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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2306.06565 |
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| _version_ | 1866918411701846016 |
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| author | Pu, Yongjie Fan, Minyu Zhang, Zhicheng Zhu, Jie Li, Huinan Wanga, Sha |
| author_facet | Pu, Yongjie Fan, Minyu Zhang, Zhicheng Zhu, Jie Li, Huinan Wanga, Sha |
| contents | Passively mode-locked fiber lasers based on nonlinear polarization rotation (NPR) have been widely used due to their ability to produce short pulses with high peak power and broad spectrum. Nevertheless, environmental disturbances can disrupt the mode-locked state, making it a challenge for practical implementation. Therefore, scientists have proposed mode-locked NPR lasers assisted with artificial intelligence, which can effectively address the issues related to mode-locking stability. Speckle patterns containing spectral information can be generated when the laser transmitting through a scattering medium, which can be served as indicators of the mode-locked state. The contrast of the Tamura texture feature of the speckle patterns exhibits periodic "V" shaped variations with respect to the rotation angles of the waveplates, according to experimental results. The stable mode-locking region is confined to the area close to the minimum contrast. Based on these characteristics, an intelligent approach employing a modified gradient algorithm to identify the region of minimum speckle contrast for achieving mode-locked state. The average number of iterations needed to achieve initial mode-locking and recover mode-locking are about 20 and 10, respectively. Once the mode-locking is achieved, the neural network can be employed to distinguish single-pulse or multi-pulses outputs based on the speckle pattern, thereby enabling intelligent stable mode-locked single-pulse genration from the NPR fiber laser. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_06565 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Intelligent mode-locked NPR fiber laser based on laser speckle characteristics Pu, Yongjie Fan, Minyu Zhang, Zhicheng Zhu, Jie Li, Huinan Wanga, Sha Optics Passively mode-locked fiber lasers based on nonlinear polarization rotation (NPR) have been widely used due to their ability to produce short pulses with high peak power and broad spectrum. Nevertheless, environmental disturbances can disrupt the mode-locked state, making it a challenge for practical implementation. Therefore, scientists have proposed mode-locked NPR lasers assisted with artificial intelligence, which can effectively address the issues related to mode-locking stability. Speckle patterns containing spectral information can be generated when the laser transmitting through a scattering medium, which can be served as indicators of the mode-locked state. The contrast of the Tamura texture feature of the speckle patterns exhibits periodic "V" shaped variations with respect to the rotation angles of the waveplates, according to experimental results. The stable mode-locking region is confined to the area close to the minimum contrast. Based on these characteristics, an intelligent approach employing a modified gradient algorithm to identify the region of minimum speckle contrast for achieving mode-locked state. The average number of iterations needed to achieve initial mode-locking and recover mode-locking are about 20 and 10, respectively. Once the mode-locking is achieved, the neural network can be employed to distinguish single-pulse or multi-pulses outputs based on the speckle pattern, thereby enabling intelligent stable mode-locked single-pulse genration from the NPR fiber laser. |
| title | Intelligent mode-locked NPR fiber laser based on laser speckle characteristics |
| topic | Optics |
| url | https://arxiv.org/abs/2306.06565 |