Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Dicke, Alexander | - |
dc.date.accessioned | 2022-05-11T12:24:01Z | - |
dc.date.available | 2022-05-11T12:24:01Z | - |
dc.date.issued | 2021-06-19 | - |
dc.identifier.uri | http://hdl.handle.net/2003/40897 | - |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-22753 | - |
dc.description.abstract | In this note, a Wegner estimate for random divergence-type operators that are monotone in the randomness is proven. The proof is based on a recently shown unique continuation estimate for the gradient and the ensuing eigenvalue liftings. The random model which is studied here contains quite general random perturbations, among others, some that have a non-linear dependence on the random parameters. | en |
dc.language.iso | en | de |
dc.relation.ispartofseries | Mathematical physics, analysis and geometry;Vol. 24. 2021, Issue 3, Artikel-ID: 22 | - |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | Random divergence-type operators | en |
dc.subject | Wegner estimate | en |
dc.subject | Eigenvalue lifting | en |
dc.subject | Breather type | en |
dc.subject.ddc | 510 | - |
dc.title | Wegner estimate for random divergence-type operators monotone in the randomness | en |
dc.type | Text | de |
dc.type.publicationtype | article | de |
dcterms.accessRights | open access | - |
eldorado.secondarypublication | true | de |
eldorado.secondarypublication.primaryidentifier | https://doi.org/10.1007/s11040-021-09396-0 | de |
eldorado.secondarypublication.primarycitation | Mathematical physics, analysis and geometry. Vol. 24. 2021, Issue 3, Artikel-ID 22 | de |
Appears in Collections: | Lehrstuhl IX Analysis, Mathematische Physik & Dynamische Systeme |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Dicke2021_Article_WegnerEstimateForRandomDiverge.pdf | 345.73 kB | Adobe PDF | View/Open |
This item is protected by original copyright |
This item is licensed under a Creative Commons License