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    "release_date": "2025-08-20T00:00:00",
    "funder": "https://doi.org/10.13039/501100003246",
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    "date": "2026-11-04T00:00:00",
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      "project_id": "NGF.1623.23.006",
      "title": "Topological Data Analysis with Quantum Many-Body Methods",
      "funding_scheme_id": 4830,
      "funding_scheme": "NGF - Quantum Delta NL Quantum Technologie 2023 2023",
      "department": "Exacte en Natuurwetenschappen",
      "sub_department": "Exacte en Natuurwetenschappen",
      "start_date": "2024-04-01T00:00:00",
      "reporting_year": 2023,
      "summary_nl": "Topologische data-analyse is een nieuwe benadering om robuuste informatie uit gecompliceerde datasets te halen. Het\n\nwordt gebruikt in de geneeskunde, biologie, financiën en tijdreeksanalyse. Topologische data-analyse kan worden\n\ngeformuleerd als een probleem in de kwantummechanica. Met deze nieuwe formulering kunnen we gebruikmaken van\n\nde kracht van variatie-kwantumalgoritmen en kwantum-geïnspireerde methoden op klassieke computers om harde\n\nproblemen in topologische gegevensanalyse op te lossen.",
      "summary_en": "Topological data analysis is a novel approach to extract robust information from complicated datasets. It is used in\n\nmedicine, biology, finance and time-series analysis. Interestingly, topological data analysis can be formulated as a\n\nproblem in quantum mechanics. Using this new formulation, we can leverage the power of variational quantum\n\nalgorithms and quantum-inspired methods on classical computers to solve hard problems in topological data analysis.",
      "award_amount": 389866,
      "grant_id": "https://doi.org/10.61686/RBLDP65717",
      "summary_updates": [
        {
          "submission_date": "2025-05-26T07:58:48",
          "update_en": "The key challenge of topological data analysis is to extract the number of holes in complex data. Intuitively, we are aiming to distinguish between a ball and a donut by finding the central hole in the donut. This intuitive picture breaks down in higher dimension. Current algorithms are limited to low dimensions or low number of holes.\n\nBy mapping the problem to a many-body problem in physics, we could show that we can compute lower bounds on the number of holes more efficiently than standard algorithms.\n\nCurrently, we are exploring implementations of related algorithms on available quantum devices.",
          "update_nl": "De belangrijkste uitdaging van topologische data-analyse is het extraheren van het aantal gaten in complexe data. Intuïtief proberen we onderscheid te maken tussen een bal en een donut door het middelste gat in de donut te vinden. Dit intuïtieve beeld valt weg in hogere dimensies. Huidige algoritmen zijn beperkt tot lage dimensies of een laag aantal gaten.\n\nDoor het probleem te koppelen aan een veeldeeltjesprobleem in de natuurkunde, konden we aantonen dat we de ondergrens voor het aantal gaten efficiënter kunnen berekenen dan met standaardalgoritmen.\n\nMomenteel onderzoeken we implementaties van gerelateerde algoritmen op beschikbare quantumapparaten."
        }
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          "initials": "P.",
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