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SUMMARY:Juan Abranches: From complex to self-adjoint matrix and tensor mod
 els via intermediate fields
DTSTART:20260520T120000Z
DTEND:20260520T130000Z
DTSTAMP:20260524T181100Z
UID:indico-event-16611@indico.math.cnrs.fr
DESCRIPTION:Random matrix and tensor models provide an analytic framework 
 for studying ensembles of discretized geometries. When one attempts to inc
 orporate geometric or causal constraints—such as those arising in causal
  dynamical triangulations—these models typically acquire technically inv
 olved structures. In this talk\, I present a reformulation that applies t
 o a broad class of complex matrix and tensor models. Using an intermediate
  field representation\, I show that they can be rewritten as equivalent se
 lf-adjoint theories with linearly coupled auxiliary fields. In this reform
 ulation\, the intermediate field acquires a dually weighted logarithmic po
 tential determined by the covariance of the original complex model. This 
 construction extends and unifies several previously known results\, which 
 were restricted to trivial covariance or specific interaction choices\, an
 d clarifies how interaction and covariance data are reorganized in matrix 
 and tensor models. This talk is based on arXiv:2512.16583.\n\nhttps://indi
 co.math.cnrs.fr/event/16611/
URL:https://indico.math.cnrs.fr/event/16611/
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