Optimizing Defect Detectability across Multiple Ultraviolet Wavelengths

Mark-Alexander Henn; Bryan M. Barnes; Hui Zhou; Richard M. Silver

doi:10.1364/MATH.2018.MM5D.3

Imaging and Applied Optics 2018 (3D, AO, AIO, COSI, DH, IS, LACSEA, LS&C, MATH, pcAOP)
OSA Technical Digest (Optica Publishing Group, 2018),
paper MM5D.3
•https://doi.org/10.1364/MATH.2018.MM5D.3

Optimizing Defect Detectability across Multiple Ultraviolet Wavelengths

Mark-Alexander Henn, Bryan M. Barnes, Hui Zhou, and Richard M. Silver

Mathematics in Imaging 2018

Orlando, Florida United States
25–28 June 2018
ISBN: 978-1-943580-44-6

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M. Henn, B. M. Barnes, H. Zhou, and R. M. Silver, "Optimizing Defect Detectability across Multiple Ultraviolet Wavelengths," in Imaging and Applied Optics 2018 (3D, AO, AIO, COSI, DH, IS, LACSEA, LS&C, MATH, pcAOP), OSA Technical Digest (Optica Publishing Group, 2018), paper MM5D.3.

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Abstract

We investigate defect detectability using simulated deep-, vacuum-, and extreme-ultraviolet wavelengths. Improvements to a signal-to-noise ratio defect metric appear achievable down to λ = 47 nm.

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