6 citations · 9 across the 9 of their papers we have counts for
4 papers · 2 filters
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…
In-situ Adjoint Wave Control in Reconfigurable Non-Hermitian Nonlinear Systems
John Guillamon, William Tuxbury, Cheng-Zhen Wang +3
Complex multipath environments are usually avoided in wave-based information processing because repeated scattering creates many interfering propagation paths, obscuring controllab…
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…