Nanopublications

@prefix dcterms: <http://purl.org/dc/terms/> .
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@prefix npx: <http://purl.org/nanopub/x/> .
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@prefix orcid: <https://orcid.org/> .
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@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

sub:Head {
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    np:hasProvenance sub:provenance ;
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sub:assertion {
  <https://doi.org/10.48550/arXiv.2504.03866> dcterms:isPartOf <https://w3id.org/np/RAvk9pmoZ2IberoDe7zUWV0bVithiy6CnbSG5y06YuKM0/quantum-computing-applications-for-biodiversity-re> ;
    ns1:hasQuotedText "Efficiently translating these classical datasets into quantum-readable formats remains a significant bottleneck. This challenge, often referred to as the state preparation problem, can negate theoretical speedups if not addressed." ;
    rdfs:comment "Critical limitation for practical applications - ecological and biodiversity data is inherently classical (species counts, GPS coordinates, environmental variables) and encoding it for quantum computation is non-trivial. This state preparation bottleneck is an essential caveat that may limit near-term practical benefits for biodiversity research." .
  orcid:0000-0002-1784-2920 ns1:quotes <https://doi.org/10.48550/arXiv.2504.03866> .
}

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sub:pubinfo {
  orcid:0000-0002-1784-2920 foaf:name "Anne Fouilloux" .
  <https://w3id.org/np/RAN4iY5PIetmng66BGer15SWBfCvJZYEAtkFt679qKL8c> dcterms:created "2026-01-06T20:53:50.178Z"^^xsd:dateTime ;
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    dcterms:license <https://creativecommons.org/licenses/by/4.0/> ;
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