The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
PYTHIA 6.4 physics and manual
Open accessAbstract
The Pythia program can be used to generate high-energy-physics ''events'', i.e. sets of outgoing particles produced in the interactions between two incoming particles. The objective is to provide as accurate as possible a representation of event properties in a wide range of reactions, within and beyond the Standard Model, with emphasis on those where strong interactions play a role, directly or indirectly, and therefore multihadronic final states are produced. The physics is then not understood well enough to give an exact description; instead the program has to be based on a combination of analytical results and various QCD-based models. This physics input is summarized here, for areas such as hard subprocesses, initial- and final-state parton showers, underlying events and beam remnants, fragmentation and decays, and much more. Furthermore, extensive information is provided on all program elements: subroutines and functions, switches and parameters, and particle and process data. This should allow the user to tailor the generation task to the topics of interest.
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Cites
Large Mass Hierarchy from a Small Extra Dimension
Randall, L., & Sundrum, R. (1999) · Physical Review Letters · doi:10.1103/physrevlett.83.3370 · Cited by 9,227
Cited by
Bähr, M., Gieseke, S., Gigg, M. A., Grellscheid, D., Hamilton, K., Latunde-Dada, O., Plätzer, S., Richardson, P., Seymour, M. H., Sherstnev, A., et al. (2008) · The European Physical Journal C · doi:10.1140/epjc/s10052-008-0798-9 · Cited by 2,119
New cosmological constraints on primordial black holes
Carr, B. J., Kohri, K., Sendouda, Y., & Yokoyama, J. (2010) · Physical Review D · doi:10.1103/physrevd.81.104019 · Cited by 1,166
Transverse-Momentum and Pseudorapidity Distributions of Charged Hadrons inppCollisions ats=7 TeV
Khachatryan, V., Sirunyan, A. M., Tumasyan, A., Adam, W., Bergauer, T., Dragicevic, M., Erö, J., Fabjan, C., Friedl, M., Frühwirth, R., et al. (2010) · Physical Review Letters · doi:10.1103/physrevlett.105.022002 · Cited by 528
Self-citationDeep learning and its application to LHC physics
Guest, D., Cranmer, K., & Whiteson, D. (2018) · Annual Review of Nuclear and Particle Science · doi:10.1146/annurev-nucl-101917-021019 · Cited by 417
Larkoski, A. J., Moult, I., & Nachman, B. (2020) · Physics Reports · doi:10.1016/j.physrep.2019.11.001 · Cited by 361
Metadata
- Authors
- Sjöstrand, T., Mrenna, S., & Skands, P.
- Venue
- Journal of High Energy Physics
- Published
- 2006-05-09
- Volume
- 2006
- Issue
- 05
- Pages
- 026-026
- ISSN
- 1029-8479 (ISSN-L)
- OpenAlex
- W2258584306
- Cited by
- 8,952
- References
- 1
- FWCI
- 122.32
- Type
- journal article
- Language
- en
- Open access
- green
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