we report on the development of a power efficient Faraday laser working at 780nm Rb transition using an atomic vapor Faraday filter as a frequency-selecting element. In the routine linear-cavity of Faraday laser, a pa...
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In this paper, optical forward error correction using recirculating frequency shifter is proposed and investigated. The optical and in-the-fly process leads to great potential for low latency and high-speed optical co...
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We propose and experimentally demonstrate a batch dimension processing scheme based on the micro-ring weighting bank, which can at least quadruple the computing capability of the photonic tensor core without extra wei...
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We propose a method of tuning the repetition rate of soliton microcombs by temperature. The tunable range reaches 12 MHz. The trade-off between acquisition rate and precision of ranging systems is overcome without add...
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A convolution neural network is proposed to reconstruct the true value from phase-wrapped interferometric sensing signals. The MAE and RMSE in a real phase dataset sampled by DAS are 0.069 p and 0.352 p respectively. ...
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3D microwave imaging of human targets has potential applications in military detection and intelligent interaction fields, we propose an auto-encoder-like capsule network to complete this task. We make two different 3...
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A dual-polarization fiber-optic gyroscope with a delay coil is realized. The bias instability reaches 5 x 10"6 °/h. An earthquake with an epicentral distance of 4200 km has been recorded, indicating the abil...
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We propose a scheme for realizing a chip-scale optical clock based on modulation transfer spectroscopy. By using on-chip laser, lithium niobate thin film waveguides and MEMS cells, the laser frequency can be stabilize...
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A convolution neural network is proposed to reconstruct the true value from phase-wrapped interferometric sensing signals. The MAE and RMSE in a real phase dataset sampled by DAS are 0.069 p and 0.352 p respectively. ...
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Intelligent indoor robotics is expected to rapidly gain importance in crucial areas of our modern society such as at-home health care and factories. Yet, existing mobile robots are limited in their ability to perceive...
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Intelligent indoor robotics is expected to rapidly gain importance in crucial areas of our modern society such as at-home health care and factories. Yet, existing mobile robots are limited in their ability to perceive and respond to dynamically evolving complex indoor environments because of their inherently limited sensing and computing resources that are, moreover, traded off against their cruise time and payload. To address these formidable challenges, here we propose intelligent indoor metasurface robotics(I2MR),where all sensing and computing are relegated to a centralized robotic brain endowed with microwave perception; and I2MR's limbs(motorized vehicles, airborne drones, etc.) merely execute the wirelessly received instructions from the brain. The key aspect of our concept is the centralized use of a computation-enabled programmable metasurface that can flexibly mold microwave propagation in the indoor wireless environment, including a sensing and localization modality based on configurational diversity and a communication modality to establish a preferential high-capacity wireless link between the I2MR's brain and limbs. The metasurface-enhanced microwave perception is capable of realizing low-latency and high-resolution three-dimensional imaging of humans, even around corners and behind thick concrete walls, which is the basis for action decisions of the I2MR's brain. I2MR is thus endowed with real-time and full-context awareness of its operating indoor environment. We implement, experimentally, a proof-of-principle demonstration at ～2.4 GHz, in which I2MR provides health-care assistance to a human inhabitant. The presented strategy opens a new avenue for the conception of smart and wirelessly networked indoor robotics.
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