EUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH (CERN)

 CERN-PH-EP-2015-132 LHCb-PAPER-2015-022 September 8, 2015

First observation of top quark production in the forward region

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

Top quark production in the forward region in proton-proton collisions is
observed for the first time. The $W\\!+\\!b$ final state with $W\to\mu\nu$ is
reconstructed using muons with a transverse momentum, $p_{\rm T}$, larger than
25$\mathrm{\,Ge\kern-1.00006ptV}$ in the pseudorapidity range $2.0<\eta<4.5$.
The $b$ jets are required to have $50<\mbox{$p_{\rm
T}$}<100\mathrm{\,Ge\kern-1.00006ptV}$ and $2.2<\eta<4.2$, while the
transverse component of the sum of the muon and $b$-jet momenta must satisfy
$\mbox{$p_{\rm T}$}>20\mathrm{\,Ge\kern-1.00006ptV}$. The results are based on
data corresponding to integrated luminosities of 1.0 and $2.0\mbox{\,fb}^{-1}$
collected at center-of-mass energies of 7 and 8$\mathrm{\,Te\kern-1.00006ptV}$
by LHCb. The inclusive top quark production cross-sections in the fiducial
region are

$\displaystyle\sigma({\rm top})[7\mathrm{\,Te\kern-1.00006ptV}]$
$\displaystyle=$ $\displaystyle\\!239\pm 53\mathrm{\,(stat)}\pm
33\mathrm{\,(syst)}\pm 24\,({\rm theory})\mbox{\,fb}\,,$
$\displaystyle\sigma({\rm top})[8\mathrm{\,Te\kern-1.00006ptV}]$
$\displaystyle=$ $\displaystyle\\!289\pm 43\mathrm{\,(stat)}\pm
40\mathrm{\,(syst)}\pm 29\,({\rm theory})\mbox{\,fb}\,.$

These results, along with the observed differential yields and charge
asymmetries, are in agreement with next-to-leading order Standard Model
predictions.

Phys. Rev. Lett. 115 (2015) 112001

© CERN on behalf of the LHCb collaboration, license CC-BY-4.0.

The production of top quarks ($t$) from proton-proton ($pp$) collisions in the
forward region is of considerable experimental and theoretical interest. In
the Standard Model (SM), four processes make significant contributions to top
quark production: $t\bar{t}$ pair production; single top production via
processes mediated by a $W$ boson in the $t$-channel ($qb\to q^{\prime}t$) or
in the $s$-channel ($q\bar{q}^{\prime}\to t\bar{b}$); and single top produced
in association with a $W$ boson ($gb\to tW$). The initial-state $b$ quarks
arise from gluon splitting to $b\bar{b}$ pairs or from the intrinsic $b$ quark
content in the proton. Top quarks decay almost entirely via $t\to Wb$. The SM
predicts that about 75% of $t\to Wb$ decays in the forward region are due to
$t\bar{t}$ pair production. The remaining 25% are mostly due to $t$-channel
single-top production, with $s$-channel and associated single-top production
making percent-level contributions.

The enhancement at forward rapidities of $t\bar{t}$ production via $q\bar{q}$
and $qg$ scattering, relative to $gg$ fusion, can result in larger charge
asymmetries, which may be sensitive to physics beyond the SM [1, 2]. Forward
$t\bar{t}$ events can be used to constrain the gluon parton distribution
function (PDF) at large momentum fraction, resulting in reduced theoretical
uncertainty for many SM predictions [3]. Furthermore, both single-top and
$t\bar{t}$ cross-section measurements in the forward region will provide
important experimental tests of differential next-to-next-to-leading order
theoretical calculations as they become available [4].

This Letter reports the first observation of top quark production in the
forward region. The data used correspond to integrated luminosities of 1.0 and
$2.0\mbox{\,fb}^{-1}$ collected at center-of-mass energies of $\sqrt{s}=7$ and
8$\mathrm{\,Te\kern-1.00006ptV}$ in $pp$ collisions with the LHCb detector.
The $W$ bosons are reconstructed using the $W\to\mu\nu$ decay with muons
having a transverse momentum, $p_{\rm T}$, larger than
25$\mathrm{\,Ge\kern-1.00006ptV}$ ($c=1$ throughout this Letter) in the
pseudorapidity range $2.0<\eta<4.5$. The analysis is performed using jets
clustered with the anti-$k_{\rm T}$ algorithm [5] using a distance parameter
$R=0.5$. The jets are required to have $50<\mbox{$p_{\rm
T}$}<100\mathrm{\,Ge\kern-1.00006ptV}$ and $2.2<\eta<4.2$. The muon and jet
($j$) must be separated by $\Delta R(\mu,j)>0.5$, with $\Delta
R\equiv\sqrt{\Delta\eta^{2}+\Delta\phi^{2}}$. Here $\Delta\eta\,(\Delta\phi)$
is the difference in pseudorapidity (azimuthal angle) between the muon and jet
momenta. The transverse component of the sum of the muon and jet momenta must
satisfy $\mbox{$p_{\rm
T}$}(\mu+j)\equiv\left(\vec{p}(\mu)+\vec{p}(j)\right)_{\rm
T}>20\mathrm{\,Ge\kern-1.00006ptV}$.

The LHCb detector is a single-arm forward spectrometer covering the
pseudorapidity range $2<\eta<5$, designed for the study of particles
containing $\mathrm{b}$ or $\mathrm{c}$ quarks. It is described in detail in
Refs. [6, 7]. The trigger [8] 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. This analysis requires at
least one muon candidate that satisfies the trigger requirement of
$\mbox{$p_{\rm T}$}>10\mathrm{\,Ge\kern-1.00006ptV}$. Global event cuts
(GECs), which prevent high-occupancy events from dominating the processing
time of the software trigger, have an efficiency of about $90\%$ for $W+$jet
and top quark events.

Simulated $pp$ collisions are generated using Pythia [9, *Sjostrand:2007gs]
with an LHCb configuration [11]. Decays of hadronic particles are described by
EvtGen [12] in which final-state radiation is generated using Photos [13]. The
interaction of the generated particles with the detector, and its response,
are implemented using the Geant4 toolkit [14, *Agostinelli:2002hh] as
described in Ref.[16]. Further theory calculations are performed at next-to-
leading order (NLO) with MCFM [17] and the CT10 PDF set [18], and are cross-
checked using PowhegBox [19] with hadronization simulated by Pythia. The
theoretical uncertainty on the cross-section predictions is a combination of
PDF, scale, and strong-coupling ($\alpha_{s}$) uncertainties. The PDF and
scale uncertainties are evaluated following Refs. [18] and [20], respectively.
The $\alpha_{s}$ uncertainty is evaluated as the envelope obtained using
$\alpha_{s}(M_{Z})\in[0.117,0.118,0.119]$ in the theory calculations.

The event selection is the same as that in Ref.[21] but a reduced fiducial
region is used to enhance the top quark contribution relative to direct
$W\\!+\\!b$ production. The signature for $W+$jet events is an isolated
high-$p_{\rm T}$ muon and a well-separated jet originating from the same $pp$
interaction. Signal events are selected by requiring a high-$p_{\rm T}$ muon
candidate and at least one jet with $\Delta R(\mu,j)>0.5$. For each event, the
highest-$p_{\rm T}$ muon candidate that satisfies the trigger requirements is
selected, along with the highest-$p_{\rm T}$ jet from the same $pp$ collision.
The primary background to top quark production is direct $W\\!+\\!b$
production; however, $Z\\!+\\!b$ events, with one muon undetected in the decay
$Z\to\mu\mu$, and di-$b$-jet events also contribute to the $\mu\\!+\\!b$-jet
final state.

The anti-$k_{T}$ clustering algorithm is used as implemented in FastJet [22].
Information from all the detector subsystems is used to create charged and
neutral particle inputs to the jet-clustering algorithm using a particle flow
approach [23]. The reconstructed jets must fall within the pseudorapidity
range $2.2<\eta(j)<4.2$. The reduced $\eta(j)$ acceptance ensures nearly
uniform jet reconstruction and heavy-flavor tagging efficiencies. The momentum
of a reconstructed jet is corrected to obtain an unbiased estimate of the true
jet momentum. The correction factor, typically between 0.9 and 1.1, is
determined from simulation and depends on the jet $p_{\rm T}$ and $\eta$, the
fraction of the jet $p_{\rm T}$ measured with the tracking system, and the
number of $pp$ interactions in the event.

The high-$p_{\rm T}$ muon candidate is not removed from the anti-$k_{T}$
inputs and so is clustered into a jet. This jet, referred to as the muon jet
and denoted as $j_{\mu}$, is used to discriminate between $W+$jet and dijet
events [21]. No correction is applied to the momentum of the muon jet. The
requirement $\mbox{$p_{\rm T}$}(j_{\mu}+j)>20\mathrm{\,Ge\kern-1.00006ptV}$ is
made to suppress dijet backgrounds, which are well balanced in $p_{\rm T}$,
unlike $W+$jet events, where there is undetected energy from the neutrino.
Events with a second, oppositely charged, high-$p_{\rm T}$ muon candidate from
the same $pp$ collision are vetoed. However, when the dimuon invariant mass is
in the range $60<M(\mu^{+}\mu^{-})<120\mathrm{\,Ge\kern-1.00006ptV}$, such
events are selected as $Z(\mu\mu)+$jet candidates, which are used to determine
the $Z+$jet background.

The jets are identified (tagged) as originating from the hadronization of a
$b$ or $c$ quark by the presence of a secondary vertex (SV) with $\Delta
R<0.5$ between the jet axis and the SV direction of flight, defined by the
vector from the $pp$ interaction point to the SV position. Two boosted
decision trees (BDTs) [24, 25], trained on the characteristics of the SV and
the jet, are used to separate heavy-flavor jets from $\rm light\mbox{-}parton$
jets, and to separate $b$ jets from $c$ jets. The two-dimensional distribution
of the BDT responses observed in data is fitted to obtain the SV-tagged $b$,
$c$ and $\rm light\mbox{-}parton$ jet yields. The SV-tagger algorithm is
described in Ref. [26], where the heavy-flavor tagging efficiencies and $\rm
light\mbox{-}parton$ mistag probabilities are measured in data. The data
samples used in Ref. [26] are too small to validate the performance of the SV-
tagger algorithm in the $\mbox{$p_{\rm
T}$}(j)>100\mathrm{\,Ge\kern-1.00006ptV}$ region. Furthermore, the mistag
probability of $\rm light\mbox{-}parton$ jets increases with jet $p_{\rm T}$.
Therefore, only jets with $\mbox{$p_{\rm
T}$}<100\mathrm{\,Ge\kern-1.00006ptV}$ are considered in the fiducial region,
which according to simulation retains about 80% of all top quark events.

Inclusive $W+$jet production, i.e. where no SV-tag requirement is made on the
jet, is only contaminated at the percent level by processes other than direct
$W+$jet production. Therefore, $W+$jet production is used to validate both the
theory predictions and the modeling of the detector response. Furthermore, the
SM prediction for $\sigma(Wb)/\sigma(Wj)$ has a smaller relative uncertainty
than $\sigma(Wb)$ alone, since the theory uncertainties partially cancel in
the ratio. The analysis strategy is to first measure the $W+$jet yields, and
then to obtain predictions for the yields of direct $W\\!+\\!b$ production
using the prediction for $\sigma(Wb)/\sigma(Wj)$. To an excellent
approximation, many experimental effects, e.g. the muon reconstruction
efficiency, are expected to be the same for both samples and do not need to be
considered in the direct $W\\!+\\!b$ yield prediction.

The $W+$jet yield is determined by performing a fit to the $\mbox{$p_{\rm
T}$}(\mu)/\mbox{$p_{\rm T}$}(j_{\mu})$ distribution with templates, histograms
obtained from data, as described in Ref. [21]. The $Z+$jet contribution is
fixed from the fully reconstructed $Z(\mu\mu)+$jet yield, where the
probability for one of the muons to escape detection is obtained using
simulation. The contributions of $b$, $c$, and light-parton jets are each free
to vary in the fit. Figure 1 shows the fit for all candidates in the data
sample. Such a fit is performed for each muon charge separately in bins of
$\mbox{$p_{\rm T}$}(\mu+j)$; the differential $W+$jet yield and charge
asymmetry, defined as
$[\sigma(W^{+}j)-\sigma(W^{-}j)]/[\sigma(W^{+}j)+\sigma(W^{-}j)]$, are given
in Fig. 2.

Figure 1: Distribution of $\mbox{$p_{\rm T}$}(\mu)/\mbox{$p_{\rm
T}$}(j_{\mu})$ with fit overlaid for all $W+$jet candidates.

Figure 2: Results for the inclusive $W+$jet yield (left) and charge asymmetry
(right) versus $\mbox{$p_{\rm T}$}(\mu+j)$ compared to SM predictions at NLO
obtained using MCFM. The data error bars are smaller than the marker size, the
SM uncertainties are highly correlated across $\mbox{$p_{\rm T}$}(\mu+j)$
bins.

To compare the data to theory predictions, the detector response must be taken
into account. All significant aspects of the detector response are determined
using data-driven techniques. The muon trigger, reconstruction, and selection
efficiencies are determined using $Z\to\mu\mu$ events [27, 23]. The GEC
efficiency is obtained following Ref. [23]: an alternative dimuon trigger
requirement, which requires a looser GEC, is used to determine the fraction of
events that are rejected. Contamination from $W\to\tau\to\mu$ decays is
estimated to be 2.5% using both simulated $W+$jet events and inclusive $W$
data samples [28]. The fraction of muons that migrate out of the fiducial
region due to final-state radiation is about 1.5% [28].

Migration of events in jet $p_{\rm T}$ due to the detector response is studied
with a data sample enriched in $b$ jets using SV tagging. The $\mbox{$p_{\rm
T}$}({\rm SV})/\mbox{$p_{\rm T}$}(j)$ distribution observed in data is
compared to templates obtained from simulation in bins of jet $p_{\rm T}$. The
resolution and scale for each jet $p_{\rm T}$ bin are varied in simulation to
find the best description of the data and to construct a detector response
matrix. Figure 2 shows that the SM predictions, obtained with all detector
response effects applied, agree with the inclusive $W+$jet data.

The yields of $W\\!+\\!c$ and $W\\!+\\!b$, which includes $t\to Wb$ decays,
are determined using the subset of candidates with an SV-tagged jet and binned
according to $\mbox{$p_{\rm T}$}(\mu)/\mbox{$p_{\rm T}$}(j_{\mu})$. In each
$\mbox{$p_{\rm T}$}(\mu)/\mbox{$p_{\rm T}$}(j_{\mu})$ bin, the two-dimensional
SV-tagger BDT-response distributions are fitted to determine the yields of
$c$-tagged and $b$-tagged jets, which are used to form the $\mbox{$p_{\rm
T}$}(\mu)/\mbox{$p_{\rm T}$}(j_{\mu})$ distributions for candidates with
$c$-tagged and $b$-tagged jets. These $\mbox{$p_{\rm T}$}(\mu)/\mbox{$p_{\rm
T}$}(j_{\mu})$ distributions are fitted to determine the SV-tagged $W\\!+\\!c$
and $W\\!+\\!b$ yields.

A fit to the $\mbox{$p_{\rm T}$}(\mu)/\mbox{$p_{\rm T}$}(j_{\mu})$
distribution built from the $c$-tagged jets from the full data sample is
provided as supplemental material to this Letter [29]. Figure 3 shows that the
$W\\!+\\!c$ yield versus $\mbox{$p_{\rm T}$}(\mu+c)$ agrees with the SM
prediction. Since the $W\\!+\\!c$ final state does not have any significant
contributions from diboson or top quark production in the SM, this comparison
validates the analysis procedures.

Figure 3: Results for $W\\!+\\!c$ compared to SM predictions at NLO obtained
using MCFM.

Figure 4 shows a fit to the $\mbox{$p_{\rm T}$}(\mu)/\mbox{$p_{\rm
T}$}(j_{\mu})$ distribution built from the $b$-tagged jets from the full data
sample. For $\mbox{$p_{\rm T}$}(\mu)/\mbox{$p_{\rm T}$}(j_{\mu})>0.9$ the data
are dominantly from $W$ decays. Figure 5 shows the yield and charge asymmetry
distributions obtained as a function of $\mbox{$p_{\rm T}$}(\mu+b)$. The
direct $W\\!+\\!b$ prediction is determined by scaling the inclusive $W+$jet
distribution observed in data by the SM prediction for $\sigma(Wb)/\sigma(Wj)$
and by the $b$-tagging efficiency measured in data [26]. As can be seen, the
data cannot be described by the expected direct $W\\!+\\!b$ contribution
alone. The observed yield is about three times larger than the SM prediction
without a top quark contribution, while the SM prediction including both
$t\bar{t}$ and single-top production does describe the data well.

Figure 4: Distribution of $\mbox{$p_{\rm T}$}(\mu)/\mbox{$p_{\rm
T}$}(j_{\mu})$ with fit overlaid for all $W\\!+\\!b$ candidates.

In Ref. [21], $W\\!+b$ is studied in a larger fiducial region ($\mbox{$p_{\rm
T}$}(\mu)>20\mathrm{\,Ge\kern-1.00006ptV},\mbox{$p_{\rm
T}$}(j)>20\mathrm{\,Ge\kern-1.00006ptV}$), where the top quark contribution is
expected to be about half as large as that of direct $W\\!+b$ production. The
ratio $[\sigma(Wb)\\!+\\!\sigma({\rm top})]/\sigma(Wj)$ is measured in the
larger fiducial region to be $1.17\pm 0.13\mathrm{\,(stat)}\pm
0.18\mathrm{\,(syst)}$% at $\sqrt{s}=7$$\mathrm{\,Te\kern-1.00006ptV}$ and
$1.29\pm 0.08\mathrm{\,(stat)}\pm 0.19\mathrm{\,(syst)}$% at
$\sqrt{s}=8$$\mathrm{\,Te\kern-1.00006ptV}$. These results agree with SM
predictions, that include top quark production, of $1.23\pm 0.24\%$ and
$1.38\pm 0.26\%$, respectively. This validates the direct $W\\!+\\!b$
prediction, since direct $W\\!+\\!b$ production is the dominant contribution
to the larger fiducial region.

Figure 5: Results for the $W\\!+\\!b$ yield (left) and charge asymmetry
(right) versus $\mbox{$p_{\rm T}$}(\mu+b)$ compared to SM predictions obtained
at NLO using MCFM.

Various sources of systematic uncertainties are considered and summarized in
Table 1. The direct $W\\!+\\!b$ prediction is normalized using the observed
inclusive $W+$jet data yields. Therefore, most experimental systematic
uncertainties cancel to a good approximation.

Since the muon kinematic distributions in $W+$jet and $W\\!+\\!b$ are similar,
all muon-based uncertainties are negligible with the exception of the trigger
GEC efficiency. The data-driven GEC study discussed above shows that the
efficiencies are consistent for $W+$jet and $W\\!+\\!b$, with the statistical
precision of this study assigned as the systematic uncertainty. Mismodeling of
the $\mbox{$p_{\rm T}$}(\mu)/\mbox{$p_{\rm T}$}(j_{\mu})$ distributions
largely cancels, since this shifts the inclusive $W+$jet and $W\\!+\\!b$
final-state yields by the same amount, leaving the observed excess over the
expected direct $W\\!+\\!b$ yield unaffected. The one exception is possible
mismodeling of the dijet templates, since the flavor content of the dijet
background is not the same in the two samples. Variations of these templates
are considered and a relative uncertainty of 5% is assigned on the $W$ boson
yields.

The jet reconstruction efficiencies for heavy-flavor and light-parton jets in
simulation are found to be consistent within 2%, which is assigned as the
systematic uncertainty for flavor-dependencies in the jet-reconstruction
efficiency. The SV-tagger BDT templates used in this analysis are two-
dimensional histograms obtained from the data samples enriched in $b$ and $c$
jets used in Ref. [26]. Following Refs. [26, 21], a 5% uncertainty on the
$b$-tagged yields is assigned due to uncertainty in these templates. The
precision of the $b$-tagging efficiency measurement (10%) in data [26] is
assigned as an additional uncertainty.

Table 1:  Relative systematic uncertainties. The symbol $\dagger$ denotes an uncertainty that only applies to the cross-section measurement and not the significance determination. Only the luminosity uncertainty depends on $\sqrt{s}$: 2% at 7 TeV and 1% at 8 TeV. source | uncertainty
---|---
GEC | 2%
$\mbox{$p_{\rm T}$}(\mu)/\mbox{$p_{\rm T}$}(j_{\mu})$ templates | 5%
jet reconstruction | 2%
SV-tag BDT templates | 5%
$b$-tag efficiency | 10%
trigger & $\mu$ selection | $2\%^{\dagger}$
jet energy | $5\%^{\dagger}$
$W\to\tau\to\mu$ | $1\%^{\dagger}$
luminosity | 1–2%†
Total | 14%
Theory | 10%

To determine the statistical significance of the top quark contribution, a
binned profile likelihood test is performed. The top quark distribution and
charge asymmetry versus $\mbox{$p_{\rm T}$}(\mu+b)$ are obtained from the SM
predictions. The total top quark yield is allowed to vary freely. Systematic
uncertainties, both theoretical and experimental, are handled as Gaussian
constraints. The profile likelihood technique is used to compare the SM
hypotheses with and without a top quark contribution. The significance
obtained using Wilks theorem [30] is $5.4\sigma$, confirming the observation
of top quark production in the forward region.

The yield and charge asymmetry distributions versus $\mbox{$p_{\rm
T}$}(\mu+b)$ observed at $\sqrt{s}=7$ and 8$\mathrm{\,Te\kern-1.00006ptV}$ are
each consistent with the SM predictions. The excess of the observed yield
relative to the direct $W\\!+\\!b$ prediction at each $\sqrt{s}$ is attributed
to top quark production, and used to measure the cross-sections. Some
additional systematic uncertainties that apply to the cross-section
measurements do not factor into the significance determination. The
uncertainties due to the muon trigger, reconstruction, and selection
efficiencies are taken from the data-driven studies of Refs. [27, 23]. The
uncertainty due to the jet energy determination is obtained from the data-
driven study used to obtain the detector response matrix. The uncertainty due
to $W\to\tau\to\mu$ contamination is taken as the difference between the
contamination in simulation versus that of a data-driven study of inclusive
$W\to\mu\nu$ production [28]. The luminosity uncertainty is described in
detail in Ref. [31]. The total systematic uncertainty is obtained by adding
the individual contributions in quadrature.

The resulting inclusive top production cross-sections in the fiducial region
defined by $\mbox{$p_{\rm T}$}(\mu)>25\mathrm{\,Ge\kern-1.00006ptV}$,
$2.0<\eta(\mu)<4.5$, ${50<\mbox{$p_{\rm
T}$}(b)<100\mathrm{\,Ge\kern-1.00006ptV}}$, $2.2<\eta(b)<4.2$, $\Delta
R(\mu,b)>0.5$, and $\mbox{$p_{\rm
T}$}(\mu+b)>20\mathrm{\,Ge\kern-1.00006ptV}$, are

$\displaystyle\sigma({\rm top})[7\mathrm{\,Te\kern-1.00006ptV}]$
$\displaystyle=$ $\displaystyle\\!239\pm 53\mathrm{\,(stat)}\pm
33\mathrm{\,(syst)}\pm 24\,({\rm theory})\mbox{\,fb}\,,$
$\displaystyle\sigma({\rm top})[8\mathrm{\,Te\kern-1.00006ptV}]$
$\displaystyle=$ $\displaystyle\\!289\pm 43\mathrm{\,(stat)}\pm
40\mathrm{\,(syst)}\pm 29\,({\rm theory})\mbox{\,fb}\,.$

The systematic uncertainties are nearly 100% correlated between the two
measurements.

In summary, top quark production is observed for the first time in the forward
region. The cross-section results are in agreement with the SM predictions of
$180_{-41}^{+51}(312_{-68}^{+83})\mbox{\,fb}$ at
$7(8)\mathrm{\,Te\kern-1.00006ptV}$ obtained at NLO using MCFM. The
differential distributions of the yield and charge asymmetry are also
consistent with SM predictions.

## Acknowledgments

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); NSFC
(China); CNRS/IN2P3 (France); BMBF, DFG, HGF and MPG (Germany); INFN (Italy);
FOM and NWO (The Netherlands); MNiSW and NCN (Poland); MEN/IFA (Romania);
MinES and FANO (Russia); MinECo (Spain); SNSF and SER (Switzerland); NASU
(Ukraine); STFC (United Kingdom); NSF (USA). The Tier1 computing centres are
supported by IN2P3 (France), KIT and BMBF (Germany), INFN (Italy), NWO and
SURF (The Netherlands), PIC (Spain), GridPP (United Kingdom). We are indebted
to the communities behind the multiple open source software packages on which
we depend. We are also thankful for the computing resources and the access to
software R&D tools provided by Yandex LLC (Russia). Individual groups or
members have received support from EPLANET, Marie Skłodowska-Curie Actions and
ERC (European Union), Conseil général de Haute-Savoie, Labex ENIGMASS and
OCEVU, Région Auvergne (France), RFBR (Russia), XuntaGal and GENCAT (Spain),
Royal Society and Royal Commission for the Exhibition of 1851 (United
Kingdom).

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## Supplemental Material

Figure 6: Distribution of $p_{\rm T}(\mu)/p_{\rm T}(j_{\mu})$ with fit
overlaid for all $W\\!+\\!c$ candidates.

LHCb collaboration

R. Aaij38, B. Adeva37, M. Adinolfi46, A. Affolder52, Z. Ajaltouni5, S. Akar6,
J. Albrecht9, F. Alessio38, M. Alexander51, S. Ali41, G. Alkhazov30, P.
Alvarez Cartelle53, A.A. Alves Jr57, S. Amato2, S. Amerio22, Y. Amhis7, L.
An3, L. Anderlini17,g, J. Anderson40, M. Andreotti16,f, J.E. Andrews58, R.B.
Appleby54, O. Aquines Gutierrez10, F. Archilli38, P. d’Argent11, A.
Artamonov35, M. Artuso59, E. Aslanides6, G. Auriemma25,n, M. Baalouch5, S.
Bachmann11, J.J. Back48, A. Badalov36, C. Baesso60, W. Baldini16,38, R.J.
Barlow54, C. Barschel38, S. Barsuk7, W. Barter38, V. Batozskaya28, V.
Battista39, A. Bay39, L. Beaucourt4, J. Beddow51, F. Bedeschi23, I. Bediaga1,
L.J. Bel41, I. Belyaev31, E. Ben-Haim8, G. Bencivenni18, S. Benson38, J.
Benton46, A. Berezhnoy32, R. Bernet40, A. Bertolin22, M.-O. Bettler38, M. van
Beuzekom41, A. Bien11, S. Bifani45, T. Bird54, A. Birnkraut9, A. Bizzeti17,i,
T. Blake48, F. Blanc39, J. Blouw10, S. Blusk59, V. Bocci25, A. Bondar34, N.
Bondar30,38, W. Bonivento15, S. Borghi54, M. Borsato7, T.J.V. Bowcock52, E.
Bowen40, C. Bozzi16, S. Braun11, D. Brett54, M. Britsch10, T. Britton59, J.
Brodzicka54, N.H. Brook46, A. Bursche40, J. Buytaert38, S. Cadeddu15, R.
Calabrese16,f, M. Calvi20,k, M. Calvo Gomez36,p, P. Campana18, D. Campora
Perez38, L. Capriotti54, A. Carbone14,d, G. Carboni24,l, R. Cardinale19,j, A.
Cardini15, P. Carniti20, L. Carson50, K. Carvalho Akiba2,38, G. Casse52, L.
Cassina20,k, L. Castillo Garcia38, M. Cattaneo38, Ch. Cauet9, G. Cavallero19,
R. Cenci23,t, M. Charles8, Ph. Charpentier38, M. Chefdeville4, S. Chen54,
S.-F. Cheung55, N. Chiapolini40, M. Chrzaszcz40, X. Cid Vidal38, G.
Ciezarek41, P.E.L. Clarke50, M. Clemencic38, H.V. Cliff47, J. Closier38, V.
Coco38, J. Cogan6, E. Cogneras5, V. Cogoni15,e, L. Cojocariu29, G.
Collazuol22, P. Collins38, A. Comerma-Montells11, A. Contu15,38, A. Cook46, M.
Coombes46, S. Coquereau8, G. Corti38, M. Corvo16,f, B. Couturier38, G.A.
Cowan50, D.C. Craik48, A. Crocombe48, M. Cruz Torres60, S. Cunliffe53, R.
Currie53, C. D’Ambrosio38, J. Dalseno46, P.N.Y. David41, A. Davis57, K. De
Bruyn41, S. De Capua54, M. De Cian11, J.M. De Miranda1, L. De Paula2, W. De
Silva57, P. De Simone18, C.-T. Dean51, D. Decamp4, M. Deckenhoff9, L. Del
Buono8, N. Déléage4, M. Demmer9, D. Derkach55, O. Deschamps5, F. Dettori38, A.
Di Canto38, F. Di Ruscio24, H. Dijkstra38, S. Donleavy52, F. Dordei11, M.
Dorigo39, A. Dosil Suárez37, D. Dossett48, A. Dovbnya43, K. Dreimanis52, L.
Dufour41, G. Dujany54, F. Dupertuis39, P. Durante38, R. Dzhelyadin35, A.
Dziurda26, A. Dzyuba30, S. Easo49,38, U. Egede53, V. Egorychev31, S.
Eidelman34, S. Eisenhardt50, U. Eitschberger9, R. Ekelhof9, L. Eklund51, I. El
Rifai5, Ch. Elsasser40, S. Ely59, S. Esen11, H.M. Evans47, T. Evans55, A.
Falabella14, C. Färber11, C. Farinelli41, N. Farley45, S. Farry52, R. Fay52,
D. Ferguson50, V. Fernandez Albor37, F. Ferrari14, F. Ferreira Rodrigues1, M.
Ferro-Luzzi38, S. Filippov33, M. Fiore16,38,f, M. Fiorini16,f, M. Firlej27, C.
Fitzpatrick39, T. Fiutowski27, K. Fohl38, P. Fol53, M. Fontana10, F.
Fontanelli19,j, R. Forty38, O. Francisco2, M. Frank38, C. Frei38, M.
Frosini17, J. Fu21, E. Furfaro24,l, A. Gallas Torreira37, D. Galli14,d, S.
Gallorini22,38, S. Gambetta50, M. Gandelman2, P. Gandini55, Y. Gao3, J. García
Pardiñas37, J. Garofoli59, J. Garra Tico47, L. Garrido36, D. Gascon36, C.
Gaspar38, U. Gastaldi16, R. Gauld55, L. Gavardi9, G. Gazzoni5, A. Geraci21,v,
D. Gerick11, E. Gersabeck11, M. Gersabeck54, T. Gershon48, Ph. Ghez4, A.
Gianelle22, S. Gianì39, V. Gibson47, O. G. Girard39, L. Giubega29, V.V.
Gligorov38, C. Göbel60, D. Golubkov31, A. Golutvin53,31,38, A. Gomes1,a, C.
Gotti20,k, M. Grabalosa Gándara5, R. Graciani Diaz36, L.A. Granado Cardoso38,
E. Graugés36, E. Graverini40, G. Graziani17, A. Grecu29, E. Greening55, S.
Gregson47, P. Griffith45, L. Grillo11, O. Grünberg63, B. Gui59, E. Gushchin33,
Yu. Guz35,38, T. Gys38, T. Hadavizadeh55, C. Hadjivasiliou59, G. Haefeli39, C.
Haen38, S.C. Haines47, S. Hall53, B. Hamilton58, T. Hampson46, X. Han11, S.
Hansmann-Menzemer11, N. Harnew55, S.T. Harnew46, J. Harrison54, J. He38, T.
Head39, V. Heijne41, K. Hennessy52, P. Henrard5, L. Henry8, J.A. Hernando
Morata37, E. van Herwijnen38, M. Heß63, A. Hicheur2, D. Hill55, M. Hoballah5,
C. Hombach54, W. Hulsbergen41, T. Humair53, N. Hussain55, D. Hutchcroft52, D.
Hynds51, M. Idzik27, P. Ilten56, R. Jacobsson38, A. Jaeger11, J. Jalocha55, E.
Jans41, A. Jawahery58, F. Jing3, M. John55, D. Johnson38, C.R. Jones47, C.
Joram38, B. Jost38, N. Jurik59, S. Kandybei43, W. Kanso6, M. Karacson38, T.M.
Karbach38,†, S. Karodia51, M. Kelsey59, I.R. Kenyon45, M. Kenzie38, T.
Ketel42, B. Khanji20,38,k, C. Khurewathanakul39, S. Klaver54, K.
Klimaszewski28, O. Kochebina7, M. Kolpin11, I. Komarov39, R.F. Koopman42, P.
Koppenburg41,38, M. Korolev32, M. Kozeiha5, L. Kravchuk33, K. Kreplin11, M.
Kreps48, G. Krocker11, P. Krokovny34, F. Kruse9, W. Kucewicz26,o, M.
Kucharczyk26, V. Kudryavtsev34, A. K. Kuonen39, K. Kurek28, T.
Kvaratskheliya31, V.N. La Thi39, D. Lacarrere38, G. Lafferty54, A. Lai15, D.
Lambert50, R.W. Lambert42, G. Lanfranchi18, C. Langenbruch48, B. Langhans38,
T. Latham48, C. Lazzeroni45, R. Le Gac6, J. van Leerdam41, J.-P. Lees4, R.
Lefèvre5, A. Leflat32,38, J. Lefrançois7, O. Leroy6, T. Lesiak26, B.
Leverington11, Y. Li7, T. Likhomanenko65,64, M. Liles52, R. Lindner38, C.
Linn38, F. Lionetto40, B. Liu15, X. Liu3, D. Loh48, S. Lohn38, I. Longstaff51,
J.H. Lopes2, D. Lucchesi22,r, M. Lucio Martinez37, H. Luo50, A. Lupato22, E.
Luppi16,f, O. Lupton55, F. Machefert7, F. Maciuc29, O. Maev30, K. Maguire54,
S. Malde55, A. Malinin64, G. Manca7, G. Mancinelli6, P. Manning59, A.
Mapelli38, J. Maratas5, J.F. Marchand4, U. Marconi14, C. Marin Benito36, P.
Marino23,38,t, R. Märki39, J. Marks11, G. Martellotti25, M. Martin6, M.
Martinelli39, D. Martinez Santos42, F. Martinez Vidal66, D. Martins Tostes2,
A. Massafferri1, R. Matev38, A. Mathad48, Z. Mathe38, C. Matteuzzi20, K.
Matthieu11, A. Mauri40, B. Maurin39, A. Mazurov45, M. McCann53, J. McCarthy45,
A. McNab54, R. McNulty12, B. Meadows57, F. Meier9, M. Meissner11, D.
Melnychuk28, M. Merk41, D.A. Milanes62, M.-N. Minard4, D.S. Mitzel11, J.
Molina Rodriguez60, S. Monteil5, M. Morandin22, P. Morawski27, A. Mordà6, M.J.
Morello23,t, J. Moron27, A.B. Morris50, R. Mountain59, F. Muheim50, J.
Müller9, K. Müller40, V. Müller9, M. Mussini14, B. Muster39, P. Naik46, T.
Nakada39, R. Nandakumar49, A. Nandi55, I. Nasteva2, M. Needham50, N. Neri21,
S. Neubert11, N. Neufeld38, M. Neuner11, A.D. Nguyen39, T.D. Nguyen39, C.
Nguyen-Mau39,q, V. Niess5, R. Niet9, N. Nikitin32, T. Nikodem11, D. Ninci23,
A. Novoselov35, D.P. O’Hanlon48, A. Oblakowska-Mucha27, V. Obraztsov35, S.
Ogilvy51, O. Okhrimenko44, R. Oldeman15,e, C.J.G. Onderwater67, B. Osorio
Rodrigues1, J.M. Otalora Goicochea2, A. Otto38, P. Owen53, A. Oyanguren66, A.
Palano13,c, F. Palombo21,u, M. Palutan18, J. Panman38, A. Papanestis49, M.
Pappagallo51, L.L. Pappalardo16,f, C. Pappenheimer57, C. Parkes54, G.
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Pellegrino41, G. Penso25,m, M. Pepe Altarelli38, S. Perazzini14,d, P. Perret5,
L. Pescatore45, K. Petridis46, A. Petrolini19,j, M. Petruzzo21, E. Picatoste
Olloqui36, B. Pietrzyk4, T. Pilař48, D. Pinci25, A. Pistone19, A. Piucci11, S.
Playfer50, M. Plo Casasus37, T. Poikela38, F. Polci8, A. Poluektov48,34, I.
Polyakov31, E. Polycarpo2, A. Popov35, D. Popov10,38, B. Popovici29, C.
Potterat2, E. Price46, J.D. Price52, J. Prisciandaro39, A. Pritchard52, C.
Prouve46, V. Pugatch44, A. Puig Navarro39, G. Punzi23,s, W. Qian4, R.
Quagliani7,46, B. Rachwal26, J.H. Rademacker46, B. Rakotomiaramanana39, M.
Rama23, M.S. Rangel2, I. Raniuk43, N. Rauschmayr38, G. Raven42, F. Redi53, S.
Reichert54, M.M. Reid48, A.C. dos Reis1, S. Ricciardi49, S. Richards46, M.
Rihl38, K. Rinnert52, V. Rives Molina36, P. Robbe7,38, A.B. Rodrigues1, E.
Rodrigues54, J.A. Rodriguez Lopez62, P. Rodriguez Perez54, S. Roiser38, V.
Romanovsky35, A. Romero Vidal37, J. W. Ronayne12, M. Rotondo22, J. Rouvinet39,
T. Ruf38, H. Ruiz36, P. Ruiz Valls66, J.J. Saborido Silva37, N. Sagidova30, P.
Sail51, B. Saitta15,e, V. Salustino Guimaraes2, C. Sanchez Mayordomo66, B.
Sanmartin Sedes37, R. Santacesaria25, C. Santamarina Rios37, M. Santimaria18,
E. Santovetti24,l, A. Sarti18,m, C. Satriano25,n, A. Satta24, D.M. Saunders46,
D. Savrina31,32, M. Schiller38, H. Schindler38, M. Schlupp9, M. Schmelling10,
T. Schmelzer9, B. Schmidt38, O. Schneider39, A. Schopper38, M. Schubiger39,
M.-H. Schune7, R. Schwemmer38, B. Sciascia18, A. Sciubba25,m, A. Semennikov31,
I. Sepp53, N. Serra40, J. Serrano6, L. Sestini22, P. Seyfert20, M. Shapkin35,
I. Shapoval16,43,f, Y. Shcheglov30, T. Shears52, L. Shekhtman34, V.
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S. Zucchelli14.

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
4LAPP, Université Savoie Mont-Blanc, CNRS/IN2P3, Annecy-Le-Vieux, France
5Clermont Université, Université Blaise Pascal, CNRS/IN2P3, LPC, Clermont-
Ferrand, France
6CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France
7LAL, Université Paris-Sud, CNRS/IN2P3, Orsay, France
8LPNHE, Université Pierre et Marie Curie, Université Paris Diderot,
CNRS/IN2P3, Paris, France
9Fakultät Physik, Technische Universität Dortmund, Dortmund, Germany
10Max-Planck-Institut für Kernphysik (MPIK), Heidelberg, Germany
11Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg,
Germany
12School of Physics, University College Dublin, Dublin, Ireland
13Sezione INFN di Bari, Bari, Italy
14Sezione INFN di Bologna, Bologna, Italy
15Sezione INFN di Cagliari, Cagliari, Italy
16Sezione INFN di Ferrara, Ferrara, Italy
17Sezione INFN di Firenze, Firenze, Italy
18Laboratori Nazionali dell’INFN di Frascati, Frascati, Italy
19Sezione INFN di Genova, Genova, Italy
20Sezione INFN di Milano Bicocca, Milano, Italy
21Sezione INFN di Milano, Milano, Italy
22Sezione INFN di Padova, Padova, Italy
23Sezione INFN di Pisa, Pisa, Italy
24Sezione INFN di Roma Tor Vergata, Roma, Italy
25Sezione INFN di Roma La Sapienza, Roma, Italy
26Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of
Sciences, Kraków, Poland
27AGH - University of Science and Technology, Faculty of Physics and Applied
Computer Science, Kraków, Poland
28National Center for Nuclear Research (NCBJ), Warsaw, Poland
29Horia Hulubei National Institute of Physics and Nuclear Engineering,
Bucharest-Magurele, Romania
30Petersburg Nuclear Physics Institute (PNPI), Gatchina, Russia
31Institute of Theoretical and Experimental Physics (ITEP), Moscow, Russia
32Institute of Nuclear Physics, Moscow State University (SINP MSU), Moscow,
Russia
33Institute for Nuclear Research of the Russian Academy of Sciences (INR RAN),
Moscow, Russia
34Budker Institute of Nuclear Physics (SB RAS) and Novosibirsk State
University, Novosibirsk, Russia
35Institute for High Energy Physics (IHEP), Protvino, Russia
36Universitat de Barcelona, Barcelona, Spain
37Universidad de Santiago de Compostela, Santiago de Compostela, Spain
38European Organization for Nuclear Research (CERN), Geneva, Switzerland
39Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
40Physik-Institut, Universität Zürich, Zürich, Switzerland
41Nikhef National Institute for Subatomic Physics, Amsterdam, The Netherlands
42Nikhef National Institute for Subatomic Physics and VU University Amsterdam,
Amsterdam, The Netherlands
43NSC Kharkiv Institute of Physics and Technology (NSC KIPT), Kharkiv, Ukraine
44Institute for Nuclear Research of the National Academy of Sciences (KINR),
Kyiv, Ukraine
45University of Birmingham, Birmingham, United Kingdom
46H.H. Wills Physics Laboratory, University of Bristol, Bristol, United
Kingdom
47Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom
48Department of Physics, University of Warwick, Coventry, United Kingdom
49STFC Rutherford Appleton Laboratory, Didcot, United Kingdom
50School of Physics and Astronomy, University of Edinburgh, Edinburgh, United
Kingdom
51School of Physics and Astronomy, University of Glasgow, Glasgow, United
Kingdom
52Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom
53Imperial College London, London, United Kingdom
54School of Physics and Astronomy, University of Manchester, Manchester,
United Kingdom
55Department of Physics, University of Oxford, Oxford, United Kingdom
56Massachusetts Institute of Technology, Cambridge, MA, United States
57University of Cincinnati, Cincinnati, OH, United States
58University of Maryland, College Park, MD, United States
59Syracuse University, Syracuse, NY, United States
60Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Rio de
Janeiro, Brazil, associated to 2
61Institute of Particle Physics, Central China Normal University, Wuhan,
Hubei, China, associated to 3
62Departamento de Fisica , Universidad Nacional de Colombia, Bogota, Colombia,
associated to 8
63Institut für Physik, Universität Rostock, Rostock, Germany, associated to 11
64National Research Centre Kurchatov Institute, Moscow, Russia, associated to
31
65Yandex School of Data Analysis, Moscow, Russia, associated to 31
66Instituto de Fisica Corpuscular (IFIC), Universitat de Valencia-CSIC,
Valencia, Spain, associated to 36
67Van Swinderen Institute, University of Groningen, Groningen, The
Netherlands, associated to 41

aUniversidade Federal do Triângulo Mineiro (UFTM), Uberaba-MG, Brazil
bP.N. Lebedev Physical Institute, Russian Academy of Science (LPI RAS),
Moscow, Russia
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 Urbino, Urbino, Italy
iUniversità di Modena e Reggio Emilia, Modena, Italy
jUniversità di Genova, Genova, Italy
kUniversità di Milano Bicocca, Milano, Italy
lUniversità di Roma Tor Vergata, Roma, Italy
mUniversità di Roma La Sapienza, Roma, Italy
nUniversità della Basilicata, Potenza, Italy
oAGH - University of Science and Technology, Faculty of Computer Science,
Electronics and Telecommunications, Kraków, Poland
pLIFAELS, La Salle, Universitat Ramon Llull, Barcelona, Spain
qHanoi University of Science, Hanoi, Viet Nam
rUniversità di Padova, Padova, Italy
sUniversità di Pisa, Pisa, Italy
tScuola Normale Superiore, Pisa, Italy
uUniversità degli Studi di Milano, Milano, Italy
vPolitecnico di Milano, Milano, Italy
†Deceased