Tianxiang Dai
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
All Publications
-
Graphene/silicon heterojunction for reconfigurable phase-relevant activation function in coherent optical neural networks.
Nature communications
2023; 14 (1): 6939
Abstract
Optical neural networks (ONNs) herald a new era in information and communication technologies and have implemented various intelligent applications. In an ONN, the activation function (AF) is a crucial component determining the network performances and on-chip AF devices are still in development. Here, we first demonstrate on-chip reconfigurable AF devices with phase activation fulfilled by dual-functional graphene/silicon (Gra/Si) heterojunctions. With optical modulation and detection in one device, time delays are shorter, energy consumption is lower, reconfigurability is higher and the device footprint is smaller than other on-chip AF strategies. The experimental modulation voltage (power) of our Gra/Si heterojunction achieves as low as 1V (0.5mW), superior to many pure silicon counterparts. In the photodetection aspect, a high responsivity of over 200mA/W is realized. Special nonlinear functions generated are fed into a complex-valued ONN to challenge handwritten letters and image recognition tasks, showing improved accuracy and potential of high-efficient, all-component-integration on-chip ONN. Our results offer new insights for on-chip ONN devices and pave the way to high-performance integrated optoelectronic computing circuits.
View details for DOI 10.1038/s41467-023-42116-6
View details for PubMedID 37907477
-
Integrated Photonic Neural Networks: Opportunities and
ACS PHOTONICS
2023; 10 (7): 2001-2010
View details for DOI 10.1021/acsphotonics.2c01516
View details for Web of Science ID 000963349400001
-
Snapshot Mueller spectropolarimeter imager.
Microsystems & nanoengineering
2023; 9: 125
Abstract
We introduce an imaging system that can simultaneously record complete Mueller polarization responses for a set of wavelength channels in a single image capture. The division-of-focal-plane concept combines a multiplexed illumination scheme based on Fourier optics together with an integrated telescopic light-field imaging system. Polarization-resolved imaging is achieved using broadband nanostructured plasmonic polarizers as functional pinhole apertures. The recording of polarization and wavelength information on the image sensor is highly interpretable. We also develop a calibration approach based on a customized neural network architecture that can produce calibrated measurements in real-time. As a proof-of-concept demonstration, we use our calibrated system to accurately reconstruct a thin film thickness map from a four-inch wafer. We anticipate that our concept will have utility in metrology, machine vision, computational imaging, and optical computing platforms.
View details for DOI 10.1038/s41378-023-00588-y
View details for PubMedID 37814609
-
Matrix eigenvalue solver based on reconfigurable photonic neural network
NANOPHOTONICS
2022; 11 (17): 4089-4099
View details for DOI 10.1515/nanoph-2022-0109
View details for Web of Science ID 000787158300001