Update on Diffractive Dijet Production Search Hardeep Bansil University of Birmingham Birmingham ATLAS Weekly Meeting 24/01/2013

Contents MC request update Data formats Distributions Next steps 2

GapJetFilter 1) Selects events with at least two jets with Et > Et threshold (Et_jet_thr) 2) Finds the largest gap from the edge of calorimeter (|eta| pt threshold (pt_part_thr) 3) Filters events to get a flat gap spectrum up to a gap threshold (gap_thr), all events with a gap > gap_thr are retained 4) Each event gets a weight (weight gap_thr). This weight calculated using a fit of the gap spectrum from unfiltered events. Parameters of this fit need to be put into JO file (i.e. each Jx of each generator requires its own set of fit parameters) Parameters adjustable using the JO file: - Jet algorithm type (default: AntiKt0.4) - Et_jet1_thr, Et_jet2_thr (default: 12 GeV, 12 GeV) - pt_part_thr (default: 0 MeV) - parameters of the fit of the gap spectrum (default: some) - gap_thr (default: 0.0) NOTE: If gap_thr=0 in JO, GapJetFilter acts as a pure dijet filter (no filtering using gaps). Validation of the filter function (= weighted events reproduce spectra from unfiltered events) was shown at MC meeting on using MC11 releases. Since then validated completely in MC12. GapJetFilter in Athena production release since

GapJetFilter with HERWIG++ v2.5 ND 4 J1+J2+J3+J4 270k of filtered events reproduce the original 1.2M events and give much better statistics for gaps > 5. Note: J1 dominates the spectra

MC request Full simulation in 2010 conditions (MC12 generation compatible with MC10 simulation) A) Gap-weighted production + dijet filter [min. Etjet=12 GeV] (using GapJetFilter): 1) HERWIG (ND) J0: 200k, J1: 600k, J2: 200k, J3: 100k, J4: 100k 2) HERWIG (SD) J0: 100k, J1: 300k, J2: 100k, J3: 50k, J4: 50k (in both dirs) 3) PYTHIA 8 (ND) J0: 200k, J1: 600k, J2: 200k, J3: 100k, J4: 100k 4) PYTHIA 8 (SD) J0j: 300k, J1j: 500k, J2j: 300k 5) PYTHIA 8 (DD) J0j: 300k, J1j: 500k, J2j: 300k B) Gap-unweighted production + dijet filter [min. Etjet = 12 GeV] (using GapJetFilter): 6) HERWIG (ND) J0: 200k, J1: 600k, J2: 400k 7) HERWIG (SD) J0: 100k, J1: 300k, J2: 200k (in both dirs) 8) PYTHIA 8 (ND) J0: 300k, J1: 500k, J2: 300k 9) PYTHIA 8 (SD) J0j: 400k, J1j: 600k 10) PYTHIA 8 (DD) J0j: 400k, J1j: 600k NB: In Py8 (SD/DD) no pthat or Mhat parameter available  Very inefficient generation of events with hard jets and large gaps. Nearly have full set of 11.5M events in evgen format now, looking to validate samples in terms of truth pt, truth gap size etc. 5

Data Formats Next step to get data and MC in same D3PD format, ideally selecting only the variables we need for analysis and excluding unnecessary collections Information on most significant cell in cluster now fully available as two cluster moments in AOD using CaloRec , Athena release Can successfully perform re-reprocessing of release 16 ESDs to extract the cluster moments, while keeping all other content unchanged  produces release 17 AODs Many problems over the last few weeks trying to get QcdD3PDMaker running on these files in release 17 due to issues with getting Python configuration set up correctly and incompatibility of different packages Definitely cannot run over them in release 16 again Currently trying modified release 16 code to make AODs but not producing moments Spoke to Toshi Sumida, suggested creating new D3PDs should be made in Release16 only Too much incompatibility between release 16 and 17? Soft QCD convener suggests it should not be problem and would like rel 17 in order to keep production support Discussing with current SM production group about how to proceed, avoid mismatch between data and MC Getting job options prepared to send to production group (for rel 16 or rel 17) to select only the necessary variables for D3PD production 6

Distributions Following discussions from proton-lead diffraction studies going on in New York ATLAS group, will look at new distributions MBTS A v C Done with Pomwig with dissociating system going to positive η (A side) 7

Distributions Following discussions from proton-lead diffraction studies going on in New York ATLAS group, will look at new distributions CaloCluster ET in FCAL A v C 8

Distributions Following discussions from proton-lead diffraction studies going on in New York ATLAS group, will look at new distributions CaloCluster average η distributions across sample Others to look at: Largest floating gap anywhere in event - compare against forward gap Mass fraction: R jj = M jj /M x Signed average η if jet average η on same side as gap start then |jet mean η| * +1 if jet average η on opp. side as gap start then |jet mean η| * -1 9

Next steps Generate MC D3PDs to validate MCs – Waiting for grid jobs to complete – Also important to test truth level D3PD code (not been able to test until now) Decide on D3PD release versions and how production will be performed Provide job options for selecting required variables Incorporate new distributions into analysis Continue work on thesis 10