Tau SUSY analysis Taikan Suehara ICEPP The Univ

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

Tau & SUSY analysis Taikan Suehara ICEPP, The Univ. of Tokyo Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 1

BG suppression cuts results • Backgrounds are suppressed to negligible level. • Signal efficiency

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% Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 2

Decay modes in Apol analysis t -> enn • Branching ratio: 17. 8% •

Decay modes in Apol analysis t -> enn • Branching ratio: 17. 8% • 3 body decay; pol. info is smeared t -> mnn • Branching ratio: 17. 4% • 3 body decay; same as enn mode t -> pn • Branching ratio: 10. 9% • Pol. can be directly observed by p distribution t -> rn, r -> pp • 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 -> a 1 n, a 1 -> ppp • Branching ratio: 9. 3% • Currently not used because statistics is low Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 3

t -> pn selection results Selection performance between geometries (look at the 2 nd

t -> pn selection results Selection performance between geometries (look at the 2 nd row from the bottom) • Efficiency: not so different • Purity: LDC’ > GLD’ > J 4 LDC – t -> rn mode (decay 2 p is mis-reconstructed as single) might be the reason (larger is better) – LDC’ has advantage due to high CAL granularity. Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 4

Apol calculation (pn mode) Statistical error is almost the same for all geometries Value

Apol calculation (pn mode) Statistical error is almost the same for all geometries Value shifts are larger in GLD’/J 4 LDC due to the lower purity. Stat error in 500 fb-1 Values obtained by signal-only events! Value shift due to the mode BG Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 5

r -> pn selection results • 3 rd row from bottom: used as “no

r -> pn selection results • 3 rd row from bottom: used as “no p 0 mass cut”. • 2 nd row from bottom: used as “p 0 mass cut”. – Events with single neutral are survived with this cut. • Most bottom row: used as “tight p 0 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. Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 6

Apol calculation (rn mode) Statistical errors are larger in GLD’/LDC, esp. with mp 0

Apol calculation (rn mode) Statistical errors are larger in GLD’/LDC, esp. with mp 0 cut. Value shift is smaller than pn mode, negligible with mp 0 cut. Stat error in 500 fb-1 Values obtained by signal-only events! Value shift due to the mode BG Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 7

イベント数 • Singal : 2. 3 M / 500 fb-1 – 可能? – Back

イベント数 • Singal : 2. 3 M / 500 fb-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. 2 fb-1 – 5 M / 50 fb-1 • ggtautau: いまのpreselectionならおそらく 500 fb-1可能 – ~0. 1 M / 500 fb-1 • 他のモードはfull scanをやろうとしている Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 8

SM separation cuts • # of SM events becomes comparable to chargino after these

SM separation cuts • # of SM events becomes comparable to chargino after these cuts. • No difference between geometries in this stage. Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 9

Cut statistics (2) chargino neutralino • BG separation is efficient (see W/Z mass cut

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. Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 10

Chargino mass fit results • Fitting function: 3 rd polynomial (4 param) (center) /

Chargino mass fit results • Fitting function: 3 rd 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. Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 11

Neutralino mass fit results • Fitting function: Error function (left) x Complementary error function

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 • J 4 LDC gives slightly larger width than other two. Corresponding fitting error is enhanced. Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 12

イベント数 • SUSY: 500 fb-1可能 (100 kくらい) • WW background – 10000 fb –

イベント数 • SUSY: 500 fb-1可能 (100 kくらい) • WW background – 10000 fb – 4 -jet 標準SMでは 20 fb-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 Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 13

今日何を話しますか? Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 14

今日何を話しますか? Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 14

Backup Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 15

Backup Taikan Suehara, ILD opt/soft asia meeting, 1 Oct. 2008 page 15