Precision RENORM / MBR Predictions for Diffraction at LHC

Transcription

1 Precision RENORM / MBR Predictions for Diffraction at LHC Konstantin Goulianos Precision predictions? Wow! 1

2 Basic and combined diffractive CONTENTS processes Diffraction SD1 p 1 p 2 p 1 +gap+x 2 Single Diffraction / Dissociation 1 SD2 p 1 p 2 X 1 +gap+p 2 Single Diffraction / Dissociation - 2 DD p 1 p 2 X 1 +gap+x 2 Double Diffraction / Double Dissociation CD/DPE p 1 p 2 gap+x+gap Central Diffraction / Double Pomeron Exchange Renormalization Unitarization RENORM Model Triple-Pomeron Coupling: unambiguously determined Total Cross Section: Unique prediction based on saturation and a tensor glue ball approach References Previous talks: LHCFPWG 2015 Madrid (21-25 Apr 2015) EDS BLOIS 2015 Borgo, Corsica, France 29 Jun-4 Jul, MBR MC Simulation in PYTHIA8, KG & R. Ciesielski, Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 2

3 Basic and combined diffractive RENORM: Basic and Combined Diffractive Processes processes particles gap rapidity distributions DD SD SD DD Cross sections analytically expressed in arxiv below: 4-gap diffractive process-snowmass Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 3

4 Regge Theory: Values of s o & g PPP? KG-PLB 358, 379 (1995) α(t)=α(0)+α t α(0)=1+ε Parameters: s 0, s 0 ' and g(t) set s 0 ' = s 0 (universal Pomeron) determine s 0 and g PPP how? Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 4

5 RENORM predictions for diffraction at LHC confirmed Theoretical A complicatiion Complication: Unitarity! σ sd grows faster than σ t as s increases * unitarity violation at high s (also true for partial x-sections in impact parameter space) the unitarity limit is already reached at s ~ 2 TeV! need unitarization * similarly for (dσ el /dt) t=0 w.r.t. σ t, but this is handled differently in RENORM Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 5

6 FACTORIZATION BREAKING IN SOFT DIFFRACTION Diffractive x-section suppressed relative to Regge prediction as s increases p p ξ,t p M Factor of ~8 (~5) suppression at s = 1800 (540) GeV RENORMALIZATION s=22 GeV 540 GeV C D F KG, PLB 358, 379 (1995) 1800 GeV Interpret flux as gap formation probability that saturates when it reaches unity Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 6

7 Single Diffraction Renormalized - 1 KG CORFU-2001: t y y 2 independent variables: d dt t, y 2 σ 2 2 = C Fp ( t) d y gap probability color factor g ( ) = IP IP IP t κ β (0) IP p p { ( ε + α t ) y} { ε y e κ σ e } o sub-energy x-section 0.17 Gap probability (re)normalize it to unity Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 7

8 Single Diffraction Renormalized - 2 color factor κ = g IP IP IP( t) β (0) IP p p 0.17 Experimentally: KG&JM, PRD 59 (114017) 1999 κ = g IP IP IP β IP p = 0.17 ± 0.02, ε = QCD: κ = 1 1 Q f f = g = 2 q N 1 N 8 3 c c 0.18 Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 8

9 Single Diffraction Renormalized - 3 σ sd s ~ b ln s ln s const set to unity determines s o Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 9

10 M 2 - Distribution: Data M2 distribution: data dσ/dm 2 t=-0.05 ~ independent of s over 6 orders of magnitude! KG&JM, PRD 59 (1999) dσ dm Regge data 2 s 2ε 2 1+ ε (M ) 1 ε factorization breaks down to ensure M 2 scaling Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 10

11 Scale s 0 and PPP Coupling Pomeron flux: interpret it as gap probability set to unity: determines g PPP and s 0 KG, PLB 358 (1995) d σ dtdξ SD = ε s o Pomeron-proton x-section f IP/p (t,ξ) σ ( t) Two free parameters: s o and g PPP Obtain product g PPP s o ε / 2 from σ SD Renormalized Pomeron flux determines s o Get unique solution for g PPP s IP/p ε /2 o (sξ) g PPP Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 11

12 DD at CDF gap probability x-section Regge Renor d x-section divided by integrated gap prob. Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 12

13 SDD at CDF Excellent agreement between data and MBR (MinBiasRockefeller) MC Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 13

14 CD/DPE at CDF Excellent agreement between data and MBR based MC Confirmation that both low and high mass x-sections are correctly implemented Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 14

15 RENORM Difractive Cross Sections α 1 =0.9, α 2 =0.1, b 1 =4.6 GeV -2, b 2 =0.6 GeV -2, s =s e - y, κ=0.17, κβ 2 (0)=σ 0, s 0 =1 GeV 2, σ 0 =2.82 mb or 7.25 GeV -2 Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 15

16 Total, Elastic, and Inelastic x-sections CMG KG MORIOND GeV 2 σ el p±p =σ tot p±p (σ el /σ tot ) p±p, with σ el /σ tot from CMG small extrapolation from 1.8 to 7 and up to 50 TeV Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 16

17 The total x-section 2009 s F =22 GeV 98 ± 8 mb at 7 TeV 109 ±12 mb at 14 TeV Uncertainty is due to s 0 Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 17

18 TOTEM (2012) vs PYTHIA8-MBR MBR: 71.1±5 mb superball ±1.2 mb NBR errors reduced by 75% by using data on exclusive π ± production from the AFS at the ISR ( next slides) σ 7 TeV inel = 72.9 ±1.5 mb σ 8 TeV inel = 74.7 ±1.7 mb TOTEM, G. Latino talk at MPI@LHC, CERN 2012 RENORM: 71.1±1.2 mb RENORM: 72.3±1.2 mb Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 18

19 ATLAS - in Diffraction 2014 (Talk by Marek Taševský, slide#19 RENORM: 98.0±1.2 mb Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 19

20 Reduce Uncertainty in s Amplitude 2 (arbitrary units) Review of CEP by Albrow, Coughlin, Forshaw Fig. from Axial Field Spectrometer at the CERN Intersecting Storage Rings 20% increase in s o x-sections decrease Data: Peter C. Cesil, AFS thesis (courtesy Mike Albrow) analysis: S and D waves Conjecture: tensor glue ball (spin 2) Fit: Gaussian <M tgb >= s 0 =2.10±0.68 GeV s 0 =4.42±0.34 GeV 2 Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 20

21 Reduced Uncertainty in s 0 Energy Total Elastic Inelastic MBR Exp 7 TeV 95.4± ± ±1.0 MBR 98.4± ±3.4 TOTEM 95.35± ± ±0.90 ATLAS CMS 8 TeV 97.1± ± ±1.0 MBR 101.7± ± ±1.7 TOTEM 73. 1±0.9±0.9syst±3.3extr (this conference) ATLAS CMS 13 TeV 103.7± ± ±1.3 MBR Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 21

22 The CMS Detector CD DD SD ND CASTOR forward calorimeter: important for separating SD from DD contributions Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 22

23 CMS Data vs MC Models (2015)-1 SD dominated data DD dominated data Error bars are dominated by systematics DD data scaled downward by 15% (within MBR and CDF data errors) PYTHIA8-MBR is the only model that describes well both the SD and DD data Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 23

24 CMS Data vs MC Models (2015) -2 Central η-gap x-sections (DD dominated) P8-MBR provides the best fit to the data All other models too low at small η Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 24

25 SD Extrapolation to ξ x 0.05 vs MC Model P8-MBR describes the normalization and shape of the CMS data and is used to extrapolate to the unmeasured regions to obtain σ SD for ξ<0.05 Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 25

26 p T Distr s of MCs vs Pythia8 Tuned to MBR Pythia8 tuned to MBR COLUMNS Mass Regions Low 5.5<MX<10 GeV Med. 32<MX<56 GeV High 176<MX<316 GeV CONCLUSION PYTHIA8-MBR agrees best with the reference model and is used by CMS in extrapolating to the unmeasured regions. ROWS MC Models PYTHIA8-MBR PYTHIA8-4C PYTHIA6-Z2* PHOJET QGSJET-II-03 QGSJET-04 EPOS-LHC Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 26

27 Charged Mult s vs MC Model 3 Mass Regions Pythia8 parameters tuned to reproduce multiplicities of modified gamma distribution (MGD) KG, PLB 193, 151 (1987) Mass Regions Low 5.5<MX<10 GeV Med. 32<MX<56 GeV High 176<MX<316 GeV CERN ISR 52.6 GeV SppS GeV Diffractive data vs MGD - CERN ISR & SppS w/mgd fit 0 < p T < 1.4 GeV Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 27

28 Pythia8-MBR Hadronization Tune Diffraction: tune SigmaPomP n ave = σ QCD σ IPp Diffraction: QuarkNorm/Power parameter P P ( q) ( g) = probpickquark probpickquark +1 1 = probpickquark + 1 PYTHIA8 default σ Pp (s) expected from Regge phenomenology for s 0 =1 GeV 2 and DL t-dependence. Red line:-best fit to multiplicity distributions. (in bins of Mx, fits to higher tails only, default pt spectra) good description of low multiplicity tails Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 28

29 SD and DD x-sections vs Models Single Diffraction Double Diffraction Includes ND background Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 29

30 CMS vs MC & ATLAS Uncorrected Δη F distribution vs MCs Stable-particle x-sections for pt>200 MeV and η <4.7 compared to the ATLAS 2012 result similar result Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 30

31 Monte Carlo Algorithm - Nesting Profile of a pp Inelastic Collision no gap final state of MC w /no-gaps gap t y' c ln s = y y > y' min gap gap gap t t t 1 t 2 evolve every cluster similarly y < y' min generate central gap hadronize repeat until y' < y' min Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 31

32 SUMMARY Introduction Review of RENORM predictions of diffractive physics basic processes: SD1,SD2, DD, CD (DPE) combined processes: multigap x-sections ND no diffractive gaps this is the only final state to be tuned Monte Carlo strategy for the LHC nesting Updated RENORM parameters Good agreement with existing measurements Predictions of cross sections at 13 TeV Thanks to Robert A. Ciesielski, my collaborator in the PYTHIA8-MBR project Thank you for your attention! Precision RENORM/NBR Predictions for Diffraction at LHC K.Goulianos 32