1

LumiCal Optimization Simulations

Iftach Sadeh

Tel Aviv University

CollaborationHigh precision design

May 6th 2008

2

Performance requirements

1. Required precision is:

2. Measure luminosity by counting the number of Bhabha events (N):

year/10,10~

year/10,10~

year/10decays) Z(hadronic GigaZ,10~

63

63

94

qqeeL

L

WWeeL

LL

L

max

min

gen

genrec

N

NN

N

N

L

L

3

1Bhabhad

d

NL

RIGH LEFTTΔθ - θθ

RIGHTθ

LEFTθ

3

Design parameters

3. Layers:

Number of layers - 30

Tungsten Thickness - 3.5 mm

Silicon Thickness - 0.3 mm

Elec. Space - 0.1 mm

Support Thickness - 0.6 mm

1. Placement:

2270 mm from the IP

Inner Radius - 80 mm

Outer Radius - 190 mm

2. Segmentation:

48 azimuthal & 64 radial divisions:

Azimuthal Cell Size - 131 mrad

Radial Cell Size - 0.8 mrad

4

Eres(θmax)Eres(θmin)

Choose constant which minimizes the resolution, σ(θ), but does not necessarily minimizes the bias as well.

Define minimal and maximal polar angles for a shower.

σ(θ) Δθ

Energy resolution (Eres) / Polar resolution and bias (σ(θ) , Δθ)

Min{Δθ}

Min{σ(θ)}

5

MIP (muon) Detection Many physics studies demand the ability to detect muons (or the lack thereof) in

the Forward Region.

Example: Discrimination between super-symmetry (SUSY) and the universal extra dimensions (UED) theories may be done by measuring the smuon-pair production process. The observable in the figure, θμ, denotes the scattering angle of the two final state muons.

“Contrasting Supersymmetry and Universal Extra Dimensions at Colliders” – M. Battaglia et al. (http://arxiv.org/pdf/hep-ph/0507284)

1 1 1 1

2UED:

~ 1 coscos

e e

d

d

0 01 1

2SUSY:

~ 1 coscos

e e

d

d

6

MIP (muon) Detection

Multiple hits for the same radius (non-zero cell size).

After averaging and fitting, an extrapolation to the IP (z = 0) can be performed.

7

Induced charge in a single cell Energy/Charge conversion:

Distribution of the deposited energy spectrum of a MIP (using 250 GeV muons):MPV = 89 keV ~ 3.9 fC.

Distributions of the charge in a single cell for 250 GeV electron showers, and of the corresponding maximal cell signal (for 96 and 64 radial divisions).

8

Digitization

σ(θ)

Δθ

Eres

9

Number of radial divisions

σ(θ) Δθ

min

2

L

L

-1

5

500GeV

1.23nb

500 fb

4 10

s

L

N

N

Dependence of the polar resolution, bias and subsequent error in the luminosity measurement on the angular cell-size, lθ.

10

Inner and outer radii

Beamstrahlung spectrum on the face of LumiCal: For the preferable antiDID case Rmin must be larger than 7cm.

( Shown by C.Grah at theOct 2007 FCAL meeting )

-1500 fbL

11

Thickness of the tungsten layers

σ(θ) Δθ

Eres

Δθ

Min{Δθ}

Min{σ(θ)}

( The cut matters! )

12

Clustering - Event Sample Bhabha scattering with √s = 500 GeV

θ ΦEnergy

Separation between photons and leptons:

- As a function of the energy of the low-energy-particle (angular distance).

- Distribution of the distance (on the face of LumiCal).

13

Clustering - Algorithm

Phase I:Near-neighbor clustering in a single layer.

Phase II:Cluster-merging in a single layer.

14

Clustering - Algorithm

Phase III:Global-clustering.

15

Clustering - Results

Merging-cuts:

16

Clustering - Geometry dependence

-1500 fbL

17

Summary

Optimal parameters for the present detector-concept:

1. [Rmin → Rmax] = [80 → 190] mm → σB = 1.23 nb.

2. 64 radial divisions (0.8 mrad radial cell-size)→ Δθ = 3.2∙10-3 , σθ = 2.2∙10-2 mrad→ ΔL/L = 1.5∙10-4 .

3. 48 azimuthal → enough for clustering, but shouldn’t be lower…

4. Tungsten thickness of 3.5 mm → 30 layers are enough for stabilizing the energy resolution at Eres ≈ 0.21 √GeV.

18

AuxiliarySlides

19

Leakage through the back layers

(normalized) energy deposited per layer for a 90-layer LumiCal.

Distribution of the total energy for a LumiCal of 30 or 90 layers.

20

Effective layer-radius, reff(l) / Moliere Radius, RM

Shower profile - RM is indicated by the red circle.

Dependence of the layer-radius on the layer number, l.

RM(layer-gap)

RMr(l)

21

Clustering - Energy density corrections

Event-by-event comparison of the energy of showers (GEN) and clusters (REC).

Before After

22

Clustering - Results (relative errors) Dependence on the merging-cuts of the errors in counting the number of

single showers which were reconstructed as two clusters (N1→2), and the number of showers pairs which were reconstructed as single clusters, (N2→1).

23

Clustering - Results (event-by-event)

Event-by-event comparison of the energy and position of showers (GEN) and clusters (REC).

θ Φ

Energy

24

Clustering - Results (measurable distributions)

Energyhigh

θhigh θlow

Energylow

Δθhigh,low

Energy and θ of high and low-energy clusters/showers.

Difference in θ between the high and low-energy clusters/showers.