{"id":222738,"date":"2025-10-01T04:21:28","date_gmt":"2025-10-01T09:21:28","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2025\/10\/ai-tensor-network-based-computational-framework-cracks-a-100-year-old-physics-challenge"},"modified":"2025-10-01T04:21:28","modified_gmt":"2025-10-01T09:21:28","slug":"ai-tensor-network-based-computational-framework-cracks-a-100-year-old-physics-challenge","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2025\/10\/ai-tensor-network-based-computational-framework-cracks-a-100-year-old-physics-challenge","title":{"rendered":"AI tensor network-based computational framework cracks a 100-year-old physics challenge"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/ai-tensor-network-based-computational-framework-cracks-a-100-year-old-physics-challenge.jpg\"><\/a><\/p>\n<p>Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics.<\/p>\n<p>The Tensors for High-dimensional Object Representation (THOR) AI framework employs tensor network algorithms to efficiently compress and evaluate the extremely large configurational integrals and <a href=\"https:\/\/phys.org\/tags\/partial+differential+equations\/\" rel=\"tag\" class=\"\">partial differential equations<\/a> central to determining the thermodynamic and mechanical properties of materials.<\/p>\n<p>The framework was integrated with machine learning potentials, which encode interatomic interactions and dynamical behavior, enabling accurate and scalable modeling of materials across diverse physical conditions.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics. The Tensors for High-dimensional Object Representation (THOR) AI framework employs tensor network algorithms to efficiently compress and evaluate the extremely large configurational integrals and partial differential equations central to [\u2026]<\/p>\n","protected":false},"author":427,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[41,219,6],"tags":[],"class_list":["post-222738","post","type-post","status-publish","format-standard","hentry","category-information-science","category-physics","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/222738","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/427"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=222738"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/222738\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=222738"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=222738"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=222738"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}