Diffraction Results at LHC: Solving a Puzzle Using Precision RENORM Predictions

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Diffraction Results at LHC: Solving a Puzzle Using Precision RENORM Predictions Konstantin Goulianos The Rockefeller University http://physics.rockefeller.edu/dino/my.html https://www.brown.edu/conference/15th-workshop-non-perturbative-quantum-chromodynamics/ Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 1

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 g. PPP Triple-Pomeron Coupling: unambiguously determined Total Cross Section: Unique prediction, based on a spin-2 tensor glue-ball model References MBR MC Simulation in PYTHIA8, KG & R. Ciesielski, http://arxiv.org/abs/1205.1446 MIAMI-2017, Dec. 13-19, https://cgc.physics.miami.edu/miami2017/goulianos2017.pdf EDS BLOIS 2015 Borgo, Corsica, France Jun 29-Jul 4, https://indico.cern.ch/event/362991/ KG, Updated RENORM/MBR-model Predictions for Diffraction at the LHC, http://dx.doi.org/10.5506/aphyspolbsupp.8.783 Moriond QCD 2016, La Thuile, Italy, March 19-26, http://moriond.in2p3.fr/qcd/2016/ NPQCD16, Paris, June, https://www.brown.edu/conference/14th-workshop-non-perturbative-quantum-chromodynamics/ DIFFRACTION 2016, Catania, Sep.2-8 2016 https://agenda.infn.it/conferencedisplay.py?confid=10935 σ tot similar talk Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 2

Basic and combined diffractive RENORM: Basic and Combined Diffractive Processes processes particles gap rapidity distributions DD SD SD DD 4-gap diffractive processes-snowmass 2001 Cross sections analytically expressed in arxiv:: http://arxiv.org/abs/hep-ph/0110240 Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 3

Regge Theory: Values of s o & g PPP? KG-PLB 358, 379 (1995) http://www.sciencedirect.com/science/article/pii/037026939501023j 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? Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 4

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 Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 5

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 http://www.sciencedirect.com/science/article/pii/037026939501023j Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 6

Single Diffraction Renormalized - 1 KG CORFU-2001 http://arxiv.org/abs/hep-ph/0203141 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 Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 7

Single Diffraction Renormalized - 2 color factor κ = g IP IP IP( t) β (0) IP p p 0.17 Experimentally κ = g IP IP IP β IP p KG&JM, PRD 59 (114017) 1999 http://dx.doi.org/10.1103/physrevd.59.114017 = 0.17 ± 0.02, ε = 0.104 1 1 Q 2 1 1 1 QCD: κ = f f = g + 0.75 + 0.25 = 0. 18 2 q N 1 N 8 3 c c Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 8

Single Diffraction Renormalized - 3 affects only the s-dependence σ sd s ~ b ln s ln s const set N(s,s o ) to unity determines s o Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 9

M 2 - Distribution: Data M2 distribution: data dσ/dm 2 t=-0.05 ~ independent of s over 6 orders of magnitude! http://physics.rockefeller.edu/publications.html KG&JM, PRD 59 (1999) 114017 http://dx.doi.org/10.1103/physrevd.59.114017 dσ dm Regge data 2 s 2ε 2 1+ ε (M ) 1 ε factorization breaks down to ensure M 2 -scaling Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 10

Scale s 0 and PPP Coupling Pomeron flux: interpreted as gap probability set to unity: determines g PPP and s 0 KG, PLB 358 (1995) 379 2 d σ dtdξ http://www.sciencedirect.com/science/article/pii/037026939501023j 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 Renormalize Pomeron flux: determines s o Get unique solution for g PPP s IP/p ε /2 o (sξ) g PPP Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 11

http://physics.rockefeller.edu/publications.html http://dx.doi.org/10.1103/physrevlett.87.141802 DD at CDF Regge factorization gap probability x-section Regge Regge RENORM x-section divided by integrated gap prob. Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 12

SDD at CDF http://physics.rockefeller.edu/publications.html http://journals.aps.org/prl/abstract/10.1103/physrevlett.91.011802 Excellent agreement between data and MBR (MinBiasRockefeller) MC Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 13

CD/DPE at CDF http://journals.aps.org/prl/abstract/10.1103/physrevlett.91.011802 Excellent agreement between data and MBR-based MC Confirmation that both low and high mass x-sections are correctly implemented Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 14

RENORM Difractive Cross Sections MBR MC Simulation in PYTHIA8 http://arxiv.org/abs/1205.1446 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 (units)=1gev 2, σ 0 =2.82 mb or7.25 GeV -2 Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 15

Total, Elastic, and Total Inelastic x-sections CMG PLB 389, 196 (1996) http://www.sciencedirect.com/science/article/pii/s0370269396013627 KG MORIOND-2011 http://moriond.in2p3.fr/qcd/2011/proceedings/goulianos.pdf 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 Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 16

http://eds09.web.cern.ch/eds09/ The total x-section 2009 CERN s F =22 GeV (see Fig.) CMG 98 ± 8 mb at 7 TeV 109 ±12 mb at 14 TeV Uncertainty is due to s o Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 17

2015 Reduce Uncertainty in s 0 http://workshops.ift.uam-csic.es/lhcfpwg2015/program EDS 2015: http://dx.doi.org/10.5506/aphyspolbsupp.8.783 Amplitude 2 (arbitrary units) 2.10 GeV ± 0.68 Review of CEP by Albrow, Coughlin, Forshaw http://arxiv.org/abs/1006.1289 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 Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 18

Predictions vs Measurements with /reduced Uncertainty in s o From my Moriond-2016 Talk s MBR/Exp σ tot σ el σ inel 7 TeV MBR 95.4±1.2 26.4±0.3 69.0±1.0 TOTEM totem-lumind 98.3±0.2±2.8 98.0±2.5 24.8±0.2±1.2 25.2±1.1 73.7±3.4 72.9±1.5 ATLAS 95.35±1.36 24.00±0.60 71.34±0.90 8 TeV MBR 97.1±1.4 27.2±0.4 69.9±1.0 TOTEM 101.7±2.9 27.1±1.4 74.7±1.7 13 TeV MBR 103.7±1.9 30.2±0.8 73.5±1.3 ATLAS RENORM/MBR with a tensor-pomeron model predicts measured cross sections to the 1% level Test of RENORM/MBR: ATLAS results using the ALFA and RP detectors to measure the cross sections Stay tuned! Totem 7 TeV http://arxiv.org/abs/1204.5689 Totem-Lum-Ind 7 TeV http://iopscience.iop.org/article/10.1209/0295-5075/101/21004 Atlas 7 TeV: http://arxiv.org/abs/1408.5778 Totem 8 TeV http://dx.doi.org/10.1103/physrevlett.111.012001 Atlas13 TeV Aspen 2016 Doug Schafer https://indico.cern.ch/event/473000/timetable/#all.detailed Atlas/Totem 13TeV DIS15 https://indico.desy.de/contributiondisplay.py?contribid=330&confid=12482 Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 19

Predictions vs Measurements w /reduced Uncertainty in s o #1 Slide from my ICNFP-2016 Talk s MBR/Exp Reference next slide ICNFP 2016 s tot s el S inel 7 TeV MBR 95.4±1.2 26.4±0.3 69.0±1.0 ATLAS 1 95.35±1.36 24.00±0.60 71.34±0.90 TOTEM 2 101.7±2.9 27.1±1.4 74.7±1.7 TOTEM_Lum_Ind 3 98.0±2.5 24.00±0.60 72.9±1.5 8 TeV MBR 97.1±1.4 27.2±0.4 69.9±1.0 TOTEM 4 101.7±2.9 27.1±1.4 74.7±1.7 13 TeV MBR 103.7±1.9 30.2±0.8 73.5±1.3 ATLAS 5 & 6 73.1±0.9 (exp) ±6.6 (lumi) ±3.8 (extr) CMS 7 71.3±0.5 (exp) ±2.1 (lumi) ±2.7 (extr) CONT Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 20

Predictions vs Measurements w /reduced Uncertainty in s o #2 Caveat (slide from my ICNFP-2016 talk) The MBR σ el is larger than the ATLAS and the TOTEM_lum_Ind measurements by ~2 mb at s=7 TeV, which might imply a higher MBR prediction at s=13 TeV by 2-3 mb. Lowering the MBR σ el prediction would lead to a larger σ inel.this interplay between σ el and σ inel should be kept in mind as more results of σ el and σ tot at s = 13 TeV become available. RENORM/MBR with a tensor-pomeron model predicts measured cross sections to the 1% level Test of RENORM/MBR: ATLAS results using the ALFA and RP detectors to measure the cross sections Stay tuned! 1) Atlas 7 TeV: http://arxiv.org/abs/1408.5778 2) Totem 7 TeV http://arxiv.org/abs/1204.5689 3) Totem-Lum-Ind 7 TeV http://iopscience.iop.org/article/10.1209/0295-5075/101/21004 4) Totem 8 TeV http://dx.doi.org/10.1103/physrevlett.111.012001 5) Atlas13 TeV Aspen 2016 D. Schafer https://indico.cern.ch/event/473000/timetable/#all.detailed 6) Atlas 13TeV DIS-2016 M. Trzebinski ttps://indico.desy.de/contributiondisplay.py?contribid=330&confid=12482 7) CMS 13TeV DIS-2016 H. Van Haevermaet https://indico.desy.de/contributiondisplay.py?contribid=105&confid=12482 Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 21

MBR vs. ICHEP 2016 cross-section results s MBR/Exp Ref. # cf. slide19 σ tot σ el σ inel 7 TeV MBR 95.4±1.2 26.4±0.3 69.0±1.0 ATLAS 1 95.35±1.36 24.00±0.60 71.34±0.90 TOTEM 2 101.7±2.9 27.1±1.4 74.7±1.7 TOTEM_Lum_Ind 3 98.0±2.5 24.00±0.60 72.9±1.5 8TeV MBR 97.1±1.4 27.2±0.4 69.9±1.0 ATLAS vs. MBR in excellent agreement at 8 TeV TOTEM ATLAS-ALFA fit 4 ICHEP16 101.7±2.9 96.1±0.9 27.1±1.4 24.3±0.4 74.7±1.7 13 TeV MBR 103.7±1.9 30.2±0.8 73.5±1.3 ATLAS ALFA-fit-result 5 & 6 ICHEP16 73.1±0.9 (exp) ±6.6 (lumi) ±3.8 (extr) 79.3±0.6(exp) ±1.3(lumi) ±2.5(extr) CMS 7+ICHEP16 71.3±0.5 (exp) ±2.1 (lumi) ±2.7 (extr) Tomáš Sýkora, ICHEP16 x-sections summary talk http://ichep2016.org/ At 13 TeV MBR is happy between the ATLAS and CMS ICHEP results awaiting settlement between the two experiments keep tuned! Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 22

MBR vs. ICHEP 2016 cross-sections Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 23

DIS-2017: MBR vs. TOTEM @ 2.76 TeV https://indico.cern.ch/event/568360/ (from talk by Frigyes Nemes, slide #20) TOTEM σ tot σ el σ inel [mb] [mb] [mb] 84.7 ± 3.3 21.8 ± 1.4 62.8 ± 2.9 MBR 85.2 21.7 63.5 Syst. Uncertainty ~1.5% due to that in s 0 Excellent agreement between TOTEM and MBR at 2.76 TeV Awaiting forthcoming results at 13 TeV from ATLAS, CMS, TOTEM Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 24

LHCC-2017: MBR vs. TOTEM @ 13 TeV https://indico.cern.ch/event/679087/ (from talk by K. Osterberg) 103.7±1.9 73.5±1.3 30.2±0.8 TOTEM paper CERN-EP-2017-321 10 December 2017 Reasonable agreement between TOTEM and MBR predictions Possible Odderon effects not included in MBR Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 25

First Experimental Hint for the Odderon Excerpt from the thesis of Richard Breedon, Rockefeller University,1988 Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 26

Pythia8-MBR Hadronization Tune An example of the diffractive tuning of PYTHIA-8 to the RENORM-NBR model n ave = σ QCD σ IPp 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) R. Ciesielski, Status of diffractive models, CTEQ Workshop 2013 https://indico.cern.ch/event/262192/contributions/1594778/attachments/463480/642352/cteq13diffraction.pdf Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 27

SD and DD x-sections vs Models http://journals.aps.org/prd/abstract/10.1103/physrevd.92.012003 Single Diffraction Double Diffraction Includes ND background Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 28

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 Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 29

SUMMARY Review of RENORM predictions of diffractive physics basic processes: SD1,SD2, DD, CD (DPE) combined processes: multigap x-sections ND no diffractive gaps: the only final state to be tuned Monte Carlo strategy for the LHC nesting Precision RENORM σ tot prediction W /tensor glue-ball model ICHEP 2016 At 8 TeV ATLAS and MBR in excellent agreement Disagreement betweentotem and MBR persists At 13 TeV MBR lies comfortably (!) between the ATLAS and CMS LHCC-201: NEW TOTEM RESULTS at 8 and 13 TeV vs. MBR Agreement at 8 TeV, compatibility at 13 TeV NESTING in MC simulation Thank you for your attention! Solving an expermentalal puzzle by using RENORM predictions K. Goulianos 30