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dc.contributor.authorHarrach, Bastian
dc.contributor.authorPohjola, Valter
dc.contributor.authorSalo, Mikko
dc.date.accessioned2019-08-01T10:34:57Z
dc.date.available2019-08-01T10:34:57Z
dc.date.issued2019
dc.identifier.citationHarrach, B., Pohjola, V., & Salo, M. (2019). Dimension Bounds in Monotonicity Methods for the Helmholtz Equation. <i>SIAM Journal on Mathematical Analysis</i>, <i>51</i>(4), 2995-3019. <a href="https://doi.org/10.1137/19M1240708" target="_blank">https://doi.org/10.1137/19M1240708</a>
dc.identifier.otherCONVID_32199156
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/65184
dc.description.abstractThe article [B. Harrach, V. Pohjola, and M. Salo, Anal. PDE] established a monotonicity inequality for the Helmholtz equation and presented applications to shape detection and local uniqueness in inverse boundary problems. The monotonicity inequality states that if two scattering coefficients satisfy $q_1 \leq q_2$, then the corresponding Neumann-to-Dirichlet operators satisfy $\Lambda(q_1) \leq \Lambda(q_2)$ up to a finite-dimensional subspace. Here we improve the bounds for the dimension of this space. In particular, if $q_1$ and $q_2$ have the same number of positive Neumann eigenvalues, then the finite-dimensional space is trivial.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherSociety for Industrial and Applied Mathematics
dc.relation.ispartofseriesSIAM Journal on Mathematical Analysis
dc.rightsIn Copyright
dc.subject.otherinverse problems
dc.subject.otherHelmholtz equation
dc.subject.othermontonicity method
dc.titleDimension Bounds in Monotonicity Methods for the Helmholtz Equation
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201908013746
dc.contributor.laitosMatematiikan ja tilastotieteen laitosfi
dc.contributor.laitosDepartment of Mathematics and Statisticsen
dc.contributor.oppiaineMatematiikkafi
dc.contributor.oppiaineMathematicsen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange2995-3019
dc.relation.issn0036-1410
dc.relation.numberinseries4
dc.relation.volume51
dc.type.versionpublishedVersion
dc.rights.copyright© 2019 Society for Industrial and Applied Mathematics
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber312121
dc.relation.grantnumber770924
dc.relation.grantnumber770924
dc.relation.grantnumber309963
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/770924/EU//IPTheoryUnified
dc.subject.ysoinversio-ongelmat
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p27912
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1137/19M1240708
dc.relation.funderSuomen Akatemiafi
dc.relation.funderEuroopan komissiofi
dc.relation.funderSuomen Akatemiafi
dc.relation.funderResearch Council of Finlanden
dc.relation.funderEuropean Commissionen
dc.relation.funderResearch Council of Finlanden
jyx.fundingprogramHuippuyksikkörahoitus, SAfi
jyx.fundingprogramERC Consolidator Grantfi
jyx.fundingprogramAkatemiahanke, SAfi
jyx.fundingprogramCentre of Excellence, AoFen
jyx.fundingprogramERC Consolidator Granten
jyx.fundingprogramAcademy Project, AoFen
jyx.fundinginformationThe work of the third author was supported by the Academy of Finland (Centre of Excellence in Inverse modeling and Imaging) grants 312121, 309963, and by the European Research Council under Horizon 2020 grant ERC CoG 770924
dc.type.okmA1


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