Search for Long-Lived,

Heavy Particles using signature of a

high track-multiplicity

displaced vertex at

the LHC-ATLAS Experiment.

Nora Pettersson, 陣内修, 音野瑛俊A

東工大、九州大学A

2014-09-18 2014年物理学会秋季大会 1

Content: 1. Introduction && Motivation 2.Background Estimation 3.Conclusion && Future

Split SUSY • Can be realised through AMSB

◄Simplest Scenario

◄One-loop splitting between scalars and fermions

• A 125 GeV Higgs ◄(MSSM) Heavy Squark

◄Due to colour charge Gluino required to decay via Squark ◄Heavy Squark Gluino becomes

long-lived

• Gauge Coupling Unification & Dark Matter Candidate

• Drawback ◄Do not solve the hierarchy problem

◄Fine-tuning..

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A.Arvanitaki, N.Craig, S.Dimopoulos and

G.Villadoro “Mini-Split”, JHEP 1302, 126

(2013)

Displaced

Gluino

Decays

Introduction (1/2)

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(Split SUSY)

Colored gluino decay supressed due to the high-

mass scale of other particles, long enough life

time to interact with quarks/gluons form R-

Hadrons

Current Final States for Split SUSY:

1. DV + JET

2. DV + MET

What is New? EXTENDED Range! Same basic principle High track-multiplicity Displace Vertex Apply different condition to Target wider range of final states!

(RPV)

Sqaurk/Gluino production Neutralino,

Decay through the RPV couplings

(making the neutralino long-lived) to

Current Final States for RPV:

1. DV + μ

2. DV + e

3. DV + MET

4. DV + μe (no multi-track DV)

e,νe

νμ

Yet unexplored possible channels: e.g. GMSB, Hidden Valley Scenarios, Long-lived

staus, bRPV…

Previously focused on RPV SUSY of a DV + μ

http://arxiv.org/abs/1210.7451

Introduction (2/2) • Displaced Vertex Search

at the LHC-ATLAS Experiment

◄Long-lived Particles (LLP)

◄The particle decay inside the volume of the ATLAS Inner Detector (The tracking detector)

◄Target Decay lengths of up to ~300 mm (R and Z)

◄“Invisible” delayed decay form a displaced vertex

◄High Track-Multiplicity

◄High Mass Vertex

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1000 mm

300 mm

1000 mm 300 mm

R

Z

Displaced Decays • Event View of a

Displaced Decay

• Using ◄ MC Signal Sample

◄χ0 qqμ

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Signal efficiency for χ0 qqμ For one mass-

point

~ 30%

Beam pipe

Pixel SCT TRT

Displaced Vertex Reconstruction Efficiency

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Great efficiency at large r!

ATLAS Standard Tracking optimised for

tracks with small impact parameters

We are using secondary tracks

(Large! Impact parameters)

Re-tracking utilised to improve tracking

efficiency for larger r

• Vertex reconstruction efficiency as a function of rDV Re-Tracking:

Uses ”left-over ” hits and allows larger

Impact Parameters wrt. Primary Vertex

ATLAS Standard Tracking

Improvement from re-tracking

Background Estimate (1/2) • All Final States Rely on a

High Track-Multiplicity Displaced Vertex (DV) ◄Need to estimate the expected

background in

Signal Region:

Mass > 10.0 GeV

&& Number of Tracks ≥ 5

• Estimate require large statistics ◄Use All Events!

◄Then: Scale Estimate

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Using 2012 Data collected at 8TeV Equal an integrated luminosity of 20.3 fb-1

Background Estimate (2/2) Potential sources of background of high track-

multiplicity vertices are:

• Hadronic Interactions (Main contribution)

◄In Dense material regions (e.g.: detector modules)

◄Random track crossings

◄Random track crossing a hadronic interaction vertex can yield a high mass vertex

• Combinatorial background

◄Inside the beam pipe (high track density)

◄Total random combination of tracks can yield a high mass vertex

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Low Contribution: Number of vertices Estimated to << 1

θ

Hadronic Interactions (1/2) • Dense material regions

such as detector layers or support structures

◄Veto vertices found in these regions

◄Using a 3D-map of the ATLAS Inner Detector

◄Constructed using a

◄(I.) data-driven study and

◄ (II.) hard-coding certain simple structures

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Previously used a 2D-map increase in cut-efficiency upgrading from a

2D map to 3D map: gain 20%

I.

II.

Worked on this previous years, Two JPS Talks 27aTH-7 2014Sp,

20aSM-1 2013-Au

Hadronic Interactions (2/2) • In between material layers

◄Hadronic Interactions expected with gas molecules

◄Typically low mass vertices

◄If a random track cross the vertex and get reconstructed as part

of the vertex

◄Could yield vertices with high mass

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Low Mass Vertices

High Mass tail due to random crossing tracks

No angle large than 0.5 in the

DV

θ

Random crossing

track at a Larger angle

θ

Background Estimation: Hadronic Interactions (1/5)

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Need to construct a model Data-Driven Method:

I. Low mass

II.High mass tail

I.

II.

I. Low Masses

These vertices should be “real” and

have no crossing tracks

Assume collimated tracks with

an average angle < 0.5

II. High Masses

Construct this template by:

Adding a random track (from all

events) to a:

(i-1) Displace vertex

e.g. Template for 3-Track

Vertices: 2-Track DV + a random track

θ

θ

3 track DV

Background Estimation: Hadronic Interactions (2/5)

• Mass distributions varies

with R

◄Better estimate: Fiducial

volume divided up into a

couple of regions

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Recipe: Adding a “Random Track” to a (i-1) DV. 1. Pick a Random Track

a)Track properties Vary with R! Construct Track templates

b)Fill templates with track parameters for each region

c)Choose random track for the corresponding region!

2.Add to a (i-1) DV (pT,η,φ) 3.Recalculate the vertex mass

Background Estimation: Hadronic Interactions (3/5)

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Mass Spectra for each Radial region in Control region 10.0 GeV < DV(Mass) < 20.0 GeV

3 Track Displaced Vertices

Region 6 Region 8 Region 9

Region 0 Region 2 Region 4

Not vetoed (dense material) regions

Background Estimation: Hadronic Interactions (4/5)

• The Model (in Red)

+ Black histogram (low mass)

+ Green histogram (high mass template)

• Compare to Data (in Blue)

◄Here for 3-Track Displaced Vertices

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Estimate in the Signal Region DV(mass) > 10. GeV

Scaled by the expect amount of random crossings

Take scale factors from comparing estimate and data for 3-track DV

(Use 4-track DV as validation region)

Green areas are dense material regions (vetoed vertices)

Background Estimation: Hadronic Interactions (5/5)

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Zero Estimate vertices for all final states

DV+MET MET scale factor 0.08% 15±8 (stat.) Vertices

Scaled 0.012±0.006 (stat.) Vertices

DV+Muon Muon scale factor 0.07%

1±2 (stat.) Vertices Scaled 0.007±0.014 (stat.) Vertices

DV+Electron Electron scale factor 3.57%

3±3 (stat.) Vertices Scaled 0.11±0.11 (stat.) Vertices

Estimated number of background vertices due to hadronic interactions and random

crossing tracks

To have enough statistics Using all events

Scale Estimates as:

DV+Jet Jet scale factor 1.66 % 15±8 (stat.) Vertices

Scaled 0.25±0.133 (stat.) Vertices

Conclusion & Future • Displace Vertex Analysis

◄Provide unique signals

◄Low SM backgrounds!

• Estimated multi-track backgrounds

◄Number of expected vertices << 1

◄Contribution of combinatorial background << 1

• Future:

◄Prepare to Unblind Analysis and finalise results

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Estimates: Zero Background Analysis!

Prepare for Run-II

BACKUP

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THE LHC-ATLAS EXPERIMENT

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ATLAS ATLAS is a multipurpose detector at

LHC, CERN,Geneva.

So far ATLAS collected data during 3 periods,

2010-2011(7TeV) and 2012 (8TeV) at increasing luminosity

and pile-up (interactions per bunch crossing).

Displaced Vertex Searches at ATLAS

• R-Parity (PR = (-1)2s+3B+L)

◄Conservation SUSY particle can not decay only to SM particles

• RPV

◄B or L individually broken do not conflict with current experimental results

◄Can provide a solution to the cosmological baryon asymmetry

◄RPV SUSY can still give a Dark Matter candidate (depending on RPV

couplings strength)

• Unique SUSY signatures to discover ◄Possibly hiding in data!

• Well motivated reason why no signal has yet been seen

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R-Parity Violating Supersymmetry (SUSY)

Re-Tracking

• In our study we utilise Re-Tracking, a

special method of re-doing the tracking

with lowered restriction to let more track

pass.

• Using left-over (“trash”) seeds from

regular tracking

◄Larger impact parameters

◄Lower pT cut on tracks

◄Allow more shared hits between tracks

◄Allow less non-shared hits between tracks

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Regular Re-Tracking

d0 < 10 mm d0 < 300 mm

z0 < 250 mm z0 < 1500 mm

Left-over hits

Impact parameters wrt a vertex

2014年物理学会秋季大会

Background Estimation: Combinatorial background

• Background vertices inside the beam pipe

◄Very high track density

◄Random combination of tracks

◄Small contribution from hadronic interactions

◄Good vacuum

• Estimate the number by use of “vertex-distance-method”

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Signal Region: # tracks ≥ 5 Contribution from Combinatorial background

DV+Jet 0.09±0.002 (stat.) Vertices DV+MET 0.004±0.00008 (stat.) Vertices

DV+Muon 0.0006±0.000007 (stat.) Vertices DV+Electron 0.05±0.0006 (stat.) Vertices

Vertex-Distrance-Method Last step of vertexing Merge vertices within 1 mm of other

vertices

1. Look at vertices in ALL events 2.Close-lying vertices can be

combined (form 2+2 DV, 2+3 DV)

As expected! Very small contribution from Combinatorial background

Estimates: Zero Background Analysis!

Background Estimation: Combinatorial background

• Approach Look at vertices in ALL events

◄Not enough vertices if look at EACH event

◄Count number of vertices found within 1 mm of each other ◄Count as a combination (2+2, 2+3, 3+3…)

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Validation:

•Compare 3D distance

between closest vertices in

Same Event

Using All Events

Zoom in at small

distances 4-trk DV

Use region d < 1 mm to estimate number of 2+2