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Initial Analysis towards a Measurement of the
Branching Fractions B- py and B-+ wy
by
Molly Bright
Submitted to the Department of Physics
in partial fulfillment of the requirements for the degree of
Bachelor of Science in Physics
at the
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
May 2006
bCuEn 9.i"n
(C) Massachusetts Institute
of Technology
,, 2006. All rights reserved.
MASSACHUSErrS INSTITJTE
OF TECHNOLOGY
JUL 0 7 2006
L~n6
Author...................................
.... LIE3RARIES
·
(JDepartment
of Physics
May 19, 2006
Certified
by...............................
Gabriella Sciolla
Assistant Professor
Thesis Supervisor
Acceptedby...............
.
.
.
*"*.
*
*-
.
.
.
.
..-. .
i
.
.
.
.
David E. Pritchard
Senior Thesis Coordinator, Physics Dept.
ARCHIVES
2
Initial Analysis towards a Measurement of the Branching
Fractions B-e py and B-e wy
by
Molly Bright
Submitted to the Department of Physics
on May 19, 2006, in partial fulfillment of the
requirements for the degree of
Bachelor of Science in Physics
Abstract
The Standard Model of particle physics predicts the existence of the "Unitary Triangle," which graphically relates the matrix elements of the Cabbibo Kobayashi
Maskawa matrix and describes the strength of transformations from one quark to
another. By measuring the ratio B(B p/wy)/B(B
, K*y) we can measure a
side length of this triangle and use the result to test the Standard Model, and perhaps
illuminate new physics. In this thesis, a new set of cuts on variables measured by the
BABAR detector is optimized to obtain high levels of efficiency and significance in
separating the rare py or w-ysignal events from the high levels of continuum background. Neural nets that can consider correlations between variables have also been
implemented to suppress the continuum. Preliminary results using Monte Carlo are
discussed. Final values using runs 1 through 5 of the BaBar experimental data will
be published in summer 2006.
Thesis Supervisor: Gabriella Sciolla
Title: Assistant Professor
3
4
Acknowledgments
Thank you to Prof. Sciolla, who graciously brought me into her group and helped me
throughout the thesis process. This work was also done with indispensible scientific
and technical support from Ming Yi, Mary-Irene Lang, Nivedita Chandrasekharen
and the other "Rad Penguins." The moral support of my parents across the telephone
lines has also been crucial in the production of this paper.
5
6
Contents
1
13
Introduction
1.1 Standard Model of Particle Physics ........
1.1.1 The Subatomic Particle Zoo ........
1.1.2
1.2
Symmetry Violation and the CKM Matrix
Radiative B Decays.
...........
...........
...........
...........
2 The BaBar Experiment
13
14
15
17
23
2.1 Charged Particle Tracking System .........
25
2.2 Detector of Internally Reflected Cherenkov Light
28
2.3 Electromagnetic Calorimeter ............
30
2.4 Instrumented Flux Return and Muon and Neutral Hadron Detection.
30
3 Analysis
33
3.1 Variables and Cuts.
3.1.1
Photon Cuts .
3.1.2
Meson and Charged Track Cuts . .
3.1.3
Continuum Background Suppression
3.1.4
B Meson Selection
3.1.5
Optimization.
.........
3.2 Neural Nets.
3.3
Efficiency
..................
3.4 Sanity Checks ................
7
...............
...............
...............
..............
...............
...............
...............
...............
...............
34
34
35
36
37
37
38
41
41
4 Results and Conclusions
51
8
List of Figures
1-1
The Unitary
Triangle.
. . . . . . . . . . . . . . . .
.
.......
17
1-2 Feynmann diagram of the b -- d quark process. ............
21
2-1 The electrons and positrons are accelerated and then fed into the two
storage ring machine PEP-II.
of BaBar detector.
.......................
2-2
Structure
2-3
Schematic of DIRC .............................
24
. . . . . . . . . . . . . .
. . .
..
26
29
3-1 Schematic illustration of how a neural net can use correlation to obtain
better separating power. ..........................
40
3-2 The separating power between signal and background of six variables
used as input to the neural net. .....................
3-3
..
42
Comparison of Off Peak Data with MC uds. ...............
44
3-4 Comparison of Off Peak Data with MC uds. ..............
45
3-5
46
RhoO mode Efficiency Table ........................
3-6 Rho mode Efficiency Table. BAD876 cuts applied to new data
.....
3-7 Omega mode Efficiency Table. BAD876 cuts applied to new data. . .
47
48
4-1
Efficiency table for p0 mode using new cuts.
..............
52
4-2
Efficiency table for p± mode using new cuts. ..............
53
4-3
Efficiency table for w mode using new cuts ................
54
9
10
List of Tables
1.1 Fundamental fermionic particles and their masses, divided into three
generations.
19
1.2 Four main types of mesons. Naming is determined by the heavier of
their quark pair.
..............................
20
3.1
Fixed Cut Values for po mode.
3.2
Optimized Cut Values for po mode.
3.3
The 33 Neural Net Variables .......................
4.1
Expected yield for the B° 0
4.2
Expected yield for the B° - po' decay mode.
. . . . . . . . . . .56
4.3
Expected yield for the B + -- p+ decay mode
. . . . . . . . . . .57
4.4
Expected yield for the B +
. . . . . . . . . . .59
4.5
Expected yield for the B° -- w' decay mode .
4.6
Expected yield for the B° -- wy decay mode .
-
......................
...................
poy decay mode .
p+7ydecay mode
11
38
38
49
......... ...55
. . . . . . . . . . .60
......... . .61
12
Chapter
1
Introduction
1.1
Standard Model of Particle Physics
Developed in the late sixties and early seventies, the Standard Model of particle
physics (SM) describes the set of known fundamental particles and their interactions
via the strong, weak, and electromagnetic forces. The SM is a quantum field theory
that is generally considered to successfullyexplain and predict the physics of quantum
mechanics and special relativity. There is still a great deal of debate over the extent
of this success; the SM currently doesn't include the gravitational force at all, the
predicted Higgs particle has never been seen, and many free parameters contained
in the model cannot be calculated but rely on experimental measurement. Proposals
of "grand unification" theories try to address current concerns, but still the model
appears to many scientists to be incomplete. For example, the SM relates matter
and antimatter in terms of CPT symmetry, which suggests there should be an equal
amount of matter and antimatter in the universe after the Big Bang. A cursory
glance at the immediate environment shows the unsettling dominance of matter in
our world, and advanced experimental research in particle physics also reveals even
more detail on the finer working of this symmetry violation.
13
1.1.1
The Subatomic Particle Zoo
It is important first to understand the general concepts presented in the SM. There
are two types of fundamental particles: fermions and bosons. Fermions possess halfinteger spin and obey the Pauli Exclusion Principle. A simple example of a fermion is
the electron, and the fermionic nature of the electron is what causes the organization
of the Periodic Table of the Elements and the principles of chemistry. In the SM,
fermions come in three groups called "generations" labeled 1, 2, and 3. Generation 1
contains the electron, the "antielectron" or positron, the electron neutrino and its antineutrino counterpart. These particles fall into the category of "leptons." The other
particles in the generation are quarks and their respective antiquarks. A summary of
the leptons and quarks is given in Table 1.1.
Ordinary matter is made up of particles form generation 1 due to their significantly
smaller masses: the higher generation particles decay quickly into first-generation
ones. Quarks are generally confined in groups of two or three as hadrons. Mesons,
which are composed of a quark-antiquark
pair, are of extreme importance to the
analysis discussed in this paper. The other possibility is the three-quark baryon,
which includes the familiar proton and neutron from atomic physics.
Mesons are
named based on the heavier of their two quarks, and the possibilities are given in
Table 1.2
Bosons possess integer spins and can actually occupy the same quantum state,
which leads to the intriguing fields of Bose-Einstein condensation and superfluidity.
Bosons are generally used as force carriers in the SM. The known bosons are:
* Photons-quanta of light, mediate the electromagnetic interactions
* W and Z Bosons- mediate the weak force, essential in decay processes
* Gluons- mediate the strong nuclear force, described in terms of "color" in Quan-
tum Chromodynamics (QCD)
* Higgs Boson- induces spontaneous symmetry breaking, responsible for the ex-
istence of inertial mass (predicted, not yet seen)
14
In this research we are focusing on the decay of B mesons. This process, a particle
decay, simply involves one fundamental particle transforming into other fundamental
particles. (This is different from radioactive decay, in which the products of the event
are parts of the original, composite substance.)
transformation
Only weak decays can cause the
of fundamental particles (i.e. a flavor change). When a fundamental
particle decays, it first changes into a less massive particle and a force-carrier particle
(generally a W boson). This W boson then re-emerges as some other particle. A
clever reader may become upset at the apparent violation of energy conservation that
the production of a massive W boson appears to imply. It must be added that these
particles exist so briefly that they can be allowed through the Heisenberg Uncertainty
Principle (i.e. they can never be observed or measured).
Because of this character
trait, this type of boson is known as a "virtual" boson [5].
1.1.2 Symmetry Violation and the CKM Matrix
There are three major symmetries present in the Standard Model:
* C - charge symmetry (transformation of a particle into its antiparticle)
* P - parity symmetry (spatial reflection of a system)
* T - time symmetry (reversal of a process)
At first, these symmetries were thought to be indelible. It came as quite a surprise when researchers saw that not only did violations occur, but they occur to the
maximum possible extent. The only symmetry which has remained thus far unbroken
is CPT symmetry.
P and C symmetry were discovered to be maximally violated in the 1950's, but
a combined CP symmetry was expected to be conserved. In 1964, however, James
Cronin and Val Fitch gave clear evidence that CP symmetry could also be broken.
(They were awarded a Nobel Prize for their work in 1980.) Kaons and B mesons are
prime examples of this type of symmetry violation, and thus an important motivation
for the research discussed here.
15
In the Standard Model, CP violation is due to a single phase in the CabbiboKobayashi-Maskawa (CKM) matrix.
The CKM matrix is a unitary matrix which
contains information on the strength of flavor-changing weak decays.
In simplest
terms, the CKM matrix states the probability of a transformation of a quark q into
another quark q'. This probability is proportional to the matrix element Vqq,,12.
In
Eq. 1.1, the CKM matrix transforms the vector of strong force eigenstates into the
vector of weak force eigenstates.
Vd
V
Ib
d)
Idl)
Vcd
Vcs
Vcb
S)
I Sl)
Vtd
V
Vt b
lb)
Ibl)
Requiring that the CKM Matrix be unitary, we arrive at the equations
E Vik
= 0.
(1.2)
k
For any fixed i and j, this is a constraint on three numbers, one for each value of
k, which states that these three values form the vertices of a triangle in the complex
plane. Given 6 choices of i and j, there are six of these triangles.
If the sides and
angles of these triangles could be measured using various techniques, they would
provide a direct means of testing the predictions of the SM. It is also important to
over-diagnose these triangles, measuring all sides and angles. Perhaps experiments
will fully agree with the model, and it can be convincingly said that the realm of
particle physics is understood.
Perhaps, however, our results will prove inconsistent
or contradictory with respect to the SM predictions. Is there something flawed,then,
with the Standard Model? Is there "new physics" not yet discovered in the field?
There are two triangles that have all three side lengths of approximately the same
order, although only one of them can be feasibly measured experimentally:
Our analysis is geared towards measuring the length lVtd/Vtl. While this length
has been recently measured in B° oscillations, our measurement, based on completely
different decay diagrams, could unveil physics beyond the SM.
16
1
Figure 1-1: The Unitary Triangle.
1.2
Radiative B Decays
This research features the radiative penguin decay of a b quark into a d quark and
a photon. A penguin decay, which received its rather unusual name as the result
of a bet, is an effective flavor changing neutral current (FCNC) process that can be
illustrated by a simple loop in the Feynman diagram describing the process in Fig.
1.2.
The main intermediate contributor in the b
, d quark transition, along with the
virtual boson, is a top quark, t. Thus, by measuring the ratio of b
, d and b
s
quark events, it is possible to determine the ratio Vtd/Vtl we are aiming to obtain.
17
To decrease theory errors, we measure the ratio of branching fractions
B(B -B(B
py)
) K*y)
Vtd
Vt,
(1.3)
where the denominator is already known with good precision.
While theoretically B -
py provides the best measurement of Vtd/Vtl, teh
statistics are limited. To lower the statistical error we include three decay modes:
pOy with pO _ 7r+r -
B
* B ± -* p±
B
-+
with p
- 7r7ro°
w where w + 7r+Tr-ro
These three modes are referred to as the p, p and w modes, respectively.
The
p0 , p and w particles are light, unflavored mesons. These then decay into pions and
photons, which can be recorded in the BABAR detector. It is necessary to use the
information about pions and photons to reconstruct what the B mesons decayed into.
The challenge arises from the incredibly small likelihood that these three decays will
occur with respect to the overwhelminglyprobable decays into strange mesons like
the kaon.
18
Particle Name
Generation
Symbol
1
Electron
e-
Electron neutrino
Positron
Electron antineutrino
Up quark
Down quark
Anti-up antiquark
Anti-down antiquark
ve
e+
ve
u
d
d
Generation 2
Muon
-
Muon neutrino
VA
Anti-Muon
Muon antineutrino
Charm quark
Strange quark
Anti-charm antiquark
Anti-strange antiquark
p+
c
s
s
Generation 3
Tau
r-
Tau neutrino
VT
Anti-tau
r+
Tau antineutrino
Top quark
Bottom quark
Anti-top antiquark
Anti-bottom antiquark
VT
t
b
b
Table 1.1: Fundamental fermionic particles and their masses, divided into three generations.
19
Heavier Quark Type
c
Name of Meson
D
s
K
t
does not exist
b
B
Table 1.2: Four main types of mesons. Naming is determined by the heavier of their
quark pair.
20
w
c
u
yct
t
1
J
d
I
d
Figure 1-2: Feynmann diagram of the b -+ d quark process.
21
22
Chapter 2
The BaBar Experiment
The Babar experiment began taking data in 1999, using the asymetric e+e - PEPII collider at the Stanford Linear Accelerator Center (SLAC). SLAC, built in 1962
in Menlo Park, California, is home to an extensive linear accelerator facility that
has helped the field of particle physics progress through the last several decades.
The electrons and positrons are first accelerated in the LINAC, and then fed into
the two storage ring machine PEP-II. The two beams are kept at different energies
(9.0 GeV and 3.1 GeV for the e- and e+ beams, respectively) and collide at a CM
energy of 10 GeV. This corresponds to the T(4s) resonance, which always decays into
two B-mesons.
B-mesons are produced essentially at rest in the rest frame of the
T(4s). While several combinations of beam energies are possible to create the desired
resonance, the beams have been optimized such that the detector that surrounds the
interaction point is capable of measuring most of the decay products but enough
boost of the resulting B mesons to look for CP violation as they sequentially decay.
The peak luminosity of the PEP-II collider was developed to be 3 x 1033 cm-1
s - l, although the current record of over 1 x 1034 cm - 1 s - 1 already triples this value.
Such high luminosities correspond to extremely high rates of T(4s) production: approximately 30-100 million BB pairs could be produced per year! [6]
The detector, shown in Fig.2, is designed asymmetrically with respect to the
collision point in order to consistently record particles exiting the interaction region.
Running at the T(4s) resonance, there is a Lorentz boost p/3yof approximately 0.56
23
PEP It
t
PDmOW
le
dIPEPII
~~~~~~~F~~~~~~n
"KW
fkuhBwp~
-----
SO&OO Mo
PP 11
(IGeV]
PEP 1LowEnergy ypss (HLEB)
JPEP
D
iEP
~~~~IR-2
r~~~~~~~~~~~B~~~~~~f~~
PEP 1
ihE
Am4PEPII
EA
a
taW3
km
PoS
Figure 2-1: The electrons and positrons are accelerated and then fed into the two
storage ring machine PEP-II.
24
in the e- direction, and the detector is constructed to cover approximately the same
solid angle in the forward and backward directions in the moving CM frame.
Several concentric cylinders surround the section of the PEP-II ring containing the
collision point. The different layers of particle detectors, as shown in Fig.2, include
the following devices (listed below with their primary purposes):
* Charged Particle Tracking System
- Silicon Vertex Tracker, to reconstruct decay vertices of particles;
- Drift Chamber, to measure the momentum of charged particles;
* Detector of Internally Reflected Cherenkov light, to identify particle species, in
particular pions and kaons;
* Electromagnetic Calorimeter, to reconstruct high energy y's, r0°'s and ro7's;
* Instrumented Flux Return, to identify muons and detect neutral hadrons.
Each portion of the detector measures specific traits of the B-meson decay products, and careful coordination of their measurements can be used to reconstruct what
events take place in the interaction region. Each of these diagnostic elements will
now be discussed in more detail.
2.1
Charged Particle Tracking System
The charged particle tracking system is made up of two components: the silicon vertex
tracker (SVT) and the drift chamber (DCH). The SVT is composed of five layers of
double-sided silicon strip detectors. The inner three layers provide primarily position
and angle information for measurement of the vertex position, while the outer two
layers, located at larger radii, provide similar information needed to link the recorded
particle tracks from the SVT and DCH. The SVT provides a spatial resolution along
the direction of the electron beam of less than 70 microns.
25
Collider ring containing
Interaction Point
IV
%IAlrAD
FPi IM -% it '
W
Approx.)
size of
person
ra
Figure 2-2: Structure of BaBar detector.
26
The drift chamber is a relative of the simple wire chamber. Wire chambers replaced the effective but time-consuming bubble chamber technique for recording a
particle's path. With bubble chambers, scientists were required to take a physical
picture of the chamber, develop the film, and then analyze the image visually. In
wire chambers, everything is done in real time and electronically. Wire chambers are
made up of many parallel wires arranged in a grid and biased with a high voltage.
As an energetic particle traverses the medium, ions and electrons left in its wake will
"drift" towards the nearest wires and cause a signal which can be traced back to
that specific location in the grid. Once a series of signal pulses are localized as the
particle passes completely through the chamber, one can reconstruct the entire path
by simply "connecting the dots." Our advanced version of this simple concept uses a
more complex 3-D grid with timing capabilities.
The DCH is a 280cm long cylinder with inner and outer radii of 24cm and 81cm
respectively. The tracking volume is made of 40 layers of wires arranged in 10 "superlayers" of 4 wires each. The super-layers are oriented in slightly different directions
to obtain an accurate and precise 3-dimensional reconstruction of the particle track.
The space between the wires is filled with 80% Helium gas and 20% Isobutane. This
arrangement allows for a spatial resolution of better than 140 microns.
The SVT and DCH are located within a 1.5T solenoidal magnetic field. The strong
magnetic field causes the charged particles exiting the interaction region to curve
strongly, in a direction determined by their charge. By quantifying the curvature of
the recorded track in these media we can determine the momentum of the particle:
'Lorentz =
ICP=
q (V x
ml
r
l
)
.
(2.1)
(2.2)
where q is the charge of the particle, v is its velocity, m is its mass, B the mag-
netic field, and r is the radius of curvature within the detector. Combining these
relationships, we see that the radius of curvature is given by
27
p
r= B
Ir-
n\
[z. )
where p is the transverse momentum of the particle.
2.2
Detector of Internally Reflected Cherenkov Light
The detector of internally reflected Cherenkov light (DIRC) is a novel device used
to separate pions and kaons. Cherenkov light is radiation emitted when a charged
particle travels through an insulator at a speed faster than the phase velocity of light in
that medium. It is named after Pavel Alekseyevich Cherenkov who first characterized
this effect and won a Nobel Prize for his efforts in 1958. A common analogy is the
notion of a "sonic boom" that occurs when a object travels faster than the speed of
sound in a medium. As a particle travels through a medium, electrons are displaced
or polarized, and if the material is an insulator, the restoration of the electrons to
their equilibrium positions is accompanied by the emission of a photon.
Normally,
the particle that is causing disruptions is moving at a speed slower than the radiation
it creates. The radiation then deconstructively interferes with itself and isn't seen.
However, when the disrupting particle travels faster than the radiation it leaves in
its wake, a cone of constructively interfering light is easily visible. The relationship
between the angle of this cone (with respect to the particle flight direction) and the
particle velocity is given by
cosOc
fin
(2.4)
where n is the index of refraction in the medium.
In our DIRC, 144 bars of fused silica arranged in 12 groups of 12 bars each are
used to create this Cherenkov radiation. The light travels through these bars into
toroidal tank of purified water, and finally reaches an array of photomultiplier tubes
(there are 10,752 PMT's in total in the BABAR detector). Using the position of the
signals from these PMT's as well as the timing of their detection, and image of the
28
I inht Cr.atnher
PMT + Base
PMT Surface
Track
T .jectory
I
Purified
Water
A6.
II
II
I
II
II
Window
13ox
Figure 2-3: Schematic of DIRC.
Cherenkov cone is inferred.
An illustration of the path of a Cherenkov light cone
through one fused silica bar is shown in Fig. 2- 3
The DIRC in BaBar is used primarily as a tool to differentiate charged pions
and kaons. These particles have different masses, and with the same momentum
(measured in the SVT and DCH discussed earlier) they will have different velocities.
The angle of Cherenkov radiation will therefore be the distinguishing characteristic
of these two particles which could look similar to the charged particle detectors.
The number of Cherenkov photons produced increases with the momentum of the
particle, and there is a threshold minimum number of photons required to accurately
seperate a pion or kaon from the background.
However, the lack of a signal also
carries information, and the detector is also used in "veto mode."
29
2.3
Electromagnetic Calorimeter
The electromagnetic calorimeter (EMC) is designed to measure electromagnetic showers with excellent efficiency, and high angular and energy resolution [2]. What is an
EM shower? When an electron, for example, passes through a material in which
there are high electric fields (i.e. E-fields due to the charge of nuclei in the material)
it will be deflected, and a virtual photon will be produced such that total energy and
momentum are conserved. The photon then has sufficient energy and momentum
that it produces a positron-electron pair, which in turn produce further pairs as they
propagate through the same medium. Thus a cascade or "shower" of electrons and
positrons is created by the initial particle. Eventually there is not enough energy to
form more pairs and all the particles of the shower are absorbed. High energy photons
also cause these showers, and we use the EMC primarily to analyze the high-energy
("hard")
y produced in signal events as well as decays of 7r°'s and O's, which decay
in turn to two photons [6].
The EMC in BaBar consists of 6,580 Thallium-doped
Cesium-Iodide (CsI(Tl))
crystals. Two photodiodes are mounted at the rear of each crystal and convert the
scintillation light produced by the EM showers into a measurable electric pulse. The
EMC is designed to detect photons in the range .02-9 GeV with a resolution of 1-2%.
2.4
Instrumented Flux Return and Muon and Neu-
tral Hadron Detection
The outer part of the BaBar detector (surrounding the superconducting magnetic
that creates the strong magnetic field inside the rest of the detector) has three main
purposes: magnetic flux return in the iron yoke support, muon detection and neutral
hadron detection [2]. The IFR uses the steel flux return of the magnet as a muon
filter and hadron absorber. The gaps between the steel plates are fitted with single
gap resistive plate chambers (RPCs), which detect streamers from ionizing particles
via capacitive readout strips. There are also two layers of cylindrical RPCs installed
30
between the EMC and the magnetic cryostat to detect particles exiting the EMC.
RPCs are gaseous parallel-plate detectors that combine the spatial resolution of
a wire chamber with the timing capabilities of a scintillation counter. They are
relatively simple to fabricate, consisting of a pair of parallel bakelite plates separated
by spacers with the gaps filled with gas. The outer surfaces are coated with Aluminum
and connected to high voltage. Two sets of copper readout strips are pressed against
the detector surfaces on opposite sides of the gap. For more detailed information
about RPCs please refer to [4] and [1].
31
32
Chapter 3
Analysis
The challenge in measuring the branching fraction of B -- p/wy lies in the great
disparity between levels of this "signal" and the much more abundant background
processes. Each step that can be taken to remove background events will have some
amount of undesirable consequence (i.e. will remove some of the signal as well). A
balance between the efficiencyof signal and background must be found to maximize
the statistical of the result.
To assist us in developing an unbiased system for background and signal separation, a Monte Carlo (MC) simulation of B decay events is generated and analyzed.
After this analysis has been completed, the real data from BABAR will be addressed.
In other words, we are doing a "blind analysis," meaning we are not looking at the
amount of signal selected by the cuts on real data until all cuts have been frozen.
Having this alternative, well-understood MC data also helps in the optimization and
analysis of cuts: because every simulated event is already labeled, we can easily observe the effects of cuts of each process individually. There is a level of uncertainty
in the labelling of the simulated events, and the term "truth-matched" is used to
indicate an extremely high level of confidence.
The enormous datasets produced in Monte Carlo simulation and in experimental
data are first processed with a set of very loose "cuts" to substantially shrink file size
and reduce process time by removing events that are obviously background. Each cut
simply looks at a certain variable (or combination of variables) and removes those
33
events with values in an undesirable range. A list of the principle variables used is
given in the following section.
After the first set of "skim" cuts is applied, more
focused work can be done to optimize each cut for the best possible total efficiency
and significance. After the data is processed in the optimized way, some variables
with especially good separating power (signal vs. background) are used to define a
"signal" region and a "fit" region in variable-space. The events remaining in the fit
region are fit with a carefully selected set of distributions.
We can then extrapolate
the fitted distributions into the signal region, and effectively count how many signal
events are present. The final analysis will use maximum likelihood fitting procedures.
3.1
Variables and Cuts
3.1.1 Photon Cuts
The production of a high energy photon is quite unlikely in typical B meson decay
processes. Because they actually do produce such a photon, the rare decays that
we are interested in can be distinguished by this feature. By requiring a high-energy
photon, we are able to reject many background events. The characteristics of all high-
and low-energy photons are aptly measured by the EMC. We choose the photon with
the highest energy to be the center of our focus.
gAcceptAngle
-0.74 < cos0 < 0.93 where 0 is the polar angle of the pulse. This
cut eliminates clusters of signals at the edges of the EMC where we cannot be
sure all particle information was successfully collected.
gnCrys Number of crystals that contribute to EMC signal must be greater than 4
to help guarantee the quality of our data.
GammaisOK
Rejects signals from EMC that include a "noisy" crystal.
Isolation (gdistNe and gdistCh) EMC cluster must be at least 25 cm away from
the nearest charged or neutral particle bump in signal.
34
gSecMom The second moment of the high energy y must be less than 0.002.
7r°/
Veto Rejects (vetoes) 7r -
yy and r -
-y' decays. These two processes
are large contributors to our background. Using our selected "high-energy" or
"hard" photon, we also select a second photon. The energies of the two photons
and the momentum of the "soft" photon can be combined to determine how
likely it is these two photons came from a r ° or a 7. We select the pair which
has the highest probability of being an unwanted 7r° or 7rdecays and use a veto
cut to remove the most probable background events.
3.1.2
Meson and Charged Track Cuts
The p0, p+ and w mesons are reconstructed in the final pion states: +rr- , 7lr±r°, and
7r+7r- r0°. These pions are required to match a variety of standards.
There are also
straightforward cuts on what these pions appear to reconstruct.
GTL+/-
"Good Tracks Loose" requires that there be at least two charged tracks
in the event which fulfill the following:
1. At least 12 "hits" in the DCH
2. Transverse momentum > 100 MeV/c 2
3. At some point track was closer than 1.5 cm to the beam axis
4. Track must have come closer than 10cm to nominal "beam spot"
5. Momentum of track < 10 GeV/c 2
Points 1 and 2 require that the track be sufficiently lengthy through the SVT
and DCH so that our data is reliable. 3-5 remove tracks induced by cosmic ray
events.
Pi+/-PID
and DRCcons Particle Identification. BaBar has analysis packages
that, using information from the DRC and the rate of energy loss in the DCH,
can select pions based on a range from very loose to very tight requirements.
There is the usual balance of efficiency and purity in the final product. In our
35
analysis, a collection of variables are analyzed to arrive at a likelihood that the
detected particle is actually a pion. Kaons must also be identified and removed.
The B -
Kir background peaks strongly in a way that overlaps and masks
our signal, and it becomes essential to remove this source of false-signal events
despite the necessary decrease in efficiencythat accompanies this type of cut.
Meson Mass Simple cut on the invariant mass of the p0 , p± or w.
RhoChi2Prob After reconstructing the tracks of the particles that come from our
signal events, we can attempt to discern the vertex at which the p must have
been when it decayed. However, given a set of tracks that have some uncertainty
in their precise location, we construct a X2 that reflects how likely it is that our
measured "vertex" is actually at the cross-point of our various individual tracks.
RhoCosHelic Cuts of the pw helicity angle based on the angular distribution of
the particles created in the decay.
3.1.3
Continuum Background Suppression
R 2 This variable provides a very efficient way to suppress continuum at the skim
level. R2 is the ratio of the second to the zeroth Fox-Wolframmoment H2 /Ho
where
HI =
,P(cos
illP
ij).
(3.1)
i,j
Here -i/j
are the momenta of two particles in the CM frame,
ij is the angle
between these momenta, Pl are the Legendre polynomials and s is the square of
the CM energy [4]. This value is a measure of how "jetlike" an event is. Continuum background events (u, d, s, or c quarks or charged leptons are produced)
are generally affiliated with two collimated bunches of particles moving in opposite directions. The desired signal events, e+e- - T(4S) - BB, are practically
isotropic. At the T(4S) resonance there is very little kinetic energy left for the
daughter B mesons, and thus these mesons have very little momentum that
could translate into jetlike decays.
36
Neural Network
Neural Nets provide a way to combine correlated variables for
optimal background rejection. Nets can be trained using Monte Carlo data to
discern the underlying probabilistic connection between variables, and then use
this "knowledge" to arrive at a probability that an unknown event is signal or
not. Neural Nets will be discussed at greater depth in a subsequent section. The
one implemented in this analysis is used to suppress the continuum background.
3.1.4
B Meson Selection
AE This variable is the difference between the reconstructed energy of the B can-
didate and the expected energy. The expected value is half of the total CM
energy, or the sum of the energies of the beams. Correctly reconstructed signal
events should therefore form a peak at around AE= 0.
mEs
The "beam energy substituted mass" is the invariant mass, but calculated using the beam energy instead of the energy of the particles reconstructed in the
detector. Because the energies of the beams are so precisely known, it is preferable that we use these values instead of the less precisely determined measured
values.
3.1.5
Optimization
Some of these cuts, especially those related to the EMC and high-energy gamma,
have been optimized by detector experts. The others, like the cuts on veto, meson
and NN, are optimized by us to obtain the most efficient and useful upper and lower
limits. The cuts that are fixed are shown in Tab. 3.1 and the optimized cuts with
their respective optimal limits are given in Tab. 3.2 for the RhoO mode. Rho+ and
Omega modes are optimized independently.
37
Category
Cut
high-energyphoton
-0.74 < cos Ohel <0.93
number of EMC crystals > 4
high-energy photon
no problem crystals
Isolation > 25 cm
Tracking and PID
Good Tracks - Loose
"veryTight" r ID
DIRC consistency
lAzj <0.4 cm
AZerr< 0.04 cm
Vertexing
Vertexing
0.63 < m,, < 0.94
Meson Mass
Table 3.1: Fixed Cut Values for pO mode.
Variable
NN Output
Lower Limit
0.957
Higher Limit
1
Prob(X2o)
0.016
1
cos(Ohel)
,r Veto
7 ° Veto
2 nd moment of y
-0.548
0.900
0.767
0
0.656
1
1
0.002
as95
0.941
1
Table 3.2: Optimized Cut Values for p0 mode.
3.2 Neural Nets
Neural networks are devices inspired by the complex workingsof the brain. In human
brains, for example, the precise mechanisms of how the organ as a whole processes,
understands, and makes decisions is still unknown. Large numbers of neurons, oper-
ating in intricate connection with each other, fire signals in parallel that then activate
neighboring neurons. In a similar way, neural nets are comprised of many similar elements that are linked together. Each link is prescribed a particular "weight," and the
signal produced by one element is passed through these links onto the next elements.
A network can be taught to determine the most accurate set of weights that provide
a desired outcome.
38
Neural nets have an intrinsic advantage in our analysis over using series of rectangular cuts on individual variables [4]. The links between NN elements (which we
can now think of as being labeled by a variable) consider the correlations between
variables.
This concept can be shown in a simplified example, illustrated in Fig.3-1. Let's
say we want to separate A from B using two variables (1 and 2). Using simple cuts,
like those described at length in the earlier section on variables, we do not consider
that there might be a correlation between these variables.
What happens when we introduce a Neural Net? Fig. 3-1 shows graphically what
correlation might look like as well as the optimized cut that best separates A from
B using the two available methods. Using normal cuts that only take one variable
into account, the optimized cut causes a portion of signal (A) to be eliminated and
a portion of background (B) to remain (see Fig. 3-1-a). Using this type of cut on
variables 1 and 2 separately, Fig. 3-1-b illustrates the consequence of such negligence:
the shaded regions in the upper right and lower left quadrants are mislabeled. If a
neural net is used, however, we can see in the two dimensional plot that the cut with
most separating power is on the diagonal.
Of course, we are not simply looking at two variables, and the correlations presetnt
in BaBar processes would require a very high-order dimensional space to describe
them. Our neural nets use 33 variables at initial inputs. These 33 each have two
links to a total of 66 "hidden nodes." These 66 nodes then combine in some way to
produce a signal output value. Each B-candidate that we feed into the NN will result
in a single number, which is the probability that the candidate is actually a B.
The neural net is trained using Monte Carlo data. A second, unrelated set of MC
data is used to "validate" the NN, making sure that the weightings being calculated in
the training process are actually helping the NN differentiate signal from background.
Short descriptions of the 33 variables used as input in our NN are given in Table
3.3. A visual example of how background and signal events are distributed across
these variables is given in Fig. 3-2. A good variable for a NN will show significant
differences between the signal and background distributions. This property, called
39
X2
Figure 3-1: Schematic illustration of how a neural net can use correlation to obtain
better separating power.
40
"separating power," helps provide the neural net with a strong foundation upon
which to train.
3.3
Efficiency
To optimize the set of variable cuts that we need to apply to our MC data, it is
essential to somehow quantify how successful a given cut or set of cuts is. We use two
such quantities:
efficiency and significance. Efficiency is then in turn broken down
into "relative" efficiency and "absolute" efficiency. Relative efficiency is a simple ratio
of how many events are still present before and after the cut. If half the events survive
the cut, then the relative efficiencyof this cut is 50%. Absolute efficiency compare
the events left after a given cut with the initial number of events present. Combined,
these give a measure of how effective each cut is.
Significance is extremely important in determining how much confidence our mea-
surement can merit, and is given by
S
S=
(3.2)
where S is the number of signal events present in the signal region after all cuts,
and B is the number of background events in the same region. The signal region is a
small area surrounding the predicted location of signal events in variable space. These
two quantities will feature prominently in the tables discussed in the next section as
well as in the final results.
3.4
Sanity Checks
It is important (and rather comforting) to be able to periodically check the analysis
to make sure that things makes sense. One possible uncertainty revolves the Monte
Carlo data: does it accurately represent was we intend it to? Clearly we would like to
directly compare some experimental results with our MC to reassure ourselves that the
simulation is running correctly. One easy way to do this is to explore the "off peak"
41
Figure 3-2: The separating power between signal and background of six variables
used as input to the neural net.
42
experimental data obtained by BaBar. Offpeak, or running off of the T(4s) resonance,
causes the u, d, s continuum background to dominate. This experimentally obtained
information, describing how real u, d, and s events are recorded by the detector, can
be directly compared with the "background" simulated by Monte Carlo. Examples
of such plots are given in Figures 3-3 and 3-4, clearly illustrating that the MC data is
being produced correctly. A similar check can be done to compare the control samples
with the MC signal.
Another source of so-called "sanity checks" is the BaBar Analysis Document
(BAD) 876. This lengthy paper includes almost all relevant facts regarding the analysis done through 2004 on this project.
Since this document was compiled, many
new techniques have been introduced, but there is a foundation of work already laid
which we can use as a reference for our progress.
Figures 3-5 through 3-7 are efficiency tables created in the same way as discussed
in the previous section. In these tables, however, the best cuts found in our optimization process are not used. Instead, the cuts used in BAD 876 are implemented.
In theory, although we are using new code and new Monte Carlo data, we should
obtain approximately the same efficienciesif we use the same cut limits. It must be
noted, however, that the neural net cut provides a slight problem. Because the net is
ever changing during training processes or reevaluation of its fundamental structure,
implementing a cut at the same value as BAD 876 will not necessarily have the same
effect. To balance this dilemma, the NN cut was tuned until the relative efficiency
was comparable to the earlier published values. BAD 876 does not provide us with
facts that we must imitate unquesitoningly. However, it is still a useful tool with
which we gauge the general trends in our analysis.
43
Figure 3-3: Comparison of Off Peak Data with MC uds.
44
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45
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46
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60
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00
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6
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le
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0
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a.,
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Figure 3-7: Omega mode Efficiency Table. BAD876 cuts applied to new data.
48
-a
C
r.
Table 3.3: The 33 Neural Net Variables
N
1
2
Name
abs(BcosAngGamThrust)
R2All
3
4
abs(BcosThetaCM)
BroeGamL2
5
6
7
8
BroeThrL2
BroeThrL1
BroeThrL3
BroeGamL1
9
BroeGamL3
10
BrecoilR2prime30
11
12
13
abs(BdeltaZ)
BRoeElelCosThMissCM
BRoeElelE9OW
14
15
16
BRoeElelP3CM
BRoeElelPid
BRoeEle2CosThMissCM
17
BRoeEle2E9OW
18
19
20
21
BRoeEle2P3CM
BRoeEle2Pid
BRoeMulCosThMissCM
BRoeMulE90W
22
23
BRoeMulP3CM
BRoeMu2CosThMissCM
24
BRoeMu2E90W
25
26
27
28
29
30
31
32
33
BRoeMu2P3CM
BRoeKChargedlP3CM
BRoeKCharged2P3CM
BRoeKShortlP3CM
BRoeKShort2P3CM
BRoeKinLepTrackslP3CM
BRoeKinLepTracks2P3CM
BRoeKShortlMass
BRoeKShort2Mass
Description
cosine of the angle of a particular gamma with respect to the Roe thrust axis
the ratio of the second to the zeroth Fox-Wolfram moments for event. ChargedTracksAcc and GoodNeutralLooseAcc are used for 'All'.
cosine of the polar angle of the center-of-mass momentum.
the second normalized Legendre moments of ROE boosted into the CM frame
with respect to the ROE thrust axis.
the second normalized Legendre moments in the CM frame
the first normalized Legendre moments in the CM frame
the third normalized Legendre moments in the CM frame
the first normalized Legendre moments of ROE boosted into the CM frame with
respect to the ROE thrust axis.
the third normalized Legendre moments of ROE boosted into the CM frame with
respect to the ROE thrust axis.
R2 of EMC bumps of energy greater than 30 MeV in a particular gamma recoil
system.
Az, the displacement between the two vertices in the z direction.
cosine of the angle between best electron's momentum and the missing momentum.
the sum of energies over all charged and netural candidates in the same hemisphere
as the best electron with respect to the direction of the virtual W± in the T(4S)
frame.
the center-of-mass momentum p* of the best electron
particle identification of the best electron
cosine of the angle between second best electron's momentum and the missing
momentum.
the sum of energies over all charged and netural candidates in the same hemisphere
as the second best electron with respect to the direction of the virtual WI in the
T(4S) frame.
the center-of-mass momentum p* of the second best electron
particle identification of the second best electron
cosine of the angle between best muon's momentum and the missing momentum.
the sum of energies over all charged and netural candidates in the same hemisphere
as the best muon with respect to the direction of the virtual WI in the T(4S)
frame.
the center-of-mass momentum p* of the best muon
cosine of the angle between the second best muon's momentum and the missing
momentum.
the sum of energies over all charged and netural candidates in the same hemisphere
as the second best muon with respect to the direction of the virtual W± in the
T(4S) frame.
the center-of-mass momentum p* of the second best muon
the center-of-mass momentum p* of the best charged kaon
the center-of-mass momentum p* of the second best charged kaon
the center-of-mass momentum p* of the best short kaon
the center-of-mass momentum p* of the second best short kaon
the center of mass momentum for the first kinematic lepton candidate
the center of mass mkentum for the second kinematic lepton candidate
invariant mass of best K short candidate
invariant mass of second best K short candidate
50
CO0! el C' ' CDqqq-
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Figure 4-2: Efficiency table for p mode using new cuts.
53
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C)
Figure 4-3: Efficiency table for w mode using new cuts.
54
k
4~
1c
a
-S
C) ,0007
corc
C
fit region
Description
B° -
p°y
B°
B° -
K*°7
K*O°, K*O -° K+Tr
B°
K*°r
-
B°
°r
B o -,
p
pOrq
B + -+
q+q
+
B
K+,r
B°
B+
B+
-
-
(300fb- 1 )
raw
raw
(300fb- 1 )
13056
10.82+0.10
12315
10.21±0.10
198
90
5.94+0.42
7.13±0.75
169
72
5.07±0.39
5.70±0.67
3
0.03±0.02
596
286
0.71±0.03
0.27±0.02
0
452
189
0.00±0.00
0.54±0.03
0.18±0.01
0
0
0.00±0.00
0.00±0.00
0
0
0.00±0.00
0.00±0.00
Ksr,
1
0.00±0.00
0
0.00±0.00
r+nr
K+7r
0
0
0.00±0.00
0.00±0.00
0
0
0.00±0.00
0.00±0.00
Sum
B°
B+
signal region
1.02±0.04
Xs
Xsfy
61
43
10.63±1.36
6.76±1.03
Sum
B°B ° background
B+B - background
Sum
0.72±0.03
31
8
17.39±1.71
5.40±0.97
1.26±0.44
6.66±1.07
53
34
15.96±2.19
9.17±1.57
25.13±2.70
25
2
udsbar
303
280.62±16.12
16
ccbar
116
106.29±9.87
10
taus
Sum
38
30.91±5.01
417.83±19.56
0
0.00±0.00
23.98±4.70
off-peak data
33
436.51±75.99
2
26.46±18.71
SI/VTV
1
0.51
7.53±1.51
0.54±0.38
8.07±1.55
14.82±3.70
9.16±2.90
1.57
Table 4.1: The expected yield for the B° -- pO7decay mode at 300fb -1 after applying
all new cuts. For the B background, the signal has been excluded, but not the peaking
B background.
55
-
fit region
signal region
r~~~~~~~~~~~
Description
B o __+
pO?
o
B -+ K*Oy, K*o
B0 -
Bo -
PO7r0
pr
Sum
B ° B° background
B+B- background
Sum
(300fb - 1 )
BAD876
16.8±0.1
K+7r -
-
-
-
(300fb - 1 )
-
BAD876
10.82±0.10
I
15.6±0.2
10. 21±0.10
11.4±0.6
7.13±0.75
9.2±0.6
5..70±0.67
1.60±0.02
0.99±0.03
2.59±0.04
33.3±4.4
43.2±7.1
76.5±8.3
0.71±0.03
0.27±0.02
0.98±0.03
1.20±0.02
0. 54±0.03
0.58±0.02
1.77±0.03
0
15.96±2.19
9.17t1.57
25.13±2.70
8.6±2.2
3.5±2.0
12.1±3.0
7. 53±1.51
udsbar
ccbar
taus
Sum
4000
280.62±16.12
106.29±9.87
30.91±5.01
417.83±19.56
off-peak data
4025±224
436.51±75.99
0. 54±0.38
8..07±1.55*
14. 82±3.70
9. 16±2.90
0. 00±0.00
23. .98±4.70
300±61
26. 46±18.71
Table 4.2: Comparison with BAD876, using new cuts for the B° -~ pOy decay mode.
Note: *For B°BO and B + B - , the old BAD had the peaking background excluded
whereas for our current values, the peaking background is included.
56
18±0.01
72±0.03
fit region
Description
B + ~ p+?
B+
K*+?
°
K*+r° , K*+ -- K+7r
B + -K*+T, K*+ -- K+r
B+
B°
p+ °r
B+
P+7/
(300fb-1 )
raw
14365
24.59±0.21
413
11
6
12.42±0.61
0.01±0.00
0.05±0.02
1976
3.48±0.08
375
3.21±0.17
Sum
B°
B+
signal region
raw
12606
145
2
1
1368
220
6.69±0.18
X-s
X8
178
227
15.51±1.16
17.84±1.18
(300fb-1 )
21.58±0.20
4.36±0.36
0.00±0.00
0.01±0.01
2.41±0.07
1.88±0.13
4.29±0.14
31
63
2.70±0.49
4.95±0.62
Sum
B°B ° background
110
33.13±3.16
17
5.12±1.24
B+B-
201
54.21±3.82
61
16.45±2.11
background
33.34±1.66
Sum
udsbar
ccbar
taus
Sum
off-peak data
7.65±0.79
87.33±4.96
21.57±2.45
1647
389
113
1525.36±37.59
356.44+ 18.07
91.92±8.65
1973.73±42.59
93
22
7
86.13±8.93
20.16±4.30
5.69±2.15
111.98±10.14
119
1574.07±144.30
11
145.50±43.87
S/V S+B
0.54
Table 4.3: The expected yield for the B+ -
1.73
p+y decay mode at 300fb-1 after
applying all new cuts. For the B background, the signal has been excluded, but not
the peaking B background.
57
2006. A journal publication will be made in fall 2006, using the entire BaBar run 1-5
statistics corresponding to a luminosity of 360fb- 1. This result will immediately be
compared with previous measurements, and it will provide a new perspective through
which to view the predictions of the Standard Model.
58
fit region
Description
BAD876
B+
p+ty
28.7±0.2
B+
p+7ro
7.0±0.1
6.5±0.2
--
B + --*p+r7
Sum
13.5±0.3
B°B ° background
74.7±6.5
95.6±10.5
B+B- background
170.3±12.4
Sum
off-peak data
J
signal region
BAD876
(300J £b- l)
25.3±0.2
21.58±t0 .20
4.7±0.1
3.5±0.2
8.2±0.2
2.41±0 .07
33.13±3.16
54.21±3.82
16.6±3.0
5.12±1 .24
19.8±4.8
16.45±2 .11
87.33±4.96
36.5±5.7
21.57t2 .45*
24.59±0.21
3.48±0.08
3.21±0.17
6.69±0.18
1.88±0 .13
4.29±0 .14
1525.36±37.59
356.44±18.07
91.92±8.65
86.13±8.93
7000
1973.73±42.59
111.98±1 0.14
7050±296
1574.07±144.30]
udsbar
ccbar
taus
Sum
(300fb-1 )
20.16±4 .30
5.69±2 .15
400±70
Table 4.4: Comparison with BAD876, using new cuts for the B + -
145.50±4 3.87
p+y decay mode.
Note: *For B°B ° and B+B - , the old BAD had the peaking background excluded
whereas for our current values, the peaking background is included.
59
fit region
Description
B° -,
B°
B°
1y
°
7r
-*
raw
wr
raw
(300fb -
3277
7.02±0.13
330
131
0.69±0.04
1.10±0.10
1.80±0.10
223
94
0.47±0.03
0.79±0.08
1.26±0.09
0.21±0.08
K*°7
31
0.93±0.17
7
K*+?
25
0.75±0.15
4
1.68±0.22
B° -+ Xsy
B + Xs?
Sum
B°B° background
B+B - background
Sum
udsbar
ccbar
taus
Sum
off-peak data
-+B
1)
7.88±0.13
Sum
SI
signal region
3677
Sum
B°
B+
(300fb- 1 )
0.12±0.06
0.33±0.10
16
2.79±0.70
4
0.70±0.35
18
2.83±0.67
5.62±0.96
4
0.63±0.31
1.33±0.47
17
15
5.12±1.24
4.05±1.04
9.16±1.62
6
2
1.81±0.74
0.54±0.38
2.35±0.83
273
79
15
252.84±:15.30
72.39±8.14
12.20±3.15
337.43±17.62
17
3
1
15.74±3.82
2.75±1.59
0.81±0.81
19.31±4.21
32
423.28±74.83
1
13.23±13.23
0.42
1.31
Table 4.5: The expected yield for the B -- wy decay mode at 300fb-1 after applying
all new cuts. For the B background, the signal has been excluded, but not the peaking
B background.
60
.
signal region
fit region
Description
(300fb - 1)
BAD876
BAD876
(300fb-.1)
B°O - w7
9.5+0.1
7.88i0.13
8.5t0.1
7.02i0.1~
B o - wr
0.50±0.03
0.69i0.04
2.2+0.1
2.7+0.1
1.10+0.10
1.80i0.10
0.35i0.03
1.3t0.1
1.7i0.1
0.47:0.0:
0.790.01
1.26+0.0'
K*O7
2.7+0.3
0.93+0.17
0.7i0.2
B+ -+K*+
2.3i0.3
0.8±0.2
Sum
5.0+0.4
0.75+0.15
1.68+0.22
5.12i1.24
4.05i1.04
9.16±1.62
1.7±1.0
0.21i0.0
0.12±0.0(
0.33+0.1(
1.81i0.74
1.2i1.2
0.54±0.3&
B°
- wr
Sum
Bo -
B°B ° background
11.5i2.6
B+B- background
14.0i4.0
Sum
25.5i4.7
udsbar
ccbar
taus
Sum
1700
337.43+17.62
off-peak data
1763i148
423.28i74.83
1.6+0.2
2.8+1.5
252.84+15.30
72.39i8.14
12.20i3.15
I
2.35±0.8
15.74i3.8'
2.75+1.5
0.81+0.81
19.31+4.21
175i46
13.23±13.23
Table 4.6: Comparison with BAD876, using new cuts, for the B° - wy decay mode.
Note: *For B°B ° and B+B - , the old BAD had the peaking background excluded
whereas for our current values, the peaking background is included.
61
62
Bibliography
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http://atlas.web.cern.ch/Atlas/TP/NEW/HTML/tp9new/tp9.html.
[2] The BaBar Collaboration. The babar detector. Technical report, Stanford Linear
Accelerator Center, 2001.
[3] M. Convery et al. Search for b
-+
py and b -, wy with run 1-4 data.
BaBar
Analysis Document 876, Stanford Linear Accelerator Center, University of Wisconsin,Madison, MIT, UC Santa Cruz, August 2004.
[4] Karsten Koeneke. Measurement of the Branching Fraction for the Decay B K*+y, K*
- K7r
°
with the BaBar Detector. PhD dissertation, University of
Massachusetts, Amherst, Department of Physics, September 2003.
[5] L.B. Okun. a,/3, ...Z, A Primer in Particle Physics. Harwood Academic Publishers, Chur, Switzerland, 1987.
[6] SLAC. Virtual visitor center (detector, experiment, and physics information).
http: //www2.slac.stanford.edu/vvc/.
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