Zobrazeno 1 - 10
of 717
pro vyhledávání: '"P, Kraml"'
Autor:
Hallin, Anna, Kasieczka, Gregor, Kraml, Sabine, Lessa, André, Moureaux, Louis, von Schwartz, Tore, Shih, David
We develop a machine learning method for mapping data originating from both Standard Model processes and various theories beyond the Standard Model into a unified representation (latent) space while conserving information about the relationship betwe
Externí odkaz:
http://arxiv.org/abs/2407.20315
Autor:
Bélanger, Geneviève, Dutta, Juhi, Godbole, Rohini M., Kraml, Sabine, Mitra, Manimala, Padhan, Rojalin, Roy, Abhishek
We study the connection between collider and dark matter phenomenology in the singlet extension of the Georgi-Machacek model. In this framework, the singlet scalar serves as a suitable thermal dark matter (DM) candidate. Our focus lies on the region
Externí odkaz:
http://arxiv.org/abs/2405.18332
Autor:
Altakach, Mohammad Mahdi, Kraml, Sabine, Lessa, Andre, Narasimha, Sahana, Pascal, Timothée, Reymermier, Théo, Waltenberger, Wolfgang
Publikováno v:
SciPost Phys. 16, 101 (2024)
Electroweak-inos, superpartners of the electroweak gauge and Higgs bosons, play a special role in supersymmetric theories. Their intricate mixing into chargino and neutralino mass eigenstates leads to a rich phenomenology, which makes it difficult to
Externí odkaz:
http://arxiv.org/abs/2312.16635
Autor:
Alguero, G., Belanger, G., Boudjema, F., Chakraborti, S., Goudelis, A., Kraml, S., Mjallal, A., Pukhov, A.
micrOMEGAs is a numerical code to compute dark matter (DM) observables in generic extensions of the Standard Model of particle physics. We present a new version of micrOMEGAs that includes a generalization of the Boltzmann equations governing the DM
Externí odkaz:
http://arxiv.org/abs/2312.14894
Autor:
Araz, Jack Y., Buckley, Andy, Kasieczka, Gregor, Kieseler, Jan, Kraml, Sabine, Kvellestad, Anders, Lessa, Andre, Procter, Tomasz, Raklev, Are, Reyes-Gonzalez, Humberto, Rolbiecki, Krzysztof, Sekmen, Sezen, Unel, Gokhan
With the increasing usage of machine-learning in high-energy physics analyses, the publication of the trained models in a reusable form has become a crucial question for analysis preservation and reuse. The complexity of these models creates practica
Externí odkaz:
http://arxiv.org/abs/2312.14575
In this talk, we present the program Lilith, a python package for constraining new physics from Higgs measurements. We discuss the usage of signal strength results in the latest published version of Lilith, which allows for constraining deviations fr
Externí odkaz:
http://arxiv.org/abs/2311.02028
Autor:
Altakach, Mohammad Mahdi, Kraml, Sabine, Lessa, Andre, Narasimha, Sahana, Pascal, Timothée, Waltenberger, Wolfgang
Publikováno v:
SciPost Phys. 15, 185 (2023)
We present version 2.3 of SModelS, a public tool for the fast reinterpretation of LHC searches for new physics on the basis of simplified-model results. The main new features are a database update with the latest available experimental results for fu
Externí odkaz:
http://arxiv.org/abs/2306.17676
Careful preservation of experimental data, simulations, analysis products, and theoretical work maximizes their long-term scientific return on investment by enabling new analyses and reinterpretation of the results in the future. Key infrastructure a
Externí odkaz:
http://arxiv.org/abs/2209.08054
Publikováno v:
SciPost Phys. 13, 124 (2022)
In scenarios with very small dark matter (DM) couplings and small mass splittings between the DM and other dark sector particles, so-called "co-scattering" or "conversion-driven freeze-out" can be the dominant mechanism for DM production. We present
Externí odkaz:
http://arxiv.org/abs/2207.10536
Publikováno v:
SciPost Phys. 14, 009 (2023)
The statistical combination of disjoint signal regions in reinterpretation studies uses more of the data of an analysis and gives more robust results than the single signal region approach. We present the implementation and usage of signal region com
Externí odkaz:
http://arxiv.org/abs/2206.14870