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dc.contributor.authorHelenius, A. P.
dc.contributor.authorPuurtinen, T. A.
dc.contributor.authorKinnunen, K. M.
dc.contributor.authorMaasilta, I. J.
dc.date.accessioned2020-07-06T07:10:15Z
dc.date.available2020-07-06T07:10:15Z
dc.date.issued2020
dc.identifier.citationHelenius, A. P., Puurtinen, T. A., Kinnunen, K. M., & Maasilta, I. J. (2020). Simultaneous Noise and Impedance Fitting to Transition-Edge Sensor Data Using Differential Evolution. <i>Journal of Low Temperature Physics</i>, <i>200</i>(5-6), 213-219. <a href="https://doi.org/10.1007/s10909-020-02489-0" target="_blank">https://doi.org/10.1007/s10909-020-02489-0</a>
dc.identifier.otherCONVID_36260892
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/71073
dc.description.abstractWe discuss a robust method to simultaneously fit a complex multi-body model both to the complex impedance and the noise data for transition-edge sensors. It is based on a differential evolution (DE) algorithm, providing accurate and repeatable results with only a small increase in computational cost compared to the Levenberg–Marquardt (LM) algorithm. Test fits are made using both DE and LM methods, and the results compared with previously determined best fits, with varying initial value deviations and limit ranges for the parameters. The robustness of DE is demonstrated with successful fits even when parameter limits up to a factor of 10 from the known values were used. It is shown that the least squares fitting becomes unreliable beyond a 10% deviation from the known values.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherSpringer Science and Business Media LLC
dc.relation.ispartofseriesJournal of Low Temperature Physics
dc.rightsCC BY 4.0
dc.subject.otherthermal model
dc.subject.othergenetic algorithm
dc.subject.otherdifferential evolution
dc.subject.othertransition-edge sensor
dc.titleSimultaneous Noise and Impedance Fitting to Transition-Edge Sensor Data Using Differential Evolution
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202007065246
dc.contributor.laitosFysiikan laitosfi
dc.contributor.laitosDepartment of Physicsen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange213-219
dc.relation.issn0022-2291
dc.relation.numberinseries5-6
dc.relation.volume200
dc.type.versionpublishedVersion
dc.rights.copyright© The Authors 2020
dc.rights.accesslevelopenAccessfi
dc.subject.ysoanturit
dc.subject.ysodifferentiaalievoluutio
dc.subject.ysotutkimuslaitteet
dc.subject.ysosignaalinkäsittely
dc.subject.ysogeneettiset algoritmit
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p11460
jyx.subject.urihttp://www.yso.fi/onto/yso/p28678
jyx.subject.urihttp://www.yso.fi/onto/yso/p2440
jyx.subject.urihttp://www.yso.fi/onto/yso/p12266
jyx.subject.urihttp://www.yso.fi/onto/yso/p7987
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1007/s10909-020-02489-0
jyx.fundinginformationOpen access funding provided by University of Jyväskylä (JYU).
dc.type.okmA1


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