Off-axis angular spectrum method with variable sampling interval

Kim, Min Su; Byun, Chun‐Won; Oh, Himchan; Pi, Jae‐Eun; Choi, Jihun; Kim, Gi Heon; Lee, Myung‐Lae; Ryu, Hojun; Hwang, Chi-Sun

doi:10.1016/j.optcom.2015.03.013

Cited by 7 publications

(1 citation statement)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hence, as illustrated in Fig. 2(c), the chirp Z-transform (CZT) is used instead to gain control over image plane sampling intervals Δxout and Δyout and window center position (x0, y0) independent to output plane settings [13][14][15] . Fig.…”

Section: Metasurface Aberration Corrector Inverse Designmentioning

confidence: 99%

Metasurface hybrid lens inverse design with diffractive/refractive co-optimization

Shih

Renshaw

2023

Advanced Optics for Imaging Applications: UV Through LWIR VIII

View full text Add to dashboard Cite

We combine metasurface optics and refractive optics to form hybrid lenses, where the refractive elements provide the optical power but metasurfaces are used to correct aberrations. We introduce an algorithm to optimize layout of metasurfaces (MSs) in hybrid lens designs where the MSs can be located anywhere in the optical train. This algorithm uses a ray-based, scalar field method to propagate through refractive optics with speed comparable to Fourier methodswhich are limited to propagation between planar surfaces. This method supports propagation of real optical fields and derived adjoint fields, both forward and backward, which enables inverse design with adjoint gradient methods to optimize the MS nanostructured layout. In contrast to previous image-space optimizations which neatly partition the problem into separate ray-optics and wave-optics domains, this algorithm provides the freedom to arbitrarily interleave metasurface optics with refractive optics during hybrid lens design. A hybrid lens design example in mid-wave infrared is presented to demonstrate this framework.

show abstract

Section: Metasurface Aberration Corrector Inverse Designmentioning

confidence: 99%