Publications 2020

 

2020

14 arXiv in Spire

Classification of Fermi-LAT sources with deep learning using energy and time spectra

Thorben Finke, Michael Krämer, Silvia Manconi   

 

13 arXiv inSpire

NLO QCD corrections to off-shell ttW production at the LHC: Correlations and Asymmetries

Giuseppe Bevilacqua, Huan-Yu Bi, Heribertus Bayu Hartanto, Manfred Kraus, Jasmina Nasufi, Malgorzata Worek

 

12 arXiv inSpire

Collider constraints on dark mediators

Hanna Mies, Christiane Scherb, Pedro Schwaller

 

11 arXiv inSpire

On the challenges of searching for GeV-scale long-lived particles at the LHC

Elias Bernreuther, Juliana Carrasco Mejia, Felix Kahlhoefer,  Michael Krämer, Patrick Tunney

 

10 arXiv         inSpire

Resonant Sub-GeV Dirac Dark Matter

Elias Bernreuther, Saniya Heeba, Felix Kahlhoefer

 

9 arXiv          inSpire

Closing in on t-channel simplified dark matter models

Chiara Arina, Benjamin Fuks, Luca Mantani, Hanna Mies, Luca Panizzi, Jakub Salko

 

8 arXiv   inspire

MUSiC: a model unspecific search for new physics in proton- proton collisions at \sqrt{s} = 13 TeV.

CMS collaboration (Lorenzo Vigilante)   

 

7 arXiv           InSpire

Exact quark-mass dependence of the Higgs-photon form factor at three loops in QCD 

Marco Niggetiedt

 

6inSpire

Reinforced sorting networks for particle physics analyses

Martin Erdmann, Benjamin Fischer and Dennis Noll

 

5 inSpire

Adversarial Neural Network-based data-simulation corrections for jet-tagging at CMS

Martin Erdmann, Benjamin Fischer, Dennis Noll, Yannik Alexander Rath, Marcel Rieger and David Josef Schmidt

 

4 arXiv               InSpire

Casting a graph net to catch dark showers

Elias Bernreuther, Thorben Finke, Felix Kahlhoefer, Michael Krämer, Alexander Mück

 

3 arXiv InSpire

A search for the standard model Higgs boson decaying to charm quarks 

CMS Collaboration (Spandan Mondal)

 

2 arXiv inSpire

Exact quark-mass dependence of the Higgs-gluon form factor at three loops in QCD

M. Czakon and M. Niggetiedt

 

1 inSpire

Knowledge sharing on deep learning in physics research using VISPA

Max Beer, Niclas Eich, Martin Erdmann, Peter Fackeldey, Benjamin Fischer, Katharina Hafner, Dennis Daniel Nick Noll, Yannik Alexander Rath, Marcel Rieger, Alexander Temme, Max Vieweg and Martin Urban