CHIMERA-Hash (Chaos-IDF Multiresolution Entropy Resonance Attractor Hash) is a novel text fingerprinting algorithm integrating four components: Count Sketch variance reduction, Sign Random Projection (SimHash-SRP) with theoretical angular bounds, multiresolution character encoding inspired by Instant-NGP, and a chaotic attractor trajectory system. Two mechanisms are introduced with no identified prior art: (1) Chaos-IDF, which derives per-token importance from the logistic map at r = 3.9 without requiring a document corpus, and (2) LSH-to-attractor seeding, which couples SimHash bit-signatures to chaotic evolution initialisation. Evaluated on a 115-pair benchmark spanning 16 challenge categories, CHIMERA-Hash achieves Pearson correlation 0.5082 and Rank Accuracy 0.7108, ranking second overall. It achieves best MAE on near-duplicate detection (0.0109), paraphrase identification (0.0755), AI rewrite detection (0.1379), and length-difference handling (0.0754). All results are computed live from executable code.
Manish Kumar Parihar (Sun,) studied this question.