{"id":2843,"date":"2011-02-14T12:02:53","date_gmt":"2011-02-14T12:02:53","guid":{"rendered":"http:\/\/hgpu.org\/?p=2843"},"modified":"2011-02-14T12:02:53","modified_gmt":"2011-02-14T12:02:53","slug":"visualising-interfaces-in-scalar-and-vector-field-model-simulations","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=2843","title":{"rendered":"Visualising Interfaces in Scalar and Vector Field-Model Simulations"},"content":{"rendered":"<p>Many scientific simulations and models are based upon one or more coupled field equations. Fields are often modelled as a regular mesh or grid of individual field variables where each degrees of freedom or site variable is a scalar or vector quantity. Visualising such quantities interactively can be a great aid to debugging as well as understanding and interpreting the results of numerical simulation. We review a number of different approaches and software technologies for visualising scalar and vector fields as they time-evolve in 1, 2 and 3 dimensional simulations. We present some performance data that can be used to plan size and time scoping for simulations on present interactive visualisation computer technology. We discuss the particular merits of different approaches for dense 3-dimensional vector-field models such as the Ginzburg-Landau equation. We offer some speculations on how these techniques could be applied to simulations of other field equations.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Many scientific simulations and models are based upon one or more coupled field equations. Fields are often modelled as a regular mesh or grid of individual field variables where each degrees of freedom or site variable is a scalar or vector quantity. Visualising such quantities interactively can be a great aid to debugging as well [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","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":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[36,11,3],"tags":[1787,1782,134],"class_list":["post-2843","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-paper","tag-algorithms","tag-computer-science","tag-visualization"],"views":1975,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2843","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=2843"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2843\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2843"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2843"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2843"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}