Usually,a multilens optical system is composed of multiple undetectable sublenses.Wavefront of a multilens optical system cannot be measured when classical transmitted phase measuring deflectometry[PMD] is used.In thi...Usually,a multilens optical system is composed of multiple undetectable sublenses.Wavefront of a multilens optical system cannot be measured when classical transmitted phase measuring deflectometry[PMD] is used.In this study,a wavefront measuring method for an optical system with multiple optics is presented based on PMD.A paraxial plane is used to represent the test multilens optical system.We introduce the calibration strategy and mathematical deduction of gradient equations.Systematic errors are suppressed with an N-rotation test.Simulations have been performed to demonstrate our method.The results showing the use of our method in multilens optical systems,such as the collimator and single-lens reflex camera lenses show that the measurement accuracy is comparable with those of interferometric tests.展开更多
Presented is a novel way to combine snapshot compressive imaging and lateral shearing interferometry in order to capture the spatio-spectral phase of an ultrashort laser pulse in a single shot.A deep unrolling algorit...Presented is a novel way to combine snapshot compressive imaging and lateral shearing interferometry in order to capture the spatio-spectral phase of an ultrashort laser pulse in a single shot.A deep unrolling algorithm is utilized for snapshot compressive imaging reconstruction due to its parameter efficiency and superior speed relative to other methods,potentially allowing for online reconstruction.The algorithm’s regularization term is represented using a neural network with 3D convolutional layers to exploit the spatio-spectral correlations that exist in laser wavefronts.Compressed sensing is not typically applied to modulated signals,but we demonstrate its success here.Furthermore,we train a neural network to predict the wavefronts from a lateral shearing interferogram in terms of Zernike polynomials,which again increases the speed of our technique without sacrificing fidelity.This method is supported with simulation-based results.While applied to the example of lateral shearing interferometry,the methods presented here are generally applicable to a wide range of signals,including Shack-Hartmann-type sensors.The results may be of interest beyond the context of laser wavefront characterization,including within quantitative phase imaging.展开更多
基金supported by the City Foundation of Nanchong(Nos.SXQHJH026 and 2021SXHZ041)。
文摘Usually,a multilens optical system is composed of multiple undetectable sublenses.Wavefront of a multilens optical system cannot be measured when classical transmitted phase measuring deflectometry[PMD] is used.In this study,a wavefront measuring method for an optical system with multiple optics is presented based on PMD.A paraxial plane is used to represent the test multilens optical system.We introduce the calibration strategy and mathematical deduction of gradient equations.Systematic errors are suppressed with an N-rotation test.Simulations have been performed to demonstrate our method.The results showing the use of our method in multilens optical systems,such as the collimator and single-lens reflex camera lenses show that the measurement accuracy is comparable with those of interferometric tests.
基金supported by the Independent Junior Research Group‘Characterization and control of high-intensity laser pulses for particle acceleration’,DFG Project No.453619281We would also like to acknowledge UKRI-STFC grant ST/V001655/1.
文摘Presented is a novel way to combine snapshot compressive imaging and lateral shearing interferometry in order to capture the spatio-spectral phase of an ultrashort laser pulse in a single shot.A deep unrolling algorithm is utilized for snapshot compressive imaging reconstruction due to its parameter efficiency and superior speed relative to other methods,potentially allowing for online reconstruction.The algorithm’s regularization term is represented using a neural network with 3D convolutional layers to exploit the spatio-spectral correlations that exist in laser wavefronts.Compressed sensing is not typically applied to modulated signals,but we demonstrate its success here.Furthermore,we train a neural network to predict the wavefronts from a lateral shearing interferogram in terms of Zernike polynomials,which again increases the speed of our technique without sacrificing fidelity.This method is supported with simulation-based results.While applied to the example of lateral shearing interferometry,the methods presented here are generally applicable to a wide range of signals,including Shack-Hartmann-type sensors.The results may be of interest beyond the context of laser wavefront characterization,including within quantitative phase imaging.
