EUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH (CERN)

 CERN-EP-2021-128 LHCb-PAPER-2021-017 January 17, 2022

Search for the

radiative ${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$ decay

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

The first search for the rare radiative decay ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$ is
performed using data collected by the LHCb experiment in proton-proton
collisions at a center-of-mass energy of 13 TeV, corresponding to an
integrated luminosity of 5.4$\text{\,fb}^{-1}$. The ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$ channel is used as
normalization. No ${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$ signal is found and an upper limit of
${\mathcal{B}}(\mbox{${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$})<1.3\times 10^{-4}$ at 95% confidence level is
obtained.

Published in JHEP 01 (2022) 069

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

##  1 Introduction

The ${b}\\!\rightarrow{s}{\gamma}$ transition, depicted in Figure 1, is a
flavor-changing neutral-current process characterized by the emission of a
photon in the final state. Decays involving this feature are also known as
radiative decays.

penguin1 (150,75) t1,t2 b,s fermionb,w1
fermion,left,tension=0.5,label=$t,,c,,u$w1,w2 fermionw2,s
photon,right,tension=0.5,label=$W$w1,w2 photon,label=$\gamma$ph,t2
(0.59w,0.39h)ph $b$b $s$s (150,75) t1,t2 b,s fermionb,w1
fermion,left,tension=0.5,label=$t,,c,,u,,...$w1,w2 fermionw2,s
scalar,right,tension=0.5,label=$H,,\chi,,\tilde{g}$w1,w2
photon,label=$\gamma$ph,t2 (0.59w,0.39h)ph $b$b $s$s

Figure 1:  The $b\rightarrow s\gamma$ penguin diagram, mediated by SM
particles (left) and BSM particles (right).

The effective Hamiltonian in the operator product expansion formalism
describing ${b}\\!\rightarrow{s}{\gamma}$ transitions at leading order is
given by

$\mathcal{H}_{eff}=-\frac{G_{F}}{\sqrt{2}}V^{*}_{ts}V_{tb}(\mathcal{C}_{7}\mathcal{O}_{7}+\mathcal{C}_{7}^{\prime}\mathcal{O}_{7}^{\prime})\,,$
(1)

where $\mathcal{O}_{7}$ $(\mathcal{O}_{7}^{\prime})$ represents the left
(right) projection of the electromagnetic penguin operator, which corresponds
to the emission of a left (right)-handed photon. The strength of each
contribution is encoded in the Wilson coefficients $\mathcal{C}_{7}$ and
$\mathcal{C}_{7}^{\prime}$. In the SM, the $W^{-}$ boson only couples to left-
handed quarks and, thus, the only source of right-handed photons is due to
helicity flips. The ratio of right- and left-handed amplitudes is expected to
be $\mathcal{O}(m_{s}/m_{b})$. Thus, the SM predicts a negligible contribution
of the right-handed operator $\mathcal{O}_{7}^{\prime}$. Measuring branching
fractions, angular and charge-parity-violating observables in
${b}\\!\rightarrow{s}{\gamma}$ transitions enables testing the presence of
right-handed contributions. Several analyses focusing on $B$-meson decays have
explored this field [1, 2, 3, 4, 5].

Radiative decays of $b$-baryons provide access to the photon polarization due
to the spin $\nicefrac{{1}}{{2}}$ ground state, the absence of flavor mixing
and the presence of two spectator quarks. Therefore, $b$-baryon decays provide
complementary measurements to those performed with radiative $B$-meson decays
[6].

The branching fraction of the ${{\mathchar
28931\relax}^{0}_{b}}\rightarrow{\mathchar 28931\relax}{\gamma}$ decay mode
has been recently measured for the first time [7] and constitutes the first
radiative $b$-baryon decay observed.111Charge-conjugated processes are implied
throughout this paper. Further radiative $b$-baryon decays can be studied with
the LHCb detector, providing complementary tests of the photon polarization in
the SM. This paper focuses on the search for the ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$ decay
mode, which is also mediated by the ${b}\\!\rightarrow{s}{\gamma}$ transition.
The LHCb experiment provides unique conditions for studying the ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$ mode
thanks to the large production of $b$-baryons at the LHC [8, 9] and the
excellent performance of the detector optimized for the analysis of $b$-hadron
decays. Additionally, previous measurements at LHCb involving radiative B
meson [1, 2, 3, 4, 5] and $b$-baryon [7] decays motivates the search for new
radiative baryonic modes, such as the ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$ decay.

The rare radiative $b$-baryon decay ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$ has not
yet been observed. Using light-cone sum rules, its branching fraction,
$\mathcal{B}$ (${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$), is predicted to be $(3.03\pm 0.10)\times 10^{-4}$
[10]. This prediction is larger than the branching fraction of other radiative
decays (${\mathcal{B}}\sim{\mathcal{O}}(10^{-5})$) [11, 12, 7]. A more recent
study uses SU(3) flavor symmetry rules to predict
${\mathcal{B}}(\mbox{${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$})=(1.23\pm 0.64)\times 10^{-5}$ [13]. This second
prediction uses the measurement of ${\mathcal{B}}(\mbox{${{\mathchar
28931\relax}^{0}_{b}}\rightarrow{\mathchar 28931\relax}{\gamma}$})$ and thus
it has a smaller dependency on estimated form factors. A measurement of the
branching fraction of this decay could discriminate different approaches used
in the theoretical predictions. This could help to estimate form-factors at
low $q^{2}$ (photon pole) for the semileptonic decay ${{\mathchar
28932\relax}^{-}_{b}}\\!\rightarrow{{\mathchar
28932\relax}^{-}}{\mu^{+}}{\mu^{-}}$ [14]. Furthermore, the possible signal
obtained could be used to perform a measurement of the photon polarization
[15].

The data sample analyzed in this paper corresponds to an integrated luminosity
of 5.4$\text{\,fb}^{-1}$ of proton-proton ($p$ $p$) collisions at a center-of-
mass energy of 13 TeV, collected by the LHCb detector. Potential
experimenters’ bias is avoided by validating the analysis procedure before
inspecting the results. A normalization channel sharing the same hadronic part
of the final state as the radiative decay is used to cancel potential
systematic effects arising from detector efficiencies and the limited
knowledge on the ${\mathchar 28932\relax}^{-}_{b}$ production, $f_{{\mathchar
28932\relax}^{-}_{b}}$. The normalization channel is chosen to be the
${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$ decay.

##  2 LHCb detector

The LHCb detector [16, 17] 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 $p$ $p$
interaction region, a large-area silicon-strip detector located upstream of a
dipole magnet with a bending power of about 4 Tm, and three stations of
silicon-strip detectors and straw drift tubes placed downstream of the magnet.
The tracking system provides measurements of the momentum 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 $p$ $p$ collision vertex (PV), the impact parameter, is measured with
a resolution of $(15\pm 29/p_{\mathrm{T}})$$\,\upmu\text{m}$, where
$p_{\mathrm{T}}$ is the component of the momentum transverse to the beam, in
$\text{\,Ge\kern-1.00006ptV\\!/}c$. The PV is reconstructed by forming a
common vertex from a large number of tracks, consistent with originating from
a pp collision [18]. Different types of charged hadrons are distinguished
using information from two ring-imaging Cherenkov detectors. Photons,
electrons and hadrons are identified by a calorimeter system consisting of
scintillating-pad and preshower detectors, an electromagnetic and a hadronic
calorimeter. Charged and neutral clusters in the electromagnetic calorimeter
are discerned by extrapolating the tracks reconstructed by the tracking system
to the calorimeter plane. Photons and neutral pions are distinguished by
cluster shape, energy and mass distributions. Muons are identified by a system
composed of alternating layers of iron and multiwire proportional chambers.
Due to the photon energy resolution, $b$-hadron decays with a high-energy
photon in their final state are reconstructed with a $b$-hadron mass
resolution around 100$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ [3].

The online event selection is performed by a trigger system [19], consisting
of a hardware stage, which uses information from the calorimeter and muon
systems, followed by two software stages, which apply a partial and a full
event reconstruction. At the hardware trigger stage, events are required to
have a high-$p_{\mathrm{T}}$ photon or electron, detected in the
electromagnetic calorimeter as a cluster of transverse energy
($E_{\mathrm{T}}$) with a threshold that varied between 2.1 and
$3.0\text{\,Ge\kern-1.00006ptV}$ during the data-taking period. The first
stage of the software trigger requires a track well separated from any PV, and
with a $p_{\mathrm{T}}$ higher than 1$\text{\,Ge\kern-1.00006ptV\\!/}c$. At
the second stage of the software trigger, the full decay chain is
reconstructed to identify decays consistent with the signal mode. Only events
signal candidate fulfilling the trigger requirements are kept.

Simulation is used to develop the selection strategy, compute the efficiency
and determine the shape of the invariant-mass distribution of the signal
decays. In the simulation, $p$ $p$ collisions are generated using Pythia [20,
*Sjostrand:2006za] with a specific LHCb configuration [22]. Decays of unstable
particles are described by EvtGen [23], in which final-state radiation is
generated using Photos [24]. The interaction of the generated particles with
the detector, and its response are simulated using the Geant4 toolkit [25,
*Agostinelli:2002hh], as described in Ref. [27]. To save computing resources,
the simulated signal decay is superimposed to a limited set of simulated
underlying interactions which are used multiple times [28].

##  3 Selection

The reconstruction of the ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$ decay,
with ${{\mathchar 28932\relax}^{-}}\rightarrow{\mathchar
28931\relax}{{\pi}^{-}}$ and ${\mathchar
28931\relax}\rightarrow{p}{{\pi}^{-}}$, involves the combination of two tracks
with opposite charges originating from a common displaced vertex, and
compatible with the $p$ and $\pi^{-}$ hypotheses. This is identified as a
${\mathchar 28931\relax}$ baryon, which is combined with a $\pi^{-}$ track to
form the ${{\mathchar 28932\relax}^{-}}$ candidate. The ${{\mathchar
28932\relax}^{-}_{b}}$ candidate is in turn reconstructed as the combination
of an energetic photon and the reconstructed ${{\mathchar 28932\relax}^{-}}$
candidate. A sketch of the full decay chain, which includes three independent
displaced vertices, is shown in Fig. 2.

Figure 2: Topology of the ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$ decay,
including three displaced vertices, with $c\tau$ of each particle given.

High-quality tracks inconsistent with originating from the PV are used for the
reconstruction. For events with multiple PVs, the PV with the lowest impact
parameter with respect to the candidate is used. Because of the long lifetime
and large Lorentz boost, most of the $\mathchar 28931\relax$ and ${\mathchar
28932\relax}^{-}$ baryons decay outside the vertex detector. However, due to
trigger limitations, only decays that occur inside the vertex detector can be
considered. Particle identification requirements, based on a multivariate
analysis technique, are applied to the charged particles [29]. Proton and pion
candidates with a minimum transverse momentum of
630$\text{\,Me\kern-1.00006ptV\\!/}c$ and
250$\text{\,Me\kern-1.00006ptV\\!/}c$, respectively, are used to form a
$\mathchar 28931\relax$ candidate. The proton-pion system is required to have
a mass within 6$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ of the known $\mathchar
28931\relax$ mass [30] and a $p_{\mathrm{T}}$ larger than
1.5$\text{\,Ge\kern-1.00006ptV\\!/}c$. The $\mathchar 28931\relax$ candidate
is then combined with a pion candidate with
$p_{\mathrm{T}}>130\text{\,Me\kern-1.00006ptV\\!/}c$ to form a ${\mathchar
28932\relax}^{-}$ candidate. This candidate is required to have decayed within
400 mm of the PV, to have a $p_{\mathrm{T}}$ larger than
2$\text{\,Ge\kern-1.00006ptV\\!/}c$ and a mass, $m({{\pi}^{-}}{{\pi}^{-}}{p})$
in the range 1310–1332$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ around the known
value of the ${\mathchar 28932\relax}^{-}$ mass of $1321.71\pm
0.07\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ [30]. After the trigger and offline
requirements, a clean sample of ${\mathchar 28932\relax}^{-}$ candidates is
obtained. The distribution of the mass of ${\mathchar 28932\relax}^{-}$
candidates is shown in Fig. 3.

Figure 3: Mass distribution $m({{\pi}^{-}}{{\pi}^{-}}{p})$ showing the
${{\mathchar 28932\relax}^{-}}\\!\rightarrow{\mathchar
28931\relax}{{\pi}^{-}}$ signal for events satisfying the trigger and the
offline requirements described in the text for ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$ decays.

Photon candidates are reconstructed from energy deposits in the
electromagnetic calorimeter not associated to any track. Background due to
photons from ${\pi}^{0}$ decays is rejected by a dedicated algorithm [31]. The
${\mathchar 28932\relax}^{-}$ candidate is combined with a photon candidate
with $E_{\mathrm{T}}$ larger than 4 GeV. Due to the unknown photon direction
and the long lifetime of the ${\mathchar 28932\relax}^{-}$ baryon, the
${\mathchar 28932\relax}^{-}_{b}$ decay vertex cannot be determined.
Consequently, the ${\mathchar 28932\relax}^{-}_{b}$ trajectory is calculated
assuming the photon originates from the PV with the smallest distance of
closest approach with respect to the ${\mathchar 28932\relax}^{-}$ trajectory.
This is a good approximation given the short decay time of the ${\mathchar
28932\relax}^{-}_{b}$ baryon. The $\gamma$ and ${\mathchar 28932\relax}^{-}$
momenta are then combined to reconstruct the ${\mathchar 28932\relax}^{-}_{b}$
candidate. The ${\mathchar 28932\relax}^{-}_{b}$ candidate must have
$p_{\mathrm{T}}$ larger than 4$\text{\,Ge\kern-1.00006ptV\\!/}c$ and a mass
within 800$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ of its known mass [30]. The
distance of closest approach between the ${\mathchar 28932\relax}^{-}_{b}$ and
the ${\mathchar 28932\relax}^{-}$ trajectories must be $<50\,\upmu\text{m}$.

The combinatorial background, formed by random combinations of final-state
particles, is suppressed by using a boosted decision tree (BDT) [32],
employing the XGBOOST algorithm [33]. The BDT classifier is trained using
simulated samples of ${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$ decays as signal, and candidates from data samples
with the ${\mathchar 28932\relax}^{-}$ $\gamma$ mass above
6.1$\text{\,Ge\kern-1.00006ptV\\!/}c^{2}$ as a background proxy. The
$k$-folding cross-validation technique [34] with $k$ = 5 is used to avoid
overfitting the BDT model. The variables used to train the BDT classifier are:
the transverse momentum and the separation from the PV of the signal decay
products; the photon pseudorapidity; the distance of closest approach between
the ${\mathchar 28932\relax}^{-}$ decay products and between the ${\mathchar
28932\relax}^{-}_{b}$ and ${\mathchar 28932\relax}^{-}$ flight directions; and
the $p_{\mathrm{T}}$ asymmetry of the ${\mathchar 28932\relax}^{-}$ and the
$\gamma$ candidates. The $p_{\mathrm{T}}$ asymmetry for a given particle is
computed as the normalized difference between the summed momenta of all tracks
within a cone of 1 rad around the particle direction, and the momentum of the
particle. The above variable discriminates against partially reconstructed
backgrounds, consisting of decays with additional particles in the final state
that have not been reconstructed. As the BDT classifier is trained using
simulation, good agreement between the simulation and data is needed. This is
validated using the ${{\mathchar
28931\relax}^{0}_{b}}\\!\rightarrow{{J\mskip-3.0mu/\mskip-2.0mu\psi}}{p}{{K}^{-}}$
and ${{B}^{0}}\\!\rightarrow{{K}^{*}}{\gamma}$ control modes employing the
selection criteria described in Refs. [35] and [3], respectively. The
normalization channel ${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$, with the selection
described below, is also used for the same purpose. The event multiplicity,
defined as the number of tracks per event, along with the $b$-baryon momentum
and transverse momentum are corrected for discrepancies between simulation and
data. These corrections are extracted from ${{\mathchar
28931\relax}^{0}_{b}}\\!\rightarrow{{J\mskip-3.0mu/\mskip-2.0mu\psi}}{p}{{K}^{-}}$
background-subtracted data and simulated samples. The BDT classifier is
optimized by maximizing the Punzi figure of merit [36],
$\epsilon_{\text{s}}/(\sqrt{B}+2.5)$, where $\epsilon_{\text{s}}$ is the
efficiency of the requirement on the BDT output extracted from simulated
signal events, and $B$ is the background yield from the high-mass sideband,
extrapolated to the signal region. The chosen working point keeps 69% of the
signal candidates, while suppressing about 98% of the combinatorial
background.

The online reconstruction of candidates from the ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$ normalization channel,
with ${{J\mskip-3.0mu/\mskip-2.0mu\psi}}\rightarrow{\mu^{+}}{\mu^{-}}$,
follows a different strategy as compared to the ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$ signal
channel. The muons, originating from inside the vertex detector, must pass the
trigger for the normalization channel. This allows $\mathchar 28931\relax$ and
${\mathchar 28932\relax}^{-}$ baryons decaying both inside and outside the
vertex detector to be used. For the trigger selection of the normalization
channel, events are required to either have a muon with a $p_{\mathrm{T}}$
above 1.5$\text{\,Ge\kern-1.00006ptV\\!/}c$, or two muons with a transverse
momentum product greater than 1.6$\text{\,Ge\kern-1.00006ptV}^{2}\\!/c^{2}$.
In the first software stage of the trigger, the event must have either a
system of two well-identified oppositely charged muons with a large mass,
$m({\mu^{+}}{\mu^{-}})>2.7\text{\,Ge\kern-1.00006ptV\\!/}c^{2}$, or at least
one muon with $p_{\mathrm{T}}>1\text{\,Ge\kern-1.00006ptV}$ that is
inconsistent with originating from any PV. In the second stage, events
containing a $\mu^{+}$ $\mu^{-}$-pair with a mass consistent with the known
${J\mskip-3.0mu/\mskip-2.0mu\psi}$ mass [30], and with a vertex significantly
displaced from any PV, are selected. The offline reconstruction follows
similar criteria to the ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$
selection. The ${J\mskip-3.0mu/\mskip-2.0mu\psi}$ candidate is reconstructed
from two oppositely-charged tracks compatible with the muon hypothesis. The
mass of the $\mu^{+}$ $\mu^{-}$ pair is required to be within a window of
60$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ around the known
${J\mskip-3.0mu/\mskip-2.0mu\psi}$ mass [30]. In this case, the ${\mathchar
28932\relax}^{-}_{b}$ vertex is reconstructed with an improved $b$-baryon mass
resolution, with respect to the radiative decay, due to a precise measurement
of the muon momenta. The ${\mathchar 28932\relax}^{-}_{b}$ candidate is
required to have a measured decay time between 0.3 and 1.4 ps, a mass within
300$\text{\,Me\kern-1.00006ptV\\!/}c^{2}$ of the ${\mathchar
28932\relax}^{-}_{b}$ measured mass [30] and a good quality decay vertex.
Given the high purity of the ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$ sample after the
described selection, no BDT selection is used.

##  4 Yield determination

The signal is isolated from the background components by a fit to the
reconstructed ${\mathchar 28932\relax}^{-}_{b}$ mass distribution of the
selected candidates. An unbinned maximum likelihood fit to the radiative,
${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$, and the normalization, ${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$, decay modes are used.
The signal-mass shape is modeled with a double-sided Crystal Ball probability
density function [37], comprising a Gaussian core and a power-law tail at both
sides. The parameters for the tails are extracted from a fit to simulated
samples. In the mass fit to data, the peak position for the radiative and
normalization channels is the same, while the peak width is related using a
scaling factor defined as the ratio of the signal and normalization widths in
simulation. Sources of non-combinatorial background are investigated using
simulated samples. The narrow width of the $\mathchar 28931\relax$ and
${\mathchar 28932\relax}^{-}$ baryons [30] and the clean sample of the latter
(see Fig. 3) reduces the contamination from decays where one or more final
state particles are misidentified, such as ${{\mathchar
28938\relax}^{-}_{b}}\\!\rightarrow{{\mathchar 28938\relax}^{-}}{\gamma}$. No
candidates from the partially reconstructed background ${{\mathchar
28932\relax}^{-}_{b}}\\!\rightarrow\Xi\eta$ with
$\eta\\!\rightarrow{\gamma}{\gamma}$ are expected in the selected data sample.
There are no predictions for ${\mathchar 28932\relax}^{-}_{b}$ baryons
decaying into ${\pi}^{0}$ mesons. This class of contamination is known to be
suppressed in ${B}^{0}$ decays to ${K}^{*}$ $\gamma$ and ${K}^{*}$ ${\pi}^{0}$
final states, and the same is assumed in the baryon sector [30]. The only
relevant background component is the combinatorial one, which is modeled with
an exponential function. The mass fit is validated using pseudoexperiments
with ${\mathcal{B}}(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$})$
hypotheses ranging from $10^{-5}$ to $10^{-3}$.

The branching fraction is determined as

$\displaystyle{\mathcal{B}}(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$})$
$\displaystyle={\mathcal{B}}(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$}){\mathcal{B}}(J/\psi\rightarrow\mu^{+}\mu^{-})$
$\displaystyle\times\frac{\epsilon(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})}{\epsilon(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$})}\frac{N(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$})}{N(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})}$ (2)
$\displaystyle=\alpha N(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$})\,,$

where $\mathcal{B}$ indicates a branching fraction, $N$ is the signal yield
extracted from the mass fit, $\epsilon$ denotes the combined reconstruction
and selection efficiency for the given decay and $\alpha$ is the single-event
sensitivity. Calibration samples of ${\mathchar
28931\relax}\\!\rightarrow{p}{{\pi}^{-}}$,
${{D}^{0}}\\!\rightarrow{{K}^{-}}{{\pi}^{+}}$,
${{J\mskip-3.0mu/\mskip-2.0mu\psi}}\\!\rightarrow{\mu^{+}}{\mu^{-}}$ and
${{B}^{0}}\\!\rightarrow{{K}^{*}}{\gamma}$ are used to calculate the
efficiencies of the particle identification requirements [29, 31]. The
remaining selection and reconstruction efficiencies are determined from
simulated samples.

The value of the ${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$ branching fraction
multiplied by the hadronization fraction of ${\mathchar 28932\relax}^{-}_{b}$
baryons, $f_{{\mathchar 28932\relax}^{-}_{b}}$, is provided in Ref. [30]. Due
to the lack of precision in the $f_{{\mathchar 28932\relax}^{-}_{b}}$ absolute
value, the ${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$ branching fraction is
computed using the SU(3) relation $\Gamma(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})=(3/2\pm
0.45)\times\Gamma(\mbox{${{\mathchar
28931\relax}^{0}_{b}}\rightarrow{\mathchar
28931\relax}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})$ [38] instead. The quoted
uncertainty is typical for flavor SU(3) predictions.

Table 1: Input parameters used to compute the branching fraction ${\mathcal{B}}(\mbox{${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})$. Parameter | Value
---|---
$\tau_{{{\mathchar 28932\relax}_{b}}}$ |  $1.57\pm 0.04\text{\,ps}$ [30]
$\tau_{{{\mathchar 28931\relax}^{0}_{b}}}$ |  $1.47\pm 0.01\text{\,ps}$ [30]
${\mathcal{B}}(\mbox{${{\mathchar 28931\relax}^{0}_{b}}\rightarrow{\mathchar 28931\relax}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})$ |  $(3.36\pm 1.11)\times 10^{-4}$ [39, 40]

Combining the values listed in Tab. 1, the computed value of
${\mathcal{B}}(\mbox{${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})$ is

$\displaystyle{\mathcal{B}}(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})=\Big{(}\frac{3}{2}\pm
0.45\Big{)}\frac{\tau_{{{\mathchar 28932\relax}_{b}}}}{\tau_{{{\mathchar
28931\relax}^{0}_{b}}}}{\mathcal{B}}(\mbox{${{\mathchar
28931\relax}^{0}_{b}}\rightarrow{\mathchar
28931\relax}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})=(5.4\pm 2.4)\times
10^{-4}\,.$ (3)

##  5 Results

Figure 4 shows the distribution of (top) the mass
$m({{\pi}^{-}}{{\pi}^{-}}{p}\gamma)$ for selected ${\mathchar
28932\relax}^{-}$ $\gamma$ and (bottom)
$m({{\pi}^{-}}{{\pi}^{-}}{p}\,{\mu^{+}}{\mu^{-}})$ for selected ${\mathchar
28932\relax}^{-}$ ${J\mskip-3.0mu/\mskip-2.0mu\psi}$ candidates.

Figure 4: Distribution of (top) mass $m({{\pi}^{-}}{{\pi}^{-}}{p}\gamma)$ for
selected ${\mathchar 28932\relax}^{-}$ $\gamma$ (${{\mathchar
28932\relax}^{-}}\\!\rightarrow{\mathchar 28931\relax}{{\pi}^{-}}$) and
(bottom) $m({{\pi}^{-}}{{\pi}^{-}}{p}{\mu^{+}}{\mu^{-}})$ for selected
${\mathchar 28932\relax}^{-}$ ${J\mskip-3.0mu/\mskip-2.0mu\psi}$
(${{J\mskip-3.0mu/\mskip-2.0mu\psi}}\\!\rightarrow{\mu^{+}}{\mu^{-}}$)
candidates. The projections of the simultaneous fit are overlaid.

The simultaneous mass fit to these mass distributions returns yields of
$N(\mbox{${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$})=-3.6\pm 3.9$ and $N(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})=1407\pm 52$. Using the
yield for the normalization channel together with the other quantities of Eq.
4, a single-event sensitivity of $\alpha=(7.9\pm 3.6)\times 10^{-6}$ is
obtained.

Systematic uncertainties on the measurement of the
${\mathcal{B}}(\mbox{${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$})$ value arise from several sources. The systematic
effect due to the choice of the mass fit model is assessed by means of
pseudoexperiments wherein the mass distribution is generated with an
alternative model and fitted using the default model. The validation of fixing
the value of the scale parameter relating the radiative and normalization
channel resolutions is assessed by repeating the measurement considering
possible differences between data and simulation. No deviation is found with
respect to the nominal measurement and, thus, no systematic uncertainty is
assigned to this effect. The uncertainty on the selection efficiencies,
originating from the limited sample size, is propagated to the branching
fraction and considered as a systematic uncertainty. The corrections applied
to the simulation to improve the agreement with data are varied within their
statistical uncertainty. The effect of a possible mismodeling of the radiative
hardware level trigger is assessed by comparing the efficiency extracted from
simulation and from a method using the
${{B}^{0}}\\!\rightarrow{{K}^{*0}}{\gamma}$ decay as a control channel. The
limited precision of the external value of ${\mathcal{B}}(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})$ induces the largest
systematic uncertainty. Table 2 summarizes the systematic uncertainties.

Table 2: Dominant systematic uncertainties on the measurement of the branching fraction $\mathcal{B}$ (${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$). Source | Uncertainty (%)
---|---
Mass fit model (signal) | 9.1
Mass fit model (background) | 7.8
Efficiency ratio | 4.6
Hardware trigger | 10.0
Simulation/Data agreement | 6.0
${\mathcal{B}}(\mbox{${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})$ | 45.6
Sum in quadrature | 48.7

Since no ${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$ signal is observed, the Feldman-Cousins (FC) method
[41] is used to set an upper limit on the value of
${\mathcal{B}}(\mbox{${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$})$. For the FC method, the relation between the
true and fitted signal yield and the statistical uncertainty are determined
from pseudoexperiments. The systematic uncertainty is added in quadrature to
the statistical uncertainty. The value of ${\mathcal{B}}(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$})$ is
calculated from the signal yield using Eq. (4). From this set of values, the
95% confidence level (CL) is built and shown in Fig. 5.

Figure 5: Confidence interval at 95% CL showing the upper limit for
${\mathcal{B}}(\mbox{${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$})$ as a function of the $\frac{N(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$})}{N(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})}$ ratio. The green line
represents the relation between the yield and the branching fractions. The
interval considering only the statistical uncertainty is shown by the dashed
blue lines, while the full blue lines also includes the systematic
uncertainties. The measured ratio of the yields and the upper limit on the
branching fraction are represented by the red line.

Combining this study with the measured yield ratio, an upper limit is set

${\mathcal{B}}(\mbox{${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$})<1.3\,(0.6)\times 10^{-4}\;\text{ at
}95\%\,(90\%)\text{ CL}\,.$

This is the first limit on this decay channel. Because the systematic
uncertainty from the normalization channel branching fraction is dominant, the
ratio of the branching fractions is reported, where the total systematic
reduces to 17%. Using the FC approach, an upper limit of

$\frac{{\mathcal{B}}(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$})}{{\mathcal{B}}(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{{J\mskip-3.0mu/\mskip-2.0mu\psi}}$})}<0.12\,(0.08)\text{ at
}95\%\,(90\%)\text{ CL}\,,$

is set.

##  6 Conclusion

The first search for $b$-baryon flavor-changing neutral-current radiative
${{\mathchar 28932\relax}^{-}_{b}}\rightarrow{{\mathchar
28932\relax}^{-}}{\gamma}$ decay is reported, using $p$ $p$ collision data at
a center-of-mass energy of $\sqrt{s}=13\text{\,Te\kern-1.00006ptV}$ collected
by the LHCb experiment. The data set corresponds to an integrated luminosity
of 5.4$\text{\,fb}^{-1}$. No evidence for a signal is found. Upper limits at
90% and 95% CL of the value of ${\mathcal{B}}(\mbox{${{\mathchar
28932\relax}^{-}_{b}}\rightarrow{{\mathchar 28932\relax}^{-}}{\gamma}$})$ are
reported, which are in slight tension with the predictions from light-cone sum
rules [10] but are consistent with flavor-symmetry driven predictions from
Ref. [13].

## 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); MICINN (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 NERSC (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 ARC and ARDC (Australia); AvH Foundation
(Germany); EPLANET, Marie Skłodowska-Curie Actions and ERC (European Union);
A*MIDEX, ANR, IPhU and Labex P2IO, and Région Auvergne-Rhône-Alpes (France);
Key Research Program of Frontier Sciences of CAS, CAS PIFI, CAS CCEPP,
Fundamental Research Funds for the Central Universities, and Sci. & Tech.
Program of Guangzhou (China); RFBR, RSF and Yandex LLC (Russia); GVA, XuntaGal
and GENCAT (Spain); the Leverhulme Trust, the Royal Society and UKRI (United
Kingdom).

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LHCb collaboration

R. Aaij32, A.S.W. Abdelmotteleb56, C. Abellán Beteta50, T. Ackernley60, B.
Adeva46, M. Adinolfi54, H. Afsharnia9, C.A. Aidala86, S. Aiola25, Z.
Ajaltouni9, S. Akar65, J. Albrecht15, F. Alessio48, M. Alexander59, A. Alfonso
Albero45, Z. Aliouche62, G. Alkhazov38, P. Alvarez Cartelle55, S. Amato2, J.L.
Amey54, Y. Amhis11, L. An48, L. Anderlini22, A. Andreianov38, M. Andreotti21,
F. Archilli17, A. Artamonov44, M. Artuso68, K. Arzymatov42, E. Aslanides10, M.
Atzeni50, B. Audurier12, S. Bachmann17, M. Bachmayer49, J.J. Back56, P.
Baladron Rodriguez46, V. Balagura12, W. Baldini21, J. Baptista Leite1, R.J.
Barlow62, S. Barsuk11, W. Barter61, M. Bartolini24,h, F. Baryshnikov83, J.M.
Basels14, S. Bashir34, G. Bassi29, B. Batsukh68, A. Battig15, A. Bay49, A.
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Belin27, V. Bellee50, K. Belous44, I. Belov40, I. Belyaev41, G. Bencivenni23,
E. Ben-Haim13, A. Berezhnoy40, R. Bernet50, D. Berninghoff17, H.C.
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N. Bondar38,48, S. Borghi62, M. Borisyak42, M. Borsato17, J.T. Borsuk35, S.A.
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Kudryavtsev43,v, H.S. Kuindersma32,33, G.J. Kunde67, T. Kvaratskheliya41, D.
Lacarrere48, G. Lafferty62, A. Lai27, A. Lampis27, D. Lancierini50, J.J.
Lane62, R. Lane54, G. Lanfranchi23, C. Langenbruch14, J. Langer15, O.
Lantwin83, T. Latham56, F. Lazzari29,q, R. Le Gac10, S.H. Lee86, R. Lefèvre9,
A. Leflat40, S. Legotin83, O. Leroy10, T. Lesiak35, B. Leverington17, H. Li72,
P. Li17, S. Li7, Y. Li4, Y. Li4, Z. Li68, X. Liang68, T. Lin61, R. Lindner48,
V. Lisovskyi15, R. Litvinov27, G. Liu72, H. Liu6, S. Liu4, A. Lobo Salvia45,
A. Loi27, J. Lomba Castro46, I. Longstaff59, J.H. Lopes2, S. Lopez Solino46,
G.H. Lovell55, Y. Lu4, D. Lucchesi28,l, S. Luchuk39, M. Lucio Martinez32, V.
Lukashenko32,52, Y. Luo3, A. Lupato62, E. Luppi21,f, O. Lupton56, A.
Lusiani29,m, X. Lyu6, L. Ma4, R. Ma6, S. Maccolini20,d, F. Machefert11, F.
Maciuc37, V. Macko49, P. Mackowiak15, S. Maddrell-Mander54, O. Madejczyk34,
L.R. Madhan Mohan54, O. Maev38, A. Maevskiy82, D. Maisuzenko38, M.W.
Majewski34, J.J. Malczewski35, S. Malde63, B. Malecki48, A. Malinin81, T.
Maltsev43,v, H. Malygina17, G. Manca27,e, G. Mancinelli10, D. Manuzzi20,d, D.
Marangotto25,i, J. Maratas9,s, J.F. Marchand8, U. Marconi20, S. Mariani22,g,
C. Marin Benito48, M. Marinangeli49, J. Marks17, A.M. Marshall54, P.J.
Marshall60, G. Martellotti30, L. Martinazzoli48,j, M. Martinelli26,j, D.
Martinez Santos46, F. Martinez Vidal47, A. Massafferri1, M. Materok14, R.
Matev48, A. Mathad50, Z. Mathe48, V. Matiunin41, C. Matteuzzi26, K.R.
Mattioli86, A. Mauri32, E. Maurice12, J. Mauricio45, M. Mazurek48, M.
McCann61, L. Mcconnell18, T.H. Mcgrath62, N.T. Mchugh59, A. McNab62, R.
McNulty18, J.V. Mead60, B. Meadows65, G. Meier15, N. Meinert76, D.
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Mikhasenko48, D.A. Milanes74, E. Millard56, M. Milovanovic48, M.-N. Minard8,
A. Minotti21, L. Minzoni21,f, S.E. Mitchell58, B. Mitreska62, D.S. Mitzel48,
A. Mödden 15, R.A. Mohammed63, R.D. Moise61, T. Mombächer46, I.A. Monroy74, S.
Monteil9, M. Morandin28, G. Morello23, M.J. Morello29,m, J. Moron34, A.B.
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D. Müller48, K. Müller50, C.H. Murphy63, D. Murray62, P. Muzzetto27,48, P.
Naik54, T. Nakada49, R. Nandakumar57, T. Nanut49, I. Nasteva2, M. Needham58,
I. Neri21, N. Neri25,i, S. Neubert75, N. Neufeld48, R. Newcombe61, T.D.
Nguyen49, C. Nguyen-Mau49,x, E.M. Niel11, S. Nieswand14, N. Nikitin40, N.S.
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Oeser14, D.P. O’Hanlon54, S. Okamura21, R. Oldeman27,e, M.E. Olivares68,
C.J.G. Onderwater79, R.H. O’neil58, A. Ossowska35, J.M. Otalora Goicochea2, T.
Ovsiannikova41, P. Owen50, A. Oyanguren47, K.O. Padeken75, B. Pagare56, P.R.
Pais48, T. Pajero63, A. Palano19, M. Palutan23, Y. Pan62, G. Panshin84, A.
Papanestis57, M. Pappagallo19,c, L.L. Pappalardo21,f, C. Pappenheimer65, W.
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Patel61, C. Patrignani20,d, C.J. Pawley80, A. Pearce48, A. Pellegrino32, M.
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Petrucci58, M. Petruzzo25, T.T.H. Pham68, A. Philippov42, L. Pica29,m, M.
Piccini78, B. Pietrzyk8, G. Pietrzyk49, M. Pili63, D. Pinci30, F. Pisani48, M.
Pizzichemi26,48,j, Resmi P.K10, V. Placinta37, J. Plews53, M. Plo Casasus46,
F. Polci13, M. Poli Lener23, M. Poliakova68, A. Poluektov10, N. Polukhina83,u,
I. Polyakov68, E. Polycarpo2, S. Ponce48, D. Popov6,48, S. Popov42, S.
Poslavskii44, K. Prasanth35, L. Promberger48, C. Prouve46, V. Pugatch52, V.
Puill11, H. Pullen63, G. Punzi29,n, H. Qi3, W. Qian6, J. Qin6, N. Qin3, R.
Quagliani13, B. Quintana8, N.V. Raab18, R.I. Rabadan Trejo10, B. Rachwal34,
J.H. Rademacker54, M. Rama29, M. Ramos Pernas56, M.S. Rangel2, F.
Ratnikov42,82, G. Raven33, M. Reboud8, F. Redi49, F. Reiss62, C. Remon
Alepuz47, Z. Ren3, V. Renaudin63, R. Ribatti29, S. Ricciardi57, K. Rinnert60,
P. Robbe11, G. Robertson58, A.B. Rodrigues49, E. Rodrigues60, J.A. Rodriguez
Lopez74, E.R.R. Rodriguez Rodriguez46, A. Rollings63, P. Roloff48, V.
Romanovskiy44, M. Romero Lamas46, A. Romero Vidal46, J.D. Roth86, M.
Rotondo23, M.S. Rudolph68, T. Ruf48, R.A. Ruiz Fernandez46, J. Ruiz Vidal47,
A. Ryzhikov82, J. Ryzka34, J.J. Saborido Silva46, N. Sagidova38, N. Sahoo56,
B. Saitta27,e, M. Salomoni48, C. Sanchez Gras32, R. Santacesaria30, C.
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Savrina41,40, H. Sazak9, L.G. Scantlebury Smead63, A. Scarabotto13, S.
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Silva Coutinho50, G. Simi28, S. Simone19,c, N. Skidmore62, T. Skwarnicki68,
M.W. Slater53, I. Slazyk21,f, J.C. Smallwood63, J.G. Smeaton55, A. Smetkina41,
E. Smith50, M. Smith61, A. Snoch32, M. Soares20, L. Soares Lavra9, M.D.
Sokoloff65, F.J.P. Soler59, A. Solovev38, I. Solovyev38, F.L. Souza De
Almeida2, B. Souza De Paula2, B. Spaan15, E. Spadaro Norella25, P. Spradlin59,
F. Stagni48, M. Stahl65, S. Stahl48, S. Stanislaus63, O. Steinkamp50,83, O.
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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
4Institute Of High Energy Physics (IHEP), Beijing, China
5School of Physics State Key Laboratory of Nuclear Physics and Technology,
Peking University, Beijing, China
6University of Chinese Academy of Sciences, Beijing, China
7Institute of Particle Physics, Central China Normal University, Wuhan, Hubei,
China
8Univ. Savoie Mont Blanc, CNRS, IN2P3-LAPP, Annecy, France
9Université Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France
10Aix Marseille Univ, CNRS/IN2P3, CPPM, Marseille, France
11Université Paris-Saclay, CNRS/IN2P3, IJCLab, Orsay, France
12Laboratoire Leprince-Ringuet, CNRS/IN2P3, Ecole Polytechnique, Institut
Polytechnique de Paris, Palaiseau, France
13LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3,
Paris, France
14I. Physikalisches Institut, RWTH Aachen University, Aachen, Germany
15Fakultät Physik, Technische Universität Dortmund, Dortmund, Germany
16Max-Planck-Institut für Kernphysik (MPIK), Heidelberg, Germany
17Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg,
Germany
18School of Physics, University College Dublin, Dublin, Ireland
19INFN Sezione di Bari, Bari, Italy
20INFN Sezione di Bologna, Bologna, Italy
21INFN Sezione di Ferrara, Ferrara, Italy
22INFN Sezione di Firenze, Firenze, Italy
23INFN Laboratori Nazionali di Frascati, Frascati, Italy
24INFN Sezione di Genova, Genova, Italy
25INFN Sezione di Milano, Milano, Italy
26INFN Sezione di Milano-Bicocca, Milano, Italy
27INFN Sezione di Cagliari, Monserrato, Italy
28Universita degli Studi di Padova, Universita e INFN, Padova, Padova, Italy
29INFN Sezione di Pisa, Pisa, Italy
30INFN Sezione di Roma La Sapienza, Roma, Italy
31INFN Sezione di Roma Tor Vergata, Roma, Italy
32Nikhef National Institute for Subatomic Physics, Amsterdam, Netherlands
33Nikhef National Institute for Subatomic Physics and VU University Amsterdam,
Amsterdam, Netherlands
34AGH - University of Science and Technology, Faculty of Physics and Applied
Computer Science, Kraków, Poland
35Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of
Sciences, Kraków, Poland
36National Center for Nuclear Research (NCBJ), Warsaw, Poland
37Horia Hulubei National Institute of Physics and Nuclear Engineering,
Bucharest-Magurele, Romania
38Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI),
Gatchina, Russia
39Institute for Nuclear Research of the Russian Academy of Sciences (INR RAS),
Moscow, Russia
40Institute of Nuclear Physics, Moscow State University (SINP MSU), Moscow,
Russia
41Institute of Theoretical and Experimental Physics NRC Kurchatov Institute
(ITEP NRC KI), Moscow, Russia
42Yandex School of Data Analysis, Moscow, Russia
43Budker Institute of Nuclear Physics (SB RAS), Novosibirsk, Russia
44Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI),
Protvino, Russia, Protvino, Russia
45ICCUB, Universitat de Barcelona, Barcelona, Spain
46Instituto Galego de Física de Altas Enerxías (IGFAE), Universidade de
Santiago de Compostela, Santiago de Compostela, Spain
47Instituto de Fisica Corpuscular, Centro Mixto Universidad de Valencia -
CSIC, Valencia, Spain
48European Organization for Nuclear Research (CERN), Geneva, Switzerland
49Institute of Physics, Ecole Polytechnique Fédérale de Lausanne (EPFL),
Lausanne, Switzerland
50Physik-Institut, Universität Zürich, Zürich, Switzerland
51NSC Kharkiv Institute of Physics and Technology (NSC KIPT), Kharkiv, Ukraine
52Institute for Nuclear Research of the National Academy of Sciences (KINR),
Kyiv, Ukraine
53University of Birmingham, Birmingham, United Kingdom
54H.H. Wills Physics Laboratory, University of Bristol, Bristol, United
Kingdom
55Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom
56Department of Physics, University of Warwick, Coventry, United Kingdom
57STFC Rutherford Appleton Laboratory, Didcot, United Kingdom
58School of Physics and Astronomy, University of Edinburgh, Edinburgh, United
Kingdom
59School of Physics and Astronomy, University of Glasgow, Glasgow, United
Kingdom
60Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom
61Imperial College London, London, United Kingdom
62Department of Physics and Astronomy, University of Manchester, Manchester,
United Kingdom
63Department of Physics, University of Oxford, Oxford, United Kingdom
64Massachusetts Institute of Technology, Cambridge, MA, United States
65University of Cincinnati, Cincinnati, OH, United States
66University of Maryland, College Park, MD, United States
67Los Alamos National Laboratory (LANL), Los Alamos, United States
68Syracuse University, Syracuse, NY, United States
69School of Physics and Astronomy, Monash University, Melbourne, Australia,
associated to 56
70Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Rio de
Janeiro, Brazil, associated to 2
71Physics and Micro Electronic College, Hunan University, Changsha City,
China, associated to 7
72Guangdong Provincial Key Laboratory of Nuclear Science, Guangdong-Hong Kong
Joint Laboratory of Quantum Matter, Institute of Quantum Matter, South China
Normal University, Guangzhou, China, associated to 3
73School of Physics and Technology, Wuhan University, Wuhan, China, associated
to 3
74Departamento de Fisica , Universidad Nacional de Colombia, Bogota, Colombia,
associated to 13
75Universität Bonn - Helmholtz-Institut für Strahlen und Kernphysik, Bonn,
Germany, associated to 17
76Institut für Physik, Universität Rostock, Rostock, Germany, associated to 17
77Eotvos Lorand University, Budapest, Hungary, associated to 48
78INFN Sezione di Perugia, Perugia, Italy, associated to 21
79Van Swinderen Institute, University of Groningen, Groningen, Netherlands,
associated to 32
80Universiteit Maastricht, Maastricht, Netherlands, associated to 32
81National Research Centre Kurchatov Institute, Moscow, Russia, associated to
41
82National Research University Higher School of Economics, Moscow, Russia,
associated to 42
83National University of Science and Technology “MISIS”, Moscow, Russia,
associated to 41
84National Research Tomsk Polytechnic University, Tomsk, Russia, associated to
41
85DS4DS, La Salle, Universitat Ramon Llull, Barcelona, Spain, associated to 45
86University of Michigan, Ann Arbor, United States, associated to 68

aUniversidade Federal do Triângulo Mineiro (UFTM), Uberaba-MG, Brazil
bHangzhou Institute for Advanced Study, UCAS, Hangzhou, China
cUniversità di Bari, Bari, Italy
dUniversità di Bologna, Bologna, Italy
eUniversità di Cagliari, Cagliari, Italy
fUniversità di Ferrara, Ferrara, Italy
gUniversità di Firenze, Firenze, Italy
hUniversità di Genova, Genova, Italy
iUniversità degli Studi di Milano, Milano, Italy
jUniversità di Milano Bicocca, Milano, Italy
kUniversità di Modena e Reggio Emilia, Modena, Italy
lUniversità di Padova, Padova, Italy
mScuola Normale Superiore, Pisa, Italy
nUniversità di Pisa, Pisa, Italy
oUniversità della Basilicata, Potenza, Italy
pUniversità di Roma Tor Vergata, Roma, Italy
qUniversità di Siena, Siena, Italy
rUniversità di Urbino, Urbino, Italy
sMSU - Iligan Institute of Technology (MSU-IIT), Iligan, Philippines
tAGH - University of Science and Technology, Faculty of Computer Science,
Electronics and Telecommunications, Kraków, Poland
uP.N. Lebedev Physical Institute, Russian Academy of Science (LPI RAS),
Moscow, Russia
vNovosibirsk State University, Novosibirsk, Russia
wDepartment of Physics and Astronomy, Uppsala University, Uppsala, Sweden
xHanoi University of Science, Hanoi, Vietnam