Mixture-of-Theories training: can we find new physics and anomalies better by mixing physical theories?
نویسندگان
چکیده
Model-independent search strategies have been increasingly proposed in recent years because on the one hand there has no clear signal for new physics and other is a lack of highly probable parameter-free extension standard model. For these reasons, simple target so far. In this work, we try to take direction ask question: bearing mind that large number theories go beyond Standard Model may contain grain truth, can improve our strategy unknown signals by using them "in combination"? particular, show hypothesis based large, intermingled set many different theoretical models be superior approach find an BSM signal. Applied data challenge, "mixture-of-theories training" outperforms optimize regions with single model as well most unsupervised strategies. Applications work include anomaly detection definition physics.
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ژورنال
عنوان ژورنال: Journal of High Energy Physics
سال: 2023
ISSN: ['1127-2236', '1126-6708', '1029-8479']
DOI: https://doi.org/10.1007/jhep03(2023)004