1. Taikan Suehara ICEPP, The Univ. of Tokyo
Tau & SUSY analysis
Taikan Suehara
ICEPP, The Univ. of Tokyo

2. BG suppression cuts results
Backgrounds are suppressed to negligible level.
Signal efficiency is ~23%, quite low but…
Most cut events in first 2 cuts are with hard-photons
Practical signal efficiency is considered ~75%

3. Decay modes in Apol analysis
Branching ratio: 17.8%
3 body decay; pol. info is smeared
t -> enn
Branching ratio: 17.4%
3 body decay; same as enn mode
t -> mnn
Branching ratio: 10.9%
Pol. can be directly observed by p distribution
t -> pn
Branching ratio: 25.2%
Pol. of r can also be obtained by p distribution in r-rest frame (pol. of r is connected to pol. of t)
t -> rn, r -> pp
Branching ratio: 9.3%
Currently not used because statistics is low
t -> a1n, a1 -> ppp

4. t -> pn selection results
Selection performance between geometries (look at the 2nd row from the bottom)
Efficiency: not so different
Purity: LDC’ > GLD > GLD’ > J4LDC
t -> rn mode (decay 2p is mis-reconstructed as single) might be the reason (larger is better)
LDC’ has advantage due to high CAL granularity.

5. Apol calculation (pn mode)
Statistical error is almost the same for all geometries
Value shifts are larger in GLD’/J4LDC due to the lower purity.
Stat error in 500fb-1
Value shift due to the mode BG
Values obtained by signal-only events!

6. r -> pn selection results
3rd row from bottom: used as “no p0 mass cut”.
2nd row from bottom: used as “p0 mass cut”.
Events with single neutral are survived with this cut.
Most bottom row: used as “tight p0 mass cut”.
Events with single neutral are eliminated with this cut.
Clear difference by geometries: LDC’s the best, bigger is better in Jupiter’s.

7. Apol calculation (rn mode)
Statistical errors are larger in GLD’/LDC, esp. with mp0 cut.
Value shift is smaller than pn mode, negligible with mp0 cut.
Stat error in 500fb-1
Value shift due to the mode BG
Values obtained by signal-only events!

8. イベント数 Singal : 2.3M / 500 fb-1 Bhabha : いまのpreselectionで20000/0.2fb-1
可能？
Back to backをpreselectしてもよい (半分弱になる)
Bhabha : いまのpreselectionで20000/0.2fb-1
5M / 50 fb-1
ggtautau: いまのpreselectionならおそらく500fb-1可能
~0.1M / 500fb-1
他のモードはfull scanをやろうとしている

9. SM separation cuts
# of SM events becomes comparable to chargino after these cuts.
No difference between geometries in this stage.

10. Cut statistics (2) chargino neutralino
BG separation is efficient (see W/Z mass cut rows)
Slightly better BG separation performance in GLD but almost within statistical fluctuations.

11. Chargino mass fit results
Fitting function: 3rd polynomial (4 param) (center) / 0 (edge) convoluted with a Gaussian with s as linear function of energy (2 param) edge position: 2 param, total # of parameters = 8
Cheat fitting: 1. fix edge positions at true value, fit other 6 parameters. 2. fix those 6 parameters and fit edge positions.
No significant difference between geometries.

12. Neutralino mass fit results
Fitting function: Error function (left) x Complementary error function (right) Width of left and right is the same, # of parameters = 4
Cheat fitting: Same as chargino
J4LDC gives slightly larger width than other two. Corresponding fitting error is enhanced.

13. イベント数 SUSY: 500fb-1可能 (100kくらい) WW background – 10000 fb
4-jet 標準SMでは20fb-1
Preselectして増やすかどうか考える
4-jet + neutrino
まだ考えてない
こちらも全BGスキャン

14. 今日何を話しますか？

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