272 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Sonified Quantum Seizures. Sonification of time series in epileptic seizures and simulation of seizures via quantum modelling Mannone, Maria Itaborai, Paulo Vitor Hamido, Omar Costa Goldack, Miriam Marwan, Norbert Fazio, Peppino Ribino, Patrizia Quantum Physics Emerging Technologies Sound We apply sonification strategies and quantum computing to the analysis of an episode of seizure. We first sonify the signal from a selection of channels (from real ECoG data), obtaining a polyphonic sequence. Then, we propose two quantum approaches to simulate a similar episode of seizure, and we sonify the results. The comparison of sonifications can give hints on similarities and discrepancies between real data and simulations, helping refine the \textit{in silico} model. This is a pioneering approach, showing how the combination of quantum computing and sonification can broaden the perspective of real-data investigation, and helping define a new test bench for analysis and prediction of seizures. |
| title | Sonified Quantum Seizures. Sonification of time series in epileptic seizures and simulation of seizures via quantum modelling |
| topic | Quantum Physics Emerging Technologies Sound |
| url | https://arxiv.org/abs/2512.19272 |