1 LumiCal Optimization Simulations Iftach Sadeh Tel Aviv University Collaboration High precision design May 6 th 2008

2 Performance requirements 1.Required precision is: 2.Measure luminosity by counting the number of Bhabha events (N):

3 Design parameters 3. Layers:  Number of layers - 30  Tungsten Thickness mm  Silicon Thickness mm  Elec. Space mm  Support Thickness mm 1. Placement:  2270 mm from the IP  Inner Radius - 80 mm  Outer Radius mm 2. Segmentation:  48 azimuthal & 64 radial divisions:  Azimuthal Cell Size mrad  Radial Cell Size mrad

4 E res ( θ max ) E res ( θ min )  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 (E res ) / 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, θ μ, denotes the scattering angle of the two final state muons. “Contrasting Supersymmetry and Universal Extra Dimensions at Colliders” – M. Battaglia et al. (

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 E res

9 Number of radial divisions σ(θ) Δθ  Dependence of the polar resolution, bias and subsequent error in the luminosity measurement on the angular cell-size, l θ.

10 Inner and outer radii  Beamstrahlung spectrum on the face of LumiCal: For the preferable antiDID case R min must be larger than 7cm. ( Shown by C.Grah at the Oct 2007 FCAL meeting )

11 Thickness of the tungsten layers σ(θ) Δθ E res ( The cut matters! )

12 Clustering - Event Sample  Bhabha scattering with √s = 500 GeV θ Φ Energy  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

17 Summary  Optimal parameters for the present detector- concept: 1.[R min → R max ] = [80 → 190] mm → σ B = 1.23 nb radial divisions (0.8 mrad radial cell-size) → Δθ = 3.2∙10 -3, σ θ = 2.2∙10 -2 mrad → ΔL/L = 1.5∙ 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 E res ≈ 0.21 √GeV.

18 Auxiliary Slides

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, r eff (l) / Moliere Radius, R M  Shower profile - R M is indicated by the red circle.  Dependence of the layer- radius on the layer number, l. R M (layer-gap) RMRM r(l)

21 Clustering - Energy density corrections  Event-by-event comparison of the energy of showers (GEN) and clusters (REC). BeforeAfter

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 (N 1→2 ), and the number of showers pairs which were reconstructed as single clusters, (N 2→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) Energy high θ high θ low Energy low Δθ high,low  Energy and θ of high and low-energy clusters/showers.  Difference in θ between the high and low-energy clusters/showers.