Quantum frequency resampling
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866918201796853760 |
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| author | Tumbiolo, Emanuele Roncallo, Simone Macchiavello, Chiara Maccone, Lorenzo |
| author_facet | Tumbiolo, Emanuele Roncallo, Simone Macchiavello, Chiara Maccone, Lorenzo |
| contents | In signal processing, resampling algorithms can modify the number of resources encoding a collection of data points. Downsampling reduces the cost of storage and communication, while upsampling interpolates new data from limited one, e.g. when resizing a digital image. We present a toolset of quantum algorithms to resample data encoded in the probabilities of a quantum register, using the quantum Fourier transform to adjust the number of high-frequency encoding qubits. We discuss advantage over classical resampling algorithms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_16283 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Quantum frequency resampling Tumbiolo, Emanuele Roncallo, Simone Macchiavello, Chiara Maccone, Lorenzo Quantum Physics Computational Physics Data Analysis, Statistics and Probability In signal processing, resampling algorithms can modify the number of resources encoding a collection of data points. Downsampling reduces the cost of storage and communication, while upsampling interpolates new data from limited one, e.g. when resizing a digital image. We present a toolset of quantum algorithms to resample data encoded in the probabilities of a quantum register, using the quantum Fourier transform to adjust the number of high-frequency encoding qubits. We discuss advantage over classical resampling algorithms. |
| title | Quantum frequency resampling |
| topic | Quantum Physics Computational Physics Data Analysis, Statistics and Probability |
| url | https://arxiv.org/abs/2501.16283 |