Monte Carlo activities in ALICE

Transcription

1 Monte Carlo activities in ALICE status and prospects Jochen Klein for the ALICE Collaboration CERN 8th International Workshop on Multiple Partonic Interactions at the LHC San Cristóbal de las Casas, Chiapas, Mexico Nov 28 th Dec 2 nd, 26

2 overview ALICE overview what s special about ALICE? Monte Carlo motivation why ALICE can contribute? pp and p Pb results what is new from ALICE? towards Pb Pb how can we get more systematic in Pb Pb? summary and outlook how can we make further progress? taking Monte Carlo from pp to Pb Pb Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 2 / 9

3 ALICE detector Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 3 / 9

4 ALICE strengths charged particle tracking over wide p range ( MeV/c GeV/c) excellent particle identification over wide p range based on de/dx, time of flight, RICH; transition radiation and calorimetry for electron identification full event reconstruction in all available collision systems (pp, p Pb, Pb Pb) complementary to other LHC experiments, gives access to interesting realms of physics Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 4 / 9

5 challenging Monte Carlo implementations as experiment we must challenge the implementations of: underlying event multiplicity dependence rope hadronization colour reconnection collectivity in small systems microscopic origin? thermal model multi parton interactions transition from small to large systems experimental constraints interesting physics to be understood Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 5 / 9

6 underlying event (pp) traditional measurement of underlying event particle yield in regions w.r.t. trigger particle towards away transverse Underlying Event measurements with ALICE 7 η Φ) ev /(N N ch RAIO.6 oward Region φ < π/3 p >. GeV/c η < ALI-PUB-4979 ALICE pp at s = 7 ev Data (corrected) Pythia 6 - Perugia Pythia 8 - une Phojet leading p (GeV/c) [JHEP 27 (22) 6]!" systematic study at various energies on-going Fig. : Definition of the regions oward, ransverse and Away w.r.t. leading track direction. important baseline measurement average summed p density vs. leading track p,l: to be extended with identified particles Dh DF Nev(p,L) Â p(p,l) (2) Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 6 / 9

7 underlying event (pp) traditional measurement of underlying event particle yield in regions w.r.t. trigger particle towards away transverse Underlying Event measurements with ALICE 7 η Φ) ev /(N N ch RAIO.2 Away Region φ > 2π/3 p >. GeV/c η < ALI-PUB-4984 ALICE pp at s = 7 ev Data (corrected) Pythia 6 - Perugia Pythia 8 - une Phojet leading p (GeV/c) [JHEP 27 (22) 6]!" systematic study at various energies on-going Fig. : Definition of the regions oward, ransverse and Away w.r.t. leading track direction. important baseline measurement average summed p density vs. leading track p,l: to be extended with identified particles Dh DF Nev(p,L) Â p(p,l) (2) Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 6 / 9

8 underlying event (pp) traditional measurement of underlying event particle yield in regions w.r.t. trigger particle towards away transverse Underlying Event measurements with ALICE 7 η Φ) ev /(N N ch RAIO ALI-PUB-4982 ransverse Region π /3 < φ < 2π/3 p >. GeV/c η < ALICE pp at s = 7 ev Data (corrected) Pythia 6 - Perugia Pythia 8 - une Phojet leading p (GeV/c) [JHEP 27 (22) 6]!" systematic study at various energies on-going Fig. : Definition of the regions oward, ransverse and Away w.r.t. leading track direction. important baseline measurement average summed p density vs. leading track p,l: to be extended with identified particles Dh DF Nev(p,L) Â p(p,l) (2) Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 6 / 9

9 pseudo-rapidity density (pp) /dη ch dn 9 8 ALICE (INEL>) ALICE (INEL) CMS (INEL) EPOS LHC PYHIA 8 (Monash-23) PYHIA 6 (Perugia-2) pp s = 3 ev primary particles for INEL INEL > ( η < ) pp, s = 3 ev reasonable agreement with MC, but room for improvement enters other (more complex) measurements 2 2 η [PLB 753 (26) ] Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 7 / 9

10 p spectra (pp) c 2 ) -2 dη) (GeV N/(dp 2 ) d /(2πp /N ev MC / Data Data EPOS LHC PYHIA 8 (Monash-23) PYHIA 6 (Perugia-2) Data, systematic uncertainties ALICE, pp, s = 3 ev, INEL> charged particles, η < Data, combined uncertainties p (GeV/c) [PLB 753 (26) ] pp s = 3 ev INEL > ( η < ) Pythia and EPOS show common patterns of deviation multiplicity estimator: meas. N ch in same acceptance: η <,.5 < p < 2 GeV/c in multiplicity classes, ratio to INEL > Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 8 / 9

11 p spectra (pp) Ratio to INEL> ALICE, pp, s = 3 ev, charged particles, η < acc Data, N ch = 6.7, N acc acc N ch < N ch acc acc N ch acc N ch N 2 N = 9.4 (p ch acc < 2 N ch ch acc ch MC, selection on N ch EPOS LHC, N =. ch PYHIA 8 (Monash-23), N >.5 GeV/c) =. ch p (GeV/c) [PLB 753 (26) ] pp s = 3 ev INEL > ( η < ) Pythia and EPOS show common patterns of deviation multiplicity estimator: meas. N ch in same acceptance: η <,.5 < p < 2 GeV/c in multiplicity classes, ratio to INEL > Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 8 / 9

12 multiplicity-dependence of strangeness production (pp) Ratio of yields to (π +π + ) 2KS Λ+Λ ( 2) + Ξ +Ξ ( 6) measurement of multiplicity dependence of strange particle production ( y <.5) strangeness enhancement in pp! effect of strangeness (not mass) Pythia and EPOS are off 2 + Ω +Ω ( 6) DIPSY describes the trend 3 ALICE pp, s = 7 ev p-pb, s NN = 5.2 ev Pb-Pb, s NN = 2.76 ev PYHIA8 DIPSY EPOS LHC 2 dn /dη ch 3 η <.5 fundamental origin of strangeness enhancement not understood; only modelled by canonical suppression, core corona [ ] Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 9 / 9

13 centrality dependence of jet spectra (p Pb) Q ppb Q ppb ALICE p-pb s.8 NN = 5.2 ev FastJet anti-k jets, η <.5 lab.6 Reference: scaled pp jets 7 ev ALICE p-pb s.8 NN = 5.2 ev FastJet anti-k jets, η <.5 lab.6 Reference: scaled pp jets 7 ev Resolution parameter R =.4 Centrality classes (ZNA) -2% 2-4% 4-6% 6-8% 8-% Centrality classes (ZNA) -2% 2-4% 4-6% 6-8% 8-% Resolution parameter R = p (GeV/c), ch jet [EPJC 76 (26) 5, 27] p spectra for charged jets: anti-kt, η <.5, R =.4 (top), R = (bottom) dnppb c Q ppb := /dp Ncoll c dnc pp/dp centrality classes from zero-degree calorimetry, avoid dynamical bias for jets (i.e. hard production) no centrality dependence heavy-ion like behaviour suggested, but jet production not influenced Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 / 9

14 - ) - - ) multiplicity dependence of identified particles (p Pb) )/( π + + π + ( K + K ( p + p )/( π + + π ALICE VA class (Pb-side) -5% p-pb s NN = 5.2 ev % p-pb ALICE.5 VA class (Pb-side) -5% p-pb s NN = 5.2 ev % p-pb % p-pb INEL pp s = 7 ev -2% p-pb INEL pp s = 2.76 ev 4-6% p-pb 6-8% p-pb p (GeV/c) 5-% p-pb INEL pp s = 7 ev -2% p-pb INEL pp s = 2.76 ev % p-pb 6-8% p-pb particle ratios vs p : K/π (top) p/π (bottom) comparison to pp comparison to pp and Pb Pb Monte Carlo comparison needed p (GeV/c) [PLB 76 (26) ] Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 / 9

15 multiplicity dependence of identified particles (p Pb) Particle ratio ALICE.6 VA class (Pb-side) -5% p-pb = 5.2 ev.4 s NN - ( p + p )/( π + + π ) Pb-Pb 6-8% s NN = 2.76 ev INEL pp s = 7 ev ( K + K )/( π + + π ) p (GeV/c) [PLB 76 (26) ] particle ratios vs p : K/π (top) p/π (bottom) comparison to pp comparison to pp and Pb Pb Monte Carlo comparison needed Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 / 9

16 strangeness in jets (Pb Pb) (Λ + Λ)/2K S ALICE Preliminary Pb Pb, s NN = 2.76 ev, % jet,ch in jets, p > GeV/c jet,ch in jets, p > 2 GeV/c feed down uncertainty inclusive Λ/K, ALICE, S ( 5 %, y <.5) V (c/gev) ) dn/dp 2 /(N jets πr Pb Pb, s NN = 2.76 ev, % ALICE Preliminary Ks, stat. unc., (x.5) (Λ+Λ)/2, stat. unc. syst. unc. full markers Ks, (x.5) open markers (Λ+Λ)/2 PYHIA 8 tune Monash PYHIA 6 tune Perugia 2 PYHIA 6 tune Perugia NoCR jet jet p smeared with true σ (δp ) jet,ch p > GeV/c.6.4 η <.7 V anti k t, R = η <.5 jet,ch leading track p > 5 GeV/c track p > 5 MeV/c p (GeV/c) ALI PREL η V <.7 anti k t, R = η <.5 jet,ch leading track p > 5 GeV/c track p > 5 MeV/c ALI PREL 2798 measure strangeness in jets probe in-medium jet fragmentation Pythia as proxy for pp p (GeV/c ) Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 2 / 9

17 multi-strange baryons (pp, p Pb, Pb Pb) (h/π) / (h/π) high mult. limit HERMUS v2.3 =55 MeV bands: MeV V c = V γ S = µ = pp p-pb s Pb-Pb = 7 ev (. x-shift) s NN s NN = 5.2 ev = 2.76 ev 2 ALICE Λ/π Ξ/π Ω/π 3 - dn/dy(π + + π ) [PLB 758 (26) 389-4] strangeness enhancement as function of π ± multiplicity: Λ, Ξ, Ω allows us to compare collision systems compare to thermal model, here HERMUS trend is described linking pp, p Pb, Pb Pb Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 3 / 9

18 multiplicity dependence of correlations (pp, p Pb, Pb Pb) balance function (charge-dependent per-trigger yields): B( η, ϕ) = [ ] c(+, ) + c 2 (,+) c (+,+) c (, ) strong multiplicity dependence of width indicator for collectivity pp (-%) p Pb (-%) Pb Pb (-5%) < p < p < 2. GeV/c (i),assoc,trig < p < p < 2. GeV/c (h),assoc,trig < p < p < 2. GeV/c (g),assoc,trig ) B( ϕ ) (rad.5..5 ALICE PYHIA8 CR off PYHIA8 CR on ) B( ϕ ) (rad.5..5 ALICE AMP DPMJE ) B( ϕ ) (rad.3. ALICE AMP HIJING ϕ (rad) ϕ (rad) ϕ (rad) [EPJC 76 (26) 2, 86] Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 4 / 9

19 systematic comparisons: Monte Carlo vs. data learn from pp community: Rivet (Robust Independent Validation of Experiment and heory): generator-agnostic analysis framework, co-evolved with fastjet reads input from Monte Carlo generator runs one (or more) analyses on the input data produces plots corresponding to available measurements with comparison MC/data distributed with (validated) analyses and corresponding data make ALICE analyses available for Rivet in the following: preview of new analyses (more are in preparation) Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 5 / 9

20 π /η production (pp) Rivet analysis: submitted E d3 σ dp 3 (µb/(gev2 c 3 )) MC/Data 6 π invariant cross section at mid-rapidity at s = 7eV Data Pythia8 (Monash 23) p (GeV/c) [PLB 77 (22) 62-72] here comparison to: Pythia 8 (Monash tune) trend looks good, but overall yield is off also ratio slightly off ) c 3 2 (pb GeV σ 3 d 3 E dp NLO fit x x 3 x σ pp uncertainty 7 ev ± ev + 5.%, 3.9% combined Spec. fit combined NLO µ=.5 p t NLO µ= p t NLO µ= 2 p t NLO µ= 2 p (BKK) t s = 7 ev syst, stat s =.9 ev syst, stat a) s = 7 ev syst, stat 3.5 Jochen Klein (CERN) 3. b) Monte Carlo activities in 2.5 ALICE LHC, Nov/Dec 26 6 / 9

21 π /η production (pp) Rivet analysis: submitted η/π η/π ratio at s = 7eV Data Pythia8 (Monash 23) η/π MC/Data p (GeV/c) [PLB 77 (22) 62-72] here comparison to: Pythia 8 (Monash tune) trend looks good, but overall yield is off also ratio slightly off stat + syst, PCM, s = 7 ev NLO µ =.5 p t NLO µ = p t NLO µ = 2 p t (GeV/c) p t Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 6 / 9

22 Jet cross section (pp) Rivet analysis: under validation d 2 σ/dp dη (mb c/gev) MC/Data anti-kt jets R =.4 Data Pythia 6 (Perugia 2) Pythia 6 (Perugia 2) p (GeV/c) [PLB 722 (23) ] dη (mb c/gev) σ/dp 2 d NLO/data NLO/data anti k, R =.4, η <.5 NLO (N. Armesto) NLO (G. Soyez) ALICE pp s = 2.76 ev: L int Systematic uncertainty = 3.6 nb NLO + Hadronization (G. Soyez) p,jet (GeV/c) p -differential jet cross section (here: anti-kt R =.4) good agreement with Pythia 6 Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 7 / 9

23 towards heavy-ion physics availability of Rivet analyses allows for automatized creation of comparison plots exploiting large number of generators and tunes mcplots project hosted at CERN to generate events (batch system and voluntary computing) run analyses provide interface to plot comparison of selected generators/tunes to data heavy-ion challenges: additional classification, e.g. centrality post-processing, e.g. division of Pb Pb and pp samples computing resources for Pb Pb generation project on heavy-ion extensions to Rivet and mcplots started efforts started in ALICE to extend tools to heavy-ion use cases Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 8 / 9

24 summary & prospects broad and diverse set of measurements needed for Monte Carlo development and tuning ALICE covers interesting and complementary aspects in order to constrain models improving tools for comparisons also for heavy-ions learn from pp community project started in ALICE more systematic comparisons ALICE ramping up Monte Carlo activities ALICE can provide important input for MC data for pp, p Pb, Pb Pb at various energies Jochen Klein (CERN) Monte Carlo activities in ALICE LHC, Nov/Dec 26 9 / 9