Beamfit：利用多幅强度图像与拉盖尔或厄米-高斯基进行激光波波前重构的算法
Beamfit: Algorithmic Wavefront Reconstruction of Laser Beams Using Multiple Intensity Images and Laguerre- or Hermite-Gaussian Basis
AI总结：
针对激光系统的波前误差问题，提出Beamfit算法，基于多幅CCD图像和高斯模式基重构波前，通过优化计算复杂度和预计算参数大幅提升效率，计划开源发布。
摘要：
波前误差是激光产生与成像过程中常见的伪影，可描述为理想高斯光束的球面波前发生的像差，由高阶厄米-高斯项或拉盖尔-高斯项组合而成。本文提出一种名为Beamfit的算法，可通过在激光束瑞利范围内拍摄的一系列CCD图像估计模式组成。该算法采用用户定义的一组厄米-高斯或拉盖尔-高斯模式作为其理论模型的基。我们提出了一种新方法，可减少计算模型强度分布所需的运算量：对于包含$N$个模式的给定模型，所需计算的厄米-高斯复振幅数量从$\boldsymbol{\text{O}}(N^2)$量级降至$\boldsymbol{\text{O}}(N)$量级，并替换为简单乘法运算。此外，非光束参数会被预先计算，以进一步降低搜索空间维度并减少由此产生的计算时间。研究团队计划以开源许可证向公众发布Beamfit软件。
英文摘要：
Wavefront errors are a common artifact in laser light generation and imaging. They can be described as an aberration from the spherical wavefront of an ideal Gaussian beam by combinations of higher-order Hermite- or Laguerre-Gaussian terms. Here, we present an algorithm called Beamfit to estimate the mode composition from a series of CCD images taken over the Rayleigh range of a laser beam. The algorithm uses a user-defined set of Hermite- or Laguerre-Gaussian modes as the basis of its theoretical model. A novel method reduces the number of calculations needed to compute the model's intensity profiles. For a given model containing $N$ modes, the number of Hermite-Gaussian complex amplitudes needed to calculate are reduced from orders of $\mathcal{O}(N^2)$ to $\mathcal{O}(N)$ and replaced by simple multiplications. Additionally, non-beam parameters are pre-calculated to further reduce the search space dimension and its resulting calculation time. It is planned to release the Beamfit software to the public under an open-source license.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
