BESIII dE/dx package: status and algorithm

studies

WANG DayongJune 1,2005

Outline

dE/dx package:OO design and software development

Calibration and systematic corrections

Reconstruction algorithm studies:A. Different estimation of most prob Eloss

B. Curve studies based on BESII data

C. Resolution and residual bias correction

dE/dx :Particle ID with energy loss measurements

Components: calibration and reconstruction

Implementation: C++ programming under BOSS framework

Design goal: Resolution 6—7%, good seperation

MDC

tracking

dE/dx~f(v)

Particle type info

Principle:

P = · m

Requirements and data flow

MDC Tracking

dE/dx Reconstruction

Global Particle Identification

TransientData Store

(TDS)

MDC digits

Tracks

MDC digitsTracks

Recon dE/dx

Recon dE/dx

partId info

physics analysis Real dataflow

Apparent dataflow

Tracks

Recon dE/dx

MDC digits

。。。

AIM: to give the partID information from the list of pulse heights of hits on the MDC track, and store them into TDS

some corrections are performed to get unbiased dE/dx information.

Some proper dE/dx estimators are constructed

UML Class diagrams

UML Sequence Diagram for dE/dx Reconstruction

Some implementation features

Uniform interface: Alternative algorithms with the same interface

Uniform data I/O format: MDC recon data model: MdcRecEvent

Input from MC : MdcFakeData package

Output:MdcDedx in MdcRecEvent

int m_id; float m_dedx; // measured value of dE/dx float m_dedx_exp[5]; // expected value of dE/dx for 5

particle hypotheses float m_sigma_dedx[5]; // sigma value of dE/dx for 5

particle hypotheses float m_pid_prob[5]; // probability for each of the 5

particle hypotheses int m_stat; // status flag SmartRef<MdcTrack> m_trk; // reference to the track

Calibration issues

Systematic and run-by-run calibrations is important for dE/dx correction

Calibration consts ~7200 are designedCalib consts stored in DataBase. They can be

retrieved from DB in reconstruction nowIn future, calib consts in ROOT format and

DB only contains meta data

dE/dx calibration and corrections

① Gain variations among cells ② Gas Gain variation within one cell ③ Sampling length corrections④ Drift distance dependence ⑤ Longitude position(z) dependence ⑥ Dependence of the sense wire voltage ⑦ Space charge effect ⑧ Gas gain saturation : from electronics⑨ Temperature,pressure and environmental effects⑩ Corrections related to particle type ⑪ Variations of the pulse height run by run

Algorithm studies: different estimation of most probable energy

lossLandau distribution has no definite mean. The

algorithm used must estimate the most probable energy loss

Truncated mean Double truncated mean: truncate at both ends Median Geometric mean

Harmonic mean

Transformation:

Logorithm truncated mean: studies based on BESII data

idea:these methods give less bias to large values,then the satured hits have less effect to give better shape and better seperation

Different estimation of most probable energy loss: resolution(1)

Truncation rate 0.7

5.51% 5.34%

6.06% 5.09%

0.05~0.75 truncation

BOOST MC, MIP muon

Different estimation of most probable energy loss: resolution(2)

5.75%5.44%

5.71% 2.61%

Truncation rate: 0.7

BOOST MC, MIP muon

Different estimation of most probable energy loss: seperation

power(1)

Pi/K Pi/P

0.7GeV 1.2GeV

Pi/K Pi/P

0.7GeV 1.2GeV

Pi/K Pi/P

0.6GeV 1.1GeVPi/K Pi/P

0.75GeV 1.3GeV

Different estimation of most probable energy loss: seperation

power(2)

Pi/K Pi/P

0.7GeV 1.2GeV

Pi/K Pi/P

0.7GeV 1.3GeV

Pi/K Pi/P

0.7GeV 1.3GeV

Pi/K Pi/P

0.75GeV 1.3GeV

Comparison of linear&logorithm TM

Cosmic rays Radiative Bhabha

Pull width: 1.020 0.9995 Pull width: 0.8477 0.9304

shape is more Gaussian-like shape is more Gaussian-like

Logorithm TM(right figure),compared to plain TM(left figure):

Suppress high-end residual Landau tail

The distribution more Gaussian likeBESII DATA, J/Psi hadrons

Study of truncated mean method

Well established method of dE/dx estimation

Simple and robust

Rejection of lower end hits to remove contributions from noise and background fluctuation

Truncation of higher tail to remove Landau tail due to hard collisions

Just cooresponding to ~5% lower cut

After truncation, distribution just Gaussian-like

Landau tail

BOOST MC, 1GeV electrons

Resolution curve with different truncation rates

70% truncation ratio is adopted for the algorthm

Number of good hits is required to no less than 10 for each track

Resolution from perfect MC consistent with empirical formula

BOOST MC, 1GeV electrons

Different most probable energy loss formulations(1)

Bethe-Bloch formula

Landau formula with density correction

Sternheimer correction : Cobb-Allison correction:

PAI: Photo-Absorption Ionization model

A

Different most probable energy loss formulations(2)

Va’vra formulation

Other formulae

B

dE/dx curve studies with BesII data

Purpose: 1. Comparison of different formula to find

the best curve to calculate expectation in reconstruction

2. A test-bed for BESIII reconstruction

data samples used: Pion:J/Psirho+pi & J/PsiKKPiPi

Kaon:J/PsiK*(892)+K(1430)KKPiPi

Proton:J/psiPPbarPi0&J/PsiPPbarEta

electron: (radiative) Bhabha

muon: dimu +cosmic rays

“Garbage” events: beam-gas protons, cosmic-rays, rad. Bhabha

To get pure samples:

Use Tof and BSC information ONLY to identify particles

use relative probability only

Strict kinetic and invariant mass cut

The cuts are checked with GENBES

Example:Cuts for Bhabha

Comparison between data and dE/dx curve

Sternheimer(A) is better at high momentum end

Va’vra(B) is relative better at low momentum end

Data need careful calibration

Practical global parameterization of curve is prefered

Sternheimer

Comparison of Sternheimer and Va’vra formula:

AB

A

B

Global 5-parameter fit for phmp_nml vs

5

44

13ln2

1p

pp

ppp

dx

dE

binning with nearly the same statisticsat each point to reduce the error

Using garbage events in order to fastly calibrate this curve for BESIII in future

A uniform formula to avoid discrete expression for density effect

The curve fit the BESII data OK

Beam-gas proton

Cosmic rays

Radiative bb

Residual theta dependence before correction (Hadron events)

After correction

The correction is then parameterized and used in mass data process

σdE/dx~ hits number relationship

35.2

0.8132.0

46.0

In

n

Empirical formula :

reso

luti

on

number of hits number of hits

reso

luti

on

J/Psi dimuon events

J/Psi radiative Bhabha events

data of different momenta bins

2

1153.0

t

A

Z

summary

OO designed BESIII dE/dx package now runs smothly under BOSS

Calibration algorithm are designed and many corrections considered

Different reconstruction algorithms are explored to get best performance

To reach design goals, there are still a long way to go

Thank you谢谢！

Backed -up slides…