{"id":5640,"date":"2025-07-28T07:02:27","date_gmt":"2025-07-28T07:02:27","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/07\/28\/2507-18824\/"},"modified":"2025-07-28T07:02:27","modified_gmt":"2025-07-28T07:02:27","slug":"2507-18824","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/07\/28\/2507-18824\/","title":{"rendered":"Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification"},"content":{"rendered":"<p>    Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>arXiv:2507.18824v1 Announce Type: cross<br \/>\nAbstract: Simulation Based Inference (SBI) is shown to yield more accurate resonance parameter estimates than traditional chi-squared minimization in certain cases of model misspecification, demonstrated through a case study of pi-pi scattering and the rho(770) resonance. Models fit to some data sets using chi-squared minimization can predict inaccurate pole positions for the rho(770), while SBI provides more robust predictions across the same models and data. This result is significant both as a proof of concept that SBI can handle model misspecification, and because accurate modeling of pi-pi scattering is essential in the study of many contemporary physical systems (e.g., a1(1260), omega(782)).<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Daniel Sadasivan, Isaac Cordero, Andrew Graham, Cecilia Marsh, Daniel Kupcho, Melana Mourad, Maxim Mai<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/arxiv.org\/abs\/2507.18824\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification arXiv:2507.18824v1 Announce Type: cross Abstract: Simulation Based Inference (SBI) is shown to yield more accurate resonance parameter estimates than traditional chi-squared minimization in certain cases of model misspecification, demonstrated through a case study of pi-pi scattering and the rho(770) resonance. [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,3340,3341,181,112],"tags":[3342,103,3343],"class_list":["post-5640","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-hep-ph","category-nucl-th","category-stat-ap","category-stat-ml","tag-misspecification","tag-model","tag-pi"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/5640"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=5640"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/5640\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=5640"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=5640"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=5640"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}