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  <doc>
    <id>10198</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>e70534</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>21</issue>
    <volume>19</volume>
    <type>other</type>
    <publisherName/>
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    <title language="eng">Uncovering Hidden Resonances in Non-Hermitian Systems with Scattering Thresholds (Laser Photonics Rev. 19(21)/2025)</title>
    <parentTitle language="deu">Laser Photonics Rev.</parentTitle>
    <identifier type="doi">10.1002/lpor.70534</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Fridtjof Betz</author>
    <submitter>Sven Burger</submitter>
    <author>Felix Binkowski</author>
    <author>Jan David Fischbach</author>
    <author>Nick Feldman</author>
    <author>Lin Zschiedrich</author>
    <author>Carsten Rockstuhl</author>
    <author>A. Femius Koenderink</author>
    <author>Sven Burger</author>
    <collection role="institutes" number="num">Numerical Mathematics</collection>
    <collection role="institutes" number="compnano">Computational Nano Optics</collection>
    <collection role="persons" number="burger">Burger, Sven</collection>
    <collection role="persons" number="zschiedrich">Zschiedrich, Lin Werner</collection>
    <collection role="persons" number="binkowski">Binkowski, Felix</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="betz">Betz, Fridtjof</collection>
    <collection role="institutes" number="MSoCP">Modeling and Simulation of Complex Processes</collection>
    <collection role="projects" number="CNO-MODAL-NANOLAB">CNO-MODAL-NANOLAB</collection>
    <collection role="projects" number="MathPlus-AA2-16">MathPlus-AA2-16</collection>
  </doc>
  <doc>
    <id>9954</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
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    <completedDate>--</completedDate>
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    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Backup ist KEINE Langzeitverfügbarkeit</title>
    <abstract language="deu">Diese Handreichung im Flyerformat soll mit den verschiedenen Missverständnissen aufräumen, die einem im Alltag begegnen, wenn man es mit digitaler Langzeitverfügbarkeit zu tun hat.</abstract>
    <identifier type="doi">10.12752/9954</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-99548</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">true</enrichment>
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    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Tim Hasler</author>
    <submitter>Tim Hasler</submitter>
    <author>Kilian Amrhein</author>
    <author>Marco Klindt</author>
    <author>Elias Oltmanns</author>
    <author>Wolfgang Peters-Kottig</author>
    <collection role="institutes" number="sis">Digital Data and Information for Society, Science, and Culture</collection>
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    <file>https://opus4.kobv.de/opus4-zib/files/9954/2024_A5_Druckvorlage.pdf</file>
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  <doc>
    <id>9886</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>2470036</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>7</volume>
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    <publisherName/>
    <publisherPlace/>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Inside Front Cover: Numerical Investigation of a Coupled Micropillar - Waveguide System for Integrated Quantum Photonic Circuits (Adv. Quantum Technol. 12/2024)</title>
    <parentTitle language="eng">Adv. Quantum Technol.</parentTitle>
    <identifier type="doi">10.1002/qute.202470036</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Léo J. Roche</author>
    <submitter>Sven Burger</submitter>
    <author>Fridtjof Betz</author>
    <author>Yuhui Yang</author>
    <author>Imad Limame</author>
    <author>Ching-Wen Shih</author>
    <author>Sven Burger</author>
    <author>Stephan Reitzenstein</author>
    <collection role="institutes" number="num">Numerical Mathematics</collection>
    <collection role="institutes" number="compnano">Computational Nano Optics</collection>
    <collection role="persons" number="burger">Burger, Sven</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="betz">Betz, Fridtjof</collection>
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    <collection role="projects" number="CNO-MODAL-NANOLAB">CNO-MODAL-NANOLAB</collection>
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  <doc>
    <id>9856</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
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    <completedDate>--</completedDate>
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    <title language="eng">The gradient projection method: Is the Polyak adaptive stepsize rule optimal?</title>
    <abstract language="eng">Not always! This is our answer to the question of whether the Polyak adaptive stepsize rule in the gradient projection method is optimal. The answer is based on revisiting the subgradient projection method by Polyak [USSR Computational Mathematics and Mathematical Physics 9 (1969)] for smooth and convex minimization problems where the objective function possesses a geometric property called flatness. Our results show that the method can be more flexible (the effective range for the parameter controlling the stepsize can be wider) and have sharper convergence rates. Applications to split feasibility/equality problems are presented, deriving for the first time the O(1/k) rate of convergence for the adaptive CQ method. A theoretical guarantee of the linear convergence of the gradient descent method with adaptive stepsizes for Google PageRank is provided. At the same time, numerical experiments are designed to spot the ``optimal" stepsize and to compare with other basic gradient methods.</abstract>
    <enrichment key="SubmissionStatus">under review</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="PeerReviewed">no</enrichment>
    <author>Thi Huong Vu</author>
    <submitter>Thi Huong Vu</submitter>
    <author>Thorsten Koch</author>
    <author>Hong-Kun Xu</author>
    <collection role="institutes" number="sis">Digital Data and Information for Society, Science, and Culture</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="persons" number="huong.vu">Vu, Thi Huong</collection>
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  </doc>
  <doc>
    <id>9844</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>2470071</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>18</volume>
    <type>other</type>
    <publisherName/>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Efficient Rational Approximation of Optical Response Functions with the AAA Algorithm (Laser Photonics Rev. 18(11)/2024)</title>
    <parentTitle language="deu">Laser Photonics Rev.</parentTitle>
    <identifier type="doi">10.1002/lpor.202470071</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Fridtjof Betz</author>
    <submitter>Sven Burger</submitter>
    <author>Martin Hammerschmidt</author>
    <author>Lin Zschiedrich</author>
    <author>Sven Burger</author>
    <author>Felix Binkowski</author>
    <collection role="persons" number="burger">Burger, Sven</collection>
    <collection role="persons" number="hammerschmidt">Hammerschmidt, Martin</collection>
    <collection role="persons" number="zschiedrich">Zschiedrich, Lin Werner</collection>
    <collection role="persons" number="binkowski">Binkowski, Felix</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="betz">Betz, Fridtjof</collection>
    <collection role="institutes" number="MSoCP">Modeling and Simulation of Complex Processes</collection>
    <collection role="projects" number="CNO-MODAL-NANOLAB">CNO-MODAL-NANOLAB</collection>
    <collection role="projects" number="MathPlus-AA2-16">MathPlus-AA2-16</collection>
  </doc>
  <doc>
    <id>9797</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
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    <type>other</type>
    <publisherName/>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-07-19</completedDate>
    <publishedDate>2024-07-19</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Electric Bus Scheduling with Non-Linear Charging, Power Grid Bottlenecks, and Dynamic Recharge Rates</title>
    <abstract language="eng">Public transport operators are gradually electrifying their bus fleets, predominantly with battery-powered drive trains. These buses commonly have to be scheduled to recharge in-service, which gives rise to a number of challenges. A major problem is that the relationship between charging time and replenished driving range is non-linear, which is often approximately modeled. We examine the associated approximation error and show how it can result in a gross over- or underestimation of the fleet size. Moreover, we demonstrate that commonly used piecewise linear underestimations of the charge curve do not result in an underestimation of the predicted charge states in electric vehicle scheduling and routing models.&#13;
Furthermore, since power grid upgrades are currently not keeping up with an ever growing electricity demand, operators are introducing active charge management tools to dynamically adjust the charging speed depending on the amount of available energy. It is therefore imperative to extend electric bus scheduling models to account for these developments.&#13;
We propose a novel mixed-integer programming formulation for the electric bus scheduling problem featuring an improved approximation of the non-linear battery charging behavior as well as dynamic recharge speeds to accommodate grid load limits. The idea is to linearly interpolate what we call the charge increment function, which is closely related to the derivative of the commonly used charge curve. This provides very good error control and integrates easily into integer programming models. We demonstrate the practical usefulness of our model on a diverse library of real-life instances.</abstract>
    <identifier type="arxiv">2407.14446</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">under review</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Fabian Löbel</author>
    <submitter>Fabian Löbel</submitter>
    <author>Ralf Borndörfer</author>
    <author>Steffen Weider</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="borndoerfer">Borndörfer, Ralf</collection>
    <collection role="persons" number="weider">Weider, Steffen</collection>
    <collection role="persons" number="fabian.loebel">Löbel, Fabian</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="neo">Network Optimization</collection>
    <collection role="projects" number="EBUS">EBUS</collection>
    <collection role="projects" number="MODAL-MobilityLab">MODAL-MobilityLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9684</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>7</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>other</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">URIs im GLAM-Bereich – was sie sind und wie man sie verwendet</title>
    <abstract language="deu">Das Papier gibt Hinweise zu URIs (Uniform Resource Identifiers) im GLAM-Sektor.</abstract>
    <parentTitle language="deu">ZENODO</parentTitle>
    <identifier type="doi">10.5281/zenodo.11608433</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC0 1.0 - Universell - Public Domain Dedication</licence>
    <author>Alexander Winkler</author>
    <submitter>Alexander Winkler</submitter>
    <collection role="institutes" number="sis">Digital Data and Information for Society, Science, and Culture</collection>
    <collection role="projects" number="no-project">no-project</collection>
    <collection role="persons" number="winkler">Winkler, Alexander</collection>
  </doc>
  <doc>
    <id>9670</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>other</type>
    <publisherName/>
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    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Implementing a unified solver for nonlinearly constrained optimization</title>
    <abstract language="eng">SQP and interior-point methods (also referred to as Lagrange-Newton methods) typically share key algorithmic components, such as strategies for computing descent directions and mechanisms that promote global convergence. Building on this insight, we introduce a unifying framework with eight building blocks that abstracts the workflows of Lagrange-Newton methods. We then present Uno, a modular C++ solver that implements our unifying framework and allows the automatic combination of a wide range of strategies with no programming effort from the user. Uno is meant to (1) organize mathematical optimization strategies into a coherent hierarchy; (2) offer a wide range of efficient and robust methods that can be compared for a given instance; (3) enable researchers to experiment with novel optimization strategies; and (4) reduce the cost of development and maintenance of multiple optimization solvers. Uno's software design allows user to compose new customized solvers for emerging optimization areas such as robust optimization or optimization problems with complementarity constraints, while building on reliable nonlinear optimization techniques. We demonstrate that Uno is highly competitive against state-of-the-art solvers filterSQP, IPOPT, SNOPT, MINOS, LANCELOT, LOQO, and CONOPT on a subset of 429 small problems from the CUTE collection. Uno is available as open-source software under the MIT license at this https URL and via its C, Julia, Python, Fortran, and AMPL interfaces.</abstract>
    <identifier type="arxiv">2406.13454</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="SubmissionStatus">accepted for publication</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Charlie Vanaret</author>
    <submitter>Charlie Vanaret</submitter>
    <author>Sven Leyffer</author>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="persons" number="vanaret">Vanaret, Charlie William</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9620</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>2470046</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>12</volume>
    <type>other</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">‘Sawfish’ Photonic Crystal Cavity for Near-Unity Emitter-to-Fiber Interfacing in Quantum Network Applications (Advanced Optical Materials 13/2024)</title>
    <parentTitle language="eng">Adv. Optical Mater.</parentTitle>
    <identifier type="doi">10.1002/adom.202470046</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Julian M. Bopp</author>
    <submitter>Sven Burger</submitter>
    <author>Matthias Plock</author>
    <author>Tim Turan</author>
    <author>Gregor Pieplow</author>
    <author>Sven Burger</author>
    <author>Tim Schröder</author>
    <collection role="institutes" number="num">Numerical Mathematics</collection>
    <collection role="institutes" number="compnano">Computational Nano Optics</collection>
    <collection role="persons" number="burger">Burger, Sven</collection>
    <collection role="institutes" number="MSoCP">Modeling and Simulation of Complex Processes</collection>
    <collection role="persons" number="plock">Plock, Matthias</collection>
    <collection role="projects" number="SIMLOPT">SIMLOPT</collection>
    <collection role="projects" number="CNO-SEQUME">CNO-SEQUME</collection>
  </doc>
  <doc>
    <id>9576</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>95</pageNumber>
    <edition/>
    <issue>DLR-FB-2023-15</issue>
    <volume/>
    <type>other</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Evaluation of Uncertainties in Linear-Optimizing Energy System Models - Compendium</title>
    <abstract language="deu">Für die Energiesystemforschung sind Software-Modelle ein Kernelement zur Analyse von Szenarien. Das Forschungsprojekt UNSEEN hatte das Ziel eine bisher unerreichte Anzahl an modellbasierten Energieszenarien zu berechnen, um Unsicherheiten – vor allem unter Nutzung linear optimierender Energiesystem-Modelle - besser bewerten zu können. Hierfür wurden umfangreiche Parametervariationen auf Energieszenarien angewendet und das wesentliche methodische Hindernis in diesem Zusammenhang adressiert: die rechnerische Beherrschbarkeit der zu lösenden mathematischen Optimierungsprobleme. Im Vorläuferprojekt BEAM-ME wurde mit der Entwicklung und Anwendung des Open-Source-Lösers PIPS-IPM++ die Grundlage für den Einsatz von High-Performance-Computing (HPC) zur Lösung dieser Modelle gelegt. In UNSEEN war dieser Löser die zentrale Komponente eines Workflows, welcher zur Generierung, Lösung und multi-kriteriellen Bewertung von Energieszenarien auf dem Hochleistungscomputer JUWELS am Forschungszentrum Jülich implementiert wurde. Zur effizienten Generierung und Kommunikation von Modellinstanzen für Methoden der mathematischen Optimierung auf HPC wurde eine weitere Workflow-Komponente von der GAMS Software GmbH entwickelt: der Szenariogenerator. Bei der Weiterentwicklung von Lösungsalgorithmen für linear optimierende Energie-Systemmodelle standen gemischt-ganzzahlige Optimierungsprobleme im Fokus, welche für die Modellierung konkreter Infrastrukturen und Maßnahmen zur Umsetzung der Energiewende gelöst werden müssen. Die in diesem Zusammenhang stehenden Arbeiten zur Entwicklung von Algorithmen wurden von der Technischen Universität Berlin verantwortet. Bei Design und Implementierung dieser Methoden wurde sie vom Zuse Instituts Berlin unterstützt.</abstract>
    <parentTitle language="deu">DLR-Forschungsbericht</parentTitle>
    <identifier type="doi">10.57676/w2rq-bj85</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Karl-Kien Cao</author>
    <submitter>Janina Zittel</submitter>
    <author>Lovis Anderson</author>
    <author>Aileen Böhme</author>
    <author>Thomas Breuer</author>
    <author>Jan Buschmann</author>
    <author>Frederick Fiand</author>
    <author>Ulrich Frey</author>
    <author>Benjamin Fuchs</author>
    <author>Nils-Christian Kempe</author>
    <author>Kai von Krbek</author>
    <author>Wided Medjroubi</author>
    <author>Judith Riehm</author>
    <author>Shima Sasanpour</author>
    <author>Sonja Simon</author>
    <author>Charlie Vanaret</author>
    <author>Manuel Wetzel</author>
    <author>Mengzhu Xiao</author>
    <author>Janina Zittel</author>
    <collection role="persons" number="zittel">Zittel, Janina</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="persons" number="vanaret">Vanaret, Charlie William</collection>
    <collection role="projects" number="UNSEEN">UNSEEN</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
</export-example>
