Surface Modification of Silica Particles and Upconverting Particles ...
Search for Long-Lived, Heavy Particles using...
Transcript of Search for Long-Lived, Heavy Particles using...
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..
2014-09-18 2014年物理学会秋季大会 2
A.Arvanitaki, N.Craig, S.Dimopoulos and
G.Villadoro “Mini-Split”, JHEP 1302, 126
(2013)
Displaced
Gluino
Decays
Introduction (1/2)
2014-09-18 2014年物理学会秋季大会 3
(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
2014-09-18 2014年物理学会秋季大会 4
1000 mm
300 mm
1000 mm 300 mm
R
Z
Displaced Decays • Event View of a
Displaced Decay
• Using ◄ MC Signal Sample
◄χ0 qqμ
2014-09-18 2014年物理学会秋季大会 5
Signal efficiency for χ0 qqμ For one mass-
point
~ 30%
Beam pipe
Pixel SCT TRT
Displaced Vertex Reconstruction Efficiency
2014-09-18 2014年物理学会秋季大会 6
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
2014-09-18 2014年物理学会秋季大会 7
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
2014-09-18 2014年物理学会秋季大会 8
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
2014-09-18 2014年物理学会秋季大会 9
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
2014-09-18 2014年物理学会秋季大会 10
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)
2014-09-18 2014年物理学会秋季大会 11
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
2014-09-18 2014年物理学会秋季大会 12
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)
2014-09-18 2014年物理学会秋季大会 13
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
2014-09-18 2014年物理学会秋季大会 14
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)
2014-09-18 2014年物理学会秋季大会 15
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
2014-09-18 2014年物理学会秋季大会 16
Estimates: Zero Background Analysis!
Prepare for Run-II
BACKUP
2014-09-18 2014年物理学会秋季大会 17
THE LHC-ATLAS EXPERIMENT
2014-09-18 2014年物理学会秋季大会 18
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
2014-09-18 2014年物理学会秋季大会 19
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
2014-09-18 20
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”
2014-09-18 2014年物理学会秋季大会 21
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…)
2014-09-18 2014年物理学会秋季大会 22
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