SS kaon tagger + OS taggers
description
Transcript of SS kaon tagger + OS taggers
SS KAON TAGGER + OS TAGGERS
Míriam Calvo, Marco Musy
12th March 2009
NNET APPROACH 1st step: calibrate p0, p1
2nd step: Use the probability per event to split into 5 categories
Or, use a probability per event including same side
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i = p0 + p1 i i = SS k , , e, OS k, Qvtx
OS from B+J/ K+ (directly)
SS from BsDs (oscillation)
OS of each category from B0J/ K* (oscillation)
eff increases to 4.5% including SS k(6.4% splitting into 5 categories)
eff increases from 2.2% to 3.4% using 5 categories
Tagging BsJ/
COMBINING SS WITH OS TAGGERS How to proceed?
Combine SS kaon to get an event-per-event probability of mistag using the already sorted tagging categories for the OS taggers.
Some conditions are needed: SS kaon vs Nnet output is the same among Bs
decays. SS and OS taggers mistag are not correlated.
Trigger effect also need to be studied.3
Compatible – same SSK (Nnet output) dependence for all Bs decaysBsDs can be used to calibrate Nnet output from dataBsDs higher annual yield, but poor proper time resolution (use double tagging method)
SS KAON VS NNET OUTPUT
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BsJ/ (98k sel)BsDs (133k sel)BsDs (27k sel)
Fit p0+p1*xp0=(7±9)·10-3
p1=0.97±0.03p0= (-1.0±0.7)·10-2
p1=1.00±0.02p0= (0.8±1.5)·10-2
p1=0.95±0.04
SS K
Correlation matrix (Tagger decision):------------------------------------------------ e OS k SS k Qvtx: +1.00e: -0.01 +1.00OS k: +0.03 +0.03 +1.00SS k: +0.02 +0.01 +0.03 +1.00Qvtx: +0.10 +0.07 +0.19 +0.02 +1.00------------------------------------------------
Higher correlations between Q_vrtx and OS muon & kaon taggersbut not with Same Side
TAGGER CORRELATIONS
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BsJ/
SS kaonOS taggers
Offset due to OS correlationsMistag is under-estimated(product of individual taggers probabilities)
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OS+SS
Correlation Qvtx and other OS taggers is ~ 10-20%
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true true
true
1- p 1- p
1- p
OS taggers () calibrated with B+J/K+. SS kaon () calibrated with BsDs.
Get rid of OS correlations by measuring OS in 5 categories (Nnet approach) in a control sample as B0J/K*.
REMINDER
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(combined)OS = 36.25 ± 0.24%tag = 44.97 ± 0.16%eff = 3.40 ± 0.11%1 2 3 4 5
OS taggers
Prob
Bd2JpsiK* (cat1) = 44.2±0.3 (cat2) = 36.3±0.5 (cat3) = 29.0±0.6 (cat4) = 23.4±0.7(cat5) = 18.2±0.5
SS kaonOS taggers
OS taggersTaking measured In 5 categories(to get rid of correlations)
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OS+SSCorrelation OS taggers – SS kaon is 2.2%
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1- p 1- p
1- p
truetrue
true
Bd2JpsiK* (cat1) = 44.2±0.3 (cat2) = 36.3±0.5 (cat3) = 29.0±0.6 (cat4) = 23.4±0.7(cat5) = 18.2±0.5
OS + Same Side probability:
)1()1()1( , SSOSiTOT ppp
Probability per event for Bs2JpsiPhi
p i, OS
)1()1())1(),1(max(
TOTTOT
TOTTOT
ppppp
GETTING A PROBABILITY PER EVENT FROM OS+SS
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(average) = 35.77 ± 0.21%tag = 55.54 ± 0.16%eff = 4.50 ± 0.13%1 2 3 4 5
p
(combined) = 33.19 ± 0.21%tag = 55.54 ± 0.16%eff = 6.28 ± 0.15%
Splitting into 5 categories
eff (OS) = 3.40%
OS taggers alone (without Qvtx)
PROBABILITY PER EVENT WITHOUT QVTX
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No bias due to correlations
OS + SS (average) = 32.10 ± 0.25%tag = 38.18 ± 0.16%eff = 4.89 ± 0.14% (> 4.50%)
OS (combined) = 31.1 ± 0.3%tag = 20.48 ± 0.13%eff = 2.93 ± 0.10% (< 3.40%)
Approximately same effective efficiency without Qvtx (work on-going to improve this tagger)
OS + SS (combined) = 30.10 ± 0.25%tag = 38.18 ± 0.16%eff = 6.05 ± 0.14% (< 6.41%)
true
1- p
INTO CATEGORIES…
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tag OS OS eff OS tag OS OS eff OSCat 1 27.18±0.15 44.9±0.3 0.28±0.04 6.14±0.08 40.8±0.7 0.21±0.03Cat 2 6.97±0.08 35.5±0.6 0.59±0.05 6.53±0.08 34.3±0.6 0.64±0.05Cat 3 5.02±0.07 30.8±0.7 0.74±0.05 4.81±0.07 28.0±0.7 0.93±0.06Cat 4 3.68±0.06 26.0±0.8 0.84±0.06 1.94±0.05 21.4±1.0 0.63±0.05Cat 5 2.13±0.05 16.7±0.8 0.95±0.05 1.07±0.03 15.0±1.1 0.52±0.04
average 45.0±0.2 39.0±0.2 2.19±0.10 20.48±0.13 32.6±0.3 2.49±0.10combine
d45.0±0.2 36.2±0.2 3.40±0.11 20.48±0.13 31.1±0.3 2.93±0.10
with Qvtx without Qvtx
BsJ/
tag OS + SS
OS + SS
eff OS + SS
tag OS + SS
OS + SS eff OS + SS
Cat 1 27.91±0.15 43.4±0.3 0.49±0.05 13.95±0.11 40.6±0.4 0.49±0.05Cat 2 10.13±0.10 35.4±0.5 0.86±0.06 9.90±0.10 34.3±0.5 0.98±0.06Cat 3 7.41±0.09 29.5±0.6 1.24±0.07 7.07±0.08 27.2±0.6 1.47±0.07Cat 4 5.33±0.07 24.3±0.6 1.41±0.07 3.78±0.06 20.9±0.7 1.29±0.06Cat 5 4.73±0.07 14.4±0.5 2.40±0.08 3.48±0.06 13.7±0.6 1.83±0.07
average 55.5±0.2 35.8±0.2 4.50±0.13 38.2±0.2 32.1±0.2 4.89±0.14combine
d55.5±0.2 33.0±0.2 6.41±0.15 38.2±0.2 30.1±0.2 6.05±0.14
L0 TISTOSTOBBINGPhase space corrections…12
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SS K
Nnet output
Fit p0+p1*xp0=(10±9)·10-3
p1=0.96±0.03p0= (-8±8)·10-4
p1=0.95±0.01p0= (4.3±1.6)·10-3
p1=0.92±0.05
Same dependence before/after L0.
SS K
Nnet output
Fit p0+p1*xp0=(7±9)·10-3
p1=0.97±0.03p0= (-1.0±0.7)·10-2
p1=1.00±0.02p0= (0.8±1.5)·10-2
p1=0.95±0.04
Before L0
After L0
BsJ/ (98k sel)BsDs (133k sel)BsDs (27k sel)
BsJ/ (92k sel)BsDs (63k sel)BsDs (24k sel)
vs Nnet
Fit p0+p1*xp0=0.408±0.006p1=(-7.4±0.7)·10-3
p0=0.417±0.008p1=(-9.1±0.7)·10-3
p0=0.416±0.013p1=(-9.2±1.1)·10-3
SS K
rec’ted Bs pt
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Differences in phase space can introduce differences in of a given category among decays.
Corrections can be performed once known the (Bs pt) dependence (obtained from control channels).
After L0
OS K
rec’ted Bs pt
BsJ/ BsDs BsDs
Fit p0+p1*xp0=0.337±0.007p1=(1.8±0.9)·10-3
p0=0.30±0.01p1=(3.4±1.0)·10-3
p0=0.340±0.016p1=(1.9±1.6)·10-3
vs Bs pt
Bs pt
Cat 1 Cat 2
Cat 3 Cat 4
Cat 5
vs Bs pt
Cat 1 Cat 2
Cat 3 Cat 4
Cat 5
after L0OS + SS taggers
Corrections might be needed when splitting into 5 categories (Nnet approach)
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BsJ/ BsDs BsDs
OS taggers SS tagger
cat1 cat1cat2 cat2
cat3 cat3cat4 cat4
cat5 cat5
all taggers1/6 of events include SS kaon
(BsJ/ )
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Nearly flat!
(OS+SS) of each category compatible forBsJ/ and BsDs
vs Bs pt
PID APPROACH OS , e, k, Qvtx from B+J/ K+ (directly)
B0J/ K* (from oscillation)
SS k from BsDs (double tagging)
BsDs (from oscillation)
41 possible combinations, sort into 5 categories according to its :eff ~ 4.9%
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Corrections needed also for:
Cat
4Cat
5 Cat
3 Cat
1Cat
2
PID combination
Nnet:
tag eff
9.2±0.1 29.0±0.6 1.6±0.1e 2.9±0.1 30.6±1.1 0.43±0.05
kopp 15.0±0.1 31.6±0.5 2.0±0.1kss 26.0±0.2 30.9±0.4 3.8±0.2
Qvrtx 39.5±0.2 40.0±0.3 1.6±0.1Combined 59.8±0.6 31.0±0.2 8.7±0.2
After L0
BsDs
tag eff
5.40±0.07 29.8±0.6 0.88±0.06e 2.73±0.05 30.5±0.9 0.42±0.04
kopp 13.83±0.11 33.5±0.4 1.51±0.08kss 23.27±0.14 32.0±0.3 2.70±0.10
Qvrtx 36.98±0.16 41.0±0.3 1.20±0.07Combined 55.4±0.7 33.0±0.3 6.4±0.2
BsJ/
Nnet: 18
(BsDs numbers in the backup)
Before L0 After L0
L0 TIS L0 TOS
(TIS: remaining differences due to offline selection)
Bs pt (GeV)
Bs pt (GeV)
TISTOSTOBBING L0
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L0 TIS (%) L0 TOS (%)BsJ/ 23.5 74.3BsDs 36.8 61.0BsDs 55.1 44.2
(TIS includes TIS+TOS)
Nnet:
BsDs
tag eff tag eff
16.55±0.25
28.1±0.8
3.16±0.22
1.95±0.05 33.8±1.2 0.02±0.03
e 3.92±0.13 31.1±1.6
0.56±0.10
2.38±0.06 30.2±1.1 0.37±0.04
kopp 17.44±0.26
32.1±0.8
2.25±0.19
12.70±0.13
33.9±0.5 1.31±0.08
kss 26.4±0.3 33.6±0.6
2.93±0.22
22.37±0.06
32.9±0.4 2.63±0.12
Qvrtx 44.5±0.3 38.7±0.5
2.26±0.20
34.64±0.18
41.8±0.3 0.92±0.07
Combined 65.8±0.3 30.6±0.4
9.9±0.4 52.4±0.2 34.0±0.3 5.4±0.2
BsJ/
Nnet: 20
TIS (23.5%) TOS (74.3%)
tag eff tag eff
15.6±0.20
28.8±0.6 2.80±0.17
1.69±0.08
31.3±2.1 0.23±0.06
e 3.68±0.10
31.4±1.3 0.51±0.07
2.13±0.09
33.6±2.0 0.23±0.06
kopp 16.97±0.20
31.3±0.6 2.37±0.16
12.2±0.2 33.3±0.8 1.31±0.20
kss 27.01±0.24
32.0±0.5 3.52±0.19
25.2±0.3 29.4±0.5 4.42±0.23
Qvrtx 44.27±0.27
39.2±0.4 2.07±0.15
32.6±0.3 42.3±0.5 0.78±0.11
Combined
65.8±0.9 30.6±0.3 9.94±0.24
52.3±0.9 31.6±0.4 7.07±0.28
TIS (55.1%) TOS (44.2%)
CONCLUSIONSSame Side Kaon can be used in combination with Opposite Side taggers to get an event-per-event probability of mistag.
• From Nnet output calibrated with control channels.• eff~6.3% (3.4% without SS)
Qvtx main source of OS tagger correlations.• Get rid of correlations by measuring global OS
wrong tag fraction from control channel (5 categories).
• Actually without it eff~6%. • Needs to be studied further.
Trigger effects matters to get a ‘global’ , but not as event-per-event weight.
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BACKUP22
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tag OS OS eff OS tag OS+SS OS+SS eff OS+SSCat 1 27.88±0.18 44.2±0.4 0.38±0.05 27.81±0.18 43.1±0.4 0.53±0.06Cat 2 7.93±0.11 34.4±0.7 0.77±0.07 10.77±0.12 33.3±0.6 1.21±0.08Cat 3 5.95±0.09 28.9±0.7 1.06±0.07 8.22±0.11 27.3±0.6 1.70±0.10Cat 4 4.33±0.08 25.0±0.8 1.09±0.07 6.18±0.10 23.7±0.7 1.70±0.09Cat 5 3.11±0.07 18.4±0.9 1.24±0.07 6.83±0.10 14.0±0.5 3.54±0.12
average 49.2±0.2 37.4±0.3 3.10±0.14 59.8±0.2 33.8±0.2 6.25±0.19combine
d49.2±0.2 34.8±0.3 4.53±0.15 59.8±0.2 31.0±0.2 8.67±0.20
BsDs
tag OS OS eff OS tag OS+SS OS+SS eff OS+SSCat 1 27.18±0.15 44.9±0.3 0.28±0.04 27.91±0.15 43.4±0.3 0.49±0.05Cat 2 6.97±0.08 35.5±0.6 0.59±0.05 10.13±0.10 35.4±0.5 0.86±0.06Cat 3 5.02±0.07 30.8±0.7 0.74±0.05 7.41±0.09 29.5±0.6 1.24±0.07Cat 4 3.68±0.06 26.0±0.8 0.84±0.06 5.33±0.07 24.3±0.6 1.41±0.07Cat 5 2.13±0.05 16.7±0.8 0.95±0.05 4.73±0.07 14.4±0.5 2.40±0.08
average 45.0±0.2 39.0±0.2 2.19±0.10 55.5±0.2 35.8±0.2 4.50±0.13combine
d45.0±0.2 36.2±0.2 3.40±0.11 55.5±0.2 33.0±0.2 6.41±0.15
BsJ/
OS kaon
TOS
SS kaon
B pt
Bs2JpsiPhiBs2DsPiBs2DsMuNu
TOS
TISTIS
p0=(34.3±0.9)·10-2
p1=(1.6±1.1)·10-3
p0= (31.9±2.0)·10-2
p1=(2.6±1.8)·10-3
p0= (33.7±2.3)·10-2
p1=(2.6±2.2)·10-3
p0=(31.0±1.4)·10-2
p1=(2.9±1.4)·10-3
p0= (29.3±1.2)·10-2
p1=(3.1±1.1)·10-3
p0= (33.3±2.4)·10-2
p1=(1.8±2.2)·10-3
p0=(40.6±0.8)·10-2
p1=(-7.7±0.8)·10-3
p0= (40.8±1.4)·10-2
p1=(-9.7±1.2)·10-3
p0= (39.0±1.7)·10-2
p1=(-7.4±1.5)·10-3
p0=(42.7±1.2)·10-2
p1=(-8.2±1.2)·10-3
p0= (42.9±1.0)·10-2
p1=(-9.4±0.9)·10-3
p0= (43.9±1.9)·10-2
p1=(-11.0±1.7)·10-3
B pt
B pt B pt
Not expected to be different between TIS and TOS (just a check)
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TOS
TIS
SS kaon tagger
Fit p0+p1*xp0=(0.9±1.1)·10-2
p1=0.96±0.03p0= (-1.8±1.3)·10-2
p1=0.98±0.04p0= (0.8±2.0)·10-2
p1=0.90±0.06
BsJ/ BsDs BsDs
Fit p0+p1*xp0=(-0.1±1.7)·10-2
p1=0.98±0.06p0= (-0.6±1.2)·10-2
p1=0.97±0.03p0= (0.3±2.4)·10-2
p1=0.91±0.07
Not expected to be different between TIS and TOS (just a check)
NNet
NNet25
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tag eff
6.85±0.17 32.0±1.2 0.89±0.12e 2.95±0.12 32.2±1.9 0.38±0.08
kopp 15.5±0.2 33.6±0.8 1.67±0.17kss 25.6±0.3 31.2±0.6 3.6±0.2
Qvrtx 37.9±0.3 40.2±0.5 1.44±0.16Combined 58.1±1.1 31.8±0.4 7.7±0.3
BsDs
Nnet:
Double tagging method:OS
OSSS
F
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1
F = probability that taggers agree = Nagree/NDT
(from S. Poss)
25 ))(·(10·3783.0)(·1296.03388.0)()(
sss
trues
rec
DMDMBpDp
BSDS MOMENTUM CORRECTION
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SAME SIDE KAON NEURAL NET OUTPUT CALIBRATIONFrom BsDs control channel28
Jeremie Borel / Vladimir Gligorov (DaVinci v19r12 / v22r0p2)Yield ~ 146/183k (after L0) DC06 selected 113/134k (~39/37k with SSK tagger); 50/63k after L0
Backgrounds:
B/S~0.34/0.41
Jeremie B/S (m=±50 MeV &
L0)
Vava B/S (m=± 50 MeV &
L0)BsDsX 0.02 0.02BdD 0.20 0.11
bDsp 0.04 0.13bc 0.02 0.01
bb 0.07 0.14
_
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BsDs BsDs XBdD bDs pbc
m (GeV/c2) m (GeV/c2)
SignalBkg
BSDS OFFLINE SELECTION
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SIGNAL:
BACKGROUND:
PDFS USED IN ROOFIT
RooHistPdfnnetPdf
ttGtmnnetppttExptAnnettPdf
MmGfMmGfmPdf
sig
sigts
ss
sig
mBmmBmsig
)(
);()]'·cos())·10·(21()'2
)[cosh(()·()|(
),;()1(),;()( 21
RooHistPdfnnetPdf
ttGtExptAtPdf
mExpmPdf
bkg
bkgbkgt
bkgbkg
bkg
)(
))21(1();();()·()(
);()(
RooBDecaymixState = unmixed if charge() = tagger_decision mixed if opposite
3
3
·1·)(tatatA
acceptance:
s, s, ms fixed
(bkg=0.5)
sig
RooDecay
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FIT RESULTS
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Nnet
SS k
RooFit p0 = (-2±5)·10-3
p1 =0.96 ±0.01
Fit: p0+p1*xp0 = (-6±7)·10-3
p1 = 0.99±0.02
Floating Parameter FinalValue +/- Error -------------------- -------------------------- B/S 3.2075e-01 +/- 2.93e-03 a 7.1132e+00 +/- 1.90e-01 bkg_S1 1.8975e-02 +/- 6.73e-02 bkg_m1 -1.9603e-01 +/- 2.44e-01 bkg_mexp -3.7567e-01 +/- 1.37e-01 bkg_tau 6.7124e-01 +/- 5.08e-03 fr1 3.4824e-01 +/- 6.33e-03 mean 3.8342e-03 +/- 7.58e-04 omegaB 5.1069e-01 +/- 3.23e-03 par0 -2.1409e-03 +/- 5.11e-03 par1 9.6138e-01 +/- 1.31e-02 sig_mass_mB 5.3683e+00 +/- 5.82e-05 sig_mass_sB 1.1764e-02 +/- 1.00e-04 sig_mass_sB2 1.9794e-02 +/- 1.58e-04 sigma 4.3791e-02 +/- 8.62e-04
OFFLINE SELECTION COMPARISONBsDs32
Jeremie Vava
All pions and kaons
IPS > 3 MIPCHI2DV(PRIMARY) > 9
P > 2 GeV P > 2 GeVDLL(pi-p) > -5
DLL(pi-mu) > -5DLL(k-p) > -10
DLL(k-mu) > -10
Ds daughtersPt > 300 MeV Pt > 300 MeV
DLL(K-pi) > 2Kaons : DLL K/p > -10
tight
Bachelor pionPt > 600 MeV Pt > 500 MeV
DLL(K-pi) > 4 loose
Ds
Pt > 2 GeV Pt > 2 GeV
IPS > 4 MIPCHI2DV(PRIMARY)>9
vtx chi2 < 16 2 < 15
BPVVDCHI2 > 100
M< 21 MeV mass window ± 21/50 MeV
Bs
z_Ds – z_Bs > 0 mm
IPS < 4 BPVIPCHI2() < 16
vtx chi2 < 9 2 < 10
M < 500 MeV (70MeV) Mass window ± 50/500 MeV
FS > 12 BPVVDCHI2 > 6.25
cos(p) > 0.99997 cos() > 0.9999
3
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N_tape (kevts)
after stripping N_sel N_sel
(L0) B/S
Bs2DsPi 2085 445550112831 50206 Y = 146k
133540 62853 Y = 183k
bbar(not phys.)
22000 8028501 (16) 1 (9) 0.07
7(62) 3(32) 0.16
Bs2DsX 2017 148554124 61 0.02
155 78 0.02
Bd2DPi 787 1544061291 661 0.2
831 441 0.11
LbDsP 41 8025104 39 0.04
484 183 0.13
Lb2LcPi 37 422614 7 0.02
12 5 0.01
m = ± 50 / 50 MeV
B/S ~ 0.34 / 0.43
+25%
+25%
Jeremie / Vava
(Increase of bkg because loose PID cuts for the bachelor pion)
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(HLT eff missing)
B mass B p
B pt B
BsDs offline selected events
VavaJeremie
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Bkg Bs mass
VavaJeremie
Bs2DsX Bd2DPi
LbDsP Lb2LcPi
bb-bar
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