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SUMMARY:Christian Lubich (University of Tübingen)
DTSTART:20200715T140000Z
DTEND:20200715T150000Z
DTSTAMP:20260423T040932Z
UID:E-NLA/13
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/E-NLA/13/">D
 ynamical low-rank approximation</a>\nby Christian Lubich (University of T
 übingen) as part of E-NLA - Online seminar series on numerical linear alg
 ebra\n\n\nAbstract\nThis talk reviews differential equations and their num
 erical solution on manifolds of low-rank matrices or of tensors with a ran
 k structure such as tensor trains or general tree tensor networks. These l
 ow-rank differential equations serve to approximate\, in a data-compressed
  format\, large time-dependent matrices and tensors or multivariate functi
 ons that are either given explicitly via their increments or are unknown s
 olutions to high-dimensional evolutionary differential equations\, with mu
 lti-particle time-dependent Schrödinger equations and kinetic equations s
 uch as Vlasov equations as noteworthy examples of applications.\n\nRecentl
 y developed numerical time integrators are  based on splitting the project
 ion onto the tangent space of the low-rank manifold at the current approxi
 mation. In contrast to all standard integrators\, these projector-splittin
 g methods are robust to the unavoidable presence of small singular values 
 in the low-rank approximation. This robustness relies on exploiting geomet
 ric properties of the manifold of low-rank matrices or tensors: in each su
 bstep of the projector-splitting algorithm\, the approximation moves along
  a flat subspace of the low-rank manifold. In this way\, high curvature du
 e to small singular values does no harm.\n\nThis talk is based on work don
 e intermittently over the last decade with Othmar Koch\, Bart Vandereycken
 \, Ivan Oseledets\, Emil Kieri\, Hanna Walach and Gianluca Ceruti.\n
LOCATION:https://researchseminars.org/talk/E-NLA/13/
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