# Presentation: 128339

## First look at PFA/clustering with RPC-based calorimeter

- Progress Report

## Step 1: Gas calorimetry

- GEANT 3.21 modeling
- Hadron shower simulation (GCALOR+GFLUKA) consistent with MINOS test calorimeter
- 2 cm iron, 1x1 cm2 readout pads
- Pad multiplicity = 1
- + with p = 2,5,10,20,50,100 GeV/c, 1000events at each momentum

-  Significant non—linearity of the response (~20% @ 100 GeV)
-  Large constant term (~10%) for the energy resolution
-  Why ?

## Gas calorimetry ctnd

-  20 GeV:
-  E/E 0.132, or
-  E/E=0.59/√E
-  Fairly gaussian response
-  2 GeV (‘low energy’):
-  long tail towards higher response
- It is caused by particles traversing long distance before the interaction
- Expect very large difference in the response to charged and neutral particles
-  100 GeV (‘high energy’):
-  long tail towards low energies
-  caused by multiply hit cells inside EM showers
-  saturation leads to degradation of energy (constant term, non-linearity)

## PFA: what do we want?

- PFA Challenge:
-  identify and discard all red/green points
- Identify and count all blue points
- Chief (?) difficulties:
-  identify ‘blue’ cluster in the midst of the red/green one
- Properly identify the disconnected red cluster (a.k.a. ‘fragment’)

## PFA: is it obviously impossible?

- Yes?
- Hadrons impact the calorimeter at ~ 10 cm distance
- Hadronic shower has transverse dimension of ~40-50 cm
- Hadronic showers are extremely irregular, they do not follow ‘shower  profile’
- No?
- Hadronic showers are extremely irregular, they do not follow ‘shower  profile’
- Shower develops in 3 dimensions. ALL displays are projections on 2D plane and they convey  unnecessarily  pessimistic picture
- Although to contain the shower energy one needs a ‘cylinder’ ~40-50 cm, L=100 cm for any particular hadron shower this cylinder is very sparsely occupied. Example: such a cylinder contains ~8,000 readout cells, 1 x 1 cm2. Only ~ 1000 of them are hit. Occupancy is ~12%

- PFA Challenge: develop a metric in the hit cells space
-  which optimizes the separation of ‘charged hadron cluster’ from ‘neutral hadron clusters’
- Figure of merit: minimize fluctuations of the energy in the clusters classified as  ’neutral hadrons’ about the true energy of the neutral hadrons
- Auxiliary information: momentum and spatial position of charged hadrons, possibly energy deposition in the hit cell

## First try: cartesian distance 

- Find trees of hits with close proximity, d<dcut
- Here the example of 20 GeV charged pion, dcut=5 cm
- ‘Objetcs’ found:
- Clusters
- Single points

## Cartesian distance, typical example

- 20 GeV +
-  dcut = 20 cm

## Total energy of the ‘main cluster’

- High energy showers are more collimated, hit cells are closer

## “Fragments” multiplicity and energy

- Energy of the ‘second’ cluster
- (~10 hits =  1 GeV)

- Total number of clusters found

## Leftovers: single hits

- ‘free floating’  single hits are probably harmless, there are so few of them that they will not lead to accidental cluster formation
- Ignoring scattered single one modifies the effective energy calibration (1-2% effect) but induced non-linearity of the response is minimal.

- This was the simplest choice. Metric closest to ones intuition, but surely not the optimal one.
- ‘Improvement’: showers are cigars rather than spheres as pt of particles produced in hadronic interaction is limited to ~ 300 MeV/c.
- Transverse distance between cells less likely than the longitudinal one

## ‘Transverse metric’  I

- Significant improvement: better energy containment in the main cluster, smaller secondary cluster

## ‘Transverse metric’ II

- Significant improvement: fewer secondary clusters, fewer left-over cells