Modal decomposition of a fibre laser beam based on the push-broom stochastic parallel gradient descent algorithm
Compared with traditional methods, the stochastic parallel gradient descent (SPGD) algorithm used in modal decomposition has its own unique advantages of faster speed, wider application range, and low experimental effort, demonstrating many development prospects. However, the current SPGD algorithm...
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| Veröffentlicht in: | Optics communications Jg. 481; S. 126538 |
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15.02.2021
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| Abstract | Compared with traditional methods, the stochastic parallel gradient descent (SPGD) algorithm used in modal decomposition has its own unique advantages of faster speed, wider application range, and low experimental effort, demonstrating many development prospects. However, the current SPGD algorithm only considers the modal weights of multimode optical fields and neglects the phase. More importantly, this algorithm is usually unsuitable for conducting modal decomposition of incoherent combined laser beams due to its serious ambiguities. In this paper, a novel modal decomposition algorithm, called the push-broom SPGD algorithm, is first proposed to achieve complete modal decomposition of optical fields emerging from multimode fibres. By iteratively evaluating the intensity profiles in different positions using the SPGD algorithm, this approach can obtain both amplitude and phase information with high accuracy. The proposed algorithm is preliminarily applied to the modal decomposition of an incoherent combined laser beam, and its feasibility is demonstrated via numerical simulations. By inserting a parallel plate, ambiguities can be solved and the influence of random noise is suppressed, demonstrating this algorithm’s potential.
•Novel Modal decomposition algorithm, named push-broom SPGD algorithm, is proposed.•This algorithm obtains both amplitude and phase information with high accuracy.•This algorithm provides an access to the modal content of combined laser beam.•The proposed off-axis method solves the ambiguity problem perfectly. |
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| AbstractList | Compared with traditional methods, the stochastic parallel gradient descent (SPGD) algorithm used in modal decomposition has its own unique advantages of faster speed, wider application range, and low experimental effort, demonstrating many development prospects. However, the current SPGD algorithm only considers the modal weights of multimode optical fields and neglects the phase. More importantly, this algorithm is usually unsuitable for conducting modal decomposition of incoherent combined laser beams due to its serious ambiguities. In this paper, a novel modal decomposition algorithm, called the push-broom SPGD algorithm, is first proposed to achieve complete modal decomposition of optical fields emerging from multimode fibres. By iteratively evaluating the intensity profiles in different positions using the SPGD algorithm, this approach can obtain both amplitude and phase information with high accuracy. The proposed algorithm is preliminarily applied to the modal decomposition of an incoherent combined laser beam, and its feasibility is demonstrated via numerical simulations. By inserting a parallel plate, ambiguities can be solved and the influence of random noise is suppressed, demonstrating this algorithm’s potential.
•Novel Modal decomposition algorithm, named push-broom SPGD algorithm, is proposed.•This algorithm obtains both amplitude and phase information with high accuracy.•This algorithm provides an access to the modal content of combined laser beam.•The proposed off-axis method solves the ambiguity problem perfectly. |
| ArticleNumber | 126538 |
| Author | Xie, Renwei Zhu, Rihong Chen, Fan Wan, Jun Wang, Qiang Ma, Jun Lu, Qiang Zhao, Shubin |
| Author_xml | – sequence: 1 givenname: Fan surname: Chen fullname: Chen, Fan email: pananchenfan@163.com organization: Jiangsu Automation Research Institute, Lianyungang 222000, China – sequence: 2 givenname: Shubin surname: Zhao fullname: Zhao, Shubin organization: Jiangsu Automation Research Institute, Lianyungang 222000, China – sequence: 3 givenname: Qiang surname: Wang fullname: Wang, Qiang organization: Jiangsu Automation Research Institute, Lianyungang 222000, China – sequence: 4 givenname: Jun surname: Ma fullname: Ma, Jun organization: School of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology, Nanjing 210094, China – sequence: 5 givenname: Qiang surname: Lu fullname: Lu, Qiang organization: Jiangsu Automation Research Institute, Lianyungang 222000, China – sequence: 6 givenname: Jun surname: Wan fullname: Wan, Jun organization: Jiangsu Automation Research Institute, Lianyungang 222000, China – sequence: 7 givenname: Renwei surname: Xie fullname: Xie, Renwei organization: Jiangsu Automation Research Institute, Lianyungang 222000, China – sequence: 8 givenname: Rihong surname: Zhu fullname: Zhu, Rihong organization: School of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology, Nanjing 210094, China |
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