Progress with the Development of Energy Flow Algorithms at Argonne José Repond for Steve Kuhlmann...

Progress with the Development of

Energy Flow Algorithms at Argonne

José Repond

for Steve Kuhlmann and Steve Magill

Argonne National Laboratory

Linear Collider Workshop, Amsterdam, April 1 – 4, 2003

Simulation Software

Package JAS and GIZMO

Conversion to GEANT4 soon

Detector SD or ‘Small’ detector

Si-W ECAL 5x5 mm2

Scintillator-Fe HCAL 10x10 mm2

Track pattern recognition included

Overview of Algorithm

1st step - Track extrapolation thru Cal

– substitute for Cal cells in road (core + tuned outlyers)

- analog* or digital techniques in HCAL – S. Magill

2nd step - Photon finder (use analytic long./trans. energy

profiles, ECAL shower max, etc.) – S. Kuhlmann

3rd step - Jet Algorithm on tracks and photons - Done

4th step – include remaining Cal cells (neutral hadron

energy) in jet (cone?)

Optimize Cal segmentation for separation of charged/neutral clusters

* V. Morgunov, CALOR2002

Define D-weight: - for every cell - area of ~ 40 cells - D-weight = #/40 E-weight: - simply take energy of cell

cell density weight = 3/40

area ~ 40 cellsred – E fraction for density > 1/#blue – E fraction outside area

# cells in window

digital cal

analog cal

Track Extrapolation/Shower Link Algorithm

D-Weights: in ECAL at Interaction Layer 20

20 layers after π interacts

Response to single π with 10 GeV…

#eve

nts·

wei

ght

If D-weight:

≡ 1 Breit-Wigner

≡ n/40 Gaussian

θ φ

D-Weights: in HCAL at Interaction Layer 10

If D-weight:

≡ 1 Breit-Wigner

≡ n/40 Gaussian

θ φ

E-CAL: Energy in cell vs cell density

MIP signal at 8 MeV

cell density n/40

cell

energ

y (

GeV

)

MIP signal at 36 MeV

what’s this?

cell

energ

y (

GeV

)

cell density n/40

H-CAL: Energy in cell vs cell density

Soft stuff

in

Scintillator???

HCAL: analog E fraction only sum up if Ecell ≥ 1 MIP

ΣE/10 GeVSome losses…

Effect on energy resolution to be investigated…

HCAL: Cell Density (in 40 cell window)

31% single cell windows

mean ~ 4 cells

Seed Cell Distribution defined as cell w/ cell density > 1/40

In most cases

number of seed

cells = 0

Number of seed cells

D-weights: comparison with event display

Blue – allRed – density > 1/40Green – density > 3/40

Track Extrapolation/Shower Link Algorithm

1. Pick up all seed cells close to extrapolated track

- Can tune for optimal seed cell definition- For cone size < 0.1 (~6o), get 85% of energy

2. Add cells in a cone around each seed cell through n layers

3. Linked seed cells in subsequent cones form the reconstructed shower

4. Discard all cells linked to the track

Hadronic Z decays at √s = 91 GeV…

To develop Photon finder

Cuts to select photon clusters and reject anything else

I. EM clusters rejected within 0.03 of extrapolated track within 0.01 if track MIP in all 30 layers

II. EM clusters required to have shower maximum energy > 30 MeV (SME is sum of layers 8,9 and 10) still needs fine tuning

III. Require Ecluster/ptrack > 0.1, if EM cluster within 0.1 of track

Definition of EM cluster

Cluster of calorimeter energies within a cone of 0.04

No requirement on EECAL/EHCAL or EHCAL

Small loss of EM clusters

I. Cut on distance to track

Probability of overlapof γ and track

0.1% within ΔR < 0.02 3.3% within ΔR < 0.1 11% within ΔR < 0.2

Reject EM clusters if ΔR < 0.03 < 0.01 if MIP in all 30 layers of ECAL

2 GeV e-

2 GeV -

MeV

II. Cut on energy at shower maximum

MeV

Require SME > 30 MeV

ΔR from EM Cluster to Track

EM

Clu

ster

Ene

rgy/

Tra

ck E

III. Energy – momentum ratio

Clusters left after previous cuts

10 GeV π-

Require Ecluster/ptrack > 0.1 for ΔR <0.1

Hadronic Z Decays at s = 91 GeV

Total Hadron Level Photon Energy (GeV)

Tot

al P

hoto

n C

andi

date

Ene

rgy

After all cuts…

μEM = 0.25 GeV

σEM = 2.8 GeV

Hadronic Z Decays at s = 91 GeV

Total Photon Energy - Total Monte Carlo Photons (GeV)

Perfect EFA

Goal σEM = 1.4 GeV

Compare to h0 σh = 2.9 GeV

Simulation of different active media

Gas Electron Multipliers

J Li, A White, J Yu: University of Texas in Arlington

Simulation of both detailed and simple GEM geometries

Resistive Plate Chambers

L Xia: Argonne National Laboratory

Single π Resolution

Summary

1. Continuing work on implementation of algorithm

2. Tune to single particles first, then to particles in jets

3. Implement photon finder

4. Deal with neutral hadron energy

5. Compare performance to analog version (SNARK)

6. Use EFA to optimize transverse cell size of DHCAL

7. Compare performance with different active media:

Scintillator, GEMs and RPCs