Quasi-Herglotz functions and convex optimization

We introduce the set of quasi-Herglotz functions and demonstrate that it has properties useful in the modelling of non-passive systems. The linear space of quasi-Herglotz functions constitutes a natural extension of the convex cone of Herglotz functions. It consists of differences of Herglotz functi...

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Main Authors: Y. Ivanenko, M. Nedic, M. Gustafsson, B. L. G. Jonsson, A. Luger, S. Nordebo
Format: Article
Language:English
Published: The Royal Society 2020-01-01
Series:Royal Society Open Science
Subjects:
Online Access:https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.191541
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author Y. Ivanenko
M. Nedic
M. Gustafsson
B. L. G. Jonsson
A. Luger
S. Nordebo
author_facet Y. Ivanenko
M. Nedic
M. Gustafsson
B. L. G. Jonsson
A. Luger
S. Nordebo
author_sort Y. Ivanenko
collection DOAJ
description We introduce the set of quasi-Herglotz functions and demonstrate that it has properties useful in the modelling of non-passive systems. The linear space of quasi-Herglotz functions constitutes a natural extension of the convex cone of Herglotz functions. It consists of differences of Herglotz functions and we show that several of the important properties and modelling perspectives are inherited by the new set of quasi-Herglotz functions. In particular, this applies to their integral representations, the associated integral identities or sum rules (with adequate additional assumptions), their boundary values on the real axis and the associated approximation theory. Numerical examples are included to demonstrate the modelling of a non-passive gain medium formulated as a convex optimization problem, where the generating measure is modelled by using a finite expansion of B-splines and point masses.
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spelling doaj.art-f31935026ce349f1b114246c2ee91d7d2022-12-21T18:39:39ZengThe Royal SocietyRoyal Society Open Science2054-57032020-01-017110.1098/rsos.191541191541Quasi-Herglotz functions and convex optimizationY. IvanenkoM. NedicM. GustafssonB. L. G. JonssonA. LugerS. NordeboWe introduce the set of quasi-Herglotz functions and demonstrate that it has properties useful in the modelling of non-passive systems. The linear space of quasi-Herglotz functions constitutes a natural extension of the convex cone of Herglotz functions. It consists of differences of Herglotz functions and we show that several of the important properties and modelling perspectives are inherited by the new set of quasi-Herglotz functions. In particular, this applies to their integral representations, the associated integral identities or sum rules (with adequate additional assumptions), their boundary values on the real axis and the associated approximation theory. Numerical examples are included to demonstrate the modelling of a non-passive gain medium formulated as a convex optimization problem, where the generating measure is modelled by using a finite expansion of B-splines and point masses.https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.191541quasi-herglotz functionsnon-passive systemsapproximationconvex optimizationsum rules
spellingShingle Y. Ivanenko
M. Nedic
M. Gustafsson
B. L. G. Jonsson
A. Luger
S. Nordebo
Quasi-Herglotz functions and convex optimization
Royal Society Open Science
quasi-herglotz functions
non-passive systems
approximation
convex optimization
sum rules
title Quasi-Herglotz functions and convex optimization
title_full Quasi-Herglotz functions and convex optimization
title_fullStr Quasi-Herglotz functions and convex optimization
title_full_unstemmed Quasi-Herglotz functions and convex optimization
title_short Quasi-Herglotz functions and convex optimization
title_sort quasi herglotz functions and convex optimization
topic quasi-herglotz functions
non-passive systems
approximation
convex optimization
sum rules
url https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.191541
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AT mgustafsson quasiherglotzfunctionsandconvexoptimization
AT blgjonsson quasiherglotzfunctionsandconvexoptimization
AT aluger quasiherglotzfunctionsandconvexoptimization
AT snordebo quasiherglotzfunctionsandconvexoptimization