{"id":7434,"date":"2020-06-23T12:36:49","date_gmt":"2020-06-23T12:36:49","guid":{"rendered":"https:\/\/www.istp.cnr.it\/?post_type=product&#038;p=7434"},"modified":"2022-06-21T09:55:09","modified_gmt":"2022-06-21T09:55:09","slug":"advanced-pulse-shape-discrimination-via-machine-learning-for-applications-in-thermonuclear-fusion","status":"publish","type":"product","link":"https:\/\/www.istp.cnr.it\/it\/research-product\/advanced-pulse-shape-discrimination-via-machine-learning-for-applications-in-thermonuclear-fusion\/","title":{"rendered":"Advanced pulse shape discrimination via machine learning for applications in thermonuclear fusion"},"content":{"rendered":"<p>Pulse shape discrimination, to distinguish between neutrons and gamma rays, is a very important classification task in thermonuclear fusion. Gaussian Mixture Models and probabilistic Support Vector Machines have been applied to hundreds of thousands of pulses obtained with a counter based on the NE213 liquid scintillator. The results of the two completely independent mathematical methods are in very good agreement, the maximum discrepancy being of the order of 2%. The achieved classification also shows an excellent value for the figure of merit, a Mahalanobis type of distance, implemented to quantify statistically the separation between the two particle distributions. These two machine learning tools provide also the probability of each example being a neutron or a gamma ray, allowing more detailed studies of the distribution of pulses. The proposed methodology therefore clearly outperforms previous techniques in practically all aspects of the classification.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Gelfusa M.; Rossi R.; Lungaroni M.; Belli F.; Spolladore L.; Wyss I.; Gaudio P.; Murari A.<\/p>\n","protected":false},"featured_media":1294,"comment_status":"closed","ping_status":"open","template":"","meta":[],"product_cat":[574],"product_tag":[2552,789,1361,2549,2550,2551],"class_list":["post-7434","product","type-product","status-publish","has-post-thumbnail","hentry","product_cat-journal-articles","product_tag-support-vector-machines","product_tag-gamma-rays","product_tag-pulse-shape-discrimination","product_tag-thermonuclear-fusion","product_tag-neutrons","product_tag-gaussian-mixture-models","prodpage-style2"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.istp.cnr.it\/it\/wp-json\/wp\/v2\/product\/7434","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.istp.cnr.it\/it\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/www.istp.cnr.it\/it\/wp-json\/wp\/v2\/types\/product"}],"replies":[{"embeddable":true,"href":"https:\/\/www.istp.cnr.it\/it\/wp-json\/wp\/v2\/comments?post=7434"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.istp.cnr.it\/it\/wp-json\/wp\/v2\/media\/1294"}],"wp:attachment":[{"href":"https:\/\/www.istp.cnr.it\/it\/wp-json\/wp\/v2\/media?parent=7434"}],"wp:term":[{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/www.istp.cnr.it\/it\/wp-json\/wp\/v2\/product_cat?post=7434"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/www.istp.cnr.it\/it\/wp-json\/wp\/v2\/product_tag?post=7434"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}