{"paper":{"title":"String theory mathematics and matrix data analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["hep-ph"],"primary_cat":"hep-th","authors_text":"Sanjaye Ramgoolam","submitted_at":"2026-07-28T09:36:39Z","abstract_excerpt":"Inspired by matrix techniques in quantum field theory and string theory, we review Permutation Invariant Gaussian Matrix Models (PIGMM), which replace the continuous symmetries of traditional Random Matrix Theory, for $ N \\times N$ matrices, with finite permutation symmetry, $S_N$. This symmetry-driven approach reduces highly multivariate $N^2$-variable matrix data analysis problems to a rich but tractable space of parameters. The representation theory of $S_N$ brings a highly correlated quadratic matrix action to a near-diagonal form with $13$ parameters. The invariant observables are paramet"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.25500","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.25500/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}