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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.
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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.
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Paper annotation: Efficiently translating these classical datasets i...
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