Zobrazeno 1 - 10
of 127
pro vyhledávání: '"Mück, Alexander"'
Autor:
Das, Ranit, Finke, Thorben, Hein, Marie, Kasieczka, Gregor, Krämer, Michael, Mück, Alexander, Shih, David
Resonant anomaly detection methods have great potential for enhancing the sensitivity of traditional bump hunt searches. A key component of these methods is a high quality background template used to produce an anomaly score. Using the LHC Olympics R
Externí odkaz:
http://arxiv.org/abs/2411.00085
Autor:
Finke, Thorben, Hein, Marie, Kasieczka, Gregor, Krämer, Michael, Mück, Alexander, Prangchaikul, Parada, Quadfasel, Tobias, Shih, David, Sommerhalder, Manuel
Weakly supervised methods have emerged as a powerful tool for model-agnostic anomaly detection at the Large Hadron Collider (LHC). While these methods have shown remarkable performance on specific signatures such as di-jet resonances, their applicati
Externí odkaz:
http://arxiv.org/abs/2309.13111
Transformers have become the primary architecture for natural language processing. In this study, we explore their use for auto-regressive density estimation in high-energy jet physics, which involves working with a high-dimensional space. We draw an
Externí odkaz:
http://arxiv.org/abs/2303.07364
Autor:
Mück, Alexander
Einleitung: Die Aufnahme von Patienten mit hämato-onkologischer Grunderkrankung auf eine Intensivstation ist Gegenstand kontroverser Diskussionen. Die hohe Mortalität intensivpflichtiger Patienten mit hämato-onkologischer Grunderkrankung scheint j
Externí odkaz:
http://edoc.ub.uni-muenchen.de/16669/1/Mueck_Alexander.pdf
http://nbn-resolving.de/urn:nbn:de:bvb:19-166698
http://nbn-resolving.de/urn:nbn:de:bvb:19-166698
We show how weakly supervised machine learning can improve the sensitivity of LHC mono-jet searches to new physics models with anomalous jet dynamics. The Classification Without Labels (CWoLa) method is used to extract all the information available f
Externí odkaz:
http://arxiv.org/abs/2204.11889
Autor:
Buss, Thorsten, Dillon, Barry M., Finke, Thorben, Krämer, Michael, Morandini, Alessandro, Mück, Alexander, Oleksiyuk, Ivan, Plehn, Tilman
Publikováno v:
SciPost Phys. 15, 168 (2023)
Searches for anomalies are a significant motivation for the LHC and help define key analysis steps, including triggers. We discuss specific examples how LHC anomalies can be defined through probability density estimates, evaluated in a physics space
Externí odkaz:
http://arxiv.org/abs/2202.00686
Publikováno v:
JHEP 06 (2021) 161
Autoencoders are widely used in machine learning applications, in particular for anomaly detection. Hence, they have been introduced in high energy physics as a promising tool for model-independent new physics searches. We scrutinize the usage of aut
Externí odkaz:
http://arxiv.org/abs/2104.09051
Publikováno v:
SciPost Phys. 10, 046 (2021)
Strongly interacting dark sectors predict novel LHC signatures such as semi-visible jets resulting from dark showers that contain both stable and unstable dark mesons. Distinguishing such semi-visible jets from large QCD backgrounds is difficult and
Externí odkaz:
http://arxiv.org/abs/2006.08639
Publikováno v:
JHEP 03 (2020) 183
We constrain the Higgs-portal model employing the vector-boson fusion channel at the LHC. In particular, we include the phenomenologically interesting parameter region near the Higgs resonance, where the Higgs-boson mass is close to the threshold for
Externí odkaz:
http://arxiv.org/abs/1912.08472
Publikováno v:
JHEP 2003 (2020) 104
New Z' gauge bosons arise in many extensions of the Standard Model and predict resonances in the dilepton invariant mass spectrum. Searches for such resonances therefore provide important constraints on many models of new physics, but the resulting b
Externí odkaz:
http://arxiv.org/abs/1912.06374