JHEP09(2018)146
Candidate Λ decays are reconstructed in the Λ→ pπ
−
decay mode from two oppositely
charged tracks. The tracks are reconstructed in one of two categories, depending on where
the Λ decayed in the detector. The two tracks either both include information from the
VELO (long candidates) or both do not include information from the VELO (downstream
candidates).
3
The Λ candidates must also have: a vertex fit with a good χ
2
; a decay time
of at least 2 ps; an invariant mass within 30 MeV/c
2
of the known Λ mass [33]; and a decay
vertex at z < 2350 mm. The requirement on the decay position removes background from
hadronic interactions in the material at the exit of the RICH1 detector. The Λ baryon and
the dimuon pair are required to form a vertex with a good fit quality. The resulting Λ
0
b
candidate is required to be consistent with originating from one of the PVs in the event
and to have a vertex position that is significantly displaced from that PV.
An artificial neural network is trained to further suppress combinatorial background,
in which tracks from an event are mistakenly combined to form a candidate. The neural
network uses simulated Λ
0
b
→ Λµ
+
µ
−
decays as a proxy for the signal and candidates
from the upper mass sideband of the data, with a Λµ
+
µ
−
invariant mass greater than
5670 MeV/c
2
, for the background. The inputs to the neural network are: the χ
2
of the
vertex fit to the Λ
0
b
candidate; the Λ
0
b
decay-time and the angle between the Λ
0
b
momentum
vector and the vector between the PV and the Λ
0
b
decay vertex; the Λ flight distance from
the PV, its p
T
and reconstructed mass; the IP of the muon with the highest p
T
; the IP
of either the pion or proton from the Λ, depending on which has the highest p
T
; and a
measure of the isolation of the Λ
0
b
baryon in the detector. The working point of the neural
network is chosen to maximise the expected significance of the Λ
0
b
→ Λµ
+
µ
−
signal in the
15 < q
2
< 20 GeV
2
/c
4
region, assuming the branching fraction measured in ref. [10]. It is
checked that selecting events based on their neural network response does not introduce
any significant bias in the reconstructed pπ
−
µ
+
µ
−
mass distribution, m(pπ
−
µ
+
µ
−
).
5 Candidate yields
Figure 1 shows the pπ
−
µ
+
µ
−
mass distribution of the selected candidates in the Run 1 and
Run 2 data sets, separated into the long-track and downstream-track pπ
−
categories. The
candidates comprise a mixture of Λ
0
b
→ Λµ
+
µ
−
decays, combinatorial background and a
negligible contribution from other b-hadron decays. The largest single component of the
latter arises from the decay B
0
→ K
0
S
µ
+
µ
−
, where the K
0
S
meson decays to π
+
π
−
and is
mis-reconstructed as a Λ baryon.
The yield of Λ
0
b
→ Λµ
+
µ
−
decays is determined by performing an unbinned extended
maximum-likelihood fit to m(pπ
−
µ
+
µ
−
). In the fit, the signal is described by the sum of
two modified Gaussian functions, one with a power-law tail on the low-mass side and the
other with a power-law tail on the high-mass side of the distribution. The two Gaussian
functions have a common peak position and width parameter but different tail parameters
and relative fractions. The tail parameters and the relative fraction of the two functions
is fixed from fits performed to simulated Λ
0
b
→ Λµ
+
µ
−
decays. The mean and width
3
Tracks with information from the VELO typically have a better momentum resolution and are associated
with Λ baryons with shorter lifetimes.
– 5 –
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