01/29/2006 22 Bs Mixing - High Energy Particle Physics group

SUNY Interview Seminar
29 Jan 2007
Tania Moulik
(University of Kansas)
DØ collaboration
01/29/2006
Tania Moulik, Bs Mixing at Tevatron
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Outline
Introduction to B Mixing.
Flavor Tagging and Bd Mixing
 Soft Electron Identification
 Electron tagging and combination with other taggers.
 Bd mixing – Tagger calibration
Bs Mixing
 Analysis Outline
 Results from D0 and CDF and interpretation.
 Sensitivity studies at D0
Conclusion
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Bs mixing saga
B mesons oscillate (mix) first seen in Bd system–
ARGUS(1987)@DESY, CLEO(1989)@CESR (Y(4S))
Bs mesons oscillate was established by comparing the timeintegrated oscillation probability measurements above with
measurement at LEP (which contained both Bd and Bs).
But what is the oscillation frequency?
Search started at LEP and continued between 1984-1999.
Formation of B oscillations working group in 1996 at LEP.
Last LEP average : 1999 (D. Abbaneo and G. Boix, JHEP
9908 (1999) or hep-ex/9909033) Dms > 12.3 ps-1
Search continued at Tevatron….observed in 2006…20 years
later..
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B mixing
Neutral B’s oscillate.
Mass eigenstates are a
mixture of flavor eigenstates:

 q B

p B 
BH  q B  p B
BL
BH and BL have a different
mass and may have different
decay width.
Dm = MH – ML = 2|M12| ,
DG = GH - GL = 2|G12|
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Time evolution follows the
Schrodinger equation
d  B(t)   M 11  iΓ11 M 12  iΓ12  B(t) 

i
 


dt  B (t)   M 21  iΓ 21 M 22  iΓ 22  B (t) 
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B Mixing
In general, probability for unmixed and mixed decays :
Pu,m(B)  Pu,m(B). In limit, G12 << M12 (DG << DM)
(Standard model estimate and confirmed by data),
e t / 
p( B  B) 
(1  cos Dmt )
2
e t / 
p( B  B ) 
(1  cos Dmt )
2
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CKM matrix and B mixing
 d   Vud
 
 s    Vcd
 b   V
   td
Vus V  d 
ub  
Vcs V  s 
cb 
Vts V  b 
tb 
 1  l2
l


l
1  l2
 3
2
A
l
(


i

)

A
l


ud ub

cb
Al3 (   i ) 

Al2


1


td tb
V V  VcdV  V V  0
complex
Vub | Vub | e i
Vtd | Vtd | e i
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Wolfenstein parametrisation
- expansion in l.
l  sin  c  0.2265  0.002
029
A  0.801 00..018
  (1  l2 2) 
  (1  l2 2)
VudVub VtdVtb



1
VcdVcb VcdVcb
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Constraints on Vtd
(,)
VudVub
Ru 
VcdVcb
a
VtdVtb
Rt 
VcdVcb


 l2  1 Vub
Ru      1  
2  l Vcb

2
2
1 Vtd
Rt  (1   )   
l Vcb
2 2
2
(0,0)
(1,0)
On solving the mixing box diagrams :
2

m
2  t
Dmd 
m
m
F 2
b
W
2
m
6
 W
GF2

 B B f B2 Vtb*Vtd
Bd
d


2
Dmd mBd 2

x Dm
2
Dms mBs
Vts
Vtd
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Vts  Vcb
2
Theoretical Inputs :
x  1.21 0.040.05
fBd BBd-1/2 = 22333 12
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Flavor Tagging
Soft Electron Id,
Other Taggers,
Bd Mixing.
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Soft Electron Identification
D0 Liquid argon calorimeter
 Central (|| < 1) (32 EM Mod.), Forward upto (|| = 4)
  x f = 0.1 x 0.1 (finer in third layer – 0.05x0.05)
 Preshower added in runII – three layers of scintillators with WLS readout.
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Soft electron Id.
Electrons non-isolated in b-jets and of low momenta.
Reach shower maximum much earlier than higher
momentum electrons.
 Need preshower for electrons bremming early on.
 Use a narrower cone to reject fake activity.
e
EM

HAD
e
EM

HAD
Soft electron reconstruction separate from standard
calorimeter reconstruction. Start with track, extrapolate
to calorimeter and cluster towers around track in a
narrower D x Df region.
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The Road Method
Steps in the Road Algorithm
 Extrapolate track in a Helix inside the magnetic field ( 58.7 cm - inner
radius of coil) and then in a straight line.
 In every layer of calorimeter, use list of cells belonging to a predefined
road --  rings and f slices spanned by entry and exit points of track in
each floor.
 road
~ 90% contained in first three floors
~ 90 % of energy contained in road
Overall ~ 80% of energy
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f road
Shower profile suggests : 2  rings
and at most 1 f slice. Neighbouring
f slice added if track close to edge.
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Performance study
Detector material
Profile
Study performance using
signal : e+e-, J/Ye+ebackground : Ks 
Use 3 Variables
EMF  EEM
EHAD
E
EM
E/p 
PT (track)
Min Single layer cluster
energy in the 3-D CPS
cluster
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Flavor Taggers
Opposite side Flavor Tagging  Identify flavor of
reconstructed BS candidate using information from B
decay in opposite hemisphere.
Lepton Tag (e,m)
Jet-Charge Tag
Additionally – Look
for a secondary
vertex
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Tagger development
Develop likelihood for the tag to be from a b or a
b
Use B+  D0 m+ n X decay data sample (No
mixing, B flavor known on both sides).
 Small contribution from B0 decays which can oscillate
(2%). Require decay length of B candidate < 500 mm.


B  D m nm X
0

K 
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
14
Lepton Tag Likelihood
Use tracks in a cone (DR <
0.7) around e/m
m
Q jet


p
qi pTi
i
T
Q ejet 

p
qi pTi
i
T
Look for Secondary Vertex
Q SV
jet



q
p





p

i
L
i
i
L
Combined likelihood:
ri 
f i b ( xi )
f i b ( xi )
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n
r   ri
i 1
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Combined Tagger
In absence of lepton, use secondary vertex tagger in
combination with event charge. EV  qi pTi 
Q jet 
Muon Charge
i
 p 
T
Use taggers in order of preference
Muon > Electron > SVT
ri 
f i b ( xi )
f i b ( xi )
1 r
d
1 r
d > 0 Intial flavor b
d < 0 Initial flavor b
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Bd mixing &Tagger calibration
B+ and Bd decays.
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Decay
Ns (CDF)
Ns (DØ)
B  mD0
~ 410 K
~ 230 K
B0  mD+
~ 219 K
B0  mD*
~ 54 K
B+  eD0
~ 142 K
B0  eD+
~ 79 K
B0  eD*
~ 21 K
Tania Moulik, Bs Mixing at Tevatron
~ 73 K
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Bd mixing and Tagger Calibration
Binned asymmetry fit :
 Bin D0 mass distribution in 7 Visible Proper decay
length VPDL bins
 (Dm, D ) 
2

i
Ai 
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( Ai  Aie (Dm, D )) 2
 2 ( Ai )
N OS  N SS
N OS  N SS
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Tagger Calibration at DØ
Asymmetry fits in dilution
bins
Increasing dilution
For final fit, bin the tag
variable |d| in 5 bins and do
a simultaneuos fit
 2 (Dm, f cc , Dd , Du ) 
 D2 * (Dm, f cc , Dd , Du ) 
 D2 0 (Dm, f cc , Dd , Du )
Dm  0.506 0.020 stat.)  0.016 (syst.)ps-1
eD2 = (2.48  0.210.07) (%)
e 19.9 0.2 %
fcc= 2.20.9(%)
Event-by-event dilution
Measurement of Bd mixing using opposite Side flavor tagging PRD 74, 112002
(2006)
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Individual Taggers performance
D (%)
eD2 (%)
6.61  0.12
0.473  0.027
1.48  0.17(stat)
Electron
1.83  0.07
0.341  0.058
0.21  0.07 (stat)
SV
2.77  0.08
0.424  0.048
0.50  0.11 (stat)
Tagger
e %
Muon
2.19  0.22 (stat)
Total OST 11.14  0.15
Note :
To evaluate the individual tagger performance |dpr| > 0.3
This cut was not imposed for final combined tagger.
Hence, final eD2 is higher.
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Flavor Tag at Tevatron
For comparison of break up, older CDF tagger results quoted. Very
recent numbers eD2 (OST) = 1.8% (With Neural network
combination of taggers) For individual tagggers at D0, |d| > 0.3
(Overall is higher).
CDF
Tagger e %
DØ
D
eD2 (%)
e%
D
eD2 (%)
SMT
4.8
0.36
0.54
6.6
0.47
1.48
SET
3.1
0.30
0.29
1.8
0.34
0.21
JVX
7.7
0.20
0.2
2.8
0.42
0.5
JJP
11.4
0.11
0.3
JPT
57.9
0.05
0.14
OST
85
SST
54
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1.500.06
28.3
19
2.480.22
4.000.10
T. Moulik, (hep-ex/0701022) , Proc. Beauty 2006 21
Tania Moulik, Bs Mixing at Tevatron
Bs Mixing
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Selection – Semileptonic Mode
B
μ(e)
X
D-S
n
Decay
Ns (CDF)
Ns (D0)
Ds (f) m n
~19K
~27 K
Ds (f) e n
~11K
~ 10 K
Ds (KK) m n
~14
~ 13 K
Ds (KK) e n
~ 8.2 K
Ds (3) (m,e) n
~ 9.9 K
Total
~ 62 K
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μ+/e+
B  Bs0
0
s
-
φ
K+
K-
~ 50 K
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Bs  Ds e ne X selection
Using road electrons with pT > 2.0 GeV in central || <
1.1.
Cuts on calorimeter quantities only: EMF > 0.7, 0.55 <
E/P < 1.1
Using the inclusive muon triggered sample : Events
already tagged.
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Selection – Hadronic Modes
Decay
Ns (CDF)
DS(f) 
~ 2.0 K
Partially rec.
~ 3.1 K
DS(K*K,3) 
~ 2.1 K
DS(K*K,f,3) 3
~ 1.5 K
Hadronic
~ 8.7 K
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Detector Effects
flavor tagging power,
background
mis-tag rate 40%
1

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
Decay length
resolution
momentum
resolution
L) ~ 50 mm
p)/p = 5%
2
2  ( Dms t )
SeD
2
e
2
S
SB
Tania Moulik, Bs Mixing at Tevatron
SM prediction :
Dms ~ 20 ps-1
Tosc~0.3 10-12 s
26
Expected p.d.f.
Prob. for oscillated and non-oscillated events as a
function of the decay time or distance (x) for signal :
p snos (t )
p sosc (t )
 Gt
 0.5  1  D cos Δms  t 
 Gt
 0.5  1  D cos Δms  t 
 Ge
 Ge
p snos / osc ( x)
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
K
c Bs

e
Kx
c Bs
Taking into
Missing energy
Visible proper decay length
(VPDL)
Dilution from flavor
tagging
 0.5  1  D cos Δms  Kx / c 
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Expected p.d.f
Transition to measured VPDL (xM). For j’th mode :

/ osc M
p nos
( x )  dK f j ( K )
j
e j (xM )
Nj
Integrate over
K-factor distribution
p snos / osc ( x)  g ( x)
Convolution with
VPDL resolution
There are contributions from other channels to same
final state as well. Overall PDF is sum over all j’s taking
into account relative contributions.
.
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Likelihood minimization for Dms
2 ln L
Minimize
L
Pi  p
xM


1  fsig Pi,bg  fsig Pi , sig 
candidates

xM , x
M

, d pr p
 xM
p
d pr
p
M f
p
 log10 y
Proper Decay Length (pxM) , Decay Length Error (pxM), Dilution (pdpr),
Mf Ds mass distribution (pMf), Signal Selection Variable (py)
Signal PDF:

/ osc M
nos / osc
p nos
(
x
,

,
d
)

dK
f
(
K
)
e
(
x
)
p
( x, d pr , K )  g ( x)
M
j
pr
j
j M
s
x
Background PDF: Fractions estimated from lifetime fit.
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Reco. Efficiency vs Lifetime
Efficiency after lifetime cuts
Depends on the decay length of the
Ds+m candidate.
Other efficiencies included in
sample composition
estimation.
Efficiency is ~ 90% for VPDL > 0.05 cm
And > 25% for VPDL < 0.05 cm
Below 0 cm, fake events increase the efficiency.
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Decay length Resolution
Decay Length Error
Tosc @ 19ps-1 ~ 0.01
cm
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Are errors estimated correctly?
Use J/ψ→mm/ee sample. Get Pull distribution
For correct errors ~ 1.
Scale Factor : 1.0 for 67 %, 1.8 for 33%
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Amplitude Scan
Modify the equation and introduce an amplitude term
p snos / osc ( x)


K
c Bs
e
Kx
c Bs

 0.5  1  D
A cosΔms  Kx / c 
Vary Dms and fit for A:
 A consistent with 0  no oscillation.
 A consistent with 1 and inconsistent with 0  oscillation.
 Range of dms for which amplitude is compatible with 0 and
incompatible with 1 can be excluded. All values for which A+1.645  <
1 are excluded at 95% C.L.
 Sensitivity : 1.645 = 1 (Will see oscillations if Dms is below this
value)
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check Using BdXμD±(f), and
sideband
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Dms Scan (Signal region)
A/A (19.0 ps-1) = 2.5 (from 0)
A/A (19.0 ps-1) = 1.6 (from 0)
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Dlog L  log Lmin – log L
17 < Dms < 21 ps-1 @ 90% CL assuming
Gaussian errors
Most probable value of Dms = 19 ps-1
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Significance of the minimum
Simulate Δms=∞ by randomizing the sign of
flavor tagging
Prob. to observe Δlog(L)>1.9 (as deep as ours)
in the range 16 < Δms < 22 ps-1 is 3.8%
 5% using lower edge of syst. error band
 Region below 16 ps-1 is experimentally excluded
 No sensitivity above 22 ps-1
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CDF Scan
A/A (17.75 ps-1) = 6.05
A (Dms = 17.75 ps-1) = 1.24  0.20
Dlog L  log L(A=0) - log Lmin (A=1)
log Lmin (A=1) = -17.26
What is the significance of the minimum ?
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Likelihood Significance
Perform 350 million experiments with randomized flavor tag. Only 28
trials with min(Dlog L) < -17.26,
p-value = 8 x 10-8 > 5  Very small prob. For background fluctuation)
(p-value = 5 x 10-7 ~ 5.0  
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Combination with other modes at D0
Bs  Ds (f) e n X
Sensitivity increase 14.1  16.5 ps-1
Amplitude peak however no longer
significantly separated from 0 but is
consistent with 1 @ 19 ps-1
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Bs  Ds (KK) m n X
Preferred value ~ 19 ps-1
But 8% expectation for
background fluctuation
(5% for published result)
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T. Moulik, A. Nomerotski, FERMILAB-CONF-06-496-E (ICHEP 2006)
Implications of current status
Dms is standard model–like (upto
present state-of-the art theory
predictions)
Dms (Not in CKM Fit) = 18.952..78
Testing New Physics in the Bs decays ?
New Physics enters the function S0(xt) (Inami-Lim function) but theoretical
uncertainties make testing difficut using the Dms measurement alone.
Will need added experimental information from DGs and CP asymmetry in
flavor specific decays afs (New measurements from DØ probing this)
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Constraining the CKM Matrix
Only Angles
Combined Fit
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Dms Future prospects at DØ
Detector upgrades
Addition of Layer 0
 Better decay length resolution ~ 10-15%
Improvement in rec. efficiency ~ 40%
Analysis improvements
Addition of Same side tagging ~ 20% improvment in eD2.
Event-by-event scale factors ~ 8% improvement in
sensitivity
Finer binning in k-factors ~ 10% improvement in
sensitivity
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Sensitivity studies
Using Analytical Expression
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Conclusion
1 fb-1 data sample was used for the Bs oscillation studies at Tevatron.
D0 : 90% C.L. interval for Δms: 17 – 21 ps-1 assuming Gaussian errors.
Probabilty for fluctuation for higher Dms ~ 5%.
CDF 5.4  result consistent with D0 result. Dms measured to be:
17.77 ± 0.10(stat) ± 0.07(sys)
|Vtd|/|Vts| = 0.2060 ± 0.0007(exp) +0.0081 -0.0060 (theor)
Improvements in the pipeline for D0 analysis.
 Layer 0 is installed and performing well.
Dms provides strong constraint on the CKM triangle. Vtd Currently limited
by theoretical errors. An independent measurement from DØ would be
interesting in its own right.
CP violation in B-sector will be measured precisely in the next few years.
CKM matrix uptil now consistent with standard model predictions.
Improvements in theoretical calculations will help to test the model further.
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BACK-UP SLIDES
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B Mixing
In general, probability for unmixed and mixed decays :
Pu,m(B)  Pu,m(B). In limit, G12 << M12 (DG << DM)
(Standard model estimate and confirmed by data),
e t / 
p( B  B) 
(1  cos Dmt )
2
e t / 
p( B  B ) 
(1  cos Dmt )
2
~ 10 3
~ 10-4 for Bs system
~ 10-3 for Bd system
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DØ Detector
Muon chambers
m/e
(identify muon)
Bs
K
K
Ds
Silicon Microstrip
Tracker (SMT)
decay length resolution
Fiber Tracker + SMT
Track momentum resolution
Calorimeter + preshower
(indentify electron)
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Bd mixing and Tagger Calibration
Binned asymmetry fit : Bin D0 mass distribution in 7 Visible
Proper decay length VPDL bins
 2 (Dm, D ) 

i
( Ai  Aie (Dm, D )) 2
Ai 
 2 ( Ai )
N OS  N SS
N OS  N SS
PDF for oscillated and non-oscillated events:
ndosc,nonosc ( x) 
K
 0.5  (1  Dd  cos( Dmd  Kx c))  e
c d
c Bd  x M K
K-factor :

K

Kx
c d
PTDm
B
PT
Rec. efficiency
,nonosc M
M
osc, nonosc
N (osc
(
x
)

dx

(
x

x
)

e
(
x
)
dK
D
(
K
)


(
x
)

n
( x, K )
j
j
d ,u , s ), j
(u , d , s )
VPDL resolution
01/29/2006
of jth channel
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K-factor
47
Layer 0 Performance
At p~ 1 GeV,
50 mm  25 mm
~ 10% improvement
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Results ofKxthe Lifetime Fit
p snos / osc ( x)

K
c Bs

e
c Bs
 0.5  1  D cos Δms  Kx / c 
Most important region
Different background models are used for cross-check and systematic errors
Trigger biases have been studied
 Central values for cτBs= 404 − 416 μm
 Statistical error ~10 μm
 HFAG value cτBs = 438 ± 12 μm
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Sample Composition
 Estimate using MC simulation, PDG Br’s, Evtgen exclusive Br’s
Signal: 85.6%
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K-factors
Use different K-factor distributions depending on the
mass of μDs system for Ds and Ds* samples
I
01/29/2006
II
III
IV
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51
Mass PDF
Contributions of background, D+, Ds+ and D+ reflections are
taken into account.
B+D+(X)  f +
BsDs+(X)  f +
Fit in the entire mass region from 1.72 to 2.22 GeV
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Signal Selection Function
Use variables that
discriminate signal and
background using Mf
distribution sidebands and
signal region. Form yi = fs/fbkg
for ith variable. y is product
over all yi’s.
Use the signal selection
function in the likelihood
 Use the full information to weight
the events
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Proper Decay Length & K-factor
Proper Decay Length is
determined from the Visible
Proper Decay Length (x M)
c B 
LBXY
 βγ 
B
T
 LBXY 
MB
PTB
c Bs  x M K
K
PTDsm
PTBs
K Factor takes into account
the escaping neutrino and
other missing particles
Decay time resolution.
t  t
01/29/2006
 L2
2
L

 K2
K2
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Event reconstruction
Look for muon pT > 2 GeV, p > 3 GeV.
All charged particles clustered into jets. Events with more than one
muon in same jet are rejected.
J/Y  mm events are rejected.
Look for two tracks in same jet as muon.
 PT > 0.7 GeV, || < 2
 Tracks are required to form a vertex with a fit 2 < 9.
 Displaced tracks
 Combined impact parameter significance
[e T  ( e T )]2  [e L  ( e L )]2  2
Requirements on the D0 vertex
 Distance dTD, between primary and D vertex in axial plane > 4 (dTD)
 (dTD) < 500 mm.
 D0 pointing to primary vertex. cos(aTD) > 0.9
D0 and m vertexed to form a B candidate
 2 < 9
 2.3 < M (mD0) < 5.2 GeV
 Cuts on distance between primary and B vertex and pointing angle for B.
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Sampling calorimters
Sampling calorimeters
ATLAS (Pb, LAr), D0 (U, LAr), CDF(Pb, Scintillator, Gas)
Homogenous calorimeters
Semiconductor calorimeters e.g. silicon or germanium
Cherenkov calorimeters e.g. lead glass or water
Scintillator calorimeters e.g. BGO, CsI, PbW04
Noble Liquid, e.g. Ar, Kr, Xe only (no absorber)
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56

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