Soft interactions in Herwig Stefan Gieseke Institut f ur - PowerPoint PPT Presentation

Soft interactions in Herwig Stefan Gieseke Institut f¨ ur Theoretische Physik KIT work with Patrick Kirchgaeßer and Frash¨ er Loshaj MPI@LHC16 – San Crist´ obal de las Casas 28 Nov–2 Dec 2016 Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 1/21

pp Event Generator Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 2/21

pp Event Generator Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 2/21

pp Event Generator Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 2/21

pp Event Generator Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 2/21

pp Event Generator Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 2/21

pp Event Generator Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 2/21

Underlying event in Herwig++ Semihard UE • Default from Herwig++ 2.1. [Herwig++, 0711.3137] • Multiple hard interactions, p t ≥ p min . [B¨ ahr, SG, Seymour, JHEP 0807:076] t • pQCD 2 → 2. • Similar to JIMMY . • Good description of harder UE data (“plateau”). Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 3/21

Underlying event in Herwig++ Soft UE • Default from Herwig++ 2.3. [Herwig++, 0812.0529] • Extension to soft interactions p t < p min . t • Theoretical work with simplest possible extension. [B¨ ahr, Butterworth, Seymour, JHEP 0901:065] • “Hot Spot” model. [B¨ ahr, Butterworth, SG, Seymour, 0905.4671] Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 3/21

Hot Spot model Fix the two parameters µ soft and σ inc soft in b , s ) = 1 � � � � � b ; µ ) σ inc hard ( s ; p min b ; µ soft ) σ inc χ tot ( A ( )+ A ( t soft 2 from two constraints. Require simultaneous description of σ tot and b el (measured/well predicted), � � � b , s ) � σ tot ( s ) ! d 2 � 1 − e − χ tot ( = 2 b , b b 2 � � � b , s ) � b el ( s ) ! d 2 � 1 − e − χ tot ( = . σ tot Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 4/21

Extending into the soft region Continuation of the differential cross section into the soft region p t < p min (here: p t integral kept fixed) t 5 /dp t (1 / GeV) p min 2 =3 GeV , = 0 . 5 GeV ✞ t ✆ ✝ p min 2 =5 GeV , =0 . 06 GeV ✞ t ✆ 4 � (5 GeV) d 3 d p min , 2 ( p 2 ) soft ✁ p t e t t ✄ ☎ ✄ dp t ✂ 2 � 1 / 1 0 0 2 4 6 8 10 p t (GeV) Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 5/21

Implementation of soft scattering Soft gluon production with soft p t < p min spectrum. t Colour structure important. Two extreme cases possible. Sensitivity to parameter colourDisrupt = P ( disrupt colour lines ) Long colour lines appear when swapping outgoing gluons. R 1 R g 1 g 3 g g g g g 4 g 2 R 2 R Colour reconnections applied! Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 6/21

b b b b b b b b b b b b b b b b So far at the LHC Soft model is extension of MPI model for Underlying Event and harder aspects of Min Bias events. Herwig 7.0 at 900 GeV and 7 TeV: [ATLAS, Eur.Phys.J. C71 (2011) 1636] , √ s = 900 GeV , √ s = 7 TeV Transverse ∑ p ⊥ density vs. p clus 1 Transverse ∑ p ⊥ density vs. p clus 1 ⊥ ⊥ 0 . 8 � d 2 ∑ p ⊥ /d η d φ � � d 2 ∑ p ⊥ /d η d φ � 2 0 . 7 0 . 6 1 . 5 0 . 5 0 . 4 1 0 . 3 Data Data Hw 7 . 0 LO ⊕ PS Hw 7 . 0 LO ⊕ PS 0 . 2 0 . 5 0 . 1 0 0 1 . 4 1 . 4 MC/Data 1 . 2 MC/Data 1 . 2 1 1 0 . 8 0 . 8 0 . 6 0 . 6 1 2 3 4 5 6 7 8 2 4 6 8 10 12 14 p ⊥ (leading particle) [GeV] p ⊥ (leading particle) [GeV] Still reasonably well for moderately soft particles. Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 7/21

b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b So far at the LHC Soft model is extension of MPI model for Underlying Event and harder aspects of Min Bias events. Herwig 7.0 at 900 GeV and 7 TeV: [ATLAS, Eur.Phys.J. C71 (2011) 1636] > 3.0 GeV, √ s = 900 GeV > 3.0 GeV, √ s = 7 TeV N density vs. ∆ φ , p clus 1 N density vs. ∆ φ , p clus 1 ⊥ ⊥ � d 2 N /d η d φ � 1 . 2 � d 2 N /d η d φ � 2 1 1 . 5 0 . 8 0 . 6 1 Data Data 0 . 4 Hw 7 . 0 LO ⊕ PS Hw 7 . 0 LO ⊕ PS 0 . 5 0 . 2 0 0 1 . 4 1 . 4 MC/Data 1 . 2 MC/Data 1 . 2 1 1 0 . 8 0 . 8 0 . 6 0 . 6 0 0 . 5 1 1 . 5 2 2 . 5 3 0 0 . 5 1 1 . 5 2 2 . 5 3 | φ | (w.r.t. leading particle) [rad] | φ | (w.r.t. leading particle) [rad] Still reasonably well for moderately soft particles. Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 7/21

b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b The bump A clear case of abusing a model for the hard UE in forward/diffractive final states. . . [ATLAS, Eur.Phys.J. C72 (2012) 1926] Rapidity gap size in η starting from η = ± 4.9, p T > 200 MeV d σ /d ∆ η F [mb] 10 2 Data Hw 7 . 0 LO ⊕ PS 10 1 1 10 − 1 1 . 4 MC/Data 1 . 2 1 0 . 8 0 . 6 0 1 2 3 4 5 6 7 8 ∆ η F Bump is artefact. No Diffraction. Poor modeling of soft interactions. Colour assignment ad hoc. Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 8/21

Outline Challenge accepted. • Model for diffractive final states. • Model for soft particle production. • Results. Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 9/21

Diffraction as part of minimum bias simulation Diffractive final states directly modeled. Not embedded in MPI approach via cuts through triple pomeron vertices. Therefore change in constraint � � � b , s ) � x σ tot ( s ) ! d 2 � 1 − e − χ tot ( = 2 b , where x ≈ 1 − σ diff ∼ 20 − 25 % . σ tot In min-bias simulation: every event is either • diffractive, directly modeled from pp initial state. • non-diffractive, modeled in the MPI picture, parton level. Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 10/21

Diffractive final states Strictly low mass diffraction only. Allow M 2 large nonetheless. M 2 power-like, t exponential (Regge). pp → ( baryonic cluster )+ p . Hadronic content from cluster fission/decay C → hh ... Cluster may be quite light. If very light, use directly pp → ∆ + p . Also double diffraction implemented. pp → ( cluster )+( cluster ) pp → ∆ + ∆ . Technically: new MEs for diffractive processes set up. Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 11/21

Model for soft particle production in Herwig Reproduce core properties of soft particle production. “flat in rapidity”, “narrow in p t ”. Main idea: “soft interaction = cut pomeron = particle ladder”. N soft from MPI model = #ladders. Clusters produced via colour connected quarks and gluons. Adopt to soft interactions in Herwig via remnant decays. Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 12/21

Multiperipheral kinematics [Baker, Ter-Martirosyan 1976] Average relative momentum fraction � x � . Leads to flat rapidity distribution of emissions in a single ladder. ∆ y ∼ ln 1 q i , z x . p i +1 , z = (1 − x i +1 ) q i ,z Choose some constant C , then � x � ∼ 1 / C . q i +1 , z = x i +1 q i, z � N � average number of emitted p A p 1 particles. q 1 p 2 q 2 ln C ln s 1 p 3 q 3 � N � = p 4 m 2 q 4 p 5 p ⊥ or m ⊥ moderate, unordered. p B p N Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 13/21

Soft particle production model in Herwig • #ladders = N soft . • N particles from Poissonian, width � N � . Model parameter 1 / ln C ≡ n ladder → tuned. • x i smeared around � x � (calculated). • p ⊥ from Gaussian acc to soft MPI model. • particles are q , g , see figure. Symmetrically produced from both remnants. • Colour connections between neighboured particles. Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 14/21

Soft particle production model in Herwig Single soft ladder with MinBias initiating process. Remnant 1 P Beam , 1 Cluster q g g P g g ¯ q P Beam, 2 Remnant 2 Further hard/soft MPI scatters possible. Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 14/21

Parameters and tuning Diffraction plus MPI incl new soft model. Diffractive cross sections adjusted to data. Tuning to Min Bias data: η , p ⊥ for various N ch , � p ⊥ � ( N ch ) . Usual MPI parameters ⊥ ( √ s ) , ( p min ⊥ , 0 , b ) → p min µ 2 , p reco . One additional parameter n ladder . Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 15/21

b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b Tuned results ATLAS Min Bias 7 TeV. [ATLAS, New.J.Phys. 13 (2011) 053033] Charged particle η at 7 TeV, track p ⊥ > 500 MeV, for N ch ≥ 6 1/ N ev d N ch /d η 4 3 . 5 3 2 . 5 2 1 . 5 Data newSoftMPI, χ 2 / n = 0 . 28 1 LHC-MB, χ 2 / n = 8 . 15 0 . 5 0 1 . 4 MC/Data 1 . 2 1 0 . 8 0 . 6 - 2 - 1 0 1 2 η Similar to previous results, “harder part of Min Bias”. Stefan Gieseke · MPI@LHC 2016 · 28 Nov – 2 Dec 2016 16/21