Monte Carlo Tuning of LUARLW Mode

Transcription

1 Monte Carlo Tuning of LUARLW Mode Lei Xia 1, Guangshun Huang 1, Ronggang Ping 2, Xi an Xiong 2 1 University of Science and Technology of China 2 Institute of High Energy Physics, Chinese Academy of Sciences BESIII R-QCD Workshop at Huangshan July 27th 2015 Huangshan University

2 Outline Introduction Data Preparing Data Set Event Selection Background estimation Choice of Distributions Fitting Result by LUARLW Model Fitting results of the parameters added in simultaneous Parameters determined by fit Tuning results Tuning results at 4.6 Ge Tuning results at 3.65Ge Summary July 27th 2015 Monte Carlo Tuning of LUARLW Mode 2

3 Introduction Motivation Overview of tuning July 27th 2015 Monte Carlo Tuning of LUARLW Mode 3

4 Motivation Tune the LUNDARLW parameters, to get the optimum values of the parameters. To ensure the accuracy of simulations, it is necessary to study the parameters of LUNDARLW for each energy point. Assumption: The detector simulation is so well that the difference between MC simulation and data is negligible, and any difference seen is due to the imperfection of event generator. July 27th 2015 Monte Carlo Tuning of LUARLW Mode 4

5 Overview of tuning strategy To get the parameters by simultaneously fitting to data distributions. Models of fit to the experimental data. Quadratic approximation: f p 0 + δp, x = a 0 0 x + n i=1 a 1 n i x δp i + n i=1 j=1 a 2 ij x δp i δp j MC p 0 + δp, x Parameter vector: p = p 0 + δp Observable : x July 27th 2015 Monte Carlo Tuning of LUARLW Mode 5

6 Overview of tuning strategy Solving a system linear equation: P a = MC Where P is the matrix of parameters, a is the vector of coefficients a 0,1,2. The optimum values of the parameters p i s, their errors σ i s and the correlated coefficients ρ ij s are determined from a standard χ 2 fit of the analytic approximation to the data using MINUIT. July 27th 2015 Monte Carlo Tuning of LUARLW Mode 6

7 Data Preparing Boss version & Data sets Event Selection Background estimation Choice of Distributions July 27th 2015 Monte Carlo Tuning of LUARLW Mode 7

8 Boss version & Data sets Boss version: Boss6.6.4.p01 Data sets: Feb, 5th, 2014 Mar, 9th, 2014 s = 4.6 Ge. Offline Luminosity: 506 pb 1 MC Sample events for each parameter of LUNDARLW Model. July 27th 2015 Monte Carlo Tuning of LUARLW Mode 8

9 Selection Criteria(I) eto Bhabha and digam Two showers with maximum energy deposition. θ 1 + θ < 10 and E > 0.65E beam Good hadron tracks r < 0.5cm, z < 5cm, cos θ < 0.93 Momentum < E beam + 5σ de dx mea de dx proton < 10 σ proton If E P > 0.8, E < 0.65E beam eto e ± from gamma conversion, if M e + e < 0.1 and angle e + e < 15 July 27th 2015 Monte Carlo Tuning of LUARLW Mode 9

10 Selection Criteria(II) Hardon event candidates For N track 2 : isible energy > 0.25E beam For N track = 2 : eto: θ 1 + θ < 15, φ 1 + φ < 10 Number of isolated photon 2 eto: both tracks are electrons 0.75 < E P < For N track = 3 : eto: Angle of two largest energetic tracks, θ 1st + θ 2nd 180 < 15, φ 1st + φ 2nd 180 < 10 July 27th 2015 Monte Carlo Tuning of LUARLW Mode 10

11 Background estimation Sources of background: bhabha e + e μ + μ e + e γγ e + e τ + τ e + e e + e + X Scale to the same luminosity of data scale = L σ Event Number TABLE I Background estimation, cross section and number of events QED Cross section(nb) Number of events bhabha e + e μ + μ e + e γγ e + e τ + τ e + e e + e + X July 27th 2015 Monte Carlo Tuning of LUARLW Mode 11

12 Choice of Distributions The distributions selected should be sensitive to the parameters in the investigation. For a given distribution MC(x), the sensitivity is defined as: Sensitivity S i x = δmc x MC x pi δp i p i ln MC x ln p i Check Sensitivities for each Parameter: p i July 27th 2015 Monte Carlo Tuning of LUARLW Mode 12

13 Choice of Distributions FIGURE I. Sensitivity and Choice of Distributions We choose this one! Yes No July 27th 2015 Monte Carlo Tuning of LUARLW Mode 13

14 Choice of Distributions FIGURE I. Sensitivity and Choice of Distributions We choose this one! Yes No July 27th 2015 Monte Carlo Tuning of LUARLW Mode 14

15 Fitting Result by Lund Area Law Model Fitting results of the parameters added in simultaneous Parameters determined by Fit July 27th 2015 Monte Carlo Tuning of LUARLW Mode 15

16 Fitting Result We take these distribution into consideration. TABLE II. Choice of distribution Distribution Choice ngamma Egamma X gam_cos Nnh Etrk pmag costheta phi rapidity pseudrapidity xf xper sph apl thr opl fw10 fw20 fw30 X fw40 July 27th 2015 Monte Carlo Tuning of LUARLW Mode 16

17 Fitting results of the parameters added in simultaneous FIGURE II. Fitting results of the parameters added in simultaneous Black: Data Red: Fitting Result July 27th 2015 Monte Carlo Tuning of LUARLW Mode 17

18 Fitting results of the parameters added in simultaneous FIGURE II. Fitting results of the parameters added in simultaneous Black: Data Red: Fitting Result July 27th 2015 Monte Carlo Tuning of LUARLW Mode 18

19 Fitting results of the parameters added in simultaneous FIGURE II. Fitting results of the parameters added in simultaneous Black: Data Red: Fitting Result July 27th 2015 Monte Carlo Tuning of LUARLW Mode 19

20 Parameters determined by fit We got a group of parameters. TABLE III. Parameters determined by fit parameters alue PARJ(11) PARJ(12) PARJ(14) PARJ(15) PARJ(16) PARJ(17) PARJ(1) PARJ(2) PARJ(21) RALPA(15) RALPA(16) RALPA(17) July 27th 2015 Monte Carlo Tuning of LUARLW Mode 20

21 Tuning results July 27th 2015 Monte Carlo Tuning of LUARLW Mode 21

22 Tuning results Tuning results at 4.6 Ge Tuning results at 3.65 Ge July 27th 2015 Monte Carlo Tuning of LUARLW Mode 22

23 Tuning results at 4.6 Ge Using fit7 parameters produced by the MINUIT to produce MC and compared with data. FIGURE III. Compare of fitting result and tuning result for nch Black:Data Green:MC Red:Fitting Result July 27th 2015 Monte Carlo Tuning of LUARLW Mode 23

24 Tuning results at 4.6 Ge FIGURE I. Tuning results Black: Data Green: MC July 27th 2015 Monte Carlo Tuning of LUARLW Mode 24

25 Tuning results at 4.6 Ge FIGURE I. Tuning results Black: Data Green: MC July 27th 2015 Monte Carlo Tuning of LUARLW Mode 25

26 Tuning results at 4.6 Ge FIGURE I. Tuning results Black: Data Green: MC July 27th 2015 Monte Carlo Tuning of LUARLW Mode 26

27 Tuning results at 4.6 Ge FIGURE I. Tuning results Black: Data Green: MC July 27th 2015 Monte Carlo Tuning of LUARLW Mode 27

28 Tuning results at 3.65 Ge Parameters for simulation TABLE I. Parameters for simulation parameters Group1 Group2 Group3 PARJ(11) PARJ(12) PARJ(14) PARJ(15) PARJ(16) PARJ(17) PARJ(1) PARJ(2) PARJ(21) RALPA(15) RALPA(16) RALPA(17) July 27th 2015 Monte Carlo Tuning of LUARLW Mode 28

29 Tuning results at 3.65 Ge FIGURE. Tuning results at 3.65 Ge Black: Data Green: MC Group1 Group2 Group3 July 27th 2015 Monte Carlo Tuning of LUARLW Mode 29

30 Summary July 27th 2015 Monte Carlo Tuning of LUARLW Mode 30

31 Summary We have a preliminary fitting result and tuning result in several energy points. We got several groups of parameters and could extend to other energy points. The first tuning is accomplished but we need more combination on sensitivity for the best result to further work. Simulate the hadron generate process and contribute to R value measure. July 27th 2015 Monte Carlo Tuning of LUARLW Mode 31

32 Thank You! July 27th 2015 Monte Carlo Tuning of LUARLW Mode 32

33 Backup TABLE I. Parameters in tuning Observable Range Description Sphericity (sph) 0 S 1 S = 0: two jet event S = 1: isotropic event A measurement of the summed 2 p with respect to an eventaxis. Aplanarity (apl) 0 A 0.5 A = 0: a planar event A = 0.5: isotropic event It measures the transverse momentum component out of the event plane. Thrust (thr) 0.5 A 1 T = 0.5: isotropic event T = 1: two jets event Oblateness (obl) O 0 O = 0: an event symmetrical around the thrust axis O > 0: a planar event July 27th 2015 Monte Carlo Tuning of LUARLW Mode 33

34 Backup TABLE I. Parameters in tuning Observable Range Description Fox-Wolfram moments h 10 h 40 H i I = 0,1,2,3,4 H 0 = 1: mass is zero H 1 = 0 momentum is balanced H 2,4,6 = 1 and H 1,3,5 = 0: two jet events Etrk E = m 2 + p 2 x + p 2 y + p2 z Charged track energy Ptrk cos θ p = p x 2 + p y 2 + p z 2 p z p Charged track momentum Azimuthal angle distribution July 27th 2015 Monte Carlo Tuning of LUARLW Mode 34

35 Backup TABLE I. Parameters in tuning Observable Range Description ϕ cos 1 p x p cos θ rapidity 1 2 ln E + p z E p z Pseudorapidity 1 2 ln p + p z p p z x 2p F z W x per 2p W Azimuthal angle distribution Assuming pion W: Total energy of event p : Transverse momentum July 27th 2015 Monte Carlo Tuning of LUARLW Mode 35