Spatio-spectral optical fission in time-varying subwavelength layers

Transparent conducting oxides are highly doped semiconductors that exhibit favourable optical features compared with metals, including reduced material losses, tuneable electronic and optical properties, and enhanced damage thresholds. Recently, the photonic community has renewed its attention towards these materials, recognizing their remarkable nonlinear optical properties in the near-infrared spectrum. The exceptionally large and ultrafast change in the refractive index, which can be optically induced in these compounds, extends beyond the boundaries of conventional perturbative analysis and makes this class of materials the closest approximation to a time-varying system. Here we report the spatio-spectral fission of an ultrafast pulse trespassing a thin film of aluminium zinc oxide with a non-stationary refractive index. By applying phase conservation to this time-varying layer, our model can account for both space and time refraction and explain, in quantitative terms, the spatial separation of both spectrum and energy. Our findings represent an example of extreme nonlinear phenomena on subwavelength propagation distances, which provides new insights into transparent conducting oxides' transient optical properties. This can be critical for the ongoing research on photonic time crystals, on-chip generation of non-classical states of light, integrated optical neural networks, ultrafast beam steering and frequency-division multiplexing.

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Publication Details

Journal
Nature Photonics
Published
2025-03-07
DOI
https://doi.org/10.1038/s41566-025-01640-1
Citations
10
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
24.81

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article

Spatio-spectral optical fission in time-varying subwavelength layers

Wallace Jaffray, Vladimir M. Shalaev, Marcello Ferrera, Colton Fruhling et al.
10 citations
Nature Photonics
Neural Networks and Reservoir Computing
24.81
article

Spatio-spectral optical fission in time-varying subwavelength layers

Wallace Jaffray, Vladimir M. Shalaev, Marcello Ferrera, Colton Fruhling, Mustafa Goksu Ozlu, Michael Scalora, Fabio Biancalana, Sven Stengel, Alexandra Boltasseva
article en
10 citations

Abstract

Transparent conducting oxides are highly doped semiconductors that exhibit favourable optical features compared with metals, including reduced material losses, tuneable electronic and optical properties, and enhanced damage thresholds. Recently, the photonic community has renewed its attention towards these materials, recognizing their remarkable nonlinear optical properties in the near-infrared spectrum. The exceptionally large and ultrafast change in the refractive index, which can be optically induced in these compounds, extends beyond the boundaries of conventional perturbative analysis and makes this class of materials the closest approximation to a time-varying system. Here we report the spatio-spectral fission of an ultrafast pulse trespassing a thin film of aluminium zinc oxide with a non-stationary refractive index. By applying phase conservation to this time-varying layer, our model can account for both space and time refraction and explain, in quantitative terms, the spatial separation of both spectrum and energy. Our findings represent an example of extreme nonlinear phenomena on subwavelength propagation distances, which provides new insights into transparent conducting oxides' transient optical properties. This can be critical for the ongoing research on photonic time crystals, on-chip generation of non-classical states of light, integrated optical neural networks, ultrafast beam steering and frequency-division multiplexing.

Nature PhotonicsVol. 19(6)
Purdue University West Lafayette (US), United States Army Combat Capabilities Development Command (US), Heriot-Watt University (GB), U.S. Army Space and Missile Defense Command (US)
U.S. Department of Energy, Heriot-Watt University, Engineering and Physical Sciences Research Council, Basic Energy Sciences, U.S. Army Combat Capabilities Development Command, Air Force Office of Scientific Research, Division of Materials Sciences and Engineering, European Office of Aerospace Research and Development
Sustainable cities and communities
Openalex Percentile: Top 1%
Neural Networks and Reservoir Computing
24.81
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