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Improving Dark Matter searches using Track Assisted Reclustered (TAR) jets with the ATLAS detector at s = 13 TeV Fabrizio Napolitano Universitt Heidelberg On behalf of the ATLAS collaboration YSF - Interpreting the LHC Run 2 Data and

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27/05/19 Fabrizio Napolitano

Improving Dark Matter searches using Track Assisted Reclustered (TAR) jets with the ATLAS detector at √s = 13 TeV

1

Fabrizio Napolitano

YSF - Interpreting the LHC Run 2 Data and Beyond

Universität Heidelberg

On behalf of the ATLAS collaboration ICTP - Trieste

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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

q q W Z χ χ W Z H

Z0

B

Z0

B

q ¯ q ¯ χ χ h

Mono - H Mono - V

DM H DM W , Z

ATLAS-CONF-2018-039 JHEP 10 (2018) 180

Most of the sensitivity comes from events where is very high. The boosted recoil poses reconstruction challenge & opportunity.

ET

miss

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Introduction

DM W , Z ET

miss

ET

miss

Aim for hadronic final states (highest branching ratio)

Can resolve decay products individually High background

Small-R jets

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Introduction

DM W , Z ET

miss

ET

miss

Can resolve decay products individually High background

DM W , Z ET

miss

Decay products start merging Moderate background

Aim for hadronic final states (highest branching ratio)

Small-R jets

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Introduction

DM W , Z ET

miss

ET

miss

Can resolve decay products individually High background

DM W , Z ET

miss

Decay products start merging Moderate background

DM W , Z ET

miss

Large-R jet contains W,Z decay products Low background

Aim for hadronic final states (highest branching ratio)

Small-R jets R = 1.0

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Introduction

DM W , Z ET

miss

ET

miss

Can resolve decay products individually Strong background

DM W , Z ET

miss

Decay products start merging Moderate background

DM W , Z ET

miss

Aim for hadronic final states (highest branching ratio) In such boosted topologies start hitting
 calorimeter angular resolution:
 exploit tracker system

R = 1.0

Large-R jet contains W,Z decay products Low background

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Introduction

DM W , Z ET

miss

ET

miss

Can resolve decay products individually Strong background

DM W , Z ET

miss

Decay products start merging Moderate background

DM W , Z ET

miss

Aim for hadronic final states (highest branching ratio) In such boosted topologies start hitting
 calorimeter angular resolution:
 exploit tracker system Track-based jet substructure can overcome 
 the course angular resolution of calorimeter TAR jets

R = 1.0

Large-R jet contains W,Z decay products Low background

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ATL-PHYS-PUB-2018-012

Removed Anti-Kt R=0.2 jet

Track-Assisted-Reclustered (TAR) jets

W , Z

Use excellent angular resolution 


  • f the ATLAS tracker system
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ATL-PHYS-PUB-2018-012

Removed Anti-Kt R=0.2 jet

W , Z

Track-Assisted-Reclustered (TAR) jets

Use excellent angular resolution 


  • f the ATLAS tracker system
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ATL-PHYS-PUB-2018-012

Removed Anti-Kt R=0.2 jet

W , Z

Track-Assisted-Reclustered (TAR) jets

Use excellent angular resolution 


  • f the ATLAS tracker system
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ATL-PHYS-PUB-2018-012

Removed Anti-Kt R=0.2 jet

Use excellent angular resolution 


  • f the ATLAS tracker system

W , Z

Track-Assisted-Reclustered (TAR) jets

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ATL-PHYS-PUB-2018-012

Removed Anti-Kt R=0.2 jet

Use excellent angular resolution 


  • f the ATLAS tracker system

W , Z

Track-Assisted-Reclustered (TAR) jets

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= flexibility of reclustered jets (can optimize R depending on final state)
 + power of track-based substructure

Use excellent angular resolution 


  • f the ATLAS tracker system

ATL-PHYS-PUB-2018-012

W , Z

Track-Assisted-Reclustered (TAR) jets

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Track-Assisted-Reclustered (TAR) jets

Superior background rejection using TAR jets D2 + mass cut tagging W jets vs QCD

~24 ~17 ~50 ~25

ATL-PHYS-PUB-2018-012

D2 substructure variable helps discriminating 2-prong jets

TAR mass vs Combined Mass

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Simplified model with: Dark Matter Z’ mediator scalar Dark Higgs (s) ms < mx m(s)≠m(H) Dark Higgs [1701.08780]
 new decay channels 
 are possible

DM s

15

TAR playground: Mono-s analysis Example application q q χ χ Z′ s Z′

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WW ZZ

B B

Dark Higgs decay to Standard Model depends 


  • n its mass (like the SM Higgs)

TAR playground: Mono-s analysis

Considering 


  • nly on-shell


decays MadGraph Branching Ratios

ms [GeV]

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WW ZZ

B B

Dark Higgs decay to Standard Model depends 


  • n its mass (like the SM Higgs)

Considering 


  • nly on-shell


decays M O N O - S ( B B ) M O N O - S ( W W )

TAR playground: Mono-s analysis

MadGraph Branching Ratios

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If ms > 160 GeV, s → bb is insensitive:


_

DM s W W Unexplored final state: resonant WW +ET

miss

Jets Jets

TAR playground: Mono-s analysis

q q χ χ Z′ s Z′ W W q q χ χ Z′ s χ W W

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The reconstruction challenge

TAR playground: Mono-s analysis

W W Resolved s Regions:

Resolved

ET

miss

ET

miss[GeV]

∆R(W,W) A.U.

Parton Level

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The reconstruction challenge

TAR playground: Mono-s analysis

W W Resolved s W W Merged s W W Intermediate s

Resolved Merged Intermediate ~ 300 GeV

ET

miss

ET

miss[GeV]

A.U.

Regions:

∆R(W,W)

Parton Level

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A.U. ∆R(W,W)

Resolved Merged Intermediate

21

The reconstruction challenge

TAR playground: Mono-s analysis

ET

miss

W W Resolved s Regions: W W Merged s W W Intermediate s

Intermediate region: Could tune TAR jet radius 
 to contain individual W Use D2 to suppress 
 background Merged region: Could tune TAR jet radius 
 to contain full s decay Use 𝛖42 (N-subjettiness ratio)
 to suppress background

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Conclusions

  • New reconstruction algorithm can improve

searches with and boosted hadronically decaying objects: TAR jets

  • Offer superior mass resolution, substructure 


and flexibility: can be adapted to the regime

  • Example application of TAR jet: mono-s(WW)


search targeting a so far unexplored final state
 resonant WW + ET

miss

ET

miss

W W ET

miss

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Conclusions

Many thanks! Questions?

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Conclusions

Back-up

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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 SM DM DM

Production Indirect Direct

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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 SM DM DM

Production

DM escapes undetected giving rise to ET

miss

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Track-Assisted-Reclustered (TAR) jets

improvements using track-assisted objects

τ42 + mass cut tagging WW* jets vs QCD 
 (τ21 for W jets,τ32 top jets, for HWW in backup)

~11 ~8 ~11 ~9

ATL-PHYS-PUB-2018-012

τ42 substructure variable helps

discriminating 4-prong jets

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ATL-PHYS-PUB-2018-012

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29 Combined mass mTAR TCC

ATL-PHYS-PUB-2017-015

Best resolution up to 800 GeV for W jets Best resolution at high pT ~2 TeV for W jets Mass resolution example: W jets

[GeV]

T

Truth jet p 500 1000 1500 2000 2500 Fractional jet mass resolution 0.1 0.15 0.2 0.25 0.3

Comb

m

TAS

m

TAR

m

ATLAS Simulation Preliminary

= 13 TeV s W jets | < 2.0 η > 200 GeV, |

T

p

ATL-COM-PHYS-2018-455

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  • Phys. Rev. Lett. 119 (2017) 181804

Exclusion limits for in bins of missing transverse momentum

JHEP 10 (2018) 180

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Eur.Phys.J. C71 (2011) 1753

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  • Eur. Phys. J. C 79 (2019) 375.

2

D 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Normalized amplitude 0.02 0.04 0.06 0.08 0.1 0.12 0.14

ATLAS Simulation = 13 TeV s = 1.0 jets R

t

k Trimmed anti- = [500, 1000] GeV

true T

p | < 2

true

η | > 60 GeV

comb

m Jets W multijets Top Jets