Polarization Modulation in Quantum-Dot Spin-VCSELs for Ultrafast Data Transmission

Spin-Vertical Cavity Surface Emitting Lasers (spin-VCSELs) are undergoing increasing research effort for new paradigms in high-speed optical communications and photon-enabled computing. To date research in spin-VCSELs has mostly focused on Quantum-Well (QW) devices. However, novel Quantum-Dot (QD) s...

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Bibliographic Details
Published inIEEE journal of quantum electronics Vol. 59; no. 5; p. 1
Main Authors Tselios, Christos, Georgiou, Panagiotis, Politi, Christina, Hurtado, Antonio, Alexandropoulos, Dimitris
Format Journal Article
LanguageEnglish
Published New York IEEE 01.10.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:Spin-Vertical Cavity Surface Emitting Lasers (spin-VCSELs) are undergoing increasing research effort for new paradigms in high-speed optical communications and photon-enabled computing. To date research in spin-VCSELs has mostly focused on Quantum-Well (QW) devices. However, novel Quantum-Dot (QD) spin-VCSELs, offer enhanced parameter controls permitting the effective, dynamical and ultrafast manipulation of their light emission's polarization. In the present contribution we investigate theoretically in detail the operation of QD spin-VCSELs subject to polarization modulation for their use as ultrafast light sources in optical communication systems. We reveal that QD spin-VCSELs outperform their QW counterparts in terms of modulation efficiency, yielding a nearly two- fold improvement. We also analyse the impact of key device parameters in QD spin-VCSELs (e.g. photon decay rate and intra-dot relaxation rate) on the large signal modulation performance with regard to simulated optical modulation amplitude and eye-diagram opening penalty. We show that in addition to exhibiting enhanced polarization modulation performance for data rates up to 250 Gb/s , QD spin-VCSELs enable operation in dual (ground and excited state) emission thus allowing future exciting routes for multiplexing of information in computing and processing applications.
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ISSN:0018-9197
1558-1713
DOI:10.1109/JQE.2023.3296732