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Eigenfunctions of Laplacian for phase estimation from wavefront gradient or curvature sensing

机译:通过波前梯度或曲率检测进行相位估计的拉普拉斯特征函数

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摘要

Modal cross coupling usually exists in wavefront estimation through Zernike polynomials. In order to cope with the problem, the eigenfunctions of Laplacian with Neumann boundary condition are proposed instead of Zernike polynomials to reconstruct phase from wavefront gradient or curvature sensing. It is proved theoretically that these modals can avoid modal cross coupling in both wavefront gradient sensing and curvature sensing. In wavefront gradient sensing, the coefficients of eigenfunctions of Laplacian can be obtained from the integral of the scalar product between the gradient of Laplacian's eigenfunctions and wavefront gradient signal. In wavefront curvature sensing, the coefficients of eigenfunctions of Laplacian can be calculated from the integral of the product of Laplacian's eigenfunctions and wavefront curvature signal. This approach is applicable on arbitrary apertures as long as eigenfunctions of Laplacian on apertures of arbitrary shape can be obtained.
机译:通过Zernike多项式在波前估计中通常存在模态交叉耦合。为了解决该问题,提出了具有诺伊曼边界条件的拉普拉斯算子的本征函数,而不是泽尼克多项式,以便从波前梯度或曲率检测中重建相位。从理论上证明这些模态可以避免波前梯度感测和曲率感测中的模态交叉耦合。在波前梯度传感中,拉普拉斯特征函数的系数可以从拉普拉斯特征函数的梯度与波前梯度信号之间的标量积的积分中获得。在波前曲率检测中,可以根据拉普拉斯特征函数与波前曲率信号乘积的积分来计算拉普拉斯特征函数的系数。该方法适用于任意孔径,只要可以获得拉普拉斯算子在任意形状孔径上的本征函数即可。

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