Status of MAPS ECAL clustering

CALICE-UK meeting

27th March, 2007

at Imperial College, London

Yoshinari Mikami

University of Birmingham

On behalf of MAPS ECAL group

Outlines:

Feasibility studies before clustering

MAPS ECAL primary electron clustering algorithm

Energy resolution after clustering

Summary and next steps

Introduction

Clustering algorithm development of primary electron for MAPS ECAL which has many cell hits in each event. -> Roughly 100 hits per GeV of electron shower with 50umX50um cell size case

First trial of MAPS clustering R&D (all shown here are very preliminary studies)

Feasibility study:
Number of hits in each layer at 1 GeV electron

Objective is enough high efficiency at 1 GeV electron.

~9 hits/event in 7th layer

~5 hits/event in 2nd layer

Longitudinal shower shape

at 1 GeV e-

Base line of clustering algorithm

Finding initial group of hits within one of inner layers.

Requiring several hits are within circle of mm order radius.

Deciding direction of cluster : Searching hits in outer layers which has located within hemisphere from initial hit. -> From the centre of gravity in the initial grouping within inner layer to the centre of gravity in the hemisphere.

Adding all hits in 30 layers within cylinder of Moliere radius order.

Clustering algorithm (1.1)

Finding initial group of hits within one of inner layers.

Requiring several hits are within circle of mm order radius.

y mm

z mm

x mm

1 GeV single e-,

single event

Clustering algorithm (1.2)

y mm

z mm

x mm

2. Deciding direction of cluster : Searching hits in outer layers which has located within hemisphere from initial hit. -> From the centre of gravity in the initial grouping within inner layer to the centre of gravity in the hemisphere.

Clustering algorithm (1.3)

3. Adding all hits in 30 layers within cylinder of Moliere radius order.

y mm

z mm

x mm

Efficiency of clustering (1);
(With initial grouping radius dependence
and with #hits dependence)

Efficiency = #Event which have hits grouping within one of inner layers

/ #Events of all generated single e-

(Grouping was done within the same layer. No threshold and no noise are applied.)

1 GeV single e- using inner seven layers

1 GeV single e- using inner three layers

Efficiency of clustering (2);
(With cell hits energy threshold dependence
and with primary electron's energy dependence)

Finding initial grouping of hits within one of inner 7 layers.

More than total 4 hits are within circle of 5.0 mm radius.

Applying threshold for all 4 hits

500 MeV e-

400 GeV e-

B fields is off:

0 10 keV

Cluster direction

ex. at

1 GeV e-

B fields is off

3.0 cm hemisphere radius

2. Deciding direction of cluster : -> From the centre of gravity in the initial

grouping within inner layer to the centre of gravity in the hemisphere.

Generated

direction

q

Centre of gravity for

initial grouping

Centre of gravity of

hits inside hemisphere

Hemisphere radius have to be optimized with physics events.

(In order to avoid merging two neighbour clusters)

Direction is affected significantly by B fields effect for low energy case.

-> Temporarily clustering hemisphere radius is using 3.0 cm.

Shower spread &
Efficiency of cell hits with clustering

B fields is off

Electron is injected from IP to zenith

All cell hits without any criteria

1 GeV e-

x position RMS ~9.1mm

5 GeV e-

x position RMS ~7.7mm

Cylinder radius have to be optimized with physics events.

(In order to avoid merging two neighbour clusters)

-> Temporarily clustering cylinder radius is 2.0 cm.

Efficiency = #Cell hits inside cylinder

/ All #cell hits in event

(With 1800eV energy threshold for both case.)

Sower spread distributions:

Tentative clustering criteria

Finding initial group of hits within one of inner 7 layers.

Requiring more than total 4 hits are within circle of 5.0 mm radius.

Deciding direction with using hits which has located within 3.0 cm hemisphere from initial hits.

Adding all hits in 30 layers within cylinder of 2.0 cm radius.

Tentative clustering criteria (red variables need be optimized):

0. Applying 1800 eV (half of MIP peak) threshold for all cell hits energy

Energy resolution after clustering at 1 GeV e-

1 GeV e-

Without clustering

s(E)/E = (13.1 +/- 0.2stat)%

1 GeV e-

After clustering

s(E)/E = (14.5 +/- 0.2stat)%

Roughly 10% effect at 1 GeV.

B fields is off

Using Gauss fitting

Using Geant4 output which would be very roughly correspond to output after charge diffusion plus digitization.

Double counts removing in clustering algorithm is not yet. (->Temporarily, one cluster per event is required.)

Weighted number of cell hits is used for different W thickness layers.

Applied 1800eV threshold for all cell hits

Linearity
after primary electron clustering

Energy resolution
after primary electron clustering

s(E) / E = (14.1Ø0.2stat)% / + (0.38Ø0.04stat)%

s(E) / E = (13.5Ø0.1stat)% / + (0.35Ø0.02stat)%

Without clustering:

After clustering:

Clustering effect is several percent. -> It looks reasonable.

Energy resolution with cylinder radius and hemisphere radius dependence

Have to be optimized with general physics event.

(In order to avoid merging two neighbour clusters)

Magnetic effect for 1 GeV e-

s(E)/E= (15.4 +/- 0.2)%

s(E)/E = (14.3 +/- 0.2)%

s(E)/E = (13.6 +/-0.2)%

s(E)/E= (13.9 +/- 0.2)%

Without

clustering:

B fields is off:

B fields is on:

After

clustering:

Electron is injected just in front of ECAL for all cases.

-> Magnet effects is roughly several to 10 percent at 1 GeV.

Summary and next steps

Summary:

Base line of MAPS clustering algorithm looks working well.

Next steps:

Algorithm of removing double counts for physics event case.

Optimizing clustering criteria using 4T magnetic fields, charge diffusion, digitization, dead area and physics events.

Study of energy resolution and spatial resolution with them.

Angular dependence study

Cleaning codes to save CPU time as possible as I can.

Clustering code release as Marlin processor

Physics event studies

yoshi mikami

2006-10-13T18:36:51