HES-HKS & KaoS meetingToshi Gogami26June2013

18June2013

Contents

• xt (52Cr target)• Matrix tuning

Analysis PC• PC1 (hyperdragon)

– CPU : Core i7-3930K @ 3.2GHz ( 3.8GHz) x 12– Memory : 16 GB– HDD : > 14 TB (available 1.2TB)– Software

• ENGINE• GEANT4• mtune• Condor

• PC2 (hyperdragon2)– CPU : Core i7-3970X @ 3.5GHz ( 4.0GHz ) x 12– Memory : 32 GB– HDD : > 10TB (available 5.2TB)– Software

• ENGINE• mtune• Condor

New

New

X-t function calibration

1. xt_initial2. xt_calib

xt_initial

Drift Distance [cm]

Drift Time [ns]

xt_calib

s0

Wire center

Track coordinate

Black : |WC-TC|Magenta : Profile of |WC-TC|Green : x-t calc.

Track

Fitting

The number Residuals

NEW PARAMETERS

• Residual better– KDC1 ; 400 [μm] 300 [μm]

• Number up– 10% increased at χ2 <20

52Cr target 2011/9/2

52Cr data

Data Base69 runs75978-75984 e05115.param.75977 --> 175987-76049 e05115.param.75977 --> 1

140 runs76646-76649 e05115.param.76646 --> 276650-76659 e05115.param.76650 --> 376662-76737 e05115.param.76660 --> 376742-76771 e05115.param.76738 --> 476772-76802 e05115.param.76660 --> 5

255 runs76845-99999 e05115.param.76845 --> 6

x-t function paramters 1 : hdriftmap.param.75988 ok2 : hdriftmap.param.766473 : hdriftmap.param.76651 ok4 : hdriftmap.param.766475 : hdriftmap.param.766656 : hdriftmap.param.76857 ok

Comparison before and after x-t function calibration (6)

1102 ± 66901 ± 57Ngreen – ( Nblue/8.0 ) =

Before After

[ns] [ns]

22 % up

Run number ( 52Cr ): 77123,77122,77121,77119,77118,77114,77113,77105,77104,77103

Matrix tuning• Fitting for event selection– Fitting range, selection range– B option

• Minuit– Parameter setting for minuit– Limits for parameters

12C target ( low + high )

初期’ マトリクスから

1 day

Polyethylene target

初期’ マトリクスから

1 day

Summary and To do• Summary– xt for 52Cr

• REPLAY was not done for all runs

– Matrix tuning• Modified Tuning from early matrices

• To do– xt for 52Cr

• Initialization calibration• New parameters REPLAY with a local PC ( ~1 week )

– Matrix tuning• 12

ΛB p-shell

• Angular component tuning with Λ and Σ0 (and 7ΛHe g.s.)

• 12ΛB g.s. ( and p-shell ) from the polyethylene target

• 10ΛBe g.s. , 7

ΛHe g.s.

END

Backup

nkaon.cc/* nkaon.cc Toshi Gogami , 26June2013 */

void nkaon(char* file){ // ========== General Conditions ================ gROOT->SetStyle("Plain"); gStyle->SetOptStat(0);

// ========== OPEN ROOT file =================== TFile* f = new TFile(file); TTree* t = (TTree*)f->Get("h9500");

// ========== Cut condtions ==================== TCut cut1 = "abs(hsp-1.2)<0.5"; TCut cut2 = "abs(htimetar-etimetar+54.95)<1.0"; TCut cut3 = "hwatnkn1+hwatnkn2>1.0"; TCut cut4 = "haernpe1+haernpe2+haernpe3<5.0"; TCut cut5 = "abs(hmsq-0.22)<0.4"; TCut cut6 = "abs(htimetar-etimetar+54.95)<9.0"; TCut cut_good = cut1 && cut2 && cut3 && cut4 && cut5 && cut6; TCut cut_bad = cut1 && !cut2 && cut3 && cut4 && cut5 && cut6;

// ========= Create Histograms ================ TH1F* h = new TH1F("h","",200,-10.0,10.0); TH1F* h_ = (TH1F*)h->Clone(); h_->SetName("h_"); t->Project("h","htimetar-etimetar+54.95",cut_good); t->Project("h_","htimetar-etimetar+54.95",cut_bad);

// ========= Histogram Options =============== h ->SetFillColor(8); h ->SetFillStyle(3003); h_->SetFillStyle(3003); h_->SetFillColor(9);

// ========= Draw Histogram ================== TCanvas* c1 = new TCanvas("c1","c1"); gPad->SetGridx();gPad->SetGridy(); h->Draw(); h_->Draw("same"); h->SetMaximum(460.); // ========== Number of events ============== double nk = 0.0; double nk_= 0.0; double nker = 0.0; double nker_= 0.0; nk = h ->GetEntries(); nker = sqrt(nk); nk_ = h_->GetEntries(); nker_ = sqrt(nk_); nk_ = nk_/8.0; nker_ = nker_/8.0; cout << " " << nk << " " << nk_ << endl; nker = sqrt( pow(nker,2.0) + pow(nker_,2.0) ); nk = nk - nk_;

cout << " Coincident Kaons --> " << nk << " " << nker << endl;

// ========== Print ================= //c1->Print("ctime_org.png","png"); //c1->Print("ctime_new.png","png"); }

x-t function calibration (5)

Layer Mean Mean_Er Width Width_Er [cm]1 0.000721219 0.000403251 0.035071678 0.0006776662 0.000373572 0.000443613 0.036882286 0.0007970783 0.000739852 0.000312642 0.029519443 0.0004510634 -0.001633575 0.000300132 0.028868848 0.0004208255 0.002384798 0.000383668 0.033972087 0.0006219026 -0.000153706 0.000304320 0.035703709 0.0007089117 0.001819091 0.000154981 0.022232188 0.0001707348 0.006979520 0.000199300 0.024565640 0.0002194389 -0.003147231 0.000148378 0.020766494 0.00015581510 -0.006006464 0.000191540 0.023975863 0.00022301711 0.003778137 0.000163696 0.023114714 0.00018780612 0.004145358 0.000150716 0.021612644 0.000161592

ROOT file = cr_test2.root All Entries = 76682 K+ Entries = 1319 Fitting results --> cr_test2.root_fit.dat

Layer Mean Mean_Er Width Width_Er [cm]1 -0.000377143 0.000337798 0.031152684 0.0005123902 0.001207701 0.000317658 0.030081196 0.0004650063 0.001827388 0.000288187 0.027404703 0.0003879894 -0.002819739 0.000332553 0.029729248 0.0004761845 -0.000759636 0.000345757 0.031530622 0.0005391016 0.001939713 0.000349821 0.031430669 0.0005393297 0.001621344 0.000153150 0.021909753 0.0001702698 0.006643900 0.000188748 0.023720792 0.0002072749 -0.002678367 0.000140221 0.019833835 0.00014622610 -0.006326482 0.000190840 0.023781061 0.00022310211 0.003250797 0.000161816 0.022808324 0.00018397812 0.003929110 0.000149137 0.021319747 0.000160130

ROOT file = cr_test.root All Entries = 75794 K+ Entries = 1297 Fitting results --> cr_test.root_fit.dat