TY  - RPRT
AU  - Buckley, Andy
AU  - Krauss, Frank
AU  - Plätzer, Simon
AU  - Seymour, Michael
AU  - Alioli, Simone
AU  - Andersen, Jeppe
AU  - Bellm, Johannes
AU  - Butterworth, Jon
AU  - Dasgupta, Mrinal
AU  - Duhr, Claude
AU  - Frixione, Stefano
AU  - Gieseke, Stefan
AU  - Hamilton, Keith
AU  - Hesketh, Gavin
AU  - Hoeche, Stefan
AU  - Jung, Hannes
AU  - Kilian, Wolfgang
AU  - Lönnblad, Leif
AU  - Maltoni, Fabio
AU  - Mangano, Michelangelo
AU  - Mrenna, Stephen
AU  - Nagy, Zoltan
AU  - Nason, Paolo
AU  - Nurse, Emily
AU  - Ohl, Thorsten
AU  - Oleari, Carlo
AU  - Papaefstathiou, Andreas
AU  - Plehn, Tilman
AU  - Prestel, Stefan
AU  - Ré, Emanuele
AU  - Reuter, Juergen
AU  - Richardson, Peter
AU  - Salam, Gavin
AU  - Schoenherr, Marek
AU  - Schumann, Steffen
AU  - Siegert, Frank
AU  - Siódmok, Andrzej
AU  - Sjödahl, Malin
AU  - Sjöstrand, Torbjörn
AU  - Skands, Peter
AU  - Soper, Davison
AU  - Soyez, Gregory
AU  - Webber, Bryan
TI  - Monte Carlo event generators for high energy particle physics event simulation
IS  - arXiv:1902.01674
M1  - PUBDB-2020-00723
M1  - arXiv:1902.01674
M1  - MCnet-19-02
SP  - 7
PY  - 2019
N1  - Monte Carlo Community input to European Strategy Update
AB  - Monte Carlo event generators (MCEGs) are the indispensable workhorses of particle physics, bridging the gap between theoretical ideas and first-principles calculations on the one hand, and the complex detector signatures and data of the experimental community on the other hand. All collider physics experiments are dependent on simulated events by MCEG codes such as Herwig, Pythia, Sherpa, POWHEG, and MG5_aMC@NLO to design and tune their detectors and analysis strategies. The development of MCEGs is overwhelmingly driven by a vibrant community of academics at European Universities, who also train the next generations of particle phenomenologists. The new challenges posed by possible future collider-based experiments and the fact that the first analyses at Run II of the LHC are now frequently limited by theory uncertainties urge the community to invest into further theoretical and technical improvements of these essential tools. In this short contribution to the European Strategy Update, we briefly review the state of the art, and the further developments that will be needed to meet the challenges of the next generation.
KW  - PYTHIA (INSPIRE)
KW  - HERWIG (INSPIRE)
KW  - programming: Monte Carlo (INSPIRE)
KW  - numerical calculations: Monte Carlo (INSPIRE)
LB  - PUB:(DE-HGF)29
DO  - DOI:10.3204/PUBDB-2020-00723
UR  - https://bib-pubdb1.desy.de/record/435595
ER  -