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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/2507.16140 |
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| _version_ | 1866914167889330176 |
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| author | Volpato, Maria Carolina Rosa, Henrique G. Reep, Tom de Assis, Pierre-Louis Frateschi, Newton Cesario |
| author_facet | Volpato, Maria Carolina Rosa, Henrique G. Reep, Tom de Assis, Pierre-Louis Frateschi, Newton Cesario |
| contents | We investigate the saturable absorption behavior of a 1T'-MoTe$_2$ monolayer integrated with a silicon nitride waveguide for applications in photonic neural networks. Using experimental transmission measurements and theoretical modeling, we characterize the nonlinear response of the material. Our model, incorporating quasi-Fermi level separation and carrier dynamics, successfully explains these behaviors and predicts the material's absorption dependence on the carrier density. Furthermore, we demonstrate a coupling efficiency of up to 20% between the 1T'-MoTe$_2$ monolayer and the silicon nitride waveguide, with saturation achievable at input powers as low as a few uW. These results suggest that 1T'-MoTe$_2$ is a promising candidate for implementing nonlinear functions in integrated photonic neural networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_16140 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | 1T'-MoTe$_2$ as an integrated saturable absorber for photonic machine learning Volpato, Maria Carolina Rosa, Henrique G. Reep, Tom de Assis, Pierre-Louis Frateschi, Newton Cesario Optics Applied Physics We investigate the saturable absorption behavior of a 1T'-MoTe$_2$ monolayer integrated with a silicon nitride waveguide for applications in photonic neural networks. Using experimental transmission measurements and theoretical modeling, we characterize the nonlinear response of the material. Our model, incorporating quasi-Fermi level separation and carrier dynamics, successfully explains these behaviors and predicts the material's absorption dependence on the carrier density. Furthermore, we demonstrate a coupling efficiency of up to 20% between the 1T'-MoTe$_2$ monolayer and the silicon nitride waveguide, with saturation achievable at input powers as low as a few uW. These results suggest that 1T'-MoTe$_2$ is a promising candidate for implementing nonlinear functions in integrated photonic neural networks. |
| title | 1T'-MoTe$_2$ as an integrated saturable absorber for photonic machine learning |
| topic | Optics Applied Physics |
| url | https://arxiv.org/abs/2507.16140 |