9 citations · 9 across the 5 of their papers we have counts for
5 papers
Physical policy gradient theorem for in situ stochastic-adjoint training
William Tuxbury, Zin Lin
In situ adjoint training extracts parameter gradients directly from measurement, but has so far been limited to reciprocal or restricted systems. Here, we introduce the physical co…
Differentiable Fast Far-Field Transform in Cylindrical Coordinates for Large-Area Cascaded Metalens Optics
Arvin Keshvari, Ata Shakeri, William Tuxbury +4
We present a fully differentiable far-field transform in cylindrical coordinates for full-area point spread function (PSF) evaluation and optimization of large axisymmetric metalen…
Adaptive Sensing beyond Non-Adaptive Information Limits: End-to-End Co-Design of Geometry, Policy, and Inference
Arvin Keshvari, William Tuxbury, Zin Lin
Inverse design has transformed vast physical parameter spaces into a substrate for emergent functionality, raising the tantalizing prospect of relocating intelligence from the digi…
Exploiting nonlinear incoherent image formation through linear volume metaoptics for inference
Nan Zhang, Arvin Keshvari, Ata Shakeri +1
We showed that a 2D depth map representing an incoherent 3D opaque scene is directly encoded in the response function of an imaging optics. As a result, the optics creates an image…
Scalable freeform optimization of wide-aperture 3D metalenses by zoned discrete axisymmetry
Mengdi Sun, Ata Shakeri, Arvin Keshvari +5
We introduce a novel framework for design and optimization of 3D freeform metalenses that attains nearly linear scaling of computational cost with diameter, by breaking the lens in…