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This paper designs a 1×2 switchable dual-mode optical 90 o hybrid device on the silicon-on-insulator (SOI) platform for the mode division multiplexing hybridized coherent transmission systems in optical communication. Our proposed hybrid uses various 2×2 multimode interference (MMI) couplers, symmetric Yjunctions, and thermo-optic phase shifters. The suggested hybrid device working principle is proved on theoretical analysis about the multimode interference and the transfer matrix relation. The optimization of geometrical parameters and metallic micro-heaters is executed through the numerical simulation method. The proposed hybrid coupler expresses lots of optical performance advantages, with an insertion loss lower than 2.5 dB, a commonmode rejection ratio (CMRR) better than -24 dB, and phase error smaller than 4° in the 50-nm wavelength bandwidth of the third telecom window for both two TE modes. Besides, the device is proven large geometrical tolerances in terms of width and height tolerances larger than ±50 nm and ±6 nm in the 1.5-dB variation limit of transmission, respectively. In addition, the proposed device attains relatively low power consumption under 75 mW and an ultrafast switching time below 10 µs. Such advantages of good performances make the device a promising potential for broadband and intra-chip MDM-hybridized coherent optical communication systems and photonic integrated circuits.

Fiction and fantasy are archetypes of long-tail domains that lack suitable NLP methodologies and tools. We present ENTYFI, a web-based system for fine-grained typing of entity mentions in fictional texts. It builds on 205 automatically induced high-quality type systems for popular fictional domains, and provides recommendations towards reference type systems for given input texts. Users can exploit the richness and diversity of these reference type systems for fine-grained supervised typing, in addition, they can choose among and combine four other typing modules: pre-trained real-world models, unsupervised dependency-based typing, knowledge base lookups, and constraint-based candidate consolidation. The demonstrator is available at https://d5demos.mpi-inf.mpg. de/entyfi. Mention Settings Default (Ref. universes + all modules) Default without type consolidation Only real-world typing Elladan & Elrohir men, hybrid peoples, elves of rivendell, real world,