Abstract
The paper presents recent advances in the design of controllable, highly accurate, and multi–band Raman gain profiles. The ultra–wideband programmable gain profiles are implemented using a machine learning approach based on the mapping between gain profiles and pump powers.
| Original language | English |
|---|---|
| Title of host publication | 2021 IEEE Photonics Conference (IPC) |
| Publisher | IEEE |
| ISBN (Electronic) | 978-1-6654-1601-6 |
| ISBN (Print) | 978-1-6654-4676-1 |
| DOIs | |
| Publication status | Published - 12 Nov 2021 |
| Event | 2021 IEEE Photonics Conference (IPC) - Vancouver, BC, Canada Duration: 18 Oct 2021 → 21 Oct 2021 |
Publication series
| Name | 2021 IEEE Photonics Conference (IPC) |
|---|---|
| Publisher | IEEE |
| ISSN (Print) | 2374-0140 |
| ISSN (Electronic) | 2575-274X |
Conference
| Conference | 2021 IEEE Photonics Conference (IPC) |
|---|---|
| Period | 18/10/21 → 21/10/21 |
Bibliographical note
Funding: This project has received funding from the European Union’s H2020 program (Marie Skłodowska-Curie grant 754462 and MSCA-ITN WON grant814276), the European Research Council (ERC CoG FRECOM grant 771878), the Villum Foundations (VYI OPTIC-AI grant no. 29344), the UK EPSRC
grants EP/M009092/1 and EP/R035342/1, and Ministero dell’Istruzione, dell’Universita e della Ricerca (PRIN 2017, project FIRST).