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dc.contributor.authorDonegan, John
dc.date.accessioned2021-09-28T21:08:02Z
dc.date.available2021-09-28T21:08:02Z
dc.date.issued2020
dc.date.submitted2020en
dc.identifier.citationWallace MJ, Naimi ST, Jain G, McKenna R, Bello F, Donegan JF. Genetic algorithm optimization of high order surface etched grating tunable laser array. Optics Express. 2020 Mar 16;28(6):8169-8184en
dc.identifier.otherY
dc.description.abstractA genetic algorithm is developed with a view to optimizing surface-etched grating tunable lasers over a large optimization space comprised of several variables. Using this approach, a new iteration of slotted lasers arrays are optimized showing significant improvements over previous designs. Output power, lower grating order, fabrication tolerance and performance at high temperatures are among key parameters improved. The new designs feature a much lower grating order (24-29) than used previously (37). The biggest improvement is a near doubling to slope efficiency to 0.1-0.13 mW/mA, with wavelengths from the array covering the C-band . The designs show a reduced sensitivity to etch depth variations. Designs with linewidths down to 100 kHz are also simulated. This algorithm can be readily applied to different wafer materials to efficiently generate slotted lasers designs at new wavelengths.en
dc.format.extent8169-8184en
dc.language.isoenen
dc.relation.ispartofseriesOptics Express;
dc.relation.ispartofseries28;
dc.relation.ispartofseries6;
dc.rightsYen
dc.subjectgenetic algorithmen
dc.subjectsurface-etched grating tunable lasersen
dc.subjectwafer materialsen
dc.subject.lcshgenetic algorithmen
dc.subject.lcshsurface-etched grating tunable lasersen
dc.subject.lcshwafer materialsen
dc.titleGenetic algorithm optimization of high order surface etched grating tunable laser arrayen
dc.typeJournal Articleen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/jdonegan
dc.identifier.rssinternalid233791
dc.identifier.doihttp://dx.doi.org/10.1364/OE.383914
dc.rights.ecaccessrightsopenAccess
dc.identifier.orcid_id0000-0002-5240-1434
dc.contributor.sponsorScience Foundation Irelanden
dc.contributor.sponsorGrantNumber15/IA/2854en
dc.identifier.urihttp://hdl.handle.net/2262/97144


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