Improving Dark Matter searches using Track Assisted Reclustered - PowerPoint PPT Presentation

Improving Dark Matter searches using Track Assisted Reclustered (TAR) jets with the ATLAS detector at √ s = 13 TeV Fabrizio Napolitano Universität Heidelberg On behalf of the ATLAS collaboration YSF - Interpreting the LHC Run 2 Data and Beyond ICTP - Trieste 27/05/19 Fabrizio Napolitano � 1

Introduction Dark Matter (DM) accounts for ~85% of the total matter in the universe Higgs, W and Z bosons provide and interesting probe 
 for DM @ LHC Mono - H Mono - V ATLAS-CONF-2018-039 JHEP 10 (2018) 180 q ¯ h q W � Z Z 0 B H χ χ Z 0 W � Z B q χ q ¯ χ DM H DM W , Z Most of the sensitivity comes from events where is very high. miss E T The boosted recoil poses reconstruction challenge & opportunity. 27/05/19 Fabrizio Napolitano � 2

Introduction Aim for hadronic final states (highest branching ratio) miss E T Can resolve decay products individually miss E T W , Z High background DM Small-R jets 27/05/19 Fabrizio Napolitano � 3

Introduction Aim for hadronic final states (highest branching ratio) miss E T Decay products start miss merging E T Moderate background W , Z DM Can resolve decay products individually miss E T W , Z High background DM Small-R jets 27/05/19 Fabrizio Napolitano � 4

Introduction Aim for hadronic final states (highest branching ratio) miss E T Large-R jet contains miss W,Z decay products E T Low background W , Z DM R = 1.0 Decay products start miss merging E T Moderate background W , Z DM Can resolve decay products individually miss E T W , Z High background DM Small-R jets 27/05/19 Fabrizio Napolitano � 5

Introduction Aim for hadronic final states (highest branching ratio) miss E T Large-R jet contains miss W,Z decay products E T Low background W , Z DM R = 1.0 In such boosted topologies start hitting 
 Decay products start calorimeter angular resolution: 
 miss merging E T exploit tracker system Moderate background W , Z DM Can resolve decay products individually miss E T W , Z Strong background DM 27/05/19 Fabrizio Napolitano � 6

Introduction Aim for hadronic final states (highest branching ratio) miss E T Large-R jet contains miss W,Z decay products E T Low background W , Z DM R = 1.0 In such boosted topologies start hitting 
 Decay products start calorimeter angular resolution: 
 miss merging E T exploit tracker system Moderate background W , Z DM Track-based jet substructure can overcome 
 Can resolve decay the course angular resolution of calorimeter products individually miss E T TAR jets W , Z Strong background DM 27/05/19 Fabrizio Napolitano � 7

Track-Assisted-Reclustered (TAR) jets ATL-PHYS-PUB-2018-012 W , Z Use excellent angular resolution 
 of the ATLAS tracker system Removed Anti-K t R=0.2 jet 27/05/19 Fabrizio Napolitano � 8

Track-Assisted-Reclustered (TAR) jets ATL-PHYS-PUB-2018-012 W , Z Use excellent angular resolution 
 of the ATLAS tracker system Removed Anti-K t R=0.2 jet 27/05/19 Fabrizio Napolitano � 9

Track-Assisted-Reclustered (TAR) jets ATL-PHYS-PUB-2018-012 W , Z Use excellent angular resolution 
 of the ATLAS tracker system Removed Anti-K t R=0.2 jet 27/05/19 Fabrizio Napolitano � 10

Track-Assisted-Reclustered (TAR) jets ATL-PHYS-PUB-2018-012 W , Z Use excellent angular resolution 
 of the ATLAS tracker system Removed Anti-K t R=0.2 jet 27/05/19 Fabrizio Napolitano � 11

Track-Assisted-Reclustered (TAR) jets ATL-PHYS-PUB-2018-012 W , Z Use excellent angular resolution 
 of the ATLAS tracker system Removed Anti-K t R=0.2 jet 27/05/19 Fabrizio Napolitano � 12

Track-Assisted-Reclustered (TAR) jets ATL-PHYS-PUB-2018-012 W , Z Use excellent angular resolution 
 of the ATLAS tracker system = flexibility of reclustered jets (can optimize R depending on final state) 
 + power of track-based substructure 27/05/19 Fabrizio Napolitano � 13

Track-Assisted-Reclustered (TAR) jets ATL-PHYS-PUB-2018-012 ~24 ~50 ~17 ~25 D 2 + mass cut tagging W jets vs QCD TAR mass vs Combined Mass Superior background rejection using TAR jets D 2 substructure variable helps discriminating 2-prong jets 27/05/19 Fabrizio Napolitano � 14

TAR playground: Mono-s analysis Example Dark Higgs [1701.08780] 
 application Simplified model with: Dark Matter Z’ mediator s Z ′ q scalar Dark Higgs (s) χ q Z ′ m s < m x χ m(s) ≠ m(H) new decay channels 
 are possible DM s 27/05/19 Fabrizio Napolitano � 15 � 15

TAR playground: Mono-s analysis Dark Higgs decay to Standard Model depends 
 on its mass (like the SM Higgs) MadGraph Branching Ratios Considering 
 only on-shell 
 B B decays WW ZZ m s [GeV] 27/05/19 Fabrizio Napolitano � 16

TAR playground: Mono-s analysis Dark Higgs decay to Standard Model depends 
 on its mass (like the SM Higgs) MadGraph Branching Ratios Considering 
 only on-shell 
 B B decays WW M O N O - S ( B B ) M O N O - S ( W W ) ZZ 27/05/19 Fabrizio Napolitano � 17

TAR playground: Mono-s analysis _ If m s > 160 GeV, s → bb is insensitive: 
 W W W W s s q Z ′ χ Z ′ q χ χ q q Z ′ χ χ miss Unexplored final state: resonant WW +E T Jets W DM s W Jets 27/05/19 Fabrizio Napolitano � 18

TAR playground: Mono-s analysis The reconstruction challenge miss [GeV] E T A.U. Resolved Parton Level ∆ R(W,W) miss Regions: E T Resolved W s W 27/05/19 Fabrizio Napolitano � 19

TAR playground: Mono-s analysis The reconstruction challenge miss [GeV] E T A.U. Resolved Parton Level Intermediate ~ 300 GeV Merged ∆ R(W,W) miss Regions: E T Intermediate Resolved Merged W W W s s W W s W 27/05/19 Fabrizio Napolitano � 20

TAR playground: Mono-s analysis The reconstruction challenge A.U. Resolved Merged region: Could tune TAR jet radius 
 Intermediate region: Intermediate to contain Could tune TAR jet radius 
 full s decay to contain individual W Merged Use D 2 to suppress 
 Use 𝛖 42 (N-subjettiness ratio) 
 background ∆ R(W,W) to suppress background Regions: miss E T Intermediate Resolved Merged W W W s s W W s W 27/05/19 Fabrizio Napolitano � 21

Conclusions • New reconstruction algorithm can improve miss searches with and boosted hadronically E T decaying objects: TAR jets • Offer superior mass resolution, substructure 
 miss and flexibility: can be adapted to the E T regime • Example application of TAR jet: mono-s(WW) 
 search targeting a so far unexplored final state 
 miss resonant WW + E T W W 27/05/19 Fabrizio Napolitano � 22

Conclusions Many thanks! Questions? 27/05/19 Fabrizio Napolitano � 23

Conclusions Back-up 27/05/19 Fabrizio Napolitano � 24

Introduction Dark Matter (DM) accounts for ~85% of the entire matter in the universe Assuming DM interacts with Standard Model (SM) particles → can produce it at colliders SM DM Indirect Direct DM SM Production 27/05/19 Fabrizio Napolitano � 25

Introduction Dark Matter (DM) accounts for ~85% of the entire matter in the universe Assuming DM interacts with Standard Model (SM) particles → can produce it at colliders DM escapes undetected giving rise to E T miss DM SM SM DM Production 27/05/19 Fabrizio Napolitano � 26

Track-Assisted-Reclustered (TAR) jets ATL-PHYS-PUB-2018-012 ~11 ~11 ~8 ~9 τ 42 + mass cut tagging WW* jets vs QCD 
 ( τ 21 for W jets , τ 32 top jets , for HWW in backup) improvements using track-assisted objects τ 42 substructure variable helps discriminating 4-prong jets 27/05/19 Fabrizio Napolitano � 27

ATL-PHYS-PUB-2018-012 27/05/19 Fabrizio Napolitano � 28

Mass resolution example: W jets ATL-COM-PHYS-2018-455 ATL-PHYS-PUB-2017-015 0.3 Fractional jet mass resolution ATLAS Simulation Preliminary Comb m s = 13 TeV TAS m 0.25 W jets η p > 200 GeV, | | < 2.0 TAR m T 0.2 0.15 0.1 500 1000 1500 2000 2500 Truth jet p [GeV] T mTAR TCC Combined mass Best resolution Best resolution up to 800 GeV at high p T ~2 TeV for W jets for W jets 30/05/18 Fabrizio Napolitano � 29

Exclusion limits for in bins of missing transverse momentum JHEP 10 (2018) 180 Phys. Rev. Lett. 119 (2017) 181804 27/05/19 Fabrizio Napolitano � 30

Eur.Phys.J. C71 (2011) 1753 27/05/19 Fabrizio Napolitano � 31

Eur. Phys. J. C 79 (2019) 375. 0.14 Normalized amplitude ATLAS Simulation s = 13 TeV W Jets 0.12 Trimmed anti- k R = 1.0 jets multijets t true p = [500, 1000] GeV Top Jets T η true | | < 2 0.1 comb m > 60 GeV 0.08 0.06 0.04 0.02 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 D 2 27/05/19 Fabrizio Napolitano � 32