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L e s s o n s f ro m t h e e a r ly L H C d a t a fo r M C t - PowerPoint PPT Presentation

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L e s s o n s f ro m t h e e a r ly L H C d a t a fo r M C t u n i n g P. S k a n d s ( C E R N ) M u l t i p l e P a r t o n i c I n t e r a c t i o n s a t L H C , N o v e m b e r 2 0 1 1 , H a m b u r g A Factorized View 1.

  1. L e s s o n s f ro m t h e e a r ly L H C d a t a fo r M C t u n i n g P. S k a n d s ( C E R N ) M u l t i p l e P a r t o n i c I n t e r a c t i o n s a t L H C , N o v e m b e r 2 0 1 1 , H a m b u r g

  2. A Factorized View 1. Where is the energy going? Note: only linearized Sphericity is IR safe IR Safe Sum(pT) densities, event shapes, mini-jet rates, ctrl&fwd energy flow, energy correlations… ≈ sensitive to pQCD + pMPI 2. How many tracks is it divided onto? N tracks , dN tracks /dp T, Associated track densities, track correlations… ≈ sensitive to hadronization + soft MPI IR Sensitive 3. Are there gaps in it? Created by diffraction (and color reconnections?). Destroyed by UE. More IR 4. What kind of tracks? Sensitive Strangeness per track, baryons per track, baryon asymmetry, … hadron-hadron correlations ≈ sensitive to details of hadronization + collective effects (+Quarkonium sensitive to color reconnections?) P . Skands - Lessons from Early LHC data … 2

  3. PYTHIA Models LHC data 2002 2006 2008 2009 2010 2011 Tune S0 ATLAS MC09 S…-Pro AMBT1 AUET2B? p T -ordered PYTHIA 6 Tune S0A Perugia 0 Z1, Z2 Perugia 2011 (+ Variations) Perugia 2010 (+ Variations) D…-Pro Pro-Q2O DW(T) Tune A Q-ordered PYTHIA 6 Q2-LHC ? D6(T) (default) 4C, 4Cx 2C p T -ordered PYTHIA 8 A1, AU1 Tune 1 2M A2, AU2 Note: tunes differ significantly in which data sets they include LEP fragmentation parameters Level of Underlying Event & Minimum-bias Tails Soft part of Drell-Yan p T spectrum P . Skands - Lessons from Early LHC data … 3

  4. PYTHIA Models LHC data 2002 2006 2008 2009 2010 2011 Tune S0 ATLAS MC09 S…-Pro AMBT1 AUET2B? p T -ordered PYTHIA 6 Tune S0A Perugia 0 Z1, Z2 Perugia 2011 (+ Variations) Perugia 2010 (+ Variations) D…-Pro Pro-Q2O DW(T) Tune A Q-ordered PYTHIA 6 (default) D6(T) Q2-LHC ? 4C, 4Cx 2C p T -ordered PYTHIA 8 A1, AU1 Tune 1 2M A2, AU2 Main Data Sets included in each Tune (no guarantee that all subsets ok) DW, Pro-…, Perugia Perugia Perugia AUET2B, A S0, S0A MC09(c) AMBT1 Z1, Z2 4C, 4Cx D6, ... 0, Tune 1, 2C, 2M 2010 2011 A2, AU2 LEP ✔ ✔ ✔ ✔ ✔ TeV MB ✔ ✔ ( ✔ ) ? ✔ ✔ ✔ TeV UE ✔ ( ✔ ) ✔ ? ✔ ✔ ✔ ✔ ✔ TeV DY ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ LHC MB ? ✔ ✔ ✔ ✔ LHC UE ✔ ✔ ✔ P . Skands - Lessons from Early LHC data … 4

  5. PYTHIA Models LHC data 2002 2006 2008 2009 2010 2011 Tune S0 ATLAS MC09 S…-Pro AMBT1 AUET2B? p T -ordered PYTHIA 6 Tune S0A Perugia 0 Z1, Z2 Perugia 2011 (+ Variations) Perugia 2010 (+ Variations) D…-Pro Pro-Q2O DW(T) Tune A Q-ordered PYTHIA 6 (default) D6(T) Q2-LHC ? 4C, 4Cx 2C p T -ordered PYTHIA 8 A1, AU1 Tune 1 2M A2, AU2 Main Data Sets included in each Tune (no guarantee that all subsets ok) DW, Pro-…, Perugia Perugia Perugia AUET2B, A S0, S0A MC09(c) AMBT1 Z1, Z2 4C, 4Cx (default) D6, ... 0, Tune 1, 2C, 2M 2010 2011 A2, AU2 LEP ✔ ✔ ✔ ✔ ✔ TeV MB ✔ ✔ ( ✔ ) ? ✔ ✔ ✔ TeV UE ✔ ( ✔ ) ✔ ? ✔ ✔ ✔ ✔ ✔ TeV DY ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ LHC MB ? ✔ ✔ ✔ ✔ LHC UE ✔ ✔ ✔ P . Skands - Lessons from Early LHC data … 5

  6. What Works * *) if you use an up-to-date tune. Here comparing to PY6 default (~ Tune A) to show changes. Underlying Event & Jet Shapes ∆φ Jet Shape p Tlead > 5 GeV UE 30 < p T < 40, All y (softest jet bin available) Σ p T (TRNS) PS: yes, we should update the PYTHIA 6 defaults ... P . Skands - Lessons from Early LHC data … Plots from mcplots.cern.ch 6

  7. What Works * *) if you use an up-to-date tune. Here comparing to PY6 default (~ Tune A) to show changes. Drell-Yan p T (Normalized to Unity) Apologies: we don’t have DY measurements from LHC on the mcplots site yet d σ d σ / σ φ * (no K-factor) (norm to unity) (norm to unity) PS: yes, we should update the PYTHIA 6 defaults ... P . Skands - Lessons from Early LHC data … Plots from mcplots.cern.ch 7

  8. What Kind of Works * *) if you use an up-to-date tune. Here comparing to PY6 default (~ Tune A) to show changes. Minimum-Bias Multiplicities (here showing as inclusive as possible) η distribution Forward-Backward Charged Correlation (UA5) Multiplicity Hoping for LHC measurements soon Distribution See Wraight + PS, EPJC71(2011)1628 Central LHC ALICE Detectors FMD PS: yes, we should update the PYTHIA 6 defaults ... P . Skands - Lessons from Early LHC data … Plots from mcplots.cern.ch 8

  9. What Doesn’t Work p T Spectra (in particular mass dependence) Strange and baryon production Structure of very soft events Very high-multiplicity events (CMS ridge) (No time to address here, plus no good model yet) Diffraction and forward energy (will return to diffraction on Friday) P . Skands - Lessons from Early LHC data … 9

  10. Organized Tuning Can we be more general than this- tune-does-this, that-tune-does-that? Yes Schulz & PS , Eur.Phys.J. C71 (2011) 1644 The new automated tuning tools can be used to generate unbiased optimizations for different observable regions Same parameters → consistent model (not just “best tune”) Critical for this task (take home message): Need “comparable” observable sets for each region Example: test ENERGY SCALING of MB: use different collider energies as “regions” (Other complementary data sets could be used to test other model aspects) P . Skands 10

  11. Tuning vs Testing Models Evolution of PARP(83) with √ s Pythia 6 TEST models PARP(83) 7 TeV PARP(83) Gauss 2 Tune parameters in several Perugia 0 900 GeV 1800 & complementary regions 1960 GeV 1.5 630 GeV Consistent model → same Exponential 1 parameters Transverse Mass 0.5 Distribution Model breakdown → non- 0 universal parameters 10 3 √ s / GeV √ Evolution of PARP(82) with √ s Evolution of PARP(78) with √ s Pythia 6 Pythia 6 3 PARP(82) PARP(78) PARP(82) PARP(78) 0.5 Perugia 0 Exp=0.25 2.5 7 TeV 630 GeV 1800 & 1960 GeV dˆ p 4 ∝ σ 0.4 ⊥ � d p 2 2 � 900 GeV ⊥ Perugia 0 E CM � 630 GeV pendence E ref 0.3 ⊥ 0 × p ⊥ 0 ( E CM ) = p ref 900 GeV CM 1.5 1800 & 7 TeV 1960 GeV erlap which determines level of in impact-parameter space 0.2 1 Color Reconnection IR Regularization See also Rick Field’s talk, p.31 ariants 0.1 Strength 0.5 PDF 0 0 10 3 10 3 √ s / GeV √ s / GeV √ “Energy Scaling of MB Tunes”, H. Schulz + PS, Eur.Phys.J. C71 (2011) 1644 √ P . Skands - Lessons from Early LHC data … 11

  12. Tuning vs Testing Models Evolution of PARP(83) with √ s Pythia 6 TEST models PARP(83) 7 TeV PARP(83) Gauss 2 Tune parameters in several Perugia 0 900 GeV 1800 & complementary regions 1960 GeV 1.5 630 GeV Consistent model → same Exponential 1 parameters Transverse Mass 0.5 Distribution Model breakdown → non- 0 universal parameters 10 3 √ s / GeV √ Evolution of PARP(82) with √ s Evolution of PARP(78) with √ s Pythia 6 Pythia 6 3 PARP(82) PARP(78) PARP(82) PARP(78) 0.5 Perugia 0 Exp=0.25 2.5 7 TeV 630 GeV 1800 & 1960 GeV dˆ p 4 ∝ σ 0.4 ⊥ � d p 2 2 � 900 GeV ⊥ Perugia 0 E CM � 630 GeV pendence E ref 0.3 ⊥ 0 × p ⊥ 0 ( E CM ) = p ref 900 GeV CM 1.5 1800 & 7 TeV 1960 GeV erlap which determines level of in impact-parameter space 0.2 1 Color Reconnection IR Regularization See also Rick Field’s talk, p.31 ariants 0.1 Strength 0.5 PDF 0 0 10 3 10 3 √ s / GeV √ s / GeV √ “Energy Scaling of MB Tunes”, H. Schulz + PS, Eur.Phys.J. C71 (2011) 1644 √ P . Skands - Lessons from Early LHC data … 11

  13. pT Spectra / Mass Dependence Must be compared with LEP SOFT SOFT OPAL ALEPH HARD HARD all charged ~ pions Λ baryons STAR: 200 GeV Pions can only be made harder STAR measurement Average pT versus particle mass Model predict too hard Pions and too soft massive particles Massive particles can only be made softer! So : tuning problem? or physics problem? Will return on Friday P . Skands - Lessons from Early LHC data … Plots from mcplots.cern.ch 12

  14. Strangeness and Baryons Tried to learn from early data, but still not there … Λ /K Again, quite difficult to adjust flavor parameters while remaining within LEP bounds … P . Skands - Lessons from Early LHC data … Plots from mcplots.cern.ch 13

  15. Very Soft Structure Minimum-Bias too lumpy? Underlying Event ok? p TLead > 1 p TLead > 5 P . Skands - Lessons from Early LHC data … Plots from mcplots.cern.ch 14

  16. Summary How did the models fare? Lots could be said… Bottom line: Not too bad on averages See also talks by Rick Field and others E.g., UE level underpredicted by ~ 10-20% relative to Tevatron tunes (I won my bet!) Significant discrepancies on more exclusive physics Strangeness, Baryons, and Baryon Transport More tuning? LEP or “new” physics? p T spectra High-multiplicity tail (+ridge!) → needs more study! Forward measurements and Diffraction No single model/tune does it all … (game still open) P . Skands - Lessons from Early LHC data … 15

  17. Diffraction Framework needs testing and tuning E.g., interplay between non-diffractive and diffractive components + LEP tuning used directly for diffractive modeling Hadronization preceded by shower at LEP, but not in diffraction → dedicated diffraction tuning of fragmentation pars? Study this bump + Room for new models, e.g., KMR (SHERPA) Others? 16 P. Skands

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