arXiv subjects

Mengwen Chen

Publications and source records attributed to Mengwen Chen.

3 recordsLinked to original sources

arXiv2024

High-gain optical parametric amplification with a continuous-wave pump using a domain-engineered thin-film lithium niobate waveguide

While thin film lithium niobate (TFLN) is known for efficient signal generation, on-chip signal amplification remains challenging from fully integrated optical communication circuits. Here we demonstrate the continuous-wave-pump optical parametric amplification (OPA) using an x-cut domain-engineered TFLN waveguide, with high gain over the telecom band up to 13.9 dB, and test it for high signal-to-noise ratio signal amplification using a commercial optical communication module pair. Fabricated in wafer scale using common process as devices including modulators, this OPA device marks an important step in TFLN photonic integration.

physics.optics↗

arXiv2023

Experimental demonstration of drone-based quantum key distribution

Quantum state transferring has been demonstrated using drones via entanglement distribution. Here we demonstrate the first drone-based quantum task, for quantum key distribution (QKD). Compact and polarization-maintaining acquisition, pointing, and tracking system and QKD modules are developed and loaded on a home-made octocopter, within takeoff weight of 30 kg. Real-time QKD is performed over 200 m distance with 8.48 kHz average secret key rate, using polarization-coded decoy-state BB84 protocol. With the capability of secret key distribution using a drone, wireless communication can be expected with enhanced security in the quantum approach, between mobile nodes towards a network.

quant-ph↗

arXiv2013

Parallelization in Extracting Fresh Information from Online Social Network

Online Social Network (OSN) is one of the most hottest services in the past years. It preserves the life of users and provides great potential for journalists, sociologists and business analysts. Crawling data from social network is a basic step for social network information analysis and processing. As the network becomes huge and information on the network updates faster than web pages, crawling is more difficult because of the limitations of band-width, politeness etiquette and computation power. To extract fresh information from social network efficiently and effectively, this paper presents a novel crawling method and discusses parallelization architecture of social network. To discover the feature of social network, we gather data from real social network, analyze them and build a model to describe the discipline of users' behavior. With the modeled behavior, we propose methods to predict users' behavior. According to the prediction, we schedule our crawler more reasonably and extract more fresh information with parallelization technologies. Experimental results demonstrate that our strategies could obtain information from OSN efficiently and effectively.

cs.SI↗