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Matrix Tuning Analysis for Particle Detection Systems

Explore performance improvements in xt calibration for particle detectors using new parameters and matrix tuning techniques. Analyze results before and after calibration to optimize data accuracy and event selection process.

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Matrix Tuning Analysis for Particle Detection Systems

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  1. HES-HKS & KaoS meeting 18June2013 Toshi Gogami 26June2013

  2. Contents • xt (52Cr target) • Matrix tuning

  3. 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

  4. X-t function calibration • xt_initial • xt_calib

  5. xt_initial Drift Time [ns] Drift Distance [cm]

  6. xt_calib Black : |WC-TC| Magenta : Profile of |WC-TC| Green : x-t calc. Track Fitting Track coordinate Wire center 2011/9/2 0 s NEW PARAMETERS 52Cr target • Residual better • KDC1 ; 400 [μm]  300 [μm] • Number up • 10% increased at χ2 <20 Residuals The number

  7. 52Cr data Data Base 69 runs 75978-75984 e05115.param.75977 --> 1 75987-76049 e05115.param.75977 --> 1 140 runs 76646-76649 e05115.param.76646 --> 2 76650-76659 e05115.param.76650 --> 3 76662-76737 e05115.param.76660 --> 3 76742-76771 e05115.param.76738 --> 4 76772-76802 e05115.param.76660 --> 5 255 runs 76845-99999 e05115.param.76845 --> 6 x-t function paramters 1 : hdriftmap.param.75988 ok 2 : hdriftmap.param.76647 3 : hdriftmap.param.76651 ok 4 : hdriftmap.param.76647 5 : hdriftmap.param.76665 6 : hdriftmap.param.76857 ok

  8. Comparison before and after x-t function calibration (6) 1102 ± 66 Before After [ns] [ns] Ngreen – ( Nblue/8.0 ) = 901 ± 57 22 % up Run number ( 52Cr ): 77123,77122,77121,77119,77118,77114,77113,77105,77104,77103

  9. Matrix tuning • Fitting for event selection • Fitting range, selection range • B option • Minuit • Parameter setting for minuit • Limits for parameters

  10. 12C target ( low + high ) 初期’ マトリクスから 1 day

  11. Polyethylene target 1 day 初期’ マトリクスから

  12. 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 • 12ΛB 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. , 7ΛHe g.s.

  13. END

  14. Backup

  15. nkaon.cc // ========= 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"); } /* 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"; TCutcut_good = cut1 && cut2 && cut3 && cut4 && cut5 && cut6; TCutcut_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);

  16. x-t function calibration (5) Layer Mean Mean_Er Width Width_Er [cm] 1 0.000721219 0.000403251 0.035071678 0.000677666 2 0.000373572 0.000443613 0.036882286 0.000797078 3 0.000739852 0.000312642 0.029519443 0.000451063 4 -0.001633575 0.000300132 0.028868848 0.000420825 5 0.002384798 0.000383668 0.033972087 0.000621902 6 -0.000153706 0.000304320 0.035703709 0.000708911 7 0.001819091 0.000154981 0.022232188 0.000170734 8 0.006979520 0.000199300 0.024565640 0.000219438 9 -0.003147231 0.000148378 0.020766494 0.000155815 10 -0.006006464 0.000191540 0.023975863 0.000223017 11 0.003778137 0.000163696 0.023114714 0.000187806 12 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 0.000512390 2 0.001207701 0.000317658 0.030081196 0.000465006 3 0.001827388 0.000288187 0.027404703 0.000387989 4 -0.002819739 0.000332553 0.029729248 0.000476184 5 -0.000759636 0.000345757 0.031530622 0.000539101 6 0.001939713 0.000349821 0.031430669 0.000539329 7 0.001621344 0.000153150 0.021909753 0.000170269 8 0.006643900 0.000188748 0.023720792 0.000207274 9 -0.002678367 0.000140221 0.019833835 0.000146226 10 -0.006326482 0.000190840 0.023781061 0.000223102 11 0.003250797 0.000161816 0.022808324 0.000183978 12 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

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