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Topological analog signal processing

Author

Listed:
  • Farzad Zangeneh-Nejad

    (Swiss Federal Institute of Technology in Lausanne (EPFL))

  • Romain Fleury

    (Swiss Federal Institute of Technology in Lausanne (EPFL))

Abstract

Analog signal processors have attracted a tremendous amount of attention recently, as they potentially offer much faster operation and lower power consumption than their digital versions. Yet, they are not preferable for large scale applications due to the considerable observational errors caused by their excessive sensitivity to environmental and structural variations. Here, we demonstrate both theoretically and experimentally the unique relevance of topological insulators for alleviating the unreliability of analog signal processors. In particular, we achieve an important signal processing task, namely resolution of linear differential equations, in an analog system that is protected by topology against large levels of disorder and geometrical perturbations. We believe that our strategy opens up large perspectives for a new generation of robust all-optical analog signal processors, which can now not only perform ultrafast, high-throughput, and power efficient signal processing tasks, but also compete with their digital counterparts in terms of reliability and flexibility.

Suggested Citation

  • Farzad Zangeneh-Nejad & Romain Fleury, 2019. "Topological analog signal processing," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10086-3
    DOI: 10.1038/s41467-019-10086-3
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    Cited by:

    1. Jérôme Sol & David R. Smith & Philipp Hougne, 2022. "Meta-programmable analog differentiator," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Ali Momeni & Romain Fleury, 2022. "Electromagnetic wave-based extreme deep learning with nonlinear time-Floquet entanglement," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    3. Michele Cotrufo & Akshaj Arora & Sahitya Singh & Andrea Alù, 2023. "Dispersion engineered metasurfaces for broadband, high-NA, high-efficiency, dual-polarization analog image processing," Nature Communications, Nature, vol. 14(1), pages 1-9, December.

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