Surface shape determination with a stitching Michelson interferometer and accuracy evaluation

Abstract

Stitching methods are increasingly used for determining the surface shape of large and high precision optical elements used in synchrotron beamlines. They consist in reconstructing the surface topography from multiple measurements on overlapping parts of the optics aperture by various algorithms. This paper is an attempt to investigate how true and accurate such a reconstruction can be. Error sources are identified and evaluated throughout the acquisition and processing steps. The analysis is based on the example SOLEIL Michelson interferometer for nano-topography, a dedicated measurement bench for stitching interferometry. We propose a method for determining the error made on the estimate of the interferometric reference surface from the stitching dataset. This determination is made before and independently of the stitching procedure itself.

Statistical Analysis of Measurement Processes Using Multi-Physic Instruments: Insights from Stitched Maps

“…But neighboring maps are different due to noise [18] or measurement point-of view, and have a shift of positioning reference due to (X/Y) table drifts or uncertainties due to the influence of the environment on instrument measurement conditions. This is why stitching can introduce errors as shown in [19]. The stitching errors depend firstly on the elementary maps coming from the instrument: resolution, overlapping percentage, or type of technology.…”

The stitching interferometry system of ALBA

“…For this reason, x-ray optics metrology has been traditionally dominated by angle-measuring instruments, like LTPs [7][8][9] and NOMs [10][11][12]. In the last decade, the rise of subaperture stitching interferometry methods (scanning measurements with Fizeau interferometers) [13][14][15] has allowed obtaining measurements of long mirrors with sub-nanometric accuracy [16][17][18][19][20][21][22][23][24][25][26].…”

“…This redundancy can be also used to retrieve additional information about the system and remove some systematic errors of the measurement [16][17][18][19][27][28][29]. Polack et al [23] and Nicolas et al [24] used this redundant data to subtract the "reference" errors in 1D. In a previous work, ref.…”