{"id":2756,"date":"2011-02-07T12:57:56","date_gmt":"2011-02-07T12:57:56","guid":{"rendered":"http:\/\/hgpu.org\/?p=2756"},"modified":"2011-02-07T12:57:56","modified_gmt":"2011-02-07T12:57:56","slug":"fitting-multi-planet-transit-models-to-photometric-time-data-series-by-evolution-strategies","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=2756","title":{"rendered":"Fitting multi-planet transit models to photometric time-data series by evolution strategies"},"content":{"rendered":"<p>In this paper we present the application of an evolution strategy to the problem of detecting multi-planet transit events in photometric time-data series. Planetary transits occur when a planet regularly eclipses its host star, reducing stellar luminosity. The transit method is amongst the most successful detection methods for exoplanet and is presently performed by space telescope missions. The goal of the presented algorithm is to find high quality fits of multi-planet transit models to observational data, which is a challenging computational task. In particular we present a method for an effective objective function evaluation and show how the algorithm can be implemented on graphics processing units. Results on artificial test data with three artificial planets are reported.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper we present the application of an evolution strategy to the problem of detecting multi-planet transit events in photometric time-data series. Planetary transits occur when a planet regularly eclipses its host star, reducing stellar luminosity. The transit method is amongst the most successful detection methods for exoplanet and is presently performed by space [&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":[36,96,89,3,12],"tags":[1787,1794,14,604,613,20,466,1783],"class_list":["post-2756","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-astrophysics","category-nvidia-cuda","category-paper","category-physics","tag-algorithms","tag-astrophysics","tag-cuda","tag-earth-and-planetary-astrophysics","tag-evolutionary-computations","tag-nvidia","tag-nvidia-geforce-9600-gt","tag-physics"],"views":1962,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2756","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=2756"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2756\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2756"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2756"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2756"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}