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Update on EIC detector Performance Simulations. E.-C. Aschenauer, T. Barton, R. Darienzo, A. Kiselev BNL, 06/05/2013. Contents. EicRoot framework development EIC detector solenoid modeling EIC smearing generator update TODO lists. EicRoot development. EIC in FairRoot framework.

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E c aschenauer t barton r darienzo a kiselev bnl 06 05 2013

Update on EIC detector

Performance Simulations

E.-C. Aschenauer, T. Barton,

R. Darienzo, A. Kiselev

BNL, 06/05/2013


Contents
Contents

  • EicRoot framework development

  • EIC detector solenoid modeling

  • EIC smearing generator update

  • TODO lists

A.Kiselev



Eic in fairroot framework
EIC in FairRoot framework

  • FairRoot is officially maintained by GSI; dedicated developers

  • O(10) active experiments; O(100) users

CbmRoot

  • ROOT

  • VMC (GEANT3, GEANT4)

  • VGM (ROOT, GEANT)

R3BRoot

FairRoot external

package bundle

FairBase

C++ classes

PandaRoot

EicRoot

eic-smear

-> Make best use of FairRoot development

-> Utilize efficiently existing codes developed by EIC taskforce

A.Kiselev


End user view
End user view

  • No executable (steering through ROOT macro scripts)

-> MC points

simulation

digitization

reconstruction

“PID” Pass

-> Hits

-> “Short” tracks

-> Clusters

-> “Combined” tracks

-> Vertices @ IP

  • ROOT files for analysis available after each step

  • C++ class structure is well defined at each I/O stage

A.Kiselev




Detector view in eicroot
Detector view in EicRoot

FEMC

CEMC

SOLENOID

BEMC

  • EMC and tracking detectors implemented so far

A.Kiselev



General
General

  • Magnetic field interface exists

  • Detector geometry is described in 0-th approximation:

  • Digitization exists (simple yet useable)

  • “Ideal” track reconstruction inherited from PandaRoot codes

  • Silicon vertex tracker

  • Silicon forward/backward tracker

  • TPC

  • GEM forward tracker

A.Kiselev


Vertex silicon tracker
Vertex silicon tracker

  • MAPS technology; ~20x20mm2 chips, ~20mm 2D pixels

  • STAR upgrade “building blocks” (cable assemblies)

MAPS R&D for EIC within BNL LDRD

A.Kiselev


Vertex silicon tracker1
Vertex silicon tracker

  • 6 layers at [30..160] mm radius

  • 0.37% X0 in acceptance per layer simulated precisely;

  • digitization: single discrete pixels, one-to-one from MC points

A.Kiselev


Other tracking elements
Other tracking elements

forward/backward silicon trackers:

  • 2x7 disks with up to 280 mm radius

  • N sectors per disk; 200mm silicon-equivalent thickness

  • digitization: discrete ~20x20mm2 pixels

TPC:

  • ~2m long; gas volume radius [300..800] mm

  • 1.2% X0 IFC, 4.0% X0 OFC; 15.0% X0 aluminum endcaps

  • digitization: idealized, assume 1x5 mm GEM pads

GEM trackers:

  • 3 disks behind the TPC endcap

  • STAR FGT design

  • digitization: 100mm resolution in X&Y; gaussian smearing

A.Kiselev


Tracker zoomed view
Tracker zoomed view

FGT

FST

VST

BST

TPC

BGT

A.Kiselev


Tracking scheme
Tracking scheme

  • So-called ideal PandaRoot track “finding”:

  • PandaRoot track fitting code:

  • Monte-Carlo hits are digitized on a per-track basis

  • Effectively NO track finder

MRS-B1 solenoid

design used

  • Kalman filter

  • Steering in magnetic field

  • Precise on-the-fly accounting of material effects

-> pretty much useable for acceptance and single-track resolution studies;

-> less suitable for radiation length scans;

-> hardly useful for efficiency and occupancy estimates;

A.Kiselev


Example plots from tracking code
Example plots from tracking code

1 GeV/c p+ tracks at h=0.5:

<ndf> = 206

32 GeV/c p+ tracks at h=3.0:

<ndf> = 9

-> look very reasonable from statistical point of view

A.Kiselev


Momentum resolution study 1
Momentum resolution study (1)

p+ track momentum resolution vs. pseudo-rapidity

-> expect 2% or better momentum resolution in the whole kinematic range

A.Kiselev


Momentum resolution study 2
Momentum resolution study (2)

p+ track momentum resolution at h = 3.0 vs. Silicon thickness

-> ~flat over inspected momentum range because of very small Si pixel size

A.Kiselev


Momentum resolution study 3
Momentum resolution study (3)

p+ track momentum resolution at h = 3.0 vs. Silicon pixel size

-> 20 micron pixel size is essential to maintain good momentum resolution

A.Kiselev


Tracking todo list
Tracking TODO list

  • Perform geometry optimization

  • Implement more realistic digitization schemes

  • Think about track finder algorithms

  • Implement vertex builder

  • Account for beam particle parameter “smearing”

A.Kiselev



General1
General

  • Written from scratch

  • Unified interface (geometry definition, digitization, clustering) for all EIC calorimeter types

  • Rather detailed digitization implemented

A.Kiselev


Backward em calorimeter bemc
Backward EM Calorimeter (BEMC)

  • PWO-II, layout a la CMS & PANDA

  • -2500mm from the IP

  • both projective and non-projective geometry implemented

  • digitization based on PANDA R&D

10 GeV/c electron hitting one

of the four BEMC quadrants

Same event (details of shower development)

A.Kiselev


Forward em calorimeter femc
Forward EM Calorimeter (FEMC)

tower (and fiber) geometry

described precisely

  • tungsten powder scintillating fiber sampling calorimeter technology

  • +2500mm from the IP; non-projective geometry

  • sampling fraction for e/m showers ~2.6%

  • “medium speed” simulation (up to energy deposit in fiber cores)

  • reasonably detailed digitization; “ideal” clustering code

A.Kiselev


Femc energy resolution study
FEMC energy resolution study

3 degree track-to-tower-axis incident angle

  • “Realistic” digitization: 40MHz SiPM noise in 50ns gate; 4m attenuation length; 5 pixel single tower threshold; 70% light reflection on upstream fiber end;

-> good agreement with original MC studies and measured data

A.Kiselev


Femc tower optimization
FEMC tower “optimization”

original mesh

-> optimized mesh design can probably decrease

“constant term” in energy resolution

optimized mesh

A.Kiselev


Barrel em calorimeter cemc
Barrel EM Calorimeter (CEMC)

-> barrel calorimeter collects less light, but

response (at a fixed 3o angle) is perfectly linear

  • same tungsten powder + fibers technology as FEMC, …

  • … but towers are tapered

  • non-projective; radial distance from beam line [815 .. 980]mm

A.Kiselev


Cemc energy resolution study
CEMC energy resolution study

3 degree track-to-tower-axis incident angle

-> simulation does not show any noticeable difference in energy

resolution between straight and tapered tower calorimeters

A.Kiselev


Calorimeter todo list
Calorimeter TODO list

  • Tune geometry

  • Perform systematic resolution studies

  • Implement shower parameterization (fast MC)

  • Implement realistic cluster split algorithm

  • Add hadronic calorimeters

A.Kiselev


Eicroot overall todo list
EicRoot overall TODO list

  • Prepare documentation

  • Take care about official release & installation

  • Perform geometry optimization

  • Implement IR (material and fields)

  • Implement PID algorithms (RICH, TPC dE/dx, …)

  • Start physics simulations

A.Kiselev


E c aschenauer t barton r darienzo a kiselev bnl 06 05 2013

EIC solenoid modeling

Richard E. Darienzo, SBU graduate student

A.Kiselev


Eic solenoid modeling
EIC solenoid modeling

main requirements:

  • Yield large enough bending for charged tracks at large h

  • Keep field inside TPC volume as homogeneous as possible

  • Keep magnetic field inside RICH volume(s) small

-> use OPERA-3D/2D

software

Presently used design: MRS-B1

A.Kiselev


Eic solenoid modeling1
EIC solenoid modeling

Other options investigated, like

4-th concept solenoid design

-> obviously helps to cancel “tails”

A.Kiselev


Solenoid modeling todo list
Solenoid modeling TODO list

  • Optimize coil geometry and currents

  • Check effects of adding iron shielding

  • Perform fine tuning of selected configuration

  • Come up with a consistent design matching all the experimental requirements

A.Kiselev



General architecture

MC generator output

PYTHIA

MC tree code:

Builds ROOT tree containing events

Smearer:

Performs fast detector smearing

Djangoh

DPMjet

PEPSI

gmc_trans

Milou

Rapgap

General architecture

eic-smear

  • C++ code running in ROOT

  • Builds with configure/Make

  • Single libeicsmear.so to load in ROOT

A.Kiselev


Functionality built in
Functionality built in

  • Easily configurable acceptance definitions

  • Kinematic variable smearing declarations

(single) quantity, X, to smear:

E, p, θ, φ

Function defining σ(X) =

f([E, p, θ, φ])

Acceptance

for X in

E, p, θ, φ, pT, pZ

+

+

either a priori knowledge of detector resolutions

is needed or parameterization based on a full

GEANT simulation

-> try out resolutions provided by EicRoot fits …

A.Kiselev


Lepton hadron separation via e p
Lepton-hadron separation via E/p

-> clearly separation becomes better in several kinematic regions

all plots: 10GeV x 100GeV beams

A.Kiselev


Hadron identification with rich
Hadron identification with RICH

consider hadrons in pseudo-rapidity range ~[1.0 .. 3.0]

-> pion/kaon/proton identification should be possible up to momenta ~40 GeV/c

A.Kiselev


Migration in x q 2 bins
Migration in (x,Q2) bins

10GeV x 100GeV

beams

-> “survival probability” is above ~80% in the region where tracking has superior resolution compared to calorimetry

A.Kiselev


Smearing code todo list
Smearing code TODO list

  • Implement vertex position smearing

  • Provide other (small) interface changes required for EicRoot integration if needed

  • Keep physics resolution studies up to date using input provided by EicRoot

see https://wiki.bnl.gov/eic!

A.Kiselev


Smearing code todo list1
Smearing code TODO list

  • Implement vertex position smearing

  • Provide other (small) interface changes required for EicRoot integration if needed

  • Keep physics resolution studies up to date using input provided by EicRoot

Details on detector performance requirements

are summarized here:

https://wiki.bnl.gov/eic/index.php/DIS:_What_is_important

A.Kiselev