{"id":14503,"date":"2015-09-03T09:27:39","date_gmt":"2015-09-03T06:27:39","guid":{"rendered":"http:\/\/hgpu.org\/?p=14503"},"modified":"2015-09-03T09:27:39","modified_gmt":"2015-09-03T06:27:39","slug":"fast-gpu-based-calculations-in-few-body-quantum-scattering","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=14503","title":{"rendered":"Fast GPU-based calculations in few-body quantum scattering"},"content":{"rendered":"<p>A principally novel approach towards solving the few-particle (many-dimensional) quantum scattering problems is described. The approach is based on a complete discretization of few-particle continuum and usage of massively parallel computations of integral kernels for scattering equations by means of GPU. The discretization for continuous spectrum of a few-particle Hamiltonian is realized with a projection of all scattering operators and wave functions onto the stationary wave-packet basis. Such projection procedure leads to a replacement of singular multidimensional integral equations with linear matrix ones having finite matrix elements. Different aspects of the employment of a multithread GPU computing for fast calculation of the matrix kernel of the equation are studied in detail. As a result, the fully realistic three-body scattering problem above the break-up threshold is solved on an ordinary desktop PC with GPU for a rather small computational time.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>A principally novel approach towards solving the few-particle (many-dimensional) quantum scattering problems is described. The approach is based on a complete discretization of few-particle continuum and usage of massively parallel computations of integral kernels for scattering equations by means of GPU. The discretization for continuous spectrum of a few-particle Hamiltonian is realized with a projection [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[89,3,12],"tags":[98,14,707,20,1394,1783],"class_list":["post-14503","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-paper","category-physics","tag-computational-physics","tag-cuda","tag-integral-equations","tag-nvidia","tag-nvidia-geforce-gtx-670","tag-physics"],"views":3023,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/14503","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=14503"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/14503\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=14503"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=14503"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=14503"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}