Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Novel Modeling Approach for All-Dielectric Metasurfaces Using Deep
  Neural Networks   Metasurfaces have become a promising means for manipulating optical
wavefronts in flat and high-performance optical devices. Conventional
metasurface device design relies on trial-and-error methods to obtain target
electromagnetic (EM) response, an approach that demands significant efforts to
investigate the enormous number of possible meta-atom structures. In this
paper, a deep neural network approach is introduced that significantly improves
on both speed and accuracy compared to techniques currently used to assemble
metasurface-based devices. Our neural network approach overcomes three key
challenges that have limited previous neural-network-based design schemes:
input/output vector dimensional mismatch, accurate EM-wave phase prediction, as
well as adaptation to 3-D dielectric structures, and can be generically applied
to a wide variety of metasurface device designs across the entire
electromagnetic spectrum. Using this new methodology, examples of neural
networks capable of producing on-demand designs for meta-atoms, metasurface
filters, and phase-change reconfigurable metasurfaces are demonstrated.

4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
33
The categories of this paper are: plasm-ph
28
The categories of this paper are: alg-geom
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
34
The categories of this paper are: chem-ph
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
32
The categories of this paper are: atom-ph
11
The categories of this paper are: hep-lat
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th