E.-C. Aschenauer, T. Barton, R. Darienzo, A. Kiselev BNL, 06/05/2013

E.-C. Aschenauer, T. Barton, R. Darienzo, A. Kiselev

BNL, 06/05/2013

Update on EIC detector Performance Simulations

06/05/2013 A.Kiselev

Contents EicRoot framework development EIC detector solenoid modeling EIC smearing generator update

TODO lists

EicRoot development



EIC in FairRoot framework

ROOT VMC (GEANT3, GEANT4) VGM (ROOT, GEANT) …

FairRoot externalpackage bundle

FairBaseC++ classes

CbmRootR3BRoot

PandaRoot

eic-smear

EicRoot

-> Make best use of FairRoot development -> Utilize efficiently existing codes developed by EIC

taskforce

FairRoot is officially maintained by GSI; dedicated developers

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

…


End user view

-> MC points simulation

No executable (steering through ROOT macro scripts)

digitization “PID” Passreconstruction-> 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


EIC detector layout (phase 2)


EIC detector layout (phase 1)


Detector view in EicRoot

EMC and tracking detectors implemented so far

CEMC

BEMCSOLENOID

FEMC

Tracking in EicRoot



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


Vertex silicon tracker MAPS technology; ~20x20mm2 chips, ~20 m 2D

pixels STAR upgrade “building blocks” (cable assemblies)MAPS R&D for EIC within BNL LDRD


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


Other tracking elements 2x7 disks with up to 280 mm radius N sectors per disk; 200 m silicon-equivalent thickness digitization: discrete ~20x20 m2 pixels

forward/backward silicon trackers:

TPC:

GEM trackers:

~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

3 disks behind the TPC endcap STAR FGT design digitization: 100 m resolution in X&Y; gaussian

smearing


Tracker zoomed view

BGT

BST

FST

VST

TPC

FGT

06/05/2013

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

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

MRS-B1 solenoiddesign used


Example plots from tracking code

1 GeV/ctracks at

32 GeV/ctracks at

<ndf> = 206

<ndf> = 9

-> look very reasonable from statistical point of view


Momentum resolution study (1)

track momentum resolution vs. pseudo-rapidity

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



track momentum resolution at vs. Silicon thickness

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



track momentum resolution at vs. Silicon pixel size

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


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”

Calorimeters in EicRoot



General Written from scratch Unified interface (geometry definition,

digitization, clustering) for all EIC calorimeter types

Rather detailed digitization implemented


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)


Forward EM Calorimeter (FEMC)

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

tower (and fiber) geometrydescribed precisely


FEMC energy resolution study

-> good agreement with original MC studies and measured data

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

3 degree track-to-tower-axis incident angle


FEMC tower “optimization”

original mesh

optimized mesh -> optimized mesh design can probably decrease “constant term” in energy resolution


Barrel EM Calorimeter (CEMC)

same tungsten powder + fibers technology as FEMC, … … but towers are tapered non-projective; radial distance from beam line [815 ..

980]mm

-> barrel calorimeter collects less light, but response (at a fixed 3o angle) is perfectly linear


CEMC energy resolution study

-> simulation does not show any noticeable difference in energy resolution between straight and tapered tower calorimeters

3 degree track-to-tower-axis incident angle


Calorimeter TODO list Tune geometry Perform systematic resolution studies Implement shower parameterization (fast

MC)

Implement realistic cluster split algorithm

Add hadronic calorimeters


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

EIC solenoid modelingRichard E. Darienzo, SBU graduate student



EIC solenoid modeling Yield large enough bending for charged tracks at

large Keep field inside TPC volume as homogeneous as

possible Keep magnetic field inside RICH volume(s) small

main requirements:

Presently used design: MRS-B1

-> use OPERA-3D/2Dsoftware


EIC solenoid modelingOther options investigated, like

4-th concept solenoid design

-> obviously helps to cancel “tails”


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

eic-smear package



General architecture

Smearer:Smearer:Performs fast Performs fast

detector detector smearingsmearing

MC MC generator generator

outputoutput

MC tree MC tree code:code:

Builds ROOT Builds ROOT tree tree

containing containing eventsevents

eic-smear

• C++ code running in ROOT

• Builds with configure/Make

• Single libeicsmear.so to load in ROOT

gmc_tragmc_transnsMilouMilouRapgRapg

apap

PEPSIDPMjet

DjangoDjangohh

PYTHIAPYTHIA


Functionality built in

Function defining σ(X)

=f([E, p, θ, φ])

(single) quantity, X,

to smear:E, p, θ, φ

+ +Acceptance

for X inE, p, θ, φ, pT,

pZ

Easily configurable acceptance definitions Kinematic variable smearing declarations

either a priori knowledge of detector resolutions is needed or parameterization based on a full

GEANT simulation-> try out resolutions provided by EicRoot

fits …


Lepton-hadron separation via E/p

-> clearly separation becomes better in several

kinematic regions

all plots: 10GeV x 100GeV beams


Hadron identification with RICH

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

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


Migration in (x,Q2) bins10GeV x 100GeV

beams

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

calorimetry


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 !


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

E.-C. Aschenauer, T. Barton, R. Darienzo, A. Kiselev BNL, 06/05/2013

Documents

Transcript of E.-C. Aschenauer, T. Barton, R. Darienzo, A. Kiselev BNL, 06/05/2013