Name
Abstract | ||
|---|---|---|
The application of methods of statistical learning to the identification of the partons from which hadronic jets originate is investigated using simulated jets in the CDF detector with the ultimate objective of applying them at the trigger level. Using only jet-related properties, it appears to be raltively easy to distinguish between jets originating from gluons and those originating from quarks in an energy-independent manner. Distinguishing between quark flavours is more difficult and will require inclusion of other variables. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/1-4020-3432-6_15 | Biological and Artificial Intelligence Environments |
Keywords | Field | DocType |
HEP,parton identification,multi-layer perceptron | Parton,Gluon,Pattern recognition,Computer science,Hadron,Quark,Multilayer perceptron,Artificial intelligence,Statistical learning,Detector | Conference |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| D. Cauz | 1 | 0 | 0.34 |
| M. Giordani | 2 | 0 | 0.34 |
| G. Pauletta | 3 | 0 | 0.34 |
| M. Rossi | 4 | 0 | 0.34 |
| L. Santi | 5 | 0 | 0.34 |