Data underpinning "Single-Mode Transmission Over Ultra-Low-Loss 0.1400 dB/km Few-Mode Fibre for Data Centre Interconnects"

DOI

This dataset contains the data points of all figures on the paper "Quasi-Single-Mode Transmission over Ultra-Low-Loss Few-Mode Fibre for Data Centre Interconnects". A description of the files is presented below:nli_ase_fitting.xlsx, snr_vs_lpower_fitting.xlsx & snr_vs_lpower_fibrea_ullfmf.xlsx: These files contain the signal-to-noise ratio as a function of launch power for the full reproduction of Fig. 2(a).filter_taps.xlsx: Filter weights obtained for the utra-low-loss few-mode fibre at optimum launch power. This file allows full reproduction of Fig. 2(b).mpi_vs_wav.xlsx: This file contains the multipath interference results as a function of the wavelength obtained based on power samples and on the modified Gaussian model. It allows full reproduction of Fig. 3.snr_vs_wav_nodbp.xlsx: This file contains the signal-to-noise ratio analysis as a function of the wavelength for fibre A and the ultra-low-loss few-mode fibre. This file allows full reproduction of Fig. 4.

Identifier
DOI https://doi.org/10.5522/04/28919747.v1
Related Identifier HasPart https://ndownloader.figshare.com/files/62621815
Related Identifier HasPart https://ndownloader.figshare.com/files/62621818
Related Identifier HasPart https://ndownloader.figshare.com/files/62621821
Related Identifier HasPart https://ndownloader.figshare.com/files/62621824
Related Identifier HasPart https://ndownloader.figshare.com/files/62621827
Related Identifier HasPart https://ndownloader.figshare.com/files/62621830
Metadata Access https://api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:figshare.com:article/28919747
Provenance
Creator Barbosa, Fabio Aparecido; Marques Ferreira, Filipe; Khrapko, Rostislav; Li, Ming-Jun
Publisher University College London UCL
Contributor Figshare
Publication Year 2026
Rights https://creativecommons.org/licenses/by/4.0/
OpenAccess true
Contact researchdatarepository(at)ucl.ac.uk
Representation
Language English
Resource Type Dataset
Discipline Other