IPM workshop

1. IPM workshop Monte Carlo generation for the LHC Filip Moortgat, ETH Zurich Filip Moortgat

2. The path to knowledge Nature Our understanding of it (= SM) LHC collisions MC generators Detector + DAQ Detector simulation Reconstruction Analysis improved understanding of Nature Filip Moortgat

3. First step: generation First step : generation Filip Moortgat

4. Why event generators ? Filip Moortgat

5. Topics • We will discuss in this lecture : • what happens in a pp collision at the LHC • how to describe all of this with a Monte Carlo generator • (some of the) latest trends in generator land • MC event production in the LHC experiments Filip Moortgat

6. The structure of an event Incoming beams Filip Moortgat

7. The structure of an event (2) The hard subprocess (is described by matrix elements) Filip Moortgat

8. The structure of an event (3) Resonance decays (correlated with hard subprocess) Filip Moortgat

9. The structure of an event (4) Initial state radiation : spacelike parton showers Filip Moortgat

10. The structure of an event (5) Final state radiation: timelike parton showers Filip Moortgat

11. The structure of an event (6) Multiple parton interactions (the “underlying event”) Filip Moortgat

12. The structure of an event (7) … with theirinitialand final state radiation Filip Moortgat

13. The structure of an event (8) Beam remnants and other outgoing partons Filip Moortgat

14. The structure of an event (9) Everything is connected through colour confinement strings Filip Moortgat

15. The structure of an event (10) The strings fragment to produce primary hadrons Filip Moortgat

16. The structure of an event (11) Many hadrons are unstable and decay further Filip Moortgat

17. The structure of an event (12) These are the particles that hit the detector Filip Moortgat

18. The Monte Carlo method Based on all our knowledge of particle physics, we want to generate events in as much detail as in nature ==> make random choices … ~ as in nature Filip Moortgat

19. Generator landscape PYTHIA HERWIG ALPGEN, Madgraph, CompHep, Helac, Phantom, Resbos, gg2WW, Charybdys, .. “specialized” often best at specific task, but need “general purpose” core Filip Moortgat

20. The hard process Lagrangian => Feynman rules => matrix elements => cross sections and kinematics : Filip Moortgat

21. Parton distribution functions Filip Moortgat

22. Parton distribution functions Filip Moortgat

23. Parton emission Probability that e+e- --> qq produces extra gluon ? rewrite ifo x3 and gq angle: Filip Moortgat

24. Parton emission (2) Filip Moortgat

25. DGLAP Filip Moortgat

26. Sudakov form factor Filip Moortgat

27. Sudakov form factor (2) Filip Moortgat

28. The parton shower approach Filip Moortgat

29. Note: time vs spacelike Filip Moortgat

30. Ordering variables for FSR Filip Moortgat

31. ME versus PS Filip Moortgat

32. Comparisons Filip Moortgat

33. PS versus ME Filip Moortgat

34. CKKW • The CKKW algorithm • Divide phase space into two regions: • Use matrix elements to describe the initial distribution of all particles having a separation larger than some minimum pT > pTcut • Modify it by “rejections” according to the parton shower  “unitarise” • Use parton showers for pT < pTcut • [W]ME |pT>pTcut* Wveto(pTcut)+ showeringpT<pTcut • [W + j]ME|pT>pTcut* Wveto(pTcut)+ showeringpT<pTcut • … • Wveto are there to kill the “double counting” • = the probability that no emission happened above pTcut • = the Sudakov factor (or the no-emission probability) Δ • SHERPA uses an analytical approximation • ARIADNE uses ‘trial’ or ‘pseudo’ showers (L-CKKW) • The “double counting” disappears since the events which would have caused it are exactly those which have emissions above pTcut Filip Moortgat

35. MLM • “MLM” matching • Simpler but similar in spirit to CKKW • First generate events the “stupid” way: • [W]ME+ showering • [W + jet]ME+ showering • … • a set of fully showered events, with double counting. To get rid of the excess, accept/reject each event based on: • (cone-)cluster showered event  njets • match partons from the ME to the clustered jets • If all partons are matched, keep event. Else discard it. • Roughly equivalent to the pseudoshower approach above • Virtue: can be done without knowledge of the internal workings of the generator. Only the fully showered final events are needed used by Alpgen and Madgraph Filip Moortgat

36. NLO calculations Filip Moortgat

37. MC@NLO • MC@NLO in comparison • Superior precision for total cross section • Equivalent to tree-level matching for event shapes (differences higher order) • Inferior to multi-jet matching for multijet topologies • So far has been using HERWIG parton shower  complicated subtractions Filip Moortgat

38. Hadronization/fragmentation Filip Moortgat

39. Hadronization (2) • LEP favours (slightly) the string picture. • Parameters have been tuned at LEP. • still many open questions: • LEP did not have color in the initial state ==> surprises at the LHC? • LEP did not have UE (see later), generating a large density • of strings • new phenomena? String interactions? Critical density? • LEP did not have the proton background • rescattering (Cronin effect)? Color wakefields? • Other coherence penomena Filip Moortgat

40. Different stages (1) Filip Moortgat

41. Different stages (2) Filip Moortgat

42. Decays Filip Moortgat

43. Multiple Interactions Filip Moortgat

44. Multiple Interactions Filip Moortgat

45. Multiple Interactions Filip Moortgat

46. Multiple Interactions Unlike pile-up, this is independent from the instantaneous luminosity! Filip Moortgat

47. MI, experimentally Without MI With MI Filip Moortgat

48. MI experimentally Double parton scattering Filip Moortgat

49. Understanding UE Filip Moortgat

50. Tuning the generators R. Field Filip Moortgat