Fast TracKing at ATLAS Why and How Jamie Saxon University of - - PowerPoint PPT Presentation

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Fast TracKing at ATLAS Why and How Jamie Saxon University of - - PowerPoint PPT Presentation

Fast TracKing at ATLAS Why and How Jamie Saxon University of Chicago What is the FTK? Global tracking early in the HLT (100 s). (p T , , , d , z , hits, and ) Dramatic step for the ID in the trigger. Currently


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SLIDE 1

Fast TracKing at ATLAS

Why and How

Jamie Saxon University of Chicago

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SLIDE 2

What is the FTK?

  • Global tracking early in the HLT (100 µs).

(pT, η, φ, d₀, z₀, hits, and χ²)

  • Dramatic step for the ID in the trigger.
  • Currently in production and installation.
  • Operating next year through 2022.
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SLIDE 3

Why do this?

  • A. Lower thresholds for b, τ triggers.
  • Tracking currently limited to cones around

L1-objects.

  • 3rd gen very interesting for Run II.
  • B. Confront pileup through vertexing.
  • Good for pileup corrections, multijet triggers,

and Ɇᵀ corrections/track Ɇᵀ.

  • C. Exotic: displaced vertices, rare flavor,

unbiased sample (large µ), ‘mini-events.’

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SLIDE 4

How? (Algorithmically)

φ2

φ1

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SLIDE 5

φ2 φ1

Not a Track Track Not a Track Maybe!?

How? (Algorithmically)

φ2

φ1

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SLIDE 6

φ2 φ1

Not a Track Track Not a Track Maybe!?

How? (Algorithmically)

  • 1. Find patterns of

plausible candidates.

φ2

φ1

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SLIDE 7

How? (Algorithmically)

  • 1. Find patterns of

plausible candidates.

  • 2. Evaluate χ², linearized in

small detector regions.

φ2

φ1

φ2 φ1

Track Maybe!?

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SLIDE 8

How? (Algorithmically)

  • 1. Find patterns of

plausible candidates.

  • 2. Evaluate χ², linearized in

small detector regions.

  • 3. ‘Guess’ missing hits.

φ2

φ1

φ2 φ1

Track Maybe!?

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SLIDE 9

How? (Algorithmically)

  • 1. Find patterns of

plausible candidates.

  • 2. Evaluate χ², linearized in

small detector regions.

  • 3. ‘Guess’ missing hits.
  • 4. Linearized calculation of

helix parameters.

φ2

φ1

φ2 φ1

Track Maybe!?

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SLIDE 10

At ATLAS…

Silicon Hits HLT

Photos: atlasftk.uchicago.edu/photos/

  • Split pixel and SCT hits from the

detector into 64 parallel pipelines.

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SLIDE 11

Data Formatter

Data Formatter

  • Cluster hits, share them among regions.
  • Finite beamspot, curvature at low-pT.

Silicon Hits

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SLIDE 12

Auxiliary Card

Data Formatter

Auxiliary Card

  • Coarse resolution hits to pattern matching.

Silicon Hits

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SLIDE 13

Auxiliary Card Assoc. Memory Board

Data Formatter

Associative Memory Board

  • Find coarse-resolution track candidates.
  • Massive fanout to 64 custom chips.

AM Chip 06

  • Loads hits in memory.
  • All candidates matched

simultaneously (magic).

  • Variable-width patterns.
  • Optimized for low-power.

Silicon Hits

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SLIDE 14

Auxiliary Card Assoc. Memory Board

Data Formatter

Auxiliary Card

  • Linearized χ² for patterns matched in

the AMB, using 8 detector layers.

Silicon Hits

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SLIDE 15

Auxiliary Card Assoc. Memory Board

Second Stage Board

  • Extrapolate aux. fit to 12 layers.
  • Calculate track parameters, new χ².

Second Stage Board

Data Formatter Silicon Hits

4 silicon layers

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SLIDE 16

Auxiliary Card FTK- Level 2 Interface Card Assoc. Memory Board

Data Formatter

Second Stage Board

FTK-Level 2 Interface Card

  • Restore ‘global’ hit coordinates.
  • Package complete events for HLT.

Silicon Hits HLT

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SLIDE 17

The System

  • 322 9U boards, 640 mezzanine cards,

7 racks… 250B fits/second.

Silicon Hits HLT

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SLIDE 18

Tracking Performance

  • Efficiencies WRT offline > 90%.
  • Excellent resolution for η, φ, d₀, z₀.
  • Good pT resolution; ‘cheap’ to refit.

[GeV]

T

p 10 20 30 40 50 60 70 80 90 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1

muon pion

Simulation, no IBL ATLAS

Efficiency WRT Offline

Resolution at 10 GeV

pT 0.5 GeV η 0.0015 φ 0.001 d₀ 0.06 mm z₀ 0.25 mm

FTK TDR: cds.cern.ch/record/1552953

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SLIDE 19

Physics Performance

d0 Significance

  • 20
  • 10

10 20 30 40 Normalized Entries

  • 5

10

  • 4

10

  • 3

10

  • 2

10

  • 1

10 ATLAS Simulation, no IBL | < 1.1) η Barrel (| > = 69 µ <

Offline Light-Flavor Offline b-Jet FTK Light-Flavor FTK b-Jet

  • Great discrimination on physics

quantities, e.g., σ(d₀)!

FTK TDR: cds.cern.ch/record/1552953

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SLIDE 20

Trigger Impact: τ’s and b’s

  • Efficiencies v. rates for b and τ triggers, WITH

and or WITHOUT FTK: significant gains.

  • What can you do with global tracking?

Tau Triggers b-Jet Triggers

FTK TDR: cds.cern.ch/record/1552953

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SLIDE 21

Take-Away

  • Starting next year, FTK will provide global

tracking for every level 1 trigger at ATLAS.

  • Good resolution of track parameters.
  • > 90% efficient WRT offline.
  • Threshold-less b and τ-tagging, PV

information, and ‘exotic’ applications.

  • Exciting time: intellectual challenges,

hands-on work, and physics potential now.