{
  "abstract": "We present a seminumerical exchange algorithm (SNK) based on the sn-LinK method [Laqua et al., J. Chem. Theory Comput. 16, 1456 (2020)], optimized for modern multi-core central processing units with single instruction multiple data vector instructions and report its implementation into the Q-Chem quantum chemistry program. Vectorization and memory management strategies for the Boys function and 3-center-1-electron (3c1e) integral kernels are given. Several new considerations are made in the computation of the 3c1e integrals: the Head-Gordon Pople horizontal recurrence relations, same-center optimizations, and multishell optimizations, all implemented symbolically employing the SymPy symbolic algebra library and exported as optimized C++ code leveraging common-sub-expression elimination (CSE) optimization techniques. A general scheme for choosing optimal integral kernels is developed through rigorous timing benchmarks. The resulting implementation is tested against traditional 4c2e exchange for several systems and basis sets, showing 1-2 orders of magnitude speedups for systems of practically relevant sizes (100-500 atoms, 2000-10000 basis functions). For smaller molecules, comparisons are also made against the more efficient occ-RI-K method showing a break-even point around 50-100 atoms beyond which SNK dramatically outperforms due to its superior sub-quadratic (between linear and quadratic) time complexity as well as its effectively negligible memory demand.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.21075",
  "author_total": 3,
  "authors": [
    {
      "name": "Jesse DiCenso"
    },
    {
      "name": "Henryk Laqua"
    },
    {
      "name": "Martin Head-Gordon"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9vsv3d2cjkf57.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.21075",
  "fulltext_url": null,
  "id": "9vsv3d2cjkf57",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.21075",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "physics.chem-ph"
    ],
    [
      "arxiv",
      "quant-ph"
    ],
    [
      "openalex",
      "1708|Parallel Computing and Optimization Techniques"
    ]
  ],
  "openalex": "W7222689581",
  "pdf_url": "https://arxiv.org/pdf/2610.21075",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-15",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/9vsv3d2cjkf57.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:29:50Z",
      "native_id": "2610.21075",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.21075"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "arxiv:physics.chem-ph",
      "subfield": "physical"
    },
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    }
  ],
  "title": "Data-Driven Optimization of Seminumerical Exchange for SIMD CPUs",
  "title_text": "Data-Driven Optimization of Seminumerical Exchange for SIMD CPUs",
  "type": "preprint",
  "updated_at": "2026-10-30T12:29:50Z",
  "url": "https://research.draconitic.com/paper/9vsv3d2cjkf57",
  "venue": "arXiv",
  "versions": []
}