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Systematic error and double Gaussian fitting Toshi Gogami 3Apr2014.

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Presentation on theme: "Systematic error and double Gaussian fitting Toshi Gogami 3Apr2014."— Presentation transcript:

1 Systematic error and double Gaussian fitting Toshi Gogami 3Apr2014

2 Contents

3 Different distorted initial matrices Distorted matrix sample 6 (dist6) Distorted matrix sample 7 (dist7) Distorted matrix sample 8 (dist8)

4 Differential non-linearity (older sample) Missing mass [GeV/c 2 ]

5 Before and after the optimization (dist6)

6 Standard deviation due to matrices (dist6) σ = sqrt(σ mat +σ stat ) σ mat = sqrt(σ-σ stat )

7 Results for (dist8) (g.s. fitting mean )– M gen [keV] A σ mat [keV] B Lambda21.2 Sigma44.3 7 Λ He23.0 9 Λ Li17.5 10 Λ Be19.9 12 Λ B15.6 52 Λ Cr5.2

8 Results for (dist7) (g.s. fitting mean )– M gen [keV] A σ mat [keV] B Lambda6.8 Sigma26.7 7 Λ He16.6 9 Λ Li29.1 10 Λ Be24.2 12 Λ B26.6 52 Λ Cr27.6

9 Results for (dist6) (g.s. fitting mean )– M gen [keV] A σ mat [keV] B Lambda32.9 Sigma43.0 7 Λ He32.8 9 Λ Li29.2 10 Λ Be9.6 12 Λ B33.0 52 Λ Cr37.0

10 Summary 1 [Systematic errors] 5% of target thickness uncertainty  Λ, Σ 0 : < 50 keV  Hypernucleus : < 20 keV

11 Decomposition of 1 - and 2 - -B Λ [MeV] Counts Chunhua’s spectrum

12 Test conditions Common conditions for tests  N point = 100  Step = 0.002 MeV  Mean1: -11.45 – Step * i (i<N point )  Mean2: -11.45 + Step * i (i<N point ) Parameters Chunhua’s spectrum σ = 0.231 (fixed) Han’s spectrum σ = 0.300 (fixed) Toshi’s spectrum σ = 0.200 (fixed)

13 |χ 2 -1.0| distribution real data

14 |χ 2 -1.0| distribution (Chunhua2009) Mean1 [MeV] Mean2 [MeV] σ = 231 keV (fixed) Mean1 [MeV] Mean2 [MeV] |χ 2 -1.0|

15 |χ 2 -1.0| distribution (Han2009) Mean1 [MeV] Mean2 [MeV] σ = 300 keV (fixed) Mean1 [MeV] Mean2 [MeV] |χ 2 -1.0|

16 |χ 2 -1.0| distribution (Toshi2009) Mean1 [MeV] Mean2 [MeV] σ = 220 keV (fixed) Mean1 [MeV] Mean2 [MeV] |χ 2 -1.0|

17 SIMULATIO N

18 Test conditions (Simulation)  N point = 100  Step = 0.002 MeV  Mean1: -11.32 – Step * i (i<N point )  Mean2: -11.32 + Step * i (i<N point )

19 Generated dummy data -B Λ [MeV] [Counts/240 keV] SIMULATION

20 Fitting results (1) Mean1 [MeV] Mean2 [MeV] Mean1 [MeV] Mean2 [MeV] σ = 180 keV σ = 190 keV Assumed width for fitting SIMULATION

21 Fitting results (2) Mean1 [MeV] Mean2 [MeV] Mean1 [MeV] Mean2 [MeV] σ = 210 keV σ = 220 keV σ = 230 keV Assumed width for fitting SIMULATION

22 Fitting results (4) Mean1 [MeV] Mean2 [MeV] Mean1 [MeV] Mean2 [MeV] σ = 240 keV SIMULATION

23 Sample s Mean1 [MeV] Mean2 [MeV] [MeV]

24 Summary 2 [About 12 Λ B(1 -,2 - ) separation] What we can say from this study We could not reproduce paper values…. (E01-011 data could be reproduced though) (I would like to see Hampton’s side study) What we thought from this study In the case of simple Gaussian Difficult to find the answer with this method… In the real case (peaks are not simple Gaussian distributions) If this method works well after some analysis improvements, we need to confirm whether the method works or not for peaks which affected by energy straggling, production point displacement from matrix origin, detector resolutions, spectrometer acceptance, beam raster and so on.  Can be checked by blind analyses. Is there any good cut (selection) condition to find the answer ?  need further study.


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