1. HES-HKS & KaoS meeting Toshi Gogami

2. Contents

3. Energy loss simulation by HES,HKS and POSI 1.POSI for beam energy loss – Harver foil is already implemented in this code. – Implemented Raster newly. 2.HKS, HES for K + and e’ energy loss – Transplant harver foil into these code from POSI. バグだし (HES 、 HKS) 変数の定義の間違え・・・昔からあるようだ が。。 (POSI)Raster を入れる際のバグ ….etc New ver. GEANT では動かない問題 (HES,HKS) コンストラクターの引数の数、順番 G4ThreeVector…..etc 日本で解決済

4. Beam Energy Loss study Used Geant4 simulation code “Modified POSI” Water ( + harver ) target in the display Virtual Detector Target Generation point (Uniform in z-direction) SIMULATION

5. Momentum distribution Incident beam After target H 2 O (500mg/cm 2 )+ Harver

6. Determination of the value of energy loss This edge is the peak value which is derived by the fitting results EDGE 31 keV Boron, 56.1 mg/cm 2

7. Water target with Harver foils EDGE 371 keV Harver foil effect Water water Foil

8. Simulation Results Target< 5 MeV< 1 MeV< 0.5 MeV KawamaToshi 7 Li 184 mg/cm 2 160 137 165 141 121 157 133 115 149 133 151 103 89 118 9 Be 188.1 mg/cm 2 161 141 170 140 122 159 132 115 150 177 (Chen) 177 138 105 90 124 10 B 56.1 mg/cm 2 55 48 55 47 40 52 45 39 50 45 52 31 27 37 12 C 112.5 mg/cm 2 111 97 111 94 82 105 89 77 100 90 89 103 66 58 77 52 Cr 154 mg/cm 2 151 140 127 113 101 117 104 93 112 93 94 99 79 71 88 Water + Harver 500 mg/cm 2 552 555 547 429 434 468 251 257 254 439*1.6 442*1.6 487*1.6 371 373 408 Polyethylene 450.8 mg/cm 2 500 436 530 406 362 454 240 241 244 436*0.8 440*0.8 502*0.8 349 296 416 Unit : keV

9. Energy Loss scan CH 2 energy loss ± 20% – How does it effect on the Missing mass – To be reported next week

10. Λ cross section from water target

11. Sensitive Nonlinear Iterative Peak (SNIP) clipping algorithm References: C. G Ryan et al.: SNIP, a statistics-sensitive background treatment for the quantitative analysis of PIXE spectra in geoscience applications. NIM, B34 (1988), 396-402. M. Morháč, J. Kliman, V. Matoušek, M. Veselský, I. Turzo: Background elimination methods for multidimensional gamma-ray spectra. NIM, A401 (1997) 113-132. D. D. Burgess, R. J. Tervo: Background estimation for gamma-ray spectroscopy. NIM 214 (1983), 431-434.

12. New Cut efficiency estimation (WC for demonstration) Real distribution  Probability density function (PDF)  Imitation data  Cut efficiency K+K+ p Normalized N.P.E Mass square [GeV/c 2 ] 2

13. Mass square Mass square [GeV/c 2 ] 2 Normalized N.P.E Water target

14. Normalized N.P.E Mass square [GeV/c 2 ] 2 Water target

15. Seems working well.

16. Summary and To do Summary – Energy loss are estimated Smaller than those of Kawama-san Seeing effect on missing mass when the energy loss is changed ± 20%. – Now cut efficiency estimation method ( KID ) On progress To do – Λ cross section from H 2 O before leaving Germany. – Matrix tuning Better cut Water TSpectrum  Background subtraction Definition of chi-square