<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>10294</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>arXiv:2602.18414</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Pole-Expansion of the T-Matrix Based on a Matrix-Valued AAA-Algorithm</title>
    <parentTitle language="eng">ArXiV</parentTitle>
    <identifier type="doi">10.48550/arXiv.2602.18414</identifier>
    <identifier type="arxiv">2602.18414</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Jan David Fischbach</author>
    <submitter>Sven Burger</submitter>
    <author>Fridtjof Betz</author>
    <author>Lukas Rebholz</author>
    <author>Puneet Garg</author>
    <author>Kristina Frizyuk</author>
    <author>Felix Binkowski</author>
    <author>Sven Burger</author>
    <author>Martin Hammerschmidt</author>
    <author>Carsten Rockstuhl</author>
    <collection role="persons" number="burger">Burger, Sven</collection>
    <collection role="persons" number="hammerschmidt">Hammerschmidt, Martin</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="CNO-MATHPLUS-AA-ENER-1">CNO-MATHPLUS-AA-ENER-1</collection>
  </doc>
  <doc>
    <id>10265</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Complex-Frequency Framework for Kerker Unidirectionality in Photonic Resonators</title>
    <identifier type="doi">10.21203/rs.3.rs-8444305/v1</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="SubmissionStatus">under review</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Loubnan Abou Hamdan</author>
    <submitter>Sven Burger</submitter>
    <author>Aloke Jana</author>
    <author>Rémi Colom</author>
    <author>Nour Aboujoussef</author>
    <author>Cooper Carlson</author>
    <author>Adam Overvig</author>
    <author>Felix Binkowski</author>
    <author>Sven Burger</author>
    <author>Patrice Genevet</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="binkowski">Binkowski, Felix</collection>
    <collection role="institutes" number="MSoCP">Modeling and Simulation of Complex Processes</collection>
    <collection role="projects" number="CNO-MATHPLUS-AA-ENER-1">CNO-MATHPLUS-AA-ENER-1</collection>
  </doc>
  <doc>
    <id>10221</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>040503</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>6</volume>
    <type>article</type>
    <publisherName>IOP Publishing</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-11-13</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Physics-informed Bayesian optimization of expensive-to-evaluate black-box functions</title>
    <abstract language="eng">Abstract&#13;
 Bayesian optimization with Gaussian process surrogates is a popular approach for optimizing expensive-to-evaluate functions in terms of time, energy, or computational resources. Typically, a Gaussian process models a scalar objective derived from observed data. However, in many real-world applications, the objective is a combination of multiple outputs from physical experiments or simulations. Converting these multidimensional observations into a single scalar can lead to information loss, slowing convergence and yielding suboptimal results. To address this, we propose to use multi-output Gaussian processes to learn the full vector of observations directly, before mapping them to the scalar objective via an inexpensive analytical function. This physics-informed approach retains more information from the underlying physical processes, improving surrogate model accuracy. As a result, the approach accelerates optimization and produces better final designs compared to standard implementations.</abstract>
    <parentTitle language="eng">Mach. Learn. Sci. Technol.</parentTitle>
    <identifier type="doi">10.1088/2632-2153/ae1f5f</identifier>
    <enrichment key="opus_doi_flag">true</enrichment>
    <enrichment key="opus_doi_json">{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T22:57:08Z","timestamp":1763074628832,"version":"3.45.0"},"reference-count":0,"publisher":"IOP Publishing","license":[{"start":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T00:00:00Z","timestamp":1762992000000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T00:00:00Z","timestamp":1762992000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100006360","name":"Bundesministerium f\u00fcr Wirtschaft und Energie","doi-asserted-by":"publisher","award":["AI-Quadrat, project ID: 50WM2253"],"id":[{"id":"10.13039\/501100006360","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004937","name":"Bundesministerium f\u00fcr Forschung und Technologie","doi-asserted-by":"publisher","award":["NanoMaC, project ID: 01IS24005"],"id":[{"id":"10.13039\/501100004937","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["EXC-2046\/1, project ID: 390685689"],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mach. Learn.: Sci. Technol."],"abstract":"&lt;jats:title&gt;Abstract&lt;\/jats:title&gt;\n                  &lt;jats:p&gt;Bayesian optimization with Gaussian process surrogates is a popular approach for optimizing expensive-to-evaluate functions in terms of time, energy, or computational resources. Typically, a Gaussian process models a scalar objective derived from observed data. However, in many real-world applications, the objective is a combination of multiple outputs from physical experiments or simulations. Converting these multidimensional observations into a single scalar can lead to information loss, slowing convergence and yielding suboptimal results. To address this, we propose to use multi-output Gaussian processes to learn the full vector of observations directly, before mapping them to the scalar objective via an inexpensive analytical function. This physics-informed approach retains more information from the underlying physical processes, improving surrogate model accuracy. As a result, the approach accelerates optimization and produces better final designs compared to standard implementations.&lt;\/jats:p&gt;","DOI":"10.1088\/2632-2153\/ae1f5f","type":"journal-article","created":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T22:53:03Z","timestamp":1763074383000},"source":"Crossref","is-referenced-by-count":0,"title":["Physics-informed Bayesian optimization of expensive-to-evaluate black-box functions"],"prefix":"10.1088","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2414-5595","authenticated-orcid":false,"given":"Ivan","family":"Sekulic","sequence":"first","affiliation":[]},{"given":"Jonas","family":"Schaible","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5980-5740","authenticated-orcid":false,"given":"Gabriel","family":"M\u00fcller","sequence":"additional","affiliation":[]},{"given":"Matthias","family":"Plock","sequence":"additional","affiliation":[]},{"given":"Sven","family":"Burger","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9094-5355","authenticated-orcid":false,"given":"V\u00edctor Jos\u00e9","family":"Mart\u00ednez-Lahuerta","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8233-5848","authenticated-orcid":false,"given":"Naceur","family":"Gaaloul","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9949-9483","authenticated-orcid":false,"given":"Philipp-Immanuel","family":"Schneider","sequence":"additional","affiliation":[]}],"member":"266","published-online":{"date-parts":[[2025,11,13]]},"container-title":["Machine Learning: Science and Technology"],"original-title":[],"link":[{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ae1f5f","content-type":"text\/html","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ae1f5f\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ae1f5f\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ae1f5f\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T22:53:03Z","timestamp":1763074383000},"score":1,"resource":{"primary":{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ae1f5f"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,13]]},"references-count":0,"URL":"https:\/\/doi.org\/10.1088\/2632-2153\/ae1f5f","relation":{},"ISSN":["2632-2153"],"issn-type":[{"value":"2632-2153","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,13]]}}}</enrichment>
    <enrichment key="opus_crossrefLicence">https://creativecommons.org/licenses/by/4.0/</enrichment>
    <enrichment key="opus_import_origin">crossref</enrichment>
    <enrichment key="opus_doiImportPopulated">PersonAuthorFirstName_1,PersonAuthorLastName_1,PersonAuthorIdentifierOrcid_1,PersonAuthorFirstName_2,PersonAuthorLastName_2,PersonAuthorFirstName_3,PersonAuthorLastName_3,PersonAuthorIdentifierOrcid_3,PersonAuthorFirstName_4,PersonAuthorLastName_4,PersonAuthorFirstName_5,PersonAuthorLastName_5,PersonAuthorFirstName_6,PersonAuthorLastName_6,PersonAuthorIdentifierOrcid_6,PersonAuthorFirstName_7,PersonAuthorLastName_7,PersonAuthorIdentifierOrcid_7,PersonAuthorFirstName_8,PersonAuthorLastName_8,PersonAuthorIdentifierOrcid_8,PublisherName,TitleMain_1,TitleAbstract_1,TitleParent_1,PublishedYear,IdentifierIssn,Enrichmentopus_crossrefLicence</enrichment>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="AcceptedDate">2025-11-13</enrichment>
    <enrichment key="opus.source">doi-import</enrichment>
    <author>Ivan Sekulic</author>
    <submitter>Sven Burger</submitter>
    <author>Jonas Schaible</author>
    <author>Gabriel Müller</author>
    <author>Matthias Plock</author>
    <author>Sven Burger</author>
    <author>Víctor José Martínez-Lahuerta</author>
    <author>Naceur Gaaloul</author>
    <author>Philipp-Immanuel Schneider</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="schneider">Schneider, Philipp-Immanuel</collection>
    <collection role="projects" number="BerOSE-CB-1">BerOSE-CB-1</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="CNO-MODAL-NANOLAB">CNO-MODAL-NANOLAB</collection>
    <collection role="persons" number="sekulic">Sekulic, Ivan</collection>
    <collection role="projects" number="MathPlus-AA2-16">MathPlus-AA2-16</collection>
    <collection role="persons" number="schaible">Schaible, Jonas</collection>
  </doc>
  <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/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <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>10197</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>researchdata</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Data publication for Physics-informed Bayesian optimization of expensive-to-evaluate black-box functions</title>
    <parentTitle language="eng">Zenodo</parentTitle>
    <identifier type="doi">10.5281/zenodo.16751507</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="ScientificResourceTypeGeneral">Dataset</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Ivan Sekulic</author>
    <submitter>Sven Burger</submitter>
    <author>Jonas Schaible</author>
    <author>Gabriel Müller</author>
    <author>Matthias Plock</author>
    <author>Sven Burger</author>
    <author>Victor J. Martinez-Lahuerta</author>
    <author>Naceur Gaaloul</author>
    <author>Philipp-Immanuel Schneider</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="schneider">Schneider, Philipp-Immanuel</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="CNO-MODAL-NANOLAB">CNO-MODAL-NANOLAB</collection>
    <collection role="persons" number="sekulic">Sekulic, Ivan</collection>
    <collection role="persons" number="schaible">Schaible, Jonas</collection>
    <collection role="projects" number="MathPlus-AA2-19">MathPlus-AA2-19</collection>
  </doc>
  <doc>
    <id>10194</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>115</pageFirst>
    <pageLast>116</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Efficient Photonic Component Analysis via AAA Rational Approximation</title>
    <parentTitle language="eng">2025 International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD)</parentTitle>
    <identifier type="doi">10.1109/NUSOD64393.2025.11199710</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Lin Zschiedrich</author>
    <submitter>Sven Burger</submitter>
    <author>Fridtjof Betz</author>
    <author>Felix Binkowski</author>
    <author>Lilli Kuen</author>
    <author>Martin Hammerschmidt</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="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>10150</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>ITu1A.2</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>IPRSN</volume>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Physics-informed Bayesian optimization of nanophotonic devices</title>
    <parentTitle language="eng">Advanced Photonics Congress</parentTitle>
    <identifier type="doi">10.1364/IPRSN.2025.ITu1A.2</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Philipp-Immanuel Schneider</author>
    <submitter>Sven Burger</submitter>
    <author>Ivan Sekulic</author>
    <author>Matthias Plock</author>
    <author>Martin Hammerschmidt</author>
    <author>Sven Rodt</author>
    <author>Stephan Reitzenstein</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="hammerschmidt">Hammerschmidt, Martin</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="schneider">Schneider, Philipp-Immanuel</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="CNO-MODAL-NANOLAB">CNO-MODAL-NANOLAB</collection>
    <collection role="persons" number="sekulic">Sekulic, Ivan</collection>
  </doc>
  <doc>
    <id>10116</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1356806</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>13568</volume>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Machine learning approach for full Bayesian parameter reconstruction</title>
    <parentTitle language="eng">Proc. SPIE</parentTitle>
    <identifier type="doi">10.1117/12.3062268</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>Martin Hammerschmidt</author>
    <submitter>Sven Burger</submitter>
    <author>Matthias Plock</author>
    <author>Sven Burger</author>
    <author>Vinh Truong</author>
    <author>Victor Soltwisch</author>
    <author>Philipp-Immanuel Schneider</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="hammerschmidt">Hammerschmidt, Martin</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="schneider">Schneider, Philipp-Immanuel</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="CNO-MODAL-NANOLAB">CNO-MODAL-NANOLAB</collection>
  </doc>
  <doc>
    <id>10115</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>PC135730R</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>PC13573</volume>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Physics informed Bayesian optimization for inverse design of diffractive optical elements</title>
    <parentTitle language="eng">Proc. SPIE</parentTitle>
    <identifier type="doi">10.1117/12.3064372</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Ivan Sekulic</author>
    <submitter>Sven Burger</submitter>
    <author>Philipp-Immanuel Schneider</author>
    <author>Martin Hammerschmidt</author>
    <author>Jonas Schaible</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="hammerschmidt">Hammerschmidt, Martin</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="schneider">Schneider, Philipp-Immanuel</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="persons" number="sekulic">Sekulic, Ivan</collection>
    <collection role="persons" number="schaible">Schaible, Jonas</collection>
  </doc>
  <doc>
    <id>10105</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>researchdata</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Source code and simulation results: High Purcell enhancement in all-TMDC nanobeam resonator designs with active monolayers for nanolasers</title>
    <parentTitle language="deu">Zenodo</parentTitle>
    <identifier type="doi">10.5281/zenodo.16533803</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="ScientificResourceTypeGeneral">Dataset</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Felix Binkowski</author>
    <submitter>Sven Burger</submitter>
    <author>Aris Koulas-Simos</author>
    <author>Fridtjof Betz</author>
    <author>Matthias Plock</author>
    <author>Ivan Sekulic</author>
    <author>Phillip Manley</author>
    <author>Martin Hammerschmidt</author>
    <author>Philipp-Immanuel Schneider</author>
    <author>Lin Zschiedrich</author>
    <author>Battulga Munkhbat</author>
    <author>Stephan Reitzenstein</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="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="schneider">Schneider, Philipp-Immanuel</collection>
    <collection role="persons" number="manley">Manley, Phillip</collection>
    <collection role="persons" number="betz">Betz, Fridtjof</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="CNO-MODAL-NANOLAB">CNO-MODAL-NANOLAB</collection>
    <collection role="persons" number="sekulic">Sekulic, Ivan</collection>
    <collection role="projects" number="CNO-MATHPLUS-AA-ENER-1">CNO-MATHPLUS-AA-ENER-1</collection>
  </doc>
</export-example>
