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The Debye scattering equation (DSE) provides a rigorous route to elastic total scattering, but its direct evaluation is computationally demanding because pairwise contributions must be accumulated at every scattering vector, whereas common acceleration strategies based on binned pair-distance distributions or gridded fast Fourier transforms can introduce discretization and aliasing artifacts that compromise diffuse-scattering accuracy. Here, we present\n                    <jats:italic>AES-Debye<\/jats:italic>\n                    , an accuracy-preserving DSE framework that aggregates pair distances into a pair distribution function (PDF) using corrected bin centers and numerically robust accumulation to suppress discretization and summation errors. A data-locality-aware parallel design enables efficient execution on CPUs and GPUs. We demonstrate strong scalability by computing a high-resolution total scattering profile for a system of 90 million atoms, (0.1\u2005\u00b5m)\n                    <jats:sup>3<\/jats:sup>\n                    , in minutes on a distributed-memory CPU platform. These capabilities extend accurate elastic total scattering calculations to large complex systems while simultaneously providing high-resolution PDFs for downstream structural analysis.\n                  <\/jats:p>","DOI":"10.1107\/s1600576726007429","type":"journal-article","created":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T12:57:21Z","timestamp":1786453041000},"page":"1478-1490","update-policy":"https:\/\/doi.org\/10.1107\/cm_01","source":"Crossref","is-referenced-by-count":0,"title":["<i>AES-Debye<\/i>\n                    : an accurate, efficient and scalable engine for Debye scattering calculations"],"prefix":"10.1107","volume":"59","author":[{"given":"Navid","family":"Panchi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebastian","family":"Kuckuk","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Markus","family":"Wittmann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Engel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2949-529X","authenticated-orcid":true,"given":"Alberto","family":"Leonardi","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00f7hpc57","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"329","published-online":{"date-parts":[[2026,9,4]]},"reference":[{"key":"po5180_bb3","doi-asserted-by":"crossref","first-page":"109363","DOI":"10.1016\/j.commatsci.2019.109363","volume":"173","author":"Anderson","year":"2020","journal-title":"Comput. 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