Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Stefan Wunsch"'
Publikováno v:
SciPost Physics, Vol 9, Iss 2, p 022 (2020)
We report on the status of efforts to improve the reinterpretation of searches and measurements at the LHC in terms of models for new physics, in the context of the LHC Reinterpretation Forum. We detail current experimental offerings in direct sea
Externí odkaz:
https://doaj.org/article/02ccb01d6e0b497a9278961b7e33cf0c
Autor:
Stefan Wunsch
Publikováno v:
Rheinisch-westfälische Zeitschrift für Volkskunde. 2021:421-422
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::866d3936bba8bfa93aab65999c44ac38
https://doi.org/10.31244/rwz/2021/29
https://doi.org/10.31244/rwz/2021/29
Autor:
Meirin Oan Evans, Jackson Carl Burzynski, Kevin Michael Nelson, Siqi Yuan, Angela Maria Burger, Judita Mamužić, Giordon Holtsberg Stark, J. Bonilla, David Chamont, Matthew Feickert, K. Lieret, Ke Li, Matthew Bellis, Emery Nibigira, Brendan Regnery, Konstantin Lehmann, Michel Hernández Villanueva, Devdatta Majumder, Sudhir Malik, G. A. Stewart, Scarlet Norberg, Henry Schreiner, Clemens Lange, Maximilian M. Horzela, D. Guest, Philipp Gadow, Marc Huwiler, Savannah Thais, Peter Elmer, Stephan Hageboeck, Lukas Heinrich, David Yakobovitch, A. Valassi, Daniel S. Katz, Riccardo-Maria Bianchi, Bernhard Manfred Gruber, Stefan Wunsch, Stephen Nicholas Swatman, Mason Proffitt, Robin Newhouse, Stefan Roiser, S. Meehan, Sizar Aziz, Gianluca Bianco, Oksana Shadura, Arturo Rodolfo Sanchez Pineda, Amber Roepe
Publikováno v:
Comput.Softw.Big Sci.
25th International Conference on Computing in High-Energy and Nuclear Physics
25th International Conference on Computing in High-Energy and Nuclear Physics, May 2021, Online, France. pp.22, ⟨10.1007/s41781-021-00069-9⟩
Computing and Software for Big Science, 5 (1), 22
Computing and Software for Big Science
25th International Conference on Computing in High-Energy and Nuclear Physics
25th International Conference on Computing in High-Energy and Nuclear Physics, May 2021, Online, France. pp.22, ⟨10.1007/s41781-021-00069-9⟩
Computing and Software for Big Science, 5 (1), 22
Computing and Software for Big Science
Long term sustainability of the high energy physics (HEP) research software ecosystem is essential for the field. With upgrades and new facilities coming online throughout the 2020s this will only become increasingly relevant throughout this decade.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8b6e387b9106cc5e9d5b9dceb313385
https://hdl.handle.net/11585/897213
https://hdl.handle.net/11585/897213
Publikováno v:
Computing and software for big science, 5 (1), Art. Nr.: 4
Data analysis in science, e.g., high-energy particle physics, is often subject to an intractable likelihood if the observables and observations span a high-dimensional input space. Typically the problem is solved by reducing the dimensionality using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e44ab20050940fd6f4a572dbaf42bdcc
http://arxiv.org/abs/2003.07186
http://arxiv.org/abs/2003.07186
Autor:
Stefan Wunsch
Publikováno v:
EPJ Web of Conferences, Vol 245, p 08006 (2020)
The CMS collaboration at the CERN LHC has made more than one petabyte of open data available to the public, including large parts of the data which formed the basis for the discovery of the Higgs boson in 2012. Apart from their scientific value, thes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::154d4b2e5955ef8cd529c65028e064dc
http://cds.cern.ch/record/2712246
http://cds.cern.ch/record/2712246
Publikováno v:
Computing and software for big science, 4 (1), Article: 5
Applications of neural networks to data analyses in natural sciences are complicated by the fact that many inputs are subject to systematic uncertainties. To control the dependence of the neural network function to variations of the input space withi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f812ee1d51bb2ff4bb497b91047e7f6e
Publikováno v:
EPJ Web of Conferences, Vol 245, p 06004 (2020)
PyROOT is the name of ROOT's automatic Python bindings, which allow to access all the ROOT functionality implemented in C++ from Python. Thanks to the ROOT type system and the Cling C++ interpreter, PyROOT creates Python proxies for C++ entities on t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a0c2ed1bf6ed4538aef5b410205596db
https://www.epj-conferences.org/articles/epjconf/pdf/2020/21/epjconf_chep2020_06004.pdf
https://www.epj-conferences.org/articles/epjconf/pdf/2020/21/epjconf_chep2020_06004.pdf
ROOT provides, through TMVA, machine learning tools for data analysis at HEP experiments and beyond. However, with the rapidly evolving ecosystem for machine learning, the focus of TMVA is shifting. In this poster, we present the new developments and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b186caf7eac742fc856f7a3ffece2e99
Autor:
Lorenzo Moneta, Marc Huwiler, Stefan Wunsch, Saurav Shekar, Omar Andres Zapata Mesa, Akshay Vashistha, Victor Estrade, Kim Albertsson, Sergei Gleyzer, Vladimir Ilievski
Publikováno v:
EPJ Web of Conferences, Vol 214, p 06014 (2019)
The Toolkit for Multivariate Analysis, TMVA, the machine learning package integrated into the ROOT data analysis framework, has recently seen improvements to its deep learning module, parallelisation of multivariate methods and cross validation. Perf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f916f10b348c80f9ff95393e2c29e45
https://www.epj-conferences.org/articles/epjconf/pdf/2019/19/epjconf_chep2018_06014.pdf
https://www.epj-conferences.org/articles/epjconf/pdf/2019/19/epjconf_chep2018_06014.pdf
Die aktuelle Ausgabe der Geschichte in Köln setzt sich kritisch mit jüngsten Forschungsergebnissen zu Person und Kult des hl. Severin auseinander, fragt nach Identität des Kölner Erzbischofs Hilduin und beleuchtet, wie man im spätmittelterlichen