Diffractive Dijet Production with 2010 data Hardeep Bansil (1), Oldřich Kepka (2), Vlastimil Kůs (2), Paul Newman (1), Marek Taševský (2) (1) University of Birmingham (2) Institute of Physics, Academy of Sciences of the Czech Republic Standard Model Plenary Meeting 24 th April 2014

Current Status Previously presented in SM Plenary meeting - July 2013 CDS supporting note available since March (also see H. Bansil thesis) Aiming for editorial board / paper Diffractive Dijet Production with 2010 Data224/04/2014

Introduction to diffraction Total cross section in hadronic scattering experiments at 7 TeV – Total = Elastic + Diffractive + Non-diffractive (ND) – 20% elastic, 80% inelastic (diffractive + ND) Diffractive channels together – 25-30% of the σ inel – Single-diffraction (SD: pp  pX) – Main process of interest – Double-diffraction (DD: pp  XY) Kinematic variables – invariant mass of the dissociated system M X (M Y ) at the LHC energy spans m p +m π to approx. 1TeV – fractional momentum loss ξ X of the scattered proton ξ X = M X 2 / s [ξ Y = M Y 2 / s] Diffraction in the realm of soft QCD – Best described by phenomenological models (e.g. Regge theory) – Exchange of color singlet (Pomeron)  large angular region in which no outgoing particles (soft QCD radiation) are detected  rapidity gap Diffractive Dijet Production with 2010 Data3 SD DD 24/04/2014

Rapidity gaps in ATLAS detector Large Rapidity Gap (LRG) … Δη ~ -log 10 ξ X … smaller ξ X (M X )  bigger gap – Region in η devoid of hadronic activity due to the exchange of colorless object (Pomeron) Detector-level LRG definition (Δη F ) – First defined by soft diffractive rapidity gaps analysis (Eur.Phys.J. C72(2012) 1926) – Biggest region in η (starting at the edge of the detector η=±4.9) absent of clusters and tracks complying selection: – no tracks with p T >p T cut (p T cut = 200 MeV) – no TopoClusters; noise suppression … (p T cluster > 200 MeV) most significant cell in the cluster: E cell /σ noise > S threshold No pile-up environment required – Pile-up could occupy the gap – Use early runs from 2010 (Period B) Diffractive Dijet Production with 2010 Data4 Δη F ~ 6 ↔ ξ ~ LRG 24/04/2014

Hard diffraction The aim – Study single diffraction at hard scale, i.e. in high p T dijet events for first time in ATLAS – Measure cross-section vs. gap size (Δη F ) and ξ (fractional momentum loss of intact proton) – Independent measurement of gap survival probability in terms of both Δη F & ξ Gap Survival Probability (S 2 ) – Hard diffraction studied precisely at HERA (ep collisions). Diffractive PDFs (dPDFs) measured. – Then Tevatron (pp collisions). Structure function ~10x smaller than HERA-based dPDFs predictions for Tevatron conditions. Explanation – rescattering of dissociated system with intact proton. – S 2 typical for hadron-hadron collisions What about S 2 at LHC? – theoretical predictions (KMR) … S 2 ~ 5-10 % Diffractive Dijet Production with 2010 Data5 CDF data Predictions based on HERA’s dPDFs z IP, Momentum fraction of parton emitted by Pomeron 24/04/2014 Rescatter with p ? ξ

PYTHIA8 + POMWIG PYTHIA8 non-diffractive samples PYTHIA8 diffractive samples can use different Pomeron flux models – influences diffractive distributions Comparison to default Schuler-Sjostrand H1 DPDFs better described by Donnachie-Landshoff model Can test against different models POMWIG samples Modified HERWIG, Based on picture to right, using H1 DPDFs Generated over kinematic range < ξ < 0.1 and < |t| < 10 GeV 2 Diffractive Dijet Production with 2010 Data624/04/2014

Event selection criteria Starting with SM2010 inclusive measurement (next slide) Good Runs List, Good primary vertex (n tracks >4), Triggers Kinematic cuts (p T jet 1 > 30 GeV, p T jet 2 > 20 GeV, |η jets |<4.4), anti-k T R=0.4 or R=0.6 Focus on 2010 Period B data adding pile-up suppression cut  L = 6.75 nb -1 need for events with 1 interaction only … no PU vertices (having n tracks >1) removes 5% of events in period B (σ-correction factors applied) Going below trigger efficiency plateau for jet triggers (next slide) improving the use of available statistics for large gaps Going to lower jet-p T ranges Increases statistics, allows smaller diffractive systems to be studied  larger gaps p T jet 1 > 20 GeV, p T jet 2 > 20 GeV, |η jets |<4.4, anti-k T R=0.4 or R=0.6 Forward gap definition (Δη F ) after extensive studies  “hybrid” gap-definition method: “Measurements of the total transverse energy in pseudorapidity bins in proton-proton collisions at √s with ATLAS” η-region devoid of activity (starting at either η=-4.8 or η=+4.8) detector-level noise cuts: tracks with pT track > 200 MeV TopoClusters with cell significance E cell /σ noise > S thr (~5.5) Corrected (truth) cross section definition: p ch (n) particle > 500 (200) MeV OR p T > 200 MeV Diffractive Dijet Production with 2010 Data724/04/2014

Trigger strategy Start from Implementation of selection cuts and trigger scheme from inclusive SM2010 dijet cross-section measurement Invariant mass spectrum successfully reproduced presented during Inclusive Jet + Dijet Cross-Section meeting in April 2012 However, event yields at large gaps unsatisfactory Optimise inclusive SM2010 measurement (OR of triggers associated with leading and sub-leading jet according to their p T, η) – L1_J5 trigger for central jets (|η| < 2.8) – Lower p T and forward jets triggered by L1_MBTS_1 (L1 forward jets not commissioned by then) Going below 99% trigger efficiency plateau (but staying above 70%) as MBTS_1 highly prescaled presented during Jet Trigger Signature Group Meeting in October 2012 (this allows to use jet triggers at lower p T )  necessity to weight events by 1/ε trig Diffractive Dijet Production with 2010 Data8 lower p T  lower invariant mass  larger gaps 24/04/2014 L1_J5 (0.3<|η|<1.2) R=0.4 jets R=0.6 jets Fit to R=0.4 Fit to R=0.6

ξ proton reconstruction Diffractive Dijet Production with 2010 Data924/04/2014 Truth level - fractional momentum loss of scattered proton – ξ proton = (3.5TeV – p Z proton ) / 3.5TeV Cross section measured in terms of observable ξ ± – approximation to real ξ – ξ ± = Σ p T e ±y / √s (TopoClusters / stable particles) – ξ + … intact proton going in the +z direction (system X in -z dir) – ξ - … intact proton going in the -z direction (system X in +z dir) Approximation performs very well for ξ<0.01 Pythia 8 SD

ND, SD and DD ranges Diffractive Dijet Production with 2010 Data1024/04/2014 Data against PYTHIA8 ND, DD and SD – all scaled to L= 6.75 nb - 1 Non diffraction dominant for Δη F 0.01 Then diffractive contributions become more prominent

Comparison of groups Comparison of uncorrected cross sections between Prague and Birmingham groups – Completely independent code bases – Minor discrepancies exist  work in progress Diffractive Dijet Production with 2010 Data1124/04/2014

Unfolding Diffractive Dijet Production with 2010 Data1224/04/2014 Bayesian 2D unfolding technique – RooUnfold – input: p T of the leading jet vs. Δη F or ξ ± Detector-level PYTHIA8 ND:(SD+DD) ratio “fitted” to data to get the best possible shape description in both Δη F and ξ ± distributions – Δη F distribution: ND×0.62, (SD+DD)×0.206 – ξ ± distribution: ND×0.577, (SD+DD)×0.283

Performance of 2D Unfolding Diffractive Dijet Production with 2010 Data1324/04/2014 Comprehensive tests of unfolding performance & stability done closure tests sensitivity tests to mixture of ND, SD and DD (different distribution shapes) convergence of iterations (χ 2 ) stability against choice of binning... (more information in the back-up note) optimum  4 iterations *Illustration based on 1D unfolding 2D unfolding actually uses several inputs to account for migrations

Systematic uncertainties Diffractive Dijet Production with 2010 Data1424/04/2014 Jet Energy Scale (JES) Jet Energy Resolution (JER) Jet Angular Resolution (JAR) Jet Reconstruction Efficiency (JRE) Jet Cleaning Efficiency (JCE) Unfolding Trigger efficiency Cluster energy scale (CES) Cell significance threshold cut (CTC) uncertainty Tracking - negligible Vertex requirement Luminosity Procedure: 1) Run uncertainty-adjusted analysis on MC 2) Produce new smearing matrix & reco-MC plots 3) Unfold uncorrected data with new smearing matrix & reco-MC 4) Compare new unfolding to standard procedure unfolding Uncertainty inputs from SM 2010 dijet analysis used here Inherited from soft diffractive analysis

Selected systematic uncertainties Diffractive Dijet Production with 2010 Data1524/04/2014 Jet Energy Scale (JES) Inherited from 2010 SM dijet analysis Split into 7 components JES can vary as much as 15% for components as a function of η, p T Added in quadrature Uncertainty range: typically 25-30% continuously rising up to large gaps Δη F, Cell significance threshold cut (CTC) Adjust noise suppression thresholds up and down by 10% Uncertainty typically 15-25% ξ ±, Cluster Energy Scale (CES) Cluster EM energy scale in MC adjusted by correction factors Uncertainty typically 10-20%

Differential cross sections Differential cross sections calculated as for Δη F N weighted accounts for trigger efficiency per data event, prescales and unfolding Compare against POMWIG and different PYTHIA8 flux models Requirement of hard scale affects kinematics  no rapidity gap plateau Cross sections slightly higher for R=0.6 but maintain the same shape For PYTHIA8, ND ~1.3x larger in first bin, SD+DD/ND fairly even for Δη F >2.5 POMWIG ~3x larger csx than data for Δη F >3, slightly higher for R= R=0.6 R=0.4 Diffractive Dijet Production with 2010 Data1624/04/2014

Differential cross sections Differential cross sections calculated as for ξ ± N weighted accounts for trigger efficiency per data event, prescales and unfolding Compare against POMWIG and different PYTHIA8 flux models Forward gap requirement of 3 units removes majority of large ξ ± events POMWIG results significantly above data, PYTHIA8 roughly equal to data csx Could be used to determine S 2 R=0.6, no gap req. Diffractive Dijet Production with 2010 Data1724/04/2014 R=0.6, Δη F > 3

Differential cross sections Differential cross sections also calculated for jet variables Without gap requirements, data compatible with PYTHIA8 ND After Forward gap requirement of 3 units to enhance diffraction: Leading jet pt: diffractive states fall away faster than ND Leading jet η: limited statistically but shows hints of double peak structure observed in diffractive MCs, ND shows single central peak Diffractive Dijet Production with 2010 Data1824/04/2014

Summary Reproduced soft diffractive & inclusive dijet cross section measurements New selection cuts & trigger strategy developed Analysis of 2010 period B data in Δη F (gap size) and ξ proton (fractional momentum loss) distributions Good agreement between Birmingham-Prague Supporting note in advanced stage Looking to request editorial board as soon as possible Some additional studies and MC generation (NLO calculations) planned to improve measurement, extract gap survival probability (S 2 ) Diffractive Dijet Production with 2010 Data1924/04/2014

BACK UP SLIDES 24/04/2014Diffractive Dijet Production with 2010 Data20

CMS vs. ATLAS CMS – L= 2.7 nb -1, jet reconstruction alg. with R = 0.5, Δη F >1.9 SD MCs predict more events than observed by factor ≈5 in lowest ξ bin (S 2 ) Gap Survival Probability S 2 = 0.12 ± 0.05 (LO) S 2 = 0.08 ± 0.04 (NLO) ATLAS results - taking average of anti-kT 0.6 and 0.4 (4 iter.), no forward gap requirement Different csx definitions so currently used to guide future results Systematics set to the same values as the CMS as guide – values within a factor of 2 24/04/2014Diffractive Dijet Production with 2010 Data21 Phys. Rev. D 87 (2013) S2S2

Validation of new triggers Period B Diffractive Dijet Production with 2010 Data22 Uncorrected distributions RAW EVENTSSM2010 BNew B Gaps > Gaps > 4952 Agreement within 5%! Significant grow of statistics at large gaps 24/04/2014

Diffractive dijet measurement by CMS CMS measured diffractive contribution to dijet production at LHC – based on L = 2.7 nb -1 – Measurement of ξ (approximates fractional momentum loss of scattered proton) – region of interest: Δη F >1.9 comparison to different MC models – ND (red): PYTHIA 6 & 8 – SD (blue): PYTHIA 8, POMPYT, POMWIG – DD: PYTHIA 8 – POWHEG for NLO comparisons Results – SD MCs predict more events than observed by factor ≈5 in lowest ξ bin (S 2 ) – data also consists of proton dissociative events (scattered proton excited into low mass state escaping undetected into the forward region) Gap Survival Probability – S 2 = 0.12 ± 0.05 (LO) – S 2 = 0.08 ± 0.04 (NLO) Diffractive Dijet Production with 2010 Data2324/04/2014 ~ ~ Phys. Rev. D 87 (2013) S2S2

Unfolding systematic Method: creating “new” MC (by reweighting) describing reco-level data well 1) Fit DataReco/MCReco by continuous function (data-MC scaled agreement doesn’t have to be perfect) 2) Rerun MC analysis with weights from the fitting function 3) Unfold scaled reco-MC by standard procedure 4) Compare unfolded MC to truth MC (scaled) -> uncertainty 24/04/2014Diffractive Dijet Production with 2010 Data24

Δη F measurement Soft diffractive measurement dσ/dΔη F ~ constant over several units of rapidity  plateau Diffractive Dijet Production with 2010 Data2524/04/2014 Soft diffraction Diffractive plateau