EUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH (CERN)

 CERN-EP-2019-067 LHCb-PAPER-2019-011 October 10, 2019

A search for

${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ decays

LHCb collaboration†††Authors are listed at the end of this paper.

A search for the ${\mathchar 28932\relax}_{{c}{c}}^{++}$ baryon through the
${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ decay
is performed with a data sample corresponding to an integrated luminosity of
1.7$\text{\,fb}^{-1}$ recorded by the LHCb experiment in ${p}{p}$ collisions
at a centre-of-mass energy of 13 TeV. No significant signal is observed in the
mass range from the kinematic threshold of the decay to
3800$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$. An upper limit is set on the ratio
of branching fractions $\mathcal{R}=\frac{\mathcal{B}({\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})}{\mathcal{B}({\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})}$ with
$\mathcal{R}<1.7\hskip 2.0pt(2.1)\times 10^{-2}$ at the 90% (95%) confidence
level at the known mass of the ${\mathchar 28932\relax}_{{c}{c}}^{++}$ state.

Published in JHEP, DOI: 10.1007/JHEP10(2019)124

© 2024 CERN for the benefit of the LHCb collaboration. CC-BY-4.0 licence.

##  1 Introduction

The first observed doubly charged and doubly charmed baryon was the
${\mathchar 28932\relax}_{{c}{c}}^{++}$ ($ccu$) state found through the
${{{\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}}}$ and ${{{\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28932\relax}_{{c}}^{+}{{\pi}^{+}}}}$ decay modes by the LHCb collaboration [1,
2]. With two heavy constituent quarks, this baryon provides a unique system
for testing quantum chromodynamics. The average mass of the ${\mathchar
28932\relax}_{{c}{c}}^{++}$ baryon from the two LHCb measurements now stands
at ${3621.24\pm
0.65(\mathrm{stat})\pm~{}0.31~{}(\mathrm{syst})}$$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$
and its lifetime is $0.256^{+0.024}_{-0.022}$ (stat) $\pm$ 0.014 (syst) ps
[3], consistent with a weakly decaying state. However, many features of the
${\mathchar 28932\relax}_{{c}{c}}^{++}$ baryon remain unknown, including its
spin and parity. Previously, signals of the singly charged ${\mathchar
28932\relax}_{{c}{c}}^{+}$ state were reported in the ${\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}$ and ${p}{{D}^{+}}{{K}^{-}}$ final
states by the SELEX collaboration [4, 5]. The masses of the ${\mathchar
28932\relax}_{{c}{c}}^{++}$ and ${\mathchar 28932\relax}_{{c}{c}}^{+}$ ground
states are expected to be approximately equal according to isospin symmetry
[6]. Searches in different production environments at the FOCUS, BaBar, Belle
and LHCb experiments have however not shown evidence for a ${\mathchar
28932\relax}_{{c}{c}}^{+}$ state with the properties reported by the SELEX
collaboration [7, 8, 9, 10].

To further understand the dynamics of weakly decaying doubly heavy baryons, it
is of prime importance to pursue searches for additional decay modes of the
${\mathchar 28932\relax}_{{c}{c}}^{++}$ baryon. These decays may differ
significantly from those of singly heavy hadrons due to interference effects
between decay amplitudes of the two heavy quarks. From an experimental
viewpoint, the decay ${{\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}(\rightarrow{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}){p}{{K}^{-}}{{\pi}^{+}}}$
is a suitable search channel, since the
${{{{D}^{+}}\rightarrow{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}}}$ trigger is proven to
be very efficient at LHCb [11].111The inclusion of charge-conjugate processes
is implied throughout this paper. The tree-level amplitudes of the inclusive
decays of ${{{\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}}}$ and
${{{\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}}}$, as shown in Fig. 1,
are comparable, which suggests that the branching fractions of these two modes
could be similar. Theoretical calculations have been performed on pseudo-two-
body decays of doubly-charmed baryons [12]. The ${{\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}}$ decay
could proceed as a pseudo-two-body decay if it decays via an excited
${\mathchar 28934\relax}^{+*}$ state with a mass greater than
1572$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$, which would then decay to a
${p}{{K}^{-}}{{\pi}^{+}}$ final state. However, the properties of such
${\mathchar 28934\relax}^{+*}$ decays are not well known [13]. The ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ decay
also has a energy release of 180 MeV, compared to 560 MeV for the
${{{\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}}}$ decay, which means it
is expected to have a lower branching fraction because of the smaller
available phase space.

The analysis presented in this paper searches for the ${\mathchar
28932\relax}_{{c}{c}}^{++}$ baryon, at its known mass, through ${{{\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}}}$
decays and also explores a larger mass range to identify the hypothetical
isospin partner of the ${\mathchar 28932\relax}_{{c}{c}}^{+}$ state that the
SELEX collaboration reported. The analysis uses ${p}{p}$ collision data
corresponding to an integrated luminosity of $1.7\text{\,fb}^{-1}$ recorded by
the LHCb experiment in 2016 at a centre-of-mass energy of 13 TeV. The
branching fraction of the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ decay
is normalised to ${\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ to reduce systematic
uncertainties.

Figure 1:  The Feynman diagram contributing to the inclusive (left)
${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ decay
with the analogous (right) ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ diagram.

The ratio of branching fractions, $\mathcal{R}$, is determined as

$\displaystyle\mathcal{R}$ $\displaystyle=$
$\displaystyle\frac{\mathcal{B}({\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})}{\mathcal{B}({\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})}$ (1) $\displaystyle=$
$\displaystyle\frac{\mathcal{B}({\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}(\rightarrow{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}){p}{{K}^{-}}{{\pi}^{+}})}{\mathcal{B}({\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}(\rightarrow{p}{{K}^{-}}{{\pi}^{+}}){{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})}\times\frac{\mathcal{B}({\mathchar
28931\relax}_{c}^{+}\rightarrow{p}{{K}^{-}}{{\pi}^{+}})}{\mathcal{B}({{D}^{+}}\rightarrow{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})}$
$\displaystyle=$
$\displaystyle\frac{N({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})}{N({\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})}\times\frac{\varepsilon({\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})}{\varepsilon({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})}\times\frac{\mathcal{B}({\mathchar
28931\relax}_{c}^{+}\rightarrow{p}{{K}^{-}}{{\pi}^{+}})}{\mathcal{B}({{D}^{+}}\rightarrow{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})},$

where $N({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})$ and $N({\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})$ refer to the measured
yields of the signal in the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ and
${\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ channels, respectively,
and $\varepsilon({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})$ and
$\varepsilon({\mathchar 28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})$
are the corresponding selection efficiencies of the decay modes. The values
for $\mathcal{B}({{D}^{+}}\rightarrow{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})$ and
$\mathcal{B}({\mathchar
28931\relax}_{c}^{+}\rightarrow{p}{{K}^{-}}{{\pi}^{+}})$ are known to be
${(8.98\pm 0.28)\%}$ and ${(6.23\pm 0.33)\%}$, respectively [13] and are
uncorrelated.

For convenience, the single-event sensitivity, $\alpha_{s}$, is defined as

$\alpha_{s}\equiv\frac{\varepsilon({\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})}{N({\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})\,\varepsilon({{D}^{+}}p{{K}^{-}}{{\pi}^{+}})}\times\frac{\mathcal{B}({\mathchar
28931\relax}_{c}^{+}\rightarrow{p}{{K}^{-}}{{\pi}^{+}})}{\mathcal{B}({{D}^{+}}\rightarrow{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})}$
(2)

such that Eq. 1 reduces to $\mathcal{R}=\alpha_{s}\times
N({{D}^{+}}p{{K}^{-}}{{\pi}^{+}})$. All aspects of the analysis are fixed
before the data in the $[3300,3800]\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ mass
region are examined.

##  2 Detector and software

The LHCb detector [14, 15] is a single-arm forward spectrometer covering the
pseudorapidity range $2<\eta<5$, designed for the study of particles
containing $b$ or $c$ quarks. The detector includes a high-precision tracking
system consisting of a silicon-strip vertex detector surrounding the $pp$
interaction region [16], a large-area silicon-strip detector located upstream
of a dipole magnet with a bending power of about $4{\mathrm{\,Tm}}$, and three
stations of silicon-strip detectors and straw drift tubes [17] placed
downstream of the magnet. The tracking system provides a measurement of the
momentum, $p$, of charged particles with a relative uncertainty that varies
from 0.5% at low momentum to 1.0% at 200$\text{\,Ge\kern-1.00006ptV\\!/}c$.
The minimum distance of a track to a primary vertex (PV), the impact parameter
(IP), is measured with a resolution of
$(15+29/p_{\mathrm{T}})\,\upmu\text{m}$, where $p_{\mathrm{T}}$ is the
component of the momentum transverse to the beam, in
$\text{\,Ge\kern-1.00006ptV\\!/}c$. Charged hadrons are identified using two
ring-imaging Cherenkov detectors [18]. Photon, electron and hadron candidates
are identified by a calorimeter system consisting of scintillating-pad, pre-
shower detectors, an electromagnetic calorimeter and a hadronic calorimeter.
Muons are identified by a system composed of alternating layers of iron and
multiwire proportional chambers [19]. The trigger consists of a hardware
stage, based on information from the calorimeter and muon systems, followed by
a software stage, which applies a full event reconstruction. The online
reconstruction incorporates near-real-time alignment and calibration of the
detector [11]. The same alignment and calibration information is propagated to
the offline reconstruction, ensuring consistent and high-quality information
between the trigger and offline software. The identical performance of the
online and offline reconstruction offers the opportunity to perform physics
analyses directly using candidates reconstructed in the trigger [20]. The
analysis described in this paper makes use of these features.

Simulated ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ decays
are used to design the candidate selection and to calculate the efficiency of
such a selection. The proton-proton interactions are generated using Pythia
[21, *Sjostrand:2006za] with a specific LHCb configuration [23]. Genxicc v2.0
[24], the dedicated generator for doubly-heavy-baryon production at LHCb, is
used to produce the signal. Decays of hadronic particles are described by
EvtGen [25], in which final-state radiation is generated using Photos [26].
The interaction of the generated particles with the detector and their
response are implemented using the Geant4 toolkit [27, *Agostinelli:2002hh] as
described in Ref. [29]. The ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ decays
are generated with a ${\mathchar 28932\relax}_{{c}{c}}^{++}$ mass of
3621.40$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ and the decay products of
${\mathchar 28932\relax}_{{c}{c}}^{++}$ and ${D}^{+}$ hadrons are distributed
uniformly in phase space.

##  3 Triggering, reconstruction and selection

The procedure to trigger, reconstruct and select candidates is designed to
retain ${\mathchar 28932\relax}_{{c}{c}}^{++}$ signal and to suppress three
primary sources of background: combinatorial background, which arises from
random combination of tracks; misreconstructed charm or beauty hadron decays,
which typically have displaced decay vertices; and combinations of a real
${D}^{+}$ meson with other tracks to form a fake ${\mathchar
28932\relax}_{{c}{c}}^{++}$ candidate. To better control systematic
uncertainties, the selection of ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ decays
is also designed to be as similar as possible to that of the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ normalisation channel,
described in Ref. [1].

The ${D}^{+}$ candidates are reconstructed in the final state
${{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$. At least one of the three tracks used to
reconstruct the ${D}^{+}$ candidate must be selected by the inclusive software
trigger, which requires that the track has $p_{\mathrm{T}}$
$>250\text{\,Me\kern-1.00006ptV\\!/}c$ and $\chi^{2}_{\text{IP}}>4$ with
respect to any PV, where $\chi^{2}_{\text{IP}}$ is defined as the difference
in $\chi^{2}$ of a given PV reconstructed with and without the considered
track. The ${D}^{+}$ candidate then must be reconstructed and accepted by a
dedicated ${{D}^{+}}\rightarrow{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ selection
algorithm in the software trigger. This algorithm applies several geometric
and kinematic requirements; at least one of the three tracks must have
${p_{\mathrm{T}}>1\text{\,Ge\kern-1.00006ptV\\!/}c}$ and
${\chi^{2}_{\text{IP}}>50}$, at least two of the tracks must have
${p_{\mathrm{T}}>0.4\text{\,Ge\kern-1.00006ptV\\!/}c}$ and
${\chi^{2}_{\text{IP}}>10}$ and the scalar sum of the $p_{\mathrm{T}}$ of the
three tracks must be larger than 3$\text{\,Ge\kern-1.00006ptV\\!/}c$.
Furthermore, the ${{D}^{+}}$ candidate must have a good vertex-fit quality
with $\chi^{2}/\rm{ndf}<6$. The candidate must also point back to its
associated PV, where the angle between its flight path and momentum vector
should be less than 0.01 radians. The associated PV is that which best fits
the flight direction of the reconstructed candidate. The ${D}^{+}$ vertex must
also be displaced from this PV such that the estimated ${D}^{+}$ decay time is
longer than $0.4\text{\,ps}$. Only candidates whose invariant mass is within
$\pm 80\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ of the known mass of the
${D}^{+}$ meson (1869.65$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ [13]) are
retained. Finally, candidates are required to pass a MatrixNet classifier [11]
within the software trigger, which has been trained on $p_{\mathrm{T}}$ and
vertex $\chi^{2}$ information prior to data taking. For events that pass the
online trigger, the offline selection of ${D}^{+}$ candidates proceeds in a
similar fashion to that used in the software trigger: three tracks are
required to form a common vertex that is significantly displaced from the
associated PV of the candidate and its combined invariant mass must be in the
range $[1847,1891]\text{\,Me\kern-1.00006ptV\\!/}c^{2}$. Particle
identification (PID) requirements are imposed on all three tracks to suppress
combinatorial background and misidentified charm decays. The ${\mathchar
28932\relax}_{{c}{c}}^{++}$ candidates are formed by combining a ${D}^{+}$
candidate with three more charged tracks, each with
${p_{\mathrm{T}}>500\text{\,Me\kern-1.00006ptV\\!/}c}$ and separately
identified as a proton, kaon and pion with good track quality. The three
tracks and the ${D}^{+}$ candidate are required to form a vertex in which each
pairwise combination of the four particles is required to have a distance of
closest approach of less than 10 mm and the fitted ${\mathchar
28932\relax}_{{c}{c}}^{++}$ vertex must have $\chi^{2}/\rm{ndf}<10$. The
${\mathchar 28932\relax}_{{c}{c}}^{++}$ candidate is also required to point
back to the PV, and to have
$p_{\mathrm{T}}>4.5$$\text{\,Ge\kern-1.00006ptV\\!/}c$. Only events that
passed the hardware trigger based on information from the muon and calorimeter
systems that are not part of the reconstructed ${\mathchar
28932\relax}_{{c}{c}}^{++}$ event are used in the analysis [11]. Hence, the
event is triggered independently of the reconstructed ${\mathchar
28932\relax}_{{c}{c}}^{++}$ candidate, which reduces the systematic
uncertainty on the efficiency ratios between the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ and
${\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ decay modes.

To improve the mass resolution, the following mass estimator is used in the
analysis

$m({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})\equiv
M({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})-M([{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}]_{{{D}^{+}}})+M_{\rm{PDG}}({{D}^{+}}),$
(3)

where $M({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})$ is the measured invariant mass of
the ${\mathchar 28932\relax}_{{c}{c}}^{++}$ candidate,
$M([{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}]_{{{D}^{+}}})$ is the measured invariant
mass of the ${{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ combination corresponding to the
intermediate ${D}^{+}$ candidate and $M_{\rm{PDG}}({{D}^{+}})$ is the known
mass of the ${D}^{+}$ meson. By using the mass definition in Eq. 3, a mild
correlation between decay time and mass is reduced and the mass resolution is
improved by 0.15$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$. The ${\mathchar
28932\relax}_{{c}{c}}^{++}$ candidates are accepted if they have a
reconstructed mass in the range ${3300\leq
m({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})\leq
3800}$$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$.

Following a comparison study of different multivariate methods, a classifier
based on the multilayer perceptron (MLP) algorithm [30] is used to further
suppress combinatorial background. Simulated ${\mathchar
28932\relax}_{{c}{c}}^{++}$ decays are used to train the MLP classifier to
recognise signal. Dedicated software triggers reconstruct an unphysical
combination of ${{D}^{+}}{p}{{K}^{+}}{{\pi}^{+}}$ (wrong-sign-plus, WSP) and
${{D}^{+}}{p}{{K}^{-}}{{\pi}^{-}}$ (wrong-sign-minus, WSM) data. The WSP and
WSM samples are expected to be good proxies for combinatorial background in
the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ (right-
sign, RS) channel. For this analysis, WSP data in the ${3550\leq
m({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})\leq
3700\text{\,Me\kern-1.00006ptV\\!/}c^{2}}$ mass region is used to train the
MLP classifier to identify background, while the WSM data is used to cross-
check the results. Fifteen input variables are used in the MLP training. The
variables with the best discriminating power between signal and background
are: the ${\mathchar 28932\relax}_{{c}{c}}^{++}$ vertex fit with a kinematic
refit [31] of the ${\mathchar 28932\relax}_{{c}{c}}^{++}$ decay chain
requiring it to originate from its PV; the smallest $p_{\mathrm{T}}$ of the
four decay products of the ${\mathchar 28932\relax}_{{c}{c}}^{++}$ candidate;
the angle between the ${\mathchar 28932\relax}_{{c}{c}}^{++}$ momentum vector
and the direction from the PV to the ${\mathchar 28932\relax}_{{c}{c}}^{++}$
decay vertex; the $\chi^{2}_{\text{IP}}$ of the ${\mathchar
28932\relax}_{{c}{c}}^{++}$ candidate with respect to its PV; the maximum
distance of the closest approach between all pairs of ${\mathchar
28932\relax}_{{c}{c}}^{++}$ tracks forming the ${\mathchar
28932\relax}_{{c}{c}}^{++}$ candidate; and the maximum distance of the closest
approach between all pairs of tracks from the decay of the ${D}^{+}$
candidate. To maintain a sizeable number of signal events, the hardware-
trigger requirements are not applied to the signal and background samples. In
addition to the training samples, disjoint testing samples are acquired from
the same source. After training, the response of the MLP is compared between
the training and testing samples. No signs of the MLP classifier being
overtrained are found based on the Kolmogorov–Smirnov test statistic.
Candidates are retained only if the MLP response output exceeds a certain
threshold. The threshold is chosen by maximising the Punzi figure of merit
[32], with a target significance of five sigma. To test for potential
misreconstruction effects, the same selection criteria are applied to the WSP
and WSM data; no peaking structures are visible in either control sample, as
expected.

After the multivariate selection, events may contain multiple ${\mathchar
28932\relax}_{{c}{c}}^{++}$ candidates. This can arise from mistakes in the
reconstruction of ${{\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}(\rightarrow{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}){p}{{K}^{-}}{{\pi}^{+}}}$
decays. For instance, there can be cases when ${\mathchar
28932\relax}_{{c}{c}}^{++}$ candidates in the same event have used the same
track more than once. To deal with this, the angle between any two tracks of
the same charge is required to be greater than 0.5 mrad. If a ${\mathchar
28932\relax}_{{c}{c}}^{++}$ candidate has been formed from at least one pair
of these cloned tracks, then the candidate is removed. This requirement
removes around 6% of ${\mathchar 28932\relax}_{{c}{c}}^{++}$ candidates in RS
data following the multivariate selection. In a separate scenario, the same
six final-state tracks may be used to reconstruct more than one ${\mathchar
28932\relax}_{{c}{c}}^{++}$ candidate in the same event but with the tracks
wrongly interchanged (e.g., the ${K}^{-}$ track originating from the
${\mathchar 28932\relax}_{{c}{c}}^{++}$ decay vertex and the ${K}^{-}$ track
coming from the ${D}^{+}$ decay vertex). In this situation, only one of the
${\mathchar 28932\relax}_{{c}{c}}^{++}$ candidate from such an event, chosen
at random, is retained. This requirement discards less than 1% of candidates
at this stage of the selection.

##  4 Mass distributions

To determine the yield of ${\mathchar 28932\relax}_{{c}{c}}^{++}$ and
${D}^{+}$ particles following the selection of ${{{\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}}}$
candidates, the $m({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})$ and
$M([{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}]_{{{D}^{+}}})$ mass distributions are
fitted using models that are developed using simulation.

The invariant-mass distribution
$M([{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}]_{{{D}^{+}}})$ of the ${D}^{+}$ candidates
after the candidate selection is shown in Fig. 2 (left). A Crystal Ball
function with exponential tails on both sides [33] is used to model the signal
component and a linear function is used to fit the background contribution.
The parameters of the signal model are fixed to values obtained from
simulation, while all parameters in the background model are free. The
selection retains 2697 ${D}^{+}$ candidates with a purity of 80% according to
the results of the fit to the mass spectrum.

The invariant-mass distributions in the RS, WSP and WSM data samples after the
candidate selection are shown in Fig. 2 (right). All the samples have similar
smoothly shaped distributions across the entire mass range studied.

Figure 2:  (left) Invariant-mass distribution of the ${D}^{+}$ candidates
after the full selection. The black points represent data and the fit is
indicated by the continuous (blue) line with the individual signal and
background components represented by the dotted (red) line and dashed (green)
line, respectively. (right) Invariant-mass distributions of right-sign (black)
${{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$, wrong-sign-plus (red)
${{D}^{+}}{p}{{K}^{+}}{{\pi}^{+}}$ and wrong-sign-minus (blue)
${{D}^{+}}{p}{{K}^{-}}{{\pi}^{-}}$ data combinations are shown. The control
samples have been normalised to the right-sign sample.

The invariant-mass distribution of the ${\mathchar 28932\relax}_{{c}{c}}^{++}$
candidates, $m({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})$, for the signal decay mode
after applying all requirements of the analysis, is shown in Fig. 3 (left).
The mass distribution is fitted with an unbinned extended maximum-likelihood
method, assuming only a background contribution, described by a second-order
Chebyshev polynomial. No signal peak is visible in the spectrum and the local
_p_ -value is calculated as a function of mass and shown in Fig. 3 (right).
The local _p_ -value is defined as the probability of observing data that is
less compatible with the background-only hypothesis than the data set. The
test statistic used is based on $q_{0}$ in Ref. [34], but instead of assigning
it the value zero when observing fewer than expected candidates, it is
assigned the value $-q_{0}$ to achieve a more intuitive behaviour of the _p_
-value for downward fluctuations. The likelihoods are evaluated with Poisson
statistics using the predicted number of background candidates and observed
number of signal candidates in regions of $\pm 3\sigma_{m}$ around each
hypothetical mass, where $\sigma_{m}=2.8\text{\,Me\kern-1.00006ptV\\!/}c^{2}$
is the ${\mathchar 28932\relax}_{{c}{c}}^{++}$ mass resolution determined from
simulated ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ decays.

There is no visible signal near the mass of
3620$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ where a ${\mathchar
28932\relax}_{{c}{c}}^{++}$ signal would be expected, nor is there any excess
of candidates near the mass of 3520$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$
where the hypothetical isospin partner was observed by the SELEX collaboration
[4, 5]. The global _p_ -value, including the look-elsewhere effect in the mass
range $3500-3800\text{\,Me\kern-1.00006ptV\\!/}c^{2}$, is 26% and only one
signal candidate is observed in the mass range from the kinematic threshold of
3441$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ to
3500$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$. Hence, no significant signal is
observed in the mass range from the kinematic threshold to
3800$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ and we proceed to set a limit on
the relative branching fraction $\mathcal{R}$.

The invariant-mass distribution of the ${\mathchar 28932\relax}_{{c}{c}}^{++}$
candidates, $m({\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})$, for the normalization
decay mode, ${\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$, is shown in Fig. 4. In
this case a signal peak is clearly visible. Both the candidate selection and
the modelling of the mass spectrum are identical to that in Ref.[1], except
for the additional requirements on the hardware trigger. An extended unbinned
maximum-likelihood fit to this invariant-mass distribution returns a signal
yield of $184\pm 29$.

Figure 3:  (left) Invariant-mass distribution of the ${{{\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}}}$
candidates with the fit overlaid. The black points represent data, the
continuous (green) line represents the combinatorial background and the two
vertical parallel dashed (blue) lines define the region where the signal is
expected. (right) The local _p_ -value expressing the compatibility of the
data with the background-only hypothesis. The horizontal dashed (red) lines
indicate _p_ -values of 1, 2 and 3$\sigma$ local significance.  Figure 4:
Invariant-mass distribution of the ${{{\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}}}$ candidates with the fit
overlaid. The black points represent data, the dashed (green) line represents
combinatorial background, the dotted (red) line represents the signal
contribution and the continuous (blue) line is the total fit.

##  5 Efficiency determination

To set an upper limit on the ratio $\mathcal{R}$, it is necessary to evaluate
the ratio of efficiencies between the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ and
${\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ decay modes.

The efficiency ratio may be factorised as

$\frac{\varepsilon({\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})}{\varepsilon({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})}=\frac{\varepsilon_{{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}}^{\text{acc}}}{\varepsilon_{{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}}^{\text{acc}}}\,\frac{\varepsilon_{{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}}^{\text{sel}|\text{acc}}}{\varepsilon_{{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}}^{\text{sel}|\text{acc}}}\,\frac{\varepsilon_{{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}}^{\text{PID}|\text{sel}}}{\varepsilon_{{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}}^{\text{PID}|\text{sel}}}\,\frac{\varepsilon_{{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}}^{\text{trig}|\text{PID}}}{\varepsilon_{{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}}^{\text{trig}|\text{PID}}},$
(4)

where efficiencies are evaluated for the geometric acceptance (acc), the
reconstruction and selection excluding particle identification requirements
(sel), the particle identification requirements (PID) and the trigger (trig).
Each factor is the efficiency relative to all previous steps in the order
given above. The individual ratios are evaluated with simulated ${\mathchar
28932\relax}_{{c}{c}}^{++}$ decays, assuming a uniform phase space model,
except for PID which is derived from data [35, 18]. The efficiencies are
corrected for known differences between simulation and data, apart from the
geometric acceptance.

The individual efficiency components, shown in Eq. 4, are found to be similar
between the two ${\mathchar 28932\relax}_{{c}{c}}^{++}$ decay modes, except
for the reconstruction and selection efficiency,
$\varepsilon^{\text{sel}|\text{acc}}$, where in the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ channel
it is found to be approximately twice as large as that of the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ decay. This leads to a
total efficiency ratio of $\varepsilon({\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})/\varepsilon({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})=0.46\pm
0.01$, where the uncertainty is statistical only. Combining this total
relative efficiency with the value for $N({\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})$ obtained in Sect. 4 and
the known values for the branching fractions
${\mathcal{B}({{D}^{+}}\rightarrow{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})}$ and
${\mathcal{B}({\mathchar
28931\relax}_{c}^{+}\rightarrow{p}{{K}^{-}}{{\pi}^{+}})}$, then according to
Eq. 2, the single-event sensitivity is ${\alpha_{s}=(1.74\pm 0.29)\times
10^{-3}}$. The uncertainty on ${\alpha_{s}}$ includes the total uncertainty on
the ${\mathcal{B}({{D}^{+}}\rightarrow{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})}$ and
${\mathcal{B}({\mathchar
28931\relax}_{c}^{+}\rightarrow{p}{{K}^{-}}{{\pi}^{+}})}$ branching fractions
and the statistical uncertainty on the $N({\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})$ and
$\varepsilon({\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})/\varepsilon({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})$
measured values.

##  6 Systematic uncertainties

The statistical uncertainty on the measured signal yield in the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ channel is the dominant
uncertainty on $\alpha_{s}$ and the systematic uncertainties on $\alpha_{s}$
have small effect on the upper limits on the ratio $\mathcal{R}$.

The largest systematic uncertainty arises from the evaluation of the
efficiency of the hardware-trigger requirement. Only candidates that are
triggered independently of the ${\mathchar 28932\relax}_{{c}{c}}^{++}$
candidate’s final-state tracks are used in the branching fraction ratio limit
to minimise this systematic uncertainty. The ratio of these efficiencies is
equal to one if the kinematic distributions of the ${\mathchar
28932\relax}_{{c}{c}}^{++}$ candidate in the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ and
${\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ decay modes are
identical. However, the efficiencies can be different if the respective
selection requirements of the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ and
${\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ analyses select different
kinematic regions of the ${\mathchar 28932\relax}_{{c}{c}}^{++}$ candidate.
This effect is studied by weighting the $p_{\mathrm{T}}$ distributions in
simulated samples. The change in efficiency of the hardware trigger after the
weighting is evaluated and results in a systematic uncertainty of 3.5%. The
impact of the model used to fit the $m({\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})$ invariant-mass
distribution on the yield of ${\mathchar 28932\relax}_{{c}{c}}^{++}$
candidates, $N({\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})$, is investigated by
using alternative signal and background models and performing the fit over
different mass ranges. The largest variation in the yield of ${\mathchar
28932\relax}_{{c}{c}}^{++}$ candidates is 3.1% and this is taken as a
systematic uncertainty on $\alpha_{s}$. The effect of the uncertainty
associated with the ${\mathchar 28932\relax}_{{c}{c}}^{++}$ baryon’s lifetime
on the relative reconstruction and selection efficiency between the
${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ and
${\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ channels is investigated
by varying the lifetime within its uncertainty and a systematic uncertainty of
2.9% is assigned to the $\alpha_{s}$ parameter. The PID efficiency is
determined in bins of particle momentum and pseudorapidity using calibration
samples taken from data [35]. The size of the bins is increased or decreased
by a factor of two and the largest deviation on $\alpha_{s}$ of 1.5% is
assigned as systematic uncertainty. Finally, since the simulation may not
describe the signal perfectly, simulated ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ decays
are weighted to make their $p_{\mathrm{T}}$ distribution match that observed
in the ${\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ data. The selection and
software-trigger efficiencies are similarly calculated using
$p_{\mathrm{T}}$-corrected simulated ${\mathchar 28932\relax}_{{c}{c}}^{++}$
decays. The number of $p_{\mathrm{T}}$ bins used is increased or decreased by
a factor of two and the efficiencies are recalculated for both decay channels.
This results in a change in $\alpha_{s}$ of 1.2%. All efficiencies calculated
from simulation are averaged over the entire phase space assuming a uniform
distribution for both the ${{{\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}}}$ and
${{{\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}}}$ decays. The phase-space
distributions of the selected candidates are uniform and show agreement in
data and simulation. Therefore, no systematic uncertainty is assigned to the
relative selection and reconstruction efficiencies for the effect of
intermediate resonances in their decay.

Table 1 summarises the systematic and statistical uncertainties on
$\alpha_{s}$. The statistical uncertainty is dominated by the uncertainty of
the yield of the normalisation mode but includes a small contribution from the
finite size of the simulated samples. The ratio of the branching fractions
${\mathcal{B}({{D}^{+}}\rightarrow{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}})}$ and
${\mathcal{B}({\mathchar
28931\relax}_{c}^{+}\rightarrow{p}{{K}^{-}}{{\pi}^{+}})}$ have a combined
uncertainty of 5.7%. The systematic uncertainties from the different sources
discussed above are considered uncorrelated and are added in quadrature to
give a total systematic uncertainty of 5.8%. Adding all sources of uncertainty
in quadrature gives a total uncertainty of 17.7% on the $\alpha_{s}$
parameter.

Table 1:  Systematic and statistical uncertainties on the single-event sensitivity $\alpha_{s}$.  Source | $\alpha_{s}\ (\%)$
---|---
Statistical | $15.7$
Branching fractions | $\phantom{0}5.7$
Trigger efficiency | $\phantom{0}3.5$
Mass fit model | $\phantom{0}3.1$
${\mathchar 28932\relax}_{{c}{c}}^{++}$ lifetime | $\phantom{0}2.9$
PID calibration | $\phantom{0}1.5$
Simulation modelling | $\phantom{0}1.2$
Total uncertainty | $17.7$

##  7 Results

In this analysis no significant ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ signal
is observed so an upper limit is set on the ratio of branching fractions,
$\mathcal{R}$. The CLs method [36] is used to determine the ratio of
confidence levels (CL) between the signal-plus-background and background-only
hypotheses. The upper limit is obtained from the total number of candidates,
$N_{\rm{obs}}$, observed in the expected signal mass region. This value is
calculated by counting the number of candidates within the mass region,
${3612<m({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})<3630\text{\,Me\kern-1.00006ptV\\!/}c^{2}}$
(indicated by two dashed blue lines in the left-hand plot of Fig. 3). This
mass region corresponds to approximately $\pm 3\sigma_{m}$ around the average
mass of the ${\mathchar 28932\relax}_{{c}{c}}^{++}$ state.

The CLs score for a possible value of ratio $\mathcal{R}$ is calculated as

$\texttt{CLs}=\frac{P(N_{\rm{b}}+N_{\rm{s}}\leq
N_{\rm{obs}})}{P(N_{\rm{b}}\leq N_{\rm{obs}})},$ (5)

where $N_{\rm{s}}$ is sampled from the distribution of the expected number of
signal candidates for a given ratio $\mathcal{R}$, $N_{\rm{b}}$ is sampled
from the distribution of the expected number of background candidates
predicted by the background-only fit (Fig. 3, left) and $P$ indicates the
probability that these statistical quantities are smaller than $N_{\rm{obs}}$.
The data points in the mass region
${3612<m({{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}})<3630\text{\,Me\kern-1.00006ptV\\!/}c^{2}}$
are removed for the fit and $N_{\rm{b}}$ is determined by performing an
integral extrapolation. The probability requirements in the numerator and
denominator of Eq. 5 are tested by running a large number of pseudoexperiments
sampling from a Poisson distribution with statistical means of
$N_{\rm{b}}+N_{\rm{s}}$ and $N_{\rm{b}}$, respectively. The 17.7% uncertainty
on $\alpha_{s}$ is fully accounted for by sampling from a Gaussian
distribution in each pseudoexperiment.

The derived CLs curve as a function of the possible values of the ratio
$\mathcal{R}$ is shown as the black line in Fig. 5. This curve is obtained
using values of $N_{\rm obs}=66$ and $N_{\rm b}=79.8$ as observables and
running $1\times 10^{6}$ pseudoexperiments for each hypothetical value of
ratio $\mathcal{R}$. The upper limit measured is

$\mathcal{R}<1.7\hskip 3.0pt(2.1)\times 10^{-2}\hskip 5.0pt\rm{at}\hskip
5.0pt90\%\hskip 3.0pt(95\%)\hskip 5.0pt\text{CL}$

as shown by the blue dotted line (red dashed line) in Fig. 5.

Figure 5:  The scores from the CLs method for each value of the assumed ratio
of branching fractions $\mathcal{R}$. Observed values are shown by the solid
black line. The set upper limits at 90% and 95% CL are indicated by the dotted
(blue) line and the dashed (red) line, respectively.

##  8 Conclusions

Following observations of the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ and ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28932\relax}_{{c}}^{+}{{\pi}^{+}}$ decay modes, a search for the decay
${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ is
performed using ${p}{p}$ collision data recorded by the LHCb experiment in
2016 at a centre-of-mass energy of 13 TeV, corresponding to an integrated
luminosity of $1.7\text{\,fb}^{-1}$. No significant signal is found in the
mass range from the kinematic threshold of the decay of
3441$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ to
3800$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$. Considering the statistical and
systematic uncertainties, an upper limit on the ratio of branching fractions
between the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ and
${\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ decay is set to be
$\mathcal{R}<1.7\hskip 1.0pt(2.1)\times 10^{-2}$ at the 90% (95%) confidence
level at the known mass of the ${\mathchar 28932\relax}_{{c}{c}}^{++}$ baryon.

The upper limit on the ratio of branching fractions between the two
${\mathchar 28932\relax}_{{c}{c}}^{++}$ decay modes is derived assuming a
uniform phase space model in the efficiency determinations. A better
theoretical understanding of the resonant and nonresonant contributions
underpinning the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ and
${\mathchar 28932\relax}_{{c}{c}}^{++}\rightarrow{\mathchar
28931\relax}_{c}^{+}{{K}^{-}}{{\pi}^{+}}{{\pi}^{+}}$ decay processes is
required to understand the at least two orders of magnitude difference between
the branching fractions of the two ${\mathchar 28932\relax}_{{c}{c}}^{++}$
decay modes. Dynamical effects or spin constraints in the resonance structures
could be suppressing the ${\mathchar
28932\relax}_{{c}{c}}^{++}\rightarrow{{D}^{+}}{p}{{K}^{-}}{{\pi}^{+}}$ decay.
The full dataset from LHCb, or future data taking with the upgraded detector,
may reveal evidence of this decay and then shed more light on the production
and decay dynamics of the ${\mathchar 28932\relax}_{{c}{c}}^{++}$ baryon.

## Acknowledgements

We express our gratitude to our colleagues in the CERN accelerator departments
for the excellent performance of the LHC. We thank the technical and
administrative staff at the LHCb institutes. We acknowledge support from CERN
and from the national agencies: CAPES, CNPq, FAPERJ and FINEP (Brazil); MOST
and NSFC (China); CNRS/IN2P3 (France); BMBF, DFG and MPG (Germany); INFN
(Italy); NWO (Netherlands); MNiSW and NCN (Poland); MEN/IFA (Romania); MSHE
(Russia); MinECo (Spain); SNSF and SER (Switzerland); NASU (Ukraine); STFC
(United Kingdom); DOE NP and NSF (USA). We acknowledge the computing resources
that are provided by CERN, IN2P3 (France), KIT and DESY (Germany), INFN
(Italy), SURF (Netherlands), PIC (Spain), GridPP (United Kingdom), RRCKI and
Yandex LLC (Russia), CSCS (Switzerland), IFIN-HH (Romania), CBPF (Brazil), PL-
GRID (Poland) and OSC (USA). We are indebted to the communities behind the
multiple open-source software packages on which we depend. Individual groups
or members have received support from AvH Foundation (Germany); EPLANET, Marie
Skłodowska-Curie Actions and ERC (European Union); ANR, Labex P2IO and OCEVU,
and Région Auvergne-Rhône-Alpes (France); Key Research Program of Frontier
Sciences of CAS, CAS PIFI, and the Thousand Talents Program (China); RFBR, RSF
and Yandex LLC (Russia); GVA, XuntaGal and GENCAT (Spain); the Royal Society
and the Leverhulme Trust (United Kingdom).

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LHCb Collaboration

R. Aaij29, C. Abellán Beteta46, B. Adeva43, M. Adinolfi50, C.A. Aidala77, Z.
Ajaltouni7, S. Akar61, P. Albicocco20, J. Albrecht12, F. Alessio44, M.
Alexander55, A. Alfonso Albero42, G. Alkhazov35, P. Alvarez Cartelle57, A.A.
Alves Jr43, S. Amato2, Y. Amhis9, L. An19, L. Anderlini19, G. Andreassi45, M.
Andreotti18, J.E. Andrews62, F. Archilli29, J. Arnau Romeu8, A. Artamonov41,
M. Artuso63, K. Arzymatov39, E. Aslanides8, M. Atzeni46, B. Audurier24, S.
Bachmann14, J.J. Back52, S. Baker57, V. Balagura9,b, W. Baldini18,44, A.
Baranov39, R.J. Barlow58, G.C. Barrand9, S. Barsuk9, W. Barter57, M.
Bartolini21, F. Baryshnikov73, V. Batozskaya33, B. Batsukh63, A. Battig12, V.
Battista45, A. Bay45, F. Bedeschi26, I. Bediaga1, A. Beiter63, L.J. Bel29, S.
Belin24, N. Beliy4, V. Bellee45, N. Belloli22,i, K. Belous41, I. Belyaev36, G.
Bencivenni20, E. Ben-Haim10, S. Benson29, S. Beranek11, A. Berezhnoy37, R.
Bernet46, D. Berninghoff14, E. Bertholet10, A. Bertolin25, C. Betancourt46, F.
Betti17,e, M.O. Bettler51, Ia. Bezshyiko46, S. Bhasin50, J. Bhom31, M.S.
Bieker12, S. Bifani49, P. Billoir10, A. Birnkraut12, A. Bizzeti19,u, M.
Bjørn59, M.P. Blago44, T. Blake52, F. Blanc45, S. Blusk63, D. Bobulska55, V.
Bocci28, O. Boente Garcia43, T. Boettcher60, A. Bondar40,x, N. Bondar35, S.
Borghi58,44, M. Borisyak39, M. Borsato14, M. Boubdir11, T.J.V. Bowcock56, C.
Bozzi18,44, S. Braun14, M. Brodski44, J. Brodzicka31, A. Brossa Gonzalo52, D.
Brundu24,44, E. Buchanan50, A. Buonaura46, C. Burr58, A. Bursche24, J.
Butter29, J. Buytaert44, W. Byczynski44, S. Cadeddu24, H. Cai67, R.
Calabrese18,g, S. Cali18, R. Calladine49, M. Calvi22,i, M. Calvo Gomez42,m, A.
Camboni42,m, P. Campana20, D.H. Campora Perez44, L. Capriotti17,e, A.
Carbone17,e, G. Carboni27, R. Cardinale21, A. Cardini24, P. Carniti22,i, K.
Carvalho Akiba2, G. Casse56, M. Cattaneo44, G. Cavallero21, R. Cenci26,p, D.
Chamont9, M.G. Chapman50, M. Charles10,44, Ph. Charpentier44, G.
Chatzikonstantinidis49, M. Chefdeville6, V. Chekalina39, C. Chen3, S. Chen24,
S.-G. Chitic44, V. Chobanova43, M. Chrzaszcz44, A. Chubykin35, P. Ciambrone20,
X. Cid Vidal43, G. Ciezarek44, F. Cindolo17, P.E.L. Clarke54, M. Clemencic44,
H.V. Cliff51, J. Closier44, V. Coco44, J.A.B. Coelho9, J. Cogan8, E.
Cogneras7, L. Cojocariu34, P. Collins44, T. Colombo44, A. Comerma-Montells14,
A. Contu24, G. Coombs44, S. Coquereau42, G. Corti44, C.M. Costa Sobral52, B.
Couturier44, G.A. Cowan54, D.C. Craik60, A. Crocombe52, M. Cruz Torres1, R.
Currie54, C.L. Da Silva78, E. Dall’Occo29, J. Dalseno43,v, C. D’Ambrosio44, A.
Danilina36, P. d’Argent14, A. Davis58, O. De Aguiar Francisco44, K. De
Bruyn44, S. De Capua58, M. De Cian45, J.M. De Miranda1, L. De Paula2, M. De
Serio16,d, P. De Simone20, J.A. de Vries29, C.T. Dean55, W. Dean77, D.
Decamp6, L. Del Buono10, B. Delaney51, H.-P. Dembinski13, M. Demmer12, A.
Dendek32, D. Derkach74, O. Deschamps7, F. Desse9, F. Dettori24, B. Dey68, A.
Di Canto44, P. Di Nezza20, S. Didenko73, H. Dijkstra44, F. Dordei24, M.
Dorigo26,y, A.C. dos Reis1, A. Dosil Suárez43, L. Douglas55, A. Dovbnya47, K.
Dreimanis56, L. Dufour44, G. Dujany10, P. Durante44, J.M. Durham78, D.
Dutta58, R. Dzhelyadin41,†, M. Dziewiecki14, A. Dziurda31, A. Dzyuba35, S.
Easo53, U. Egede57, V. Egorychev36, S. Eidelman40,x, S. Eisenhardt54, U.
Eitschberger12, R. Ekelhof12, L. Eklund55, S. Ely63, A. Ene34, S. Escher11, S.
Esen29, T. Evans61, A. Falabella17, C. Färber44, N. Farley49, S. Farry56, D.
Fazzini22,i, M. Féo44, P. Fernandez Declara44, A. Fernandez Prieto43, F.
Ferrari17,e, L. Ferreira Lopes45, F. Ferreira Rodrigues2, S. Ferreres Sole29,
M. Ferro-Luzzi44, S. Filippov38, R.A. Fini16, M. Fiorini18,g, M. Firlej32, C.
Fitzpatrick44, T. Fiutowski32, F. Fleuret9,b, M. Fontana44, F. Fontanelli21,h,
R. Forty44, V. Franco Lima56, M. Frank44, C. Frei44, J. Fu23,q, W. Funk44, E.
Gabriel54, A. Gallas Torreira43, D. Galli17,e, S. Gallorini25, S. Gambetta54,
Y. Gan3, M. Gandelman2, P. Gandini23, Y. Gao3, L.M. Garcia Martin76, J. García
Pardiñas46, B. Garcia Plana43, J. Garra Tico51, L. Garrido42, D. Gascon42, C.
Gaspar44, G. Gazzoni7, D. Gerick14, E. Gersabeck58, M. Gersabeck58, T.
Gershon52, D. Gerstel8, Ph. Ghez6, V. Gibson51, O.G. Girard45, P. Gironella
Gironell42, L. Giubega34, K. Gizdov54, V.V. Gligorov10, C. Göbel65, D.
Golubkov36, A. Golutvin57,73, A. Gomes1,a, I.V. Gorelov37, C. Gotti22,i, E.
Govorkova29, J.P. Grabowski14, R. Graciani Diaz42, L.A. Granado Cardoso44, E.
Graugés42, E. Graverini46, G. Graziani19, A. Grecu34, R. Greim29, P.
Griffith24, L. Grillo58, L. Gruber44, B.R. Gruberg Cazon59, C. Gu3, E.
Gushchin38, A. Guth11, Yu. Guz41,44, T. Gys44, T. Hadavizadeh59, C.
Hadjivasiliou7, G. Haefeli45, C. Haen44, S.C. Haines51, B. Hamilton62, Q.
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Harrison56, C. Hasse44, M. Hatch44, J. He4, M. Hecker57, K. Heinicke12, A.
Heister12, K. Hennessy56, L. Henry76, M. Heß70, J. Heuel11, A. Hicheur64, R.
Hidalgo Charman58, D. Hill59, M. Hilton58, P.H. Hopchev45, J. Hu14, W. Hu68,
W. Huang4, Z.C. Huard61, W. Hulsbergen29, T. Humair57, M. Hushchyn74, D.
Hutchcroft56, D. Hynds29, P. Ibis12, M. Idzik32, P. Ilten49, A. Inglessi35, A.
Inyakin41, K. Ivshin35, R. Jacobsson44, S. Jakobsen44, J. Jalocha59, E.
Jans29, B.K. Jashal76, A. Jawahery62, F. Jiang3, M. John59, D. Johnson44, C.R.
Jones51, C. Joram44, B. Jost44, N. Jurik59, S. Kandybei47, M. Karacson44, J.M.
Kariuki50, S. Karodia55, N. Kazeev74, M. Kecke14, F. Keizer51, M. Kelsey63, M.
Kenzie51, T. Ketel30, B. Khanji44, A. Kharisova75, C. Khurewathanakul45, K.E.
Kim63, T. Kirn11, V.S. Kirsebom45, S. Klaver20, K. Klimaszewski33, S.
Koliiev48, M. Kolpin14, R. Kopecna14, P. Koppenburg29, I. Kostiuk29,48, O.
Kot48, S. Kotriakhova35, M. Kozeiha7, L. Kravchuk38, M. Kreps52, F. Kress57,
S. Kretzschmar11, P. Krokovny40,x, W. Krupa32, W. Krzemien33, W. Kucewicz31,l,
M. Kucharczyk31, V. Kudryavtsev40,x, G.J. Kunde78, A.K. Kuonen45, T.
Kvaratskheliya36, D. Lacarrere44, G. Lafferty58, A. Lai24, D. Lancierini46, G.
Lanfranchi20, C. Langenbruch11, T. Latham52, C. Lazzeroni49, R. Le Gac8, R.
Lefèvre7, A. Leflat37, F. Lemaitre44, O. Leroy8, T. Lesiak31, B.
Leverington14, H. Li66, P.-R. Li4,ab, X. Li78, Y. Li5, Z. Li63, X. Liang63, T.
Likhomanenko72, R. Lindner44, F. Lionetto46, V. Lisovskyi9, G. Liu66, X. Liu3,
D. Loh52, A. Loi24, I. Longstaff55, J.H. Lopes2, G. Loustau46, G.H. Lovell51,
D. Lucchesi25,o, M. Lucio Martinez43, Y. Luo3, A. Lupato25, E. Luppi18,g, O.
Lupton52, A. Lusiani26, X. Lyu4, F. Machefert9, F. Maciuc34, V. Macko45, P.
Mackowiak12, S. Maddrell-Mander50, O. Maev35,44, K. Maguire58, D.
Maisuzenko35, M.W. Majewski32, S. Malde59, B. Malecki44, A. Malinin72, T.
Maltsev40,x, H. Malygina14, G. Manca24,f, G. Mancinelli8, D. Marangotto23,q,
J. Maratas7,w, J.F. Marchand6, U. Marconi17, C. Marin Benito9, M.
Marinangeli45, P. Marino45, J. Marks14, P.J. Marshall56, G. Martellotti28, M.
Martinelli44,22, D. Martinez Santos43, F. Martinez Vidal76, A. Massafferri1,
M. Materok11, R. Matev44, A. Mathad46, Z. Mathe44, V. Matiunin36, C.
Matteuzzi22, K.R. Mattioli77, A. Mauri46, E. Maurice9,b, B. Maurin45, M.
McCann57,44, A. McNab58, R. McNulty15, J.V. Mead56, B. Meadows61, C. Meaux8,
N. Meinert70, D. Melnychuk33, M. Merk29, A. Merli23,q, E. Michielin25, D.A.
Milanes69, E. Millard52, M.-N. Minard6, L. Minzoni18,g, D.S. Mitzel14, A.
Mödden12, A. Mogini10, R.D. Moise57, T. Mombächer12, I.A. Monroy69, S.
Monteil7, M. Morandin25, G. Morello20, M.J. Morello26,t, J. Moron32, A.B.
Morris8, R. Mountain63, F. Muheim54, M. Mukherjee68, M. Mulder29, D. Müller44,
J. Müller12, K. Müller46, V. Müller12, C.H. Murphy59, D. Murray58, P. Naik50,
T. Nakada45, R. Nandakumar53, A. Nandi59, T. Nanut45, I. Nasteva2, M.
Needham54, N. Neri23,q, S. Neubert14, N. Neufeld44, R. Newcombe57, T.D.
Nguyen45, C. Nguyen-Mau45,n, S. Nieswand11, R. Niet12, N. Nikitin37, N.S.
Nolte44, A. Oblakowska-Mucha32, V. Obraztsov41, S. Ogilvy55, D.P. O’Hanlon17,
R. Oldeman24,f, C.J.G. Onderwater71, J. D. Osborn77, A. Ossowska31, J.M.
Otalora Goicochea2, T. Ovsiannikova36, P. Owen46, A. Oyanguren76, P.R. Pais45,
T. Pajero26,t, A. Palano16, M. Palutan20, G. Panshin75, A. Papanestis53, M.
Pappagallo54, L.L. Pappalardo18,g, W. Parker62, C. Parkes58,44, G.
Passaleva19,44, A. Pastore16, M. Patel57, C. Patrignani17,e, A. Pearce44, A.
Pellegrino29, G. Penso28, M. Pepe Altarelli44, S. Perazzini17, D. Pereima36,
P. Perret7, L. Pescatore45, K. Petridis50, A. Petrolini21,h, A. Petrov72, S.
Petrucci54, M. Petruzzo23,q, B. Pietrzyk6, G. Pietrzyk45, M. Pikies31, M.
Pili59, D. Pinci28, J. Pinzino44, F. Pisani44, A. Piucci14, V. Placinta34, S.
Playfer54, J. Plews49, M. Plo Casasus43, F. Polci10, M. Poli Lener20, M.
Poliakova63, A. Poluektov8, N. Polukhina73,c, I. Polyakov63, E. Polycarpo2,
G.J. Pomery50, S. Ponce44, A. Popov41, D. Popov49,13, S. Poslavskii41, E.
Price50, C. Prouve43, V. Pugatch48, A. Puig Navarro46, H. Pullen59, G.
Punzi26,p, W. Qian4, J. Qin4, R. Quagliani10, B. Quintana7, N.V. Raab15, B.
Rachwal32, J.H. Rademacker50, M. Rama26, M. Ramos Pernas43, M.S. Rangel2, F.
Ratnikov39,74, G. Raven30, M. Ravonel Salzgeber44, M. Reboud6, F. Redi45, S.
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Rodrigues45, E. Rodrigues61, J.A. Rodriguez Lopez69, M. Roehrken44, S.
Roiser44, A. Rollings59, V. Romanovskiy41, A. Romero Vidal43, J.D. Roth77, M.
Rotondo20, M.S. Rudolph63, T. Ruf44, J. Ruiz Vidal76, J.J. Saborido Silva43,
N. Sagidova35, B. Saitta24,f, V. Salustino Guimaraes65, C. Sanchez Gras29, C.
Sanchez Mayordomo76, B. Sanmartin Sedes43, R. Santacesaria28, C. Santamarina
Rios43, M. Santimaria20,44, E. Santovetti27,j, G. Sarpis58, A. Sarti20,k, C.
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Schellenberg12, M. Schiller55, H. Schindler44, M. Schmelling13, T.
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Schubiger45, S. Schulte45, M.H. Schune9, R. Schwemmer44, B. Sciascia20, A.
Sciubba28,k, A. Semennikov36, E.S. Sepulveda10, A. Sergi49,44, N. Serra46, J.
Serrano8, L. Sestini25, A. Seuthe12, P. Seyfert44, M. Shapkin41, T. Shears56,
L. Shekhtman40,x, V. Shevchenko72, E. Shmanin73, B.G. Siddi18, R. Silva
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1Centro Brasileiro de Pesquisas Físicas (CBPF), Rio de Janeiro, Brazil
2Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil
3Center for High Energy Physics, Tsinghua University, Beijing, China
4University of Chinese Academy of Sciences, Beijing, China
5Institute Of High Energy Physics (ihep), Beijing, China
6Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, IN2P3-LAPP, Annecy,
France
7Université Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France
8Aix Marseille Univ, CNRS/IN2P3, CPPM, Marseille, France
9LAL, Univ. Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France
10LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3,
Paris, France
11I. Physikalisches Institut, RWTH Aachen University, Aachen, Germany
12Fakultät Physik, Technische Universität Dortmund, Dortmund, Germany
13Max-Planck-Institut für Kernphysik (MPIK), Heidelberg, Germany
14Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg,
Germany
15School of Physics, University College Dublin, Dublin, Ireland
16INFN Sezione di Bari, Bari, Italy
17INFN Sezione di Bologna, Bologna, Italy
18INFN Sezione di Ferrara, Ferrara, Italy
19INFN Sezione di Firenze, Firenze, Italy
20INFN Laboratori Nazionali di Frascati, Frascati, Italy
21INFN Sezione di Genova, Genova, Italy
22INFN Sezione di Milano-Bicocca, Milano, Italy
23INFN Sezione di Milano, Milano, Italy
24INFN Sezione di Cagliari, Monserrato, Italy
25INFN Sezione di Padova, Padova, Italy
26INFN Sezione di Pisa, Pisa, Italy
27INFN Sezione di Roma Tor Vergata, Roma, Italy
28INFN Sezione di Roma La Sapienza, Roma, Italy
29Nikhef National Institute for Subatomic Physics, Amsterdam, Netherlands
30Nikhef National Institute for Subatomic Physics and VU University Amsterdam,
Amsterdam, Netherlands
31Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of
Sciences, Kraków, Poland
32AGH - University of Science and Technology, Faculty of Physics and Applied
Computer Science, Kraków, Poland
33National Center for Nuclear Research (NCBJ), Warsaw, Poland
34Horia Hulubei National Institute of Physics and Nuclear Engineering,
Bucharest-Magurele, Romania
35Petersburg Nuclear Physics Institute (PNPI), Gatchina, Russia
36Institute of Theoretical and Experimental Physics (ITEP), Moscow, Russia
37Institute of Nuclear Physics, Moscow State University (SINP MSU), Moscow,
Russia
38Institute for Nuclear Research of the Russian Academy of Sciences (INR RAS),
Moscow, Russia
39Yandex School of Data Analysis, Moscow, Russia
40Budker Institute of Nuclear Physics (SB RAS), Novosibirsk, Russia
41Institute for High Energy Physics (IHEP), Protvino, Russia
42ICCUB, Universitat de Barcelona, Barcelona, Spain
43Instituto Galego de Física de Altas Enerxías (IGFAE), Universidade de
Santiago de Compostela, Santiago de Compostela, Spain
44European Organization for Nuclear Research (CERN), Geneva, Switzerland
45Institute of Physics, Ecole Polytechnique Fédérale de Lausanne (EPFL),
Lausanne, Switzerland
46Physik-Institut, Universität Zürich, Zürich, Switzerland
47NSC Kharkiv Institute of Physics and Technology (NSC KIPT), Kharkiv, Ukraine
48Institute for Nuclear Research of the National Academy of Sciences (KINR),
Kyiv, Ukraine
49University of Birmingham, Birmingham, United Kingdom
50H.H. Wills Physics Laboratory, University of Bristol, Bristol, United
Kingdom
51Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom
52Department of Physics, University of Warwick, Coventry, United Kingdom
53STFC Rutherford Appleton Laboratory, Didcot, United Kingdom
54School of Physics and Astronomy, University of Edinburgh, Edinburgh, United
Kingdom
55School of Physics and Astronomy, University of Glasgow, Glasgow, United
Kingdom
56Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom
57Imperial College London, London, United Kingdom
58School of Physics and Astronomy, University of Manchester, Manchester,
United Kingdom
59Department of Physics, University of Oxford, Oxford, United Kingdom
60Massachusetts Institute of Technology, Cambridge, MA, United States
61University of Cincinnati, Cincinnati, OH, United States
62University of Maryland, College Park, MD, United States
63Syracuse University, Syracuse, NY, United States
64Laboratory of Mathematical and Subatomic Physics , Constantine, Algeria,
associated to 2
65Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Rio de
Janeiro, Brazil, associated to 2
66South China Normal University, Guangzhou, China, associated to 3
67School of Physics and Technology, Wuhan University, Wuhan, China, associated
to 3
68Institute of Particle Physics, Central China Normal University, Wuhan,
Hubei, China, associated to 3
69Departamento de Fisica , Universidad Nacional de Colombia, Bogota, Colombia,
associated to 10
70Institut für Physik, Universität Rostock, Rostock, Germany, associated to 14
71Van Swinderen Institute, University of Groningen, Groningen, Netherlands,
associated to 29
72National Research Centre Kurchatov Institute, Moscow, Russia, associated to
36
73National University of Science and Technology “MISIS”, Moscow, Russia,
associated to 36
74National Research University Higher School of Economics, Moscow, Russia,
associated to 39
75National Research Tomsk Polytechnic University, Tomsk, Russia, associated to
36
76Instituto de Fisica Corpuscular, Centro Mixto Universidad de Valencia -
CSIC, Valencia, Spain, associated to 42
77University of Michigan, Ann Arbor, United States, associated to 63
78Los Alamos National Laboratory (LANL), Los Alamos, United States, associated
to 63

aUniversidade Federal do Triângulo Mineiro (UFTM), Uberaba-MG, Brazil
bLaboratoire Leprince-Ringuet, Palaiseau, France
cP.N. Lebedev Physical Institute, Russian Academy of Science (LPI RAS),
Moscow, Russia
dUniversità di Bari, Bari, Italy
eUniversità di Bologna, Bologna, Italy
fUniversità di Cagliari, Cagliari, Italy
gUniversità di Ferrara, Ferrara, Italy
hUniversità di Genova, Genova, Italy
iUniversità di Milano Bicocca, Milano, Italy
jUniversità di Roma Tor Vergata, Roma, Italy
kUniversità di Roma La Sapienza, Roma, Italy
lAGH - University of Science and Technology, Faculty of Computer Science,
Electronics and Telecommunications, Kraków, Poland
mLIFAELS, La Salle, Universitat Ramon Llull, Barcelona, Spain
nHanoi University of Science, Hanoi, Vietnam
oUniversità di Padova, Padova, Italy
pUniversità di Pisa, Pisa, Italy
qUniversità degli Studi di Milano, Milano, Italy
rUniversità di Urbino, Urbino, Italy
sUniversità della Basilicata, Potenza, Italy
tScuola Normale Superiore, Pisa, Italy
uUniversità di Modena e Reggio Emilia, Modena, Italy
vH.H. Wills Physics Laboratory, University of Bristol, Bristol, United Kingdom
wMSU - Iligan Institute of Technology (MSU-IIT), Iligan, Philippines
xNovosibirsk State University, Novosibirsk, Russia
ySezione INFN di Trieste, Trieste, Italy
zSchool of Physics and Information Technology, Shaanxi Normal University
(SNNU), Xi’an, China
aaPhysics and Micro Electronic College, Hunan University, Changsha City, China
abLanzhou University, Lanzhou, China
†Deceased