Overview of Physics Benefits of STT

STT review, 12 March 1998

Horst D. Wahl

\underline{Outline}

• Gains from STTpp – better momentum resolution

– E_{T}/p_{T} cut possible at L2

– determination of track impact parameter (rϕ) and its

significance

• Physics Benefits – t (tt̄, single top)

– Associated Higgs production

– Z → bb̄ events

– b-physics

• z-vertex finding for use in L3 – sharper electron and jet turn-on curves

Present RunII Trigger Scheme

• Bandwidth Allocations:

– L1 in: 7MHz, out: 5-10kHz ; time: 4.2μs

– L2 in: 10kHz, out: 1kHz ; time: 100μs

– L3 in: 1kHz, out: 20Hz ; time: 100 ms/ 50 nodes

• Current Configuration:

– L1: Uses Calorimeter, Fiber tracker (CFT), Muon and Preshower objects. ⇒trigger on Cal E_{T} (em and jets), muon p_{T} (use CFT), track p_{T}, track-preshower stubs

– L2: trigger combines L1 objects into electrons, muons, jets.

• use of SMT information in trigger:

– Currently L1 and L2 track triggers do not make use of hits in the Silicon detector.

– Questionable if L3 will be able to use Silicon information for triggering, as cpu constraints may require starting from L2 object seeds!

Possible Benefits of a Silicon Track Trigger

1. Add Silicon hits in track fit to improve momentum resolution ⇒sharper p_{t} thresholds,

E/p for electrons at L2;

– Potentially benefits ANY trigger

2. Trigger on high impact parameter tracks ⇒trigger on events containing b-quarks;

– Benefits specific physics channels otherwise difficult to trigger on e.g. b-physics, Z → b\overline{b}, Higgs→ b\overline{b}, tphysics, …

3. Use Silicon detector (90^{∘} stereo) information for fast zvertex position ⇒sharper electron and jets p_{T} thresholds at L3,

beam tilt → need z for impact parameter determination;

– Benefits ANY trigger

4. Hit Finder for Level3 ⇒Save processing time in L3 by providing hits positions for r/ϕ and stereo (both 90^{∘} and 2^{∘}, enabling efficient/possible use of Silicon information.

Tasks of the STT (L2 preprocessor)

• finds hit clusters in Silicon Detector

• finds tracks in Silicon Detector (in roads from CFT)

• determines track parameters (p⃗, impact parameter)

• find z-vertex from 90^{∘} stereo hits

• ships information to global L2 processor for decision • ships z-vertex and hit cluster to L3

Performance Studies

Use single track events, μ and e (|η|∼^{<}1.0, 1.5∼^{<}p_{T} ∼^{<}15 GeV)

p_{T} resolution

• CFT momentum computed two ways

(a) use fibers in inner and outer layer only (L2).

(b) use p_{t}^{min} and p_{t}^{max}, the momentum limits from CFT track eqn (L1) ⇒\frac{1}{p_{t}} = \frac{1}{2}(\frac{1}{p_{t}^{min}} + \frac{1}{p_{t}^{max}})

• resolution using STT improves compared to CFT

– for p_{T} = 3 GeV ⇒\frac{σ(ST T)}{σ(CF T (a))} ≈ 0.5 \frac{σ(ST T)}{σ(CF T (b))} ≈ 0.8

– for p_{T} = 15 GeV ⇒\frac{σ(ST T)}{σ(CF T (a))} ≈ 0.3 \frac{σ(ST T)}{σ(CF T (b))} ≈ 0.6

Using E_{T}/p_{T} at L2

Compare E_{T}/p_{T} for tracks with and without SVX info. note : Use both types of CFT momentum calculation.

• E_{T}/p_{T} resolution is better by a factor of 2 for high p_{T} electrons.

• Rejection and efficiency relative to the ‘standard isolated’ electron definition :

p_{T}(ele) = 20 GeV p_{T}(ele) = 5 GeV
p_{T} type  Eff. (%) Bkg Rej. Eff. (%) Bkg Rej.
CFT (a)  90  x3  99  x2
STT+CFT  87  x5  99  x8

Impact Parameter Resolution

• resolution ∼ 15 μm at p_{T} = 15; 35 μm at 2 GeV.

• Tuning of impact parameter errors performed with single pion samples ( p_{T} = 2 to 15 GeV/c.)

• Using the parameterization:

σ_{B}^{2} = σ_{0}^{2} + (\frac{α_{ms}}{P_{T}})^{2}

• Find σ_{0} = 12.6 μm α_{MS} = 49.7 (GeV/c) · μm.

• Define IP significance as:

S_{B} = \frac{B}{σ_{B}(p_{T})}

Impact Parameter Resolution

• Check impact parameter resolution in bb̄ (upper plot) and tt̄ events (lower plot) for STT tracks matched to MC tracks coming from the primary vertex:

• The parameterization of impact parameter errors derived from single pion events is also valid for bb̄ and tt̄ events.

Track Selection

• Select good STT tracks using quality cuts:

1. N_{layer} ≥ 3;

2. Track fit reduced χ^{2} ≤ 4. Note : tracks with χ^{2} ≥ 4 are refitted after dropping the hit with the largest χ^{2} and the cut is reasserted. This leads to 30% gain in efficiency

• χ^{2} cut removes badly reconstructed tracks

– plot shows increase in the width of impact parameter distribution for primary tracks for different χ^{2} ranges : 0–2, 2–4, 4–10, ≥ 10.

Impact Parameter Significance

• IP significance distribution for matched tracks:

– Yellow → tracks coming from primary vertex

• Correlation between high impact parameter tracks and tracks from b-quark decays (yellow histogram)

tt̄ Events

• Signal samples (ISAJET):

1. tt̄ → all jets events (+0, +3 min.bias)

2. tt̄ → μ + jets events

• Background Samples :

– ‘Standard’ QCD background samples generated in 6 p_{T} bins

– samples with 1, 3, 5, 7 additional interactions mixed to simulate L = 2·10^{32} cm^{−2}s^{−1} and beam crossing time = 132 ns;

• high multiplicity of STT tracks, even after | S_{B} |> 2.5 cut

Efficiency Versus Rates

• Calorimeter–only trigger (JET2MED): Level 1: ≥ 2 jets with E_{T} > 7 GeV Level 2: ≥ 2 jets with E_{T} > 20 GeV

⇒ tt̄ → all jets efficiency = 98.3%

L2 background rate = 85 Hz

• JET2MED + STT

⇒ Factor of ∼ 4 background rejection for signal efficiency = 80%

tt̄ Trigger Scheme

• Optimize signal efficiency by combining various triggers

Bgd.(Hz) tt̄ → μ + jets tt̄ → all jets
Trigger  L1 L2 L1(%) L2(%) L1(%) L2(%)
1–JMULT  49.7 2.1 88.9 27.4 98.6 69.8
2–MJTMET  55.2 3.3 93.4 68.5 82.0 48.7
3–JMAX  49.7 13.0 88.9 68.3 98.6 84.2
4–MUJET  64.1 41.6 75.4 74.3 53.2 53.6
5–JET2MED  186 85.2 96.5 88.3 99.3 98.3
Σ (1 → 3)  82.5 17.2 96.0 86.0 99.6 96.2
Σ (1 → 5)  239 113 98.4 96.1 99.9 99.8
Σ (1 → 3)+  239 38.5 98.4 92.9 99.9 98.6

Σ(4 → 5)×ST T

JMULT: ≥ 4 jets with E_{T} ≥ 15 GeV MJTMET: ≥ 3 E_{T}^{jet} ≥ 10 GeV + missing E_{T} ≥ 20 GeV JMAX: ≥ 1 jet with E_{T} ≥ 45 GeV MUJET: ≥ 1 p_{T}^{μ} ≥ 6, E_{T}^{1} ≥ 20 GeV and E_{T}^{2} ≥ 10 GeV JET2MED: ≥ 2 jets with E_{T} ≥ 20 GeV STT: at least 2 tracks with | S |≥ 2.5 (ϵ_{signal} = 80%)

⇒ The STT would allow to optimize the trigger efficiency for tt̄ events without leading to a large background rate increase.

Efficiency and Background for tt̄ Events

• L2JET 2 MED trigger defined as :

≥ 2 jets with E_{T} ≥ 20 GeV.

• Signal efficiency and QCD background trigger rates for the trigger combination L2JET 2 MED * STT:

• e.g requiring at least 1 track with | S_{B} |≥ 3 ⇒a factor 2 reduction of the background rates while keeping a 87% efficiency for the signal.

Efficiency versus Background (tt̄)

Higgs Search

• Signal Sample : pp̄ → W + H^{0}, Z + H^{0} with H → bb̄ and and W → qq̄ (67%); Z → qq̄ (70%)

• Background : “standard sample”

• Tev2000 study pp̄ → W (→ eν, μν) + H^{0}(→ bb̄)

\begin{matrix}M_{Higgs} & ∫ L fb^{−1} \\ 80 & 5 \\ 100 & 10 \\ 120 & 25 \end{matrix}

• extend study beyond leptonic W decays, and include also Z → νν and Z → hadrons

• Specific study :

pp̄ → W + H^{0} → qq̄bb̄

• jet trigger rate and efficiencies :

Cal. Thresh. L1 L2
Trigger  n (L1,L2) GeV r (Hz) ϵ(%) r(Hz) ϵ(%)
JET 3 LOW  3 (3,5)  2000 100 140 78
JET 3 MED  3 (5,10)  200 91  63 74
JET 3 HIGH  3 (7,15)  52 71  15 52
JET 4 LOW  4 (3,5)  670 98  13 36
JET 5 LOW  5 (3,5)  250 93 2.0  8

• All studies relative to JET 3 MED trigger

Track multiplicity

Track multiplicity for signal and background for various track p_{T} thresholds

CFT tracks STT tracks

Efficiency vs. Background Rate

STT p_{T} threshold

Impact parameter and Significance

Benefits of STT for Higgs triggers

Trigger  Background Rejection for ϵ =
90% 80% 50%  10%

N CFT tracks

w/p_{T} ≥ 3 2.5 4.7 10 35

N STT tracks

w/p_{T} ≥ 3  3.1 7.5 40  1000
w/b ≥ 30  2 3.8 27  900

N STT tracks

\overline{b_{25}} ≥ X  2.2 3.8 21  300
w/S_{25} ≥ X  2  5 27  200

N w/p_{T} ≥ 3

and \overline{S_{25}} ≥ X 2.8 7.1 33  650

• rejection(STT)/rejection(CFT) ≈ 1.2 for ϵ_{signal} = 90% ≈ 1.5 for ϵ_{signal} = 80% ≈ 4 for ϵ_{signal} = 50% ≈ 10 for ϵ_{signal} = 10%

• can maintain L2 trigger rate of 20 Hz with efficiency = 68%

Triggering on Z → bb̄

• Control sample for – top mass measurement

– Higgs→ bb̄

• Check b-jet energy scale

• Optimize/check bb̄ mass resolution

• Signal Sample : Z → bb̄ – 10k events

• Background : “standard sample”

• Trigger rates and efficiencies using Cal and CFT objects

Cal  L1  L2
Trigger  n(L1,L2)  r (Hz) ϵ(%) r(Hz) ϵ(%)
JET 2 MIN  2(3,10)  8028 82 1390 67
JET 2 MED  2(5,15)  621 56 264 41
JET 2 MAX  2(7,20)  186 32  85 20
JET 3 MIN  3(3,10)  1502 68 132  9
JET 3 MED  3(5,15)  167 31  25  4

Cal/CFT n(L1,L2)+(n,p_{T})

JET 2 MIN T1 2(3,10)+(2,3)  2389 67 866 57
JET 2 MIN T2 2(3,10)+(3,3)  1319 57 541 50
JET 2 MED T1 2(5,15)+(2,3)  450 48 201 35

• cannot trigger with Cal/CFT only

Z → bb̄: Improvement with STT

Cal/CFT  Silicon Trigger
Trigger  r (Hz) ϵ(%) r(Hz) ϵ(%) r(Hz) ϵ(%)
JET 2 MIN  1390 67  60 35  20 19
JET 2 MED  264 41 110 35  20 23
JET 2 MIN T1  866 57  62 35  20 20
JET 2 MIN T2  541 50  77 35  20 19
JET 2 MED T1  201 35
JET 3 MED  25  4

• ⇒Signal efficiency of 20% with a background rate of 20Hz is achievable • Z → bb̄: expected signal

σ(pp̄ → Z → bb̄) ∼ 1 nb
ϵ(trigger)  =  20%
ϵ(offline)  =  25%  (double b-tag)
⇒σ(vis)  = 5 ×10^{4} fb

• ... over background

σ = 20Hz/2 × 10^{32}/cm^{2}/s = 100 nb
ϵ(offline)  = 10% (double b-tag)
⇒σ(vis)  = 10^{7} fb

• for 1 fb^{−1} : S/B = 5 ×10^{4}/10^{7} S/\sqrt{B} = 17

SUSY 4 b Signature

• g̃g̃ → 4b could give us a handle on the region of SUSY parameter space

• B(g̃g̃ → 4b) is very model dependent.

• Trigger sets are extensions of the JetMax trigger and include CFT and/or STT information.

• Rejections determined relative to JetMax trigger ∼ 13 Hz.

JetMAx: Four L1 jets with E_{T} > 5 GeV and one L2 jet with E_{T} > 45 GeV.

• CFT and STT give comparable eff/rejections for this channel as the track multiplicity in these events are extremely high

\underline{B-physics}

• STT studies using various samples:

1. B_{d}^{∘} → K_{s}^{∘} + J/ψ, J/ψ → μ^{+}μ^{−} (CP asymmetry)

2. B_{s}^{∘} → D_{s}^{−} + 3π^{±}, D_{s}^{−} → K^{+}K^{−}π^{−} (B_{s} mixing)

3. B_{s}^{∘} → D_{s}^{−} + μ^{+} + ν_{μ}, D_{s}^{−} → K^{+}K^{−}π^{−} (B_{s} mixing)

• Low multiplicity of charged particles

• Investigate various combinations of muon triggers and STT.

• Possible trigger scheme for bb̄ events.

Trigger  rate ψ K_{s} D_{s}^{−} + μ^{+} D_{s}^{−} + 3π^{±}
• Single muon 38.6 Hz 23.9% 11.8% 4.6%
• Dimuon +STT 7.6 Hz 14.9% 5.5%  0.3%
• Single + dimuon 45.0 Hz 31.9% 15.6%  4.9%

• ϵ_{trig}(B_{d}^{∘} → J/ψ K_{s}) = 32% ⇒ 8.5k — 13k fully reconstructed events

Single Muon Triggers

• Investigate various options of a single muon trigger.

Trigger Conf.  L2 rate ψ K_{s} D_{s}^{−} + 3π^{±}
• p_{T} > 6, | η |< 2 13.5 Hz 10.8% 1.4%
• p_{T} > 4, | η |< 2 38.6 Hz 23.9% 4.6%
• p_{T} > 4 + CFT 21.0 Hz 13.5% 2.0%
• p_{T} > 4 + STT 13.2 Hz 17.3% 2.5%

• In case the single muon trigger rate would need to be reduced, the STT would be very helpful to preserve a good signal efficiency.

Dimuon Triggers

• Play with p_{T} threshold on both muons:

Trigger  L2 rate ψ K_{s} D_{s}^{−} + μ^{+}
• (2 GeV, 4 GeV)  1.1 Hz 8.8% 2.5%
• (2 GeV, 2 GeV)  272 Hz 20.1% 8.2%
• (2,2) + STT  7.6 Hz 14.9% 5.5%
• (2,2)+ E_{T}^{jet} > 10 GeV 102 Hz 0.9% 0.5%

• The STT allows to reduce the rate of the low threshold trigger (2,2) while preserving a better efficiency than (2,4). It is much more efficiency than asking for a jet.

z vertex Determination

Use hits in Layer1 and Layer3 of the 4 inner barrels of the Silicon detector instrumented with 90^{∘} stereo strips for fast z-vertex position determination

Possible algorithms for z vertex finding:

1. Form all possible tracks connecting the hits in both layers, intersect with beam axis and look for peak(s) in resulting z-distribution to find the vertex;

– number of combinations formidable (4000+) for high multiple interaction events

2. Move along z-axis (in bins), connect with hit on outer layer, look for matching hit on inner layer; look for z-bins with many matching hits (find peak(s) in z-distribution).

– Possible to implement this by scaling the inner layer hits to outer layer radii and looking for possible coincidences.

– Independent of number of interaction in the events

• z-vertex finding region limited to ∼ ±25cm due to limited # of barrels with 90^{∘} stereo strips.

Event vertices

Z → bb̄+ 2 minbias events

• Event 1: – High p_{T} vertex correctly identified

– 3rd vertex at 45 cm

• Event 2: – Min Bias vertex identified as high p_{T} vertex – High p_{T} vertex at 15.5 cm

– 3rd vertex at -71 cm

z-vertex Resolution and efficiencies

• Sample used :

– Z → bb̄ events (199 events)

– Z → bb̄+ 2 minbias events (199 events)

• z-vertex resolution ∼ 600μm ⇒independent of additional interactions in the event

No of events  199 199
Found at least one vertex  145 196
vertex not found  54 3
High p_{T} vertex |z|∼^{<} 30cm  153 153
Found vertex is High p_{T} vertex  145 112
High p_{T} vertex (|z|∼^{<} 30cm)
Efficiency of finding High p_{T} vertex 95% 73%
”wrong vertex” events  - 26%

z-vertex Distributions

Gain for electron and jet thresholds at L3

• Electrons :

• Jets : (Ransom Stephens)

• Sharper turn-on for electron and jets at L3

• (Not clear if fast vertexing available at L3)

\underline{Conclusions}

• use of Si detector hits in track fit

⇒improve momentum resolution

⇒sharper p_{t} thresholds, E/p for electrons at L2;

• trigger on tracks with high impact parameter ⇒trigger on events containing b-quarks;

– provides very powerful handle for background rejection, with good signal efficiency, for many interesting physics channels:

∗ B-physics,

∗ Z → b\overline{b},

∗ Higgs→ b\overline{b},

∗ tt̄,

∗ single top

∗ …

• use Si detector (90^{∘} stereo) information for fast z-vertex position ⇒ sharper electron and jet p_{T} thresholds at L3

• Hit finder for L3 ⇒ save processing time in L3 by providing hit positions for r/ϕ and stereo (both 90^{∘} and 2^{∘}), making use of Si detector information at L3 possible or more efficient.

SUMMARY

• have done simulations of performance of STT as realistic as possible with the available tools;

• have made assessment of incremental gains in rejection power over that possible with existing trigger tools;

• simulation of performance was done with algorithms similar to what can be implemented in hardware;

• have shown that STT expands capabilities of presently foreseen trigger system, adding additional handles for background rejection and rate control.