Orthogonal Thermal Noise and Transmission Signals: A New Coherent Perfect Absorption’s Feature

Coherent perfect absorption (CPA) is an interference process associated with the zeros of the scattering matrix of interest for optical computing, data processing, and sensing. However, the noise properties of CPA remain relatively unexplored. Here, we demonstrate that CPA thermal noise signals exhibit a unique property: they are orthogonal to the signals transmitted through the network. In turn, such property enables a variety of thermal noise management effects, such as the physical separability of thermal noise and transmitted signals, and "externally lossless" networks that internally host radiative heat transfer processes. We believe that our results provide a new perspective on the many CPA technologies currently under development.

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Publication Details

Journal
Physical Review Letters
Published
2024-09-06
DOI
https://doi.org/10.1103/physrevlett.133.103801
Citations
3
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
1.04

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article

Orthogonal Thermal Noise and Transmission Signals: A New Coherent Perfect Absorption’s Feature

Ángel Ortega-Gomez, Iñigo Liberal, Osmery Hernández, Douglas Oña
3 citations
Physical Review Letters
Neural Networks and Reservoir Computing
1.04
article

Orthogonal Thermal Noise and Transmission Signals: A New Coherent Perfect Absorption’s Feature

Ángel Ortega-Gomez, Iñigo Liberal, Osmery Hernández, Douglas Oña
article en
3 citations

Abstract

Coherent perfect absorption (CPA) is an interference process associated with the zeros of the scattering matrix of interest for optical computing, data processing, and sensing. However, the noise properties of CPA remain relatively unexplored. Here, we demonstrate that CPA thermal noise signals exhibit a unique property: they are orthogonal to the signals transmitted through the network. In turn, such property enables a variety of thermal noise management effects, such as the physical separability of thermal noise and transmitted signals, and "externally lossless" networks that internally host radiative heat transfer processes. We believe that our results provide a new perspective on the many CPA technologies currently under development.

Physical Review LettersVol. 133(10)
Universidad Pública de Navarra (UPNA) (ES)
H2020 European Research Council
Affordable and clean energy
Openalex Percentile: Top 19%
Neural Networks and Reservoir Computing
1.04
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