activity
20242026
most citedPhase-change metasurfaces for reconfigurable image processing

13 citations · 13 across the 6 of their papers we have counts for

collaborators

14 papers

physics.optics2026

Broad-angle photon-pair generation from flatband quasi-BIC resonant 3R-MoS metasurfaces

Tingting Liu, Huifu Qiu, Xintong Shi +2

Spontaneous parametric down-conversion (SPDC) in ultrathin optical resonant metasurfaces offers a promising platform for integrated quantum light sources. However, conventional res…

physics.optics2026

Edge-Enhanced Diffractive Neural Networks Based on Spin-Multiplexed Nonlocal Metasurfaces

Qianqian He, Kenan Guo, Jumin Qiu +2

Single-layer diffractive neural networks often face classification accuracy bottlenecks due to limited wavefront modulation capabilities. Edge detection, as an optical image proces…

physics.optics2026

Omnidirectional photonic chiral flatband in nonlocal membrane metasurfaces

Baohe Zhang, Jumin Qiu, Meng Qin +7

Omnidirectional flat-band resonances, characterized by an enhanced photonic density of states and inherent angular robustness, are highly sought-after in integrated nanophotonic de…

physics.optics2026

Flat optics for analog computing: from fundamental mechanisms to advanced meta-processors

Tingting Liu, Jumin Qiu, Xintong Shi +2

As the explosive growth of visual data increasingly strains the latency and energy limits of conventional electronic computing, optical analog computing has re-emerged as a disrupt…

physics.optics2026

Doubly resonant nonlinear metasurfaces enabling NIR-to-UV upconversion for reconfigurable Fourier optical processing

Jumin Qiu, Meibao Qin, Tingting Liu +6

Fourier optical processing underpins optical information manipulation, yet extending such operations to short wavelengths within compact platforms remains challenging. Here, we add…

physics.optics2025

Metasurface-based all-optical diffractive convolutional neural networks

Zhijiang Liang, Chenxuan Xiang, Shuyuan Xiao +5

The escalating energy demands and parallel-processing bottlenecks of electronic neural networks underscore the need for alternative computing paradigms. Optical neural networks, ca…