Measurement of meson resonance production in \(\pi ^+\) C interactions at SPS energies
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Abstract
We present measurements of \(\rho ^0\), \(\omega \) and K\(^{*0}\) spectra in \(\pi ^{} + \) C production interactions at 158 \(\text{ GeV }{/}\text{ c }\) and \(\rho ^0\) spectra at 350 \(\text{ GeV }{/}\text{ c }\) using the NA61/SHINE spectrometer at the CERN SPS. Spectra are presented as a function of the Feynman’s variable \(x_\text {F}\) in the range \(0< x_\text {F} < 1\) and \(0< x_\text {F} < 0.5\) for 158 and 350 \(\text{ GeV }{/}\text{ c }\) respectively. Furthermore, we show comparisons with previous measurements and predictions of several hadronic interaction models. These measurements are essential for a better understanding of hadronic shower development and for improving the modeling of cosmic ray air showers.
1 Introduction
When cosmic rays of high energy collide with the nuclei of the atmosphere, they initiate extensive air showers (EAS). Earth’s atmosphere then acts as a medium in which the particle shower evolves. It proceeds mainly through the production and interaction of secondary pions and kaons. Depending on the particle energy and density of the medium in which the shower evolves, secondary particles either decay or reinteract, producing further secondaries. Neutral pions have a special role. Instead of interacting hadronically, they immediately decay (\(c\bar{\tau }= 25\) nm) into two photons with a branching ratio of 99.9%, giving rise to an electromagnetic shower component. When only the primary particle energy is of interest, and all shower components are sampled, a detailed understanding of the energy transfer from the hadronic particles to the electromagnetic shower component is not needed. However, for other measurements of air shower properties this understanding is of central importance.
A complete measurement of an air shower is not possible and particles are typically sampled only in select positions at the ground level or the ionization energy deposited in the atmosphere is measured. Therefore, the interpretation of EAS data, and in particular the determination of the composition of cosmic rays, relies to a large extent on a correct modelling of hadronair interactions that occur during the shower development (see e.g. [1]). Experiments such as the Pierre Auger Observatory [2], IceTop [3], KASCADEGrande [4] or the Telescope Array [5] use models for the interpretation of measurements. However, there is mounting evidence that current hadronic interaction models do not provide a satisfactory description of the muon production in air showers and that there is a deficit in the number of muons predicted at the ground level by the models when compared to the air shower measurements (see Refs. [6, 7, 8, 9, 10]).
To understand the possible cause of this deficit it is instructive to study the air shower development in a very simplified model [11] in which mesons are produced in subsequent interactions of the air cascade until the average meson energy is low enough such that its decay length is smaller than its interaction length. In each interaction a fraction \(f_\mathrm {em}\) of the shower energy is transferred to the electromagnetic shower component via the production and decay of neutral mesons. After n interactions the energy available in the hadronic part of the shower to produce muons is therefore \(E_\mathrm {had} = E_0 \, (1f_\mathrm {em})^n\), where \(E_0\) denotes the primary energy of the cosmic ray initiating the air shower. In the standard simplified picture, one third of the interactions products of charged pions with air are neutral mesons. Assuming a typical value of \(n=7\) for the number of interactions needed to reach particle energies low enough that the charged mesons decay to muons rather than interact again, the simplistic model gives \(E_\mathrm {had} / E_0 \simeq 6\%\). One way to increase this number is to account for the production of baryons and antibaryons to decrease \(f_\mathrm {em}\) [12]. Another possibilty has been recently identified [13, 14] by noting that accelerator data on \(\pi ^+ + \text {p}\) interactions [15, 16, 17] indicate that most of the neutral mesons produced in the forward direction are not \(\pi ^0\)s but \(\rho ^0\) mesons. With \(\rho ^0\) decaying into \(\pi ^+\,\pi ^\) this would imply that the energy of the leading particle is not transferred to the electromagnetic shower component as it would be in the case of neutral pions and corresponingly \(f_\mathrm {em}\) is decreased leading to more muons at ground level.
Given these considerations it is evident that the modeling of air showers depends crucially on our knowledge of pion interactions with air. It can be shown (see e.g. [18, 19]) that the relevant energies for the interactions in the last stage of the air shower development are in the range from 10 to \(10^3\) \(\text{ GeV }\). This range is accessible to fixedtarget experiments with charged pion beams.
A large body of data is available at these energies for protonnucleus interactions (e.g. [20, 21, 22, 23, 24]), but only a very limited amount of data exists for pion or kaon beams. A number of dedicated measurements for airshower simulations have been performed by studying particle production on light nuclei at beam momenta up to 12 \(\text{ GeV }{/}\text{ c }\) (see, e.g. Refs. [25, 26]). Unfortunately, at higher energies, there are no comprehensive and precise particle production measurements of \(\pi \) interactions with light nuclei of masses similar to air. Earlier measurements were either limited to a small acceptance in momentum space (e.g. Ref. [27]) or protons as target [15, 16, 17, 28], or did not discriminate between the different secondaries [29].
To address the lack of suitable data for the tuning of hadronic interaction models used in air shower simulations, NA61/SHINE [30] collected new data with negatively charged pion beams at 158 and 350 \(\text{ GeV }{/}\text{ c }\) on a thin carbon target. Preliminary spectra of unidentified hadrons and identified pions were previously derived from this data set [31, 32, 33] and in this paper, we present the results of the measurement of \(\rho ^0\), \(\omega \) and K\(^{*0}\) spectra in \(\pi ^{}\) + C interactions at 158 and 350 \(\text{ GeV }{/}\text{ c }\).
It is worthwhile noting that the measurements presented in this paper will not only be useful for interpretation of cosmicray calorimetry in air, but can also be beneficial for the understanding of hadronic calorimeters used in highenergy laboratory experiments. Hadronic interaction models used for calorimeter simulations are mostly tuned to and validated with the overall calorimeter response from testbeam data (see e.g. [34, 35, 36]). A tuning of these models to the data presented here will improve the description of the energy transfer from the hadronic to the electromagnetic shower component for individual interactions inside the calorimeter and thus increase the predictive power of the calorimeter simulation.
2 Experimental setup, data processing and simulation
The NA61/SHINE apparatus is a wideacceptance hadron spectrometer at the CERN SPS on the H2 beam line of the CERN North Area. A detailed description of the experiment is presented in Ref. [30]. Only features relevant for the \(\pi ^\) + C data are briefly mentioned here. Numerous components of the NA61/SHINE setup were inherited from its predecessor, the NA49 experiment [37]. An overview of the setup used for data taking on \(\pi ^\) + C interactions in 2009 is shown in Fig. 1.
The magnet current setting for data taking at 158 and 350 \(\text{ GeV }{/}\text{ c }\) corresponds to 1.5 T in the first and 1.1 T, in the second magnet. It results in a precise measurement of the particle momenta p with a resolution of \(\sigma (p)/p^2\approx (0.3{}7)\times 10^{4}\,\mathrm {(GeV/c)}^{1}\).
Two scintillation counters, S1 and S2, together with the three veto counters V0, V1 and V1\(^\text {p}\), define the beam upstream of the target. The setup of these counters can be seen in Fig. 1a for the 158 \(\text{ GeV }{/}\text{ c }\) run. The S1 counter also provides the start time for all timing measurements.
The 158 and 350 \(\text{ GeV }{/}\text{ c }\) secondary hadron beam was produced by 400 \(\text{ GeV }{/}\text{ c }\) primary protons impinging on a 10 cm long beryllium target. Negatively charged hadrons (\(\text {h}^\)) produced at the target are transported downstream to the NA61/SHINE experiment by the H2 beamline, in which collimation and momentum selection occur. The beam particles, mostly \(\pi ^\) mesons, are identified by a differential ringimaging Cherenkov detector CEDAR [38]. The fraction of pions is \({\approx }95\%\) for 158 \(\text{ GeV }{/}\text{ c }\) and \({\approx }100\%\) for 350 \(\text{ GeV }{/}\text{ c }\) (see Fig. 2). The CEDAR signal is recorded during data taking and then used as an offline selection cut (see Sect. 3.1). The beam particles are selected by the beam trigger, T\(_\text {beam}\), then defined by the coincidence \(\text {S1}\wedge \text {S2}\wedge \overline{\text {V0}} \wedge \overline{\text {V1}}\wedge \overline{\text {V1}^\text {p}}\). The interaction trigger (\(\text {T}_\text {int} = \text {T}_\text {beam} \wedge \overline{\text {S4}}\)) is given by the anticoincidence of the incoming beam particle and S4, a scintillation counter, with a diameter of 2 cm, placed between the VTPC1 and VTPC2 detectors along the beam trajectory at about 3.7 m from the target, see Fig. 1a, b. Almost all beam particles that interact inelastically in the target do not reach S4. The interaction and beam triggers were recorded in parallel. The beam trigger events were recorded with a frequency by a factor of about 10 lower than the frequency of interaction trigger events.
For data taking on \(\pi ^\) + C interactions, the target was an isotropic graphite plate with a thickness along the beam axis of 2 cm with a density of \(\rho =1.84\) g/cm\(^3\), equivalent to about 4% of a nuclear interaction length. During the data taking the target was placed 80 cm upstream of VTPC1. 90% of data was recorded with the target inserted and 10% with the removed target. The latter set was used to estimate the bias due to interactions with the material upstream and downstream of the target.
 (i)
detector geometry and TPC drift velocities and
 (ii)
magnetic field map.
 (i)
finding of clusters in the TPC raw data, calculation of the cluster centreofgravity and total charge,
 (ii)
reconstruction of local track segments in each TPC separately,
 (iii)
matching of track segments into global tracks,
 (iv)
fitting of the track through the magnetic field and determination of track parameters at the first measured TPC cluster,
 (v)
determination of the interaction vertex using the beam trajectory fitted in the BPDs and the trajectories of tracks reconstructed in the TPCs (the final data analysis uses the middle of the target as the zposition, \(z=580\,\)cm) and
 (vi)
refitting of the particle trajectory using the interaction vertex as an additional point and determining the particle momentum at the interaction vertex.
A simulation of the NA61/SHINE detector response is used to correct the measured raw yields of resonances. For the purposes of this analysis, the Epos 1.99 model was used for the simulation and calculation of correction factors. DPMJet 3.06 [40] was used as a comparison for estimation of systematic uncertainties. The choice of Epos was made due to both the number of resonances included in the model, as well as the ability to include the intrinsic width of these resonances in the simulation. Epos 1.99 rather than Epos LHC was used as it is better tuned to the measurements at SPS energies [41].
 (i)
generation of inelastic \(\pi ^\) + C interactions using the Epos 1.99 model,
 (ii)
propagation of outgoing particles through the detector material using the Geant 3.21 package [42] which takes into account the magnetic field as well as relevant physics processes, such as particle interactions and decays,
 (iii)
simulation of the detector response using dedicated NA61/SHINE packages which also introduce distortions corresponding to all corrections applied to the real data,
 (iv)
simulation of the interaction trigger selection by checking whether a charged particle hits the S4 counter,
 (v)
storage of the simulated events in a file which has the same format as the raw data,
 (vi)
reconstruction of the simulated events with the same reconstruction chain as used for the real data and
 (vii)
matching of the reconstructed to the simulated tracks based on the cluster positions.
3 Analysis
 (i)
application of event and track selection criteria,
 (ii)
combination of oppositely charged tracks,
 (iii)
accumulating the combinations in bins of Feynmanx, \(x_\text {F}\), calculated by using the mass of the \(\rho ^0\) meson for the boost between the lab and centre of mass frames,
 (iv)
calculation of the invariant mass of each combination, assuming pion masses for the particles,
 (v)
fitting of the invariant mass distributions with templates of resonance decays to obtain raw yields and
 (vi)
application of corrections to the raw yields calculated from simulations.
3.1 Event and track selection
 (i)
Wellcontained measurements of the beam with the BPDs and a successful reconstruction of the beam direction.
 (ii)
Pion identification with the CEDAR (only for 158 \(\text{ GeV }{/}\text{ c }\) as the impurity of the 350 \(\text{ GeV }{/}\text{ c }\) beam is below 0.1%).
 (iii)
No extra (offtime) beam particles detected within \(\pm 2\,\upmu \)s of the triggered beam particle.
 (iv)
All events must have an interaction trigger as defined in Sect. 2.
 (v)
The main vertex point is properly reconstructed.
 (vi)
The zposition of the interaction vertex must be between \(597\) and \(563\) cm.
The cut (vi) is illustrated in Fig. 4 and its purpose is to remove the majority of interactions that do not occur in the target. This cut will increase the Monte Carlo correction because some intarget events are removed due to the vertexz resolution. The vertexz resolution depends on the multiplicity of an event and is about 4.5 cm for low multiplicities and better than 0.5 cm for high multiplicites. The cut is choosen loose enough (\(\pm 17\) cm around the target center) to assure both a high efficiency for all multiplicities and a purity of intarget of better than 99%.
An alternative method to correct for outoftarget interactions would be to measure the resonance yields in the targetremoved data, but the templatefitting method used in this paper can not be applied to data sets with small statistics such as the targetremoved data.
Number of events after each event selection cut and selection efficiency with respect to the previous cut for the target inserted data set for 158 and 350 \(\text{ GeV }{/}\text{ c }\) beam momentum
\(p_\text {beam}\)  \(158\,\text{ GeV }{/}\text{ c } \)  \(350\,\text{ GeV }{/}\text{ c } \)  

Cut  \(N_\text {events}\)  Efficiency (%)  \(N_\text {events}\)  Efficiency (%)  
Total  \(5.49\times 10^6\)  100  \(4.48\times 10^6\)  100  
(i)  BPD  \(4.96\times 10^6\)  90.3  \(4.08\times 10^6\)  91.1 
(ii)  CEDAR  \(4.26\times 10^6\)  85.9  \(4.08\times 10^6\)  100 
(iii)  Offtime  \(4.03\times 10^6\)  94.5  \(3.94\times 10^6\)  96.5 
(iv)  Trigger  \(3.34\times 10^6\)  83.0  \(2.97\times 10^6\)  75.3 
(v)  Vertex fit  \(3.29\times 10^6\)  98.5  \(2.95\times 10^6\)  99.5 
(vi)  zposition  \(2.78\times 10^6\)  84.6  \(2.59\times 10^6\)  87.9 
Number of tracks after each track selection cut and selection efficiency with respect to the previous cut for the target inserted data set for 350 \(\text{ GeV }{/}\text{ c }\) beam momentum
\(p_\text {beam}\)  \(158\,\text{ GeV }{/}\text{ c } \)  \(350\,\text{ GeV }{/}\text{ c } \)  

Cut  \(N_\text {tracks}\)  Efficiency (%)  \(N_\text {tracks}\)  Efficiency (%)  
Total  \(3.85\times 10^7\)  100  \(4.41\times 10^7\)  100  
(i)  Track quality  \(2.27\times 10^7\)  59.0  \(2.77\times 10^7\)  62.8 
(ii)  Acceptance  \(1.57\times 10^7\)  69.0  \(1.99\times 10^7\)  72.0 
(iii)  Total clusters  \(1.54 \times 10^7\)  98.1  \(1.95 \times 10^7\)  98.2 
(iv)  TPC clusters  \(1.51 \times 10^7\)  98.0  \(1.91 \times 10^7\)  97.8 
(v)  Impact parameters  \(1.42 \times 10^7\)  94.4  \(1.80 \times 10^7\)  94.1 
The number of events after these cuts is \(2.78 \times 10^6\) for 158 \(\text{ GeV }{/}\text{ c }\) and \(2.59 \times 10^6\) for 350 \(\text{ GeV }{/}\text{ c }\). The efficiency of these cuts is shown in Table 1 for 158 and 350 \(\text{ GeV }{/}\text{ c }\) beam momentum.
 (i)
The track is well reconstructed at the interaction vertex.
 (ii)
The fitted track is inside the geometrical acceptance of the detector.
 (iii)
The total number of clusters on the track should be greater than or equal to 30.
 (iv)
The sum of clusters on the track in VTPC1 and VTPC2 should be greater than or equal to 15, or the total number of clusters on the track in GTPC should be greater than or equal to 6.
 (v)
The distance of closest approach of the fitted track to the interaction point (impact parameter) is required to be less than 2 cm in the xplane and 0.4 cm in the yplane.
3.2 Signal extraction
The raw yields of \(\rho ^0\), \(\omega \) and K\(^{*0}\) mesons were obtained by performing a fit of inclusive invariant mass spectra. These were calculated by assuming every track that passes the cuts is a charged \(\pi \). Then, for all pairs of positively and negatively charged particles, the invariant mass was calculated assuming pion masses for both particles. Examples of invariant mass spectra at 158 and 350 \(\text{ GeV }{/}\text{ c }\) are shown in Fig. 5.

combinations of tracks that come from decays of different resonances, i.e. one track from a \(\rho ^0\) and one from an \(\omega \) (this can be done as the parent particles of tracks are known in the simulation),

combinations of tracks coming directly from the interaction vertex and

combinations of tracks coming from resonances (both meson and baryon) that are not included in the individual fittingtemplates listed below.
Event mixing was also investigated as an alternative way to estimate the background by taking particles from different events to make invariant mass spectra of \(\pi ^+\pi ^\) candidates, but this method was found to not describe the shape of the background in simulations over the mass range of the \(\rho ^0\), \(\omega \) and K\(^{*0}\) distributions needed to obtain reliable fit results. Refining the event mixing method by splitting the data into multiplicity classes did not improve the quality of this method.
As there is a large number of resonances in the \(m_\text {inv} (\pi ^+\pi ^)\) region around the mass of the \(\rho ^0\), such as the \(\omega \) and K\(^{*0}\) mesons, they all have to be taken into account. This has previously been shown in Ref. [44], where only taking into account \(\rho ^0\) and \(\omega \) mesons resulted in an inadequate fit, with a spurious peak at 0.6 \(\text{ GeV }{/}\text{ c }^2\) in the \(\pi ^+\pi ^\) invariant mass spectra, due to decays of K\(^{*0}\) mesons, where the kaon is assigned the mass of a pion. As there is no particle identification used in this analysis, the effect due to K\(^{*0}\) meson production is expected to be strong and it must be included in the fitting procedure. Other contributions that are not represented by an individual template, such as \(\Lambda \) decay products, are included in the Monte Carlo background.
The fitting procedure uses templates of the invariant mass distribution for each resonance of importance. This method of template fitting is similar to ideas used by many other experiments such as ALICE [45], ATLAS [46], CDF [47] and CMS [48], where it is also known as the cocktail fit method. The use of independent templates without interference terms is a good approximation, because the mass differences between resonances decaying to \(\pi ^+ + \pi ^\) are either large as compared to their width or they decay to \(\pi ^+ + \pi ^\) with small branching ratio only (e.g. about 1.5% for \(\omega \)).
The templates are constructed by passing simulated \(\pi ^\) + C production interactions, generated with the Epos 1.99 [12] hadronic interaction model using Crmc 1.5.3 [49], through the full NA61/SHINE detector Monte Carlo chain and then through the same reconstruction routines as the data. Crmc is an event generator package with access to a variety of different event generators, such as DPMJet 3.06 [40] and Epos LHC [50].
Decays of resonances for which \(m_\text {inv} (\pi ^+\pi ^)\) templates were calculated and fitted. Only decays with a branching ratio greater than 1% into at least one positively and one negatively charged particle are considered. Branching ratios were taken from [51]
Resonance  Decay  Branching ratio 

\(\rho ^0\)  \(\pi ^+\pi ^\)  100.0 
\(\omega \)  \(\pi ^+\pi ^\pi ^0\)  89.1 
\(\pi ^+\pi ^\)  1.53  
K\(^{*0}\)  K \(\pi \)  100.0 
f\(_2\)  \(\pi ^+\pi ^\)  57.0 
\(\pi ^+\pi ^\,2\pi ^0\)  7.7  
K\(^+\)K\(^\)  4.6  
\(2\pi ^+\,2\pi ^\)  2.8  
\(\eta \)  \(\pi ^+\pi ^\pi ^0\)  22.7 
\(\pi ^+\pi ^\gamma \)  4.6  
f\(_0\) (980)  \(\pi ^+\pi ^\)  50.0 
K\(^+\)K\(^\)  12.5  
a\(_2\)  \(3\pi \)  70.1 
\(\eta \,\pi \)  14.5  
\(\omega \,\pi \,\pi \)  10.6  
K \(\bar{\text {K}}\)  4.9  
\(\rho _3\)  \(4\pi \)  71.1 
\(\pi \,\pi \)  23.6  
K K \(\pi \)  3.8  
K \(\bar{\text {K}}\)  1.58  
K\(^0_\text {S}\)  \(\pi ^+\pi ^\)  69.20 
The templates in the fit are the charge mixing background and the following resonances: \(\rho ^0\), K\(^{*0}\), \(\omega \), f\(_2\), f\(_0\) (980), a\(_2\), \(\rho _3\), \(\eta \) and K\(^0_\text {S}\). The templates were generated from reconstructed simulations that have all the standard reconstruction cuts applied; they include effects due to the resolution of the detector and the fiducial acceptance. The templates used in the fits are presented in Fig. 15 in Appendix B. As can be seen, the a\(_2\) and \(\rho _3\) templates are broad and featureless similar to the background template. For this reason, these resonances cannot be fitted reliably and will be subtracted together with the background from figures displaying the result of the template fitting in the following.
3.3 Correction factors
 (i)The Monte Carlo simulations that were used to obtain the templates for the fitting procedure were used to calculate corrections due to geometrical acceptance, reconstruction efficiency, losses due to trigger bias, quality cuts and bin migration effects. For each \(x_\text {F}\) bin, the correction factor \(C(x_\text {F})\) is given bywhere$$\begin{aligned} C(x_\text {F}) = \frac{n_\text {MC}^\text {gen}(x_\text {F})}{n_\text {MC}^\text {acc}(x_\text {F})}, \end{aligned}$$(5)The statistical uncertainties of the corrections factors were calculated assuming binomial distributions for the number of events and resonances.
 (a)
\(n_\text {MC}^\text {gen}(x_\text {F})\) is the mean multiplicity per event of \(\rho ^0\) (\(\omega \), K\(^{*0}\)) mesons produced in a given \(x_\text {F}\) bin in \(\pi ^\) + C production interactions at a given beam momentum, including \(\rho ^0\) (\(\omega \), K\(^{*0}\)) mesons from higher mass resonance decays and
 (b)
\(n_\text {MC}^\text {acc}(x_\text {F})\) is the mean multiplicity per event of reconstructed \(\rho ^0\) (\(\omega \), K\(^{*0}\)) mesons that are accepted after applying all event and track cuts.
 (a)
 (ii)
The contribution from \(\rho ^0\) mesons produced by reinteractions in the target. This was estimated from the simulations. This contribution is less than 1% for all bins apart from \(x_\text {F} <0.15\), where the contribution is 1.7%.
 (iii)
The fitting method was validated by applying the same procedure to the simulated data set, using the background estimated from either the charge mixing method or the true background obtained from the simulation. This difference is then applied as a multiplicative correction to the raw yield, \(f_i^\text {true} / f_i^\text {fit}\), where \(f_i^\text {true}\) is the true yield of resonance i and \(f_i^\text {fit}\) is the yield that comes from the fit to the simulations. This correction is calculated separately for both background estimations and applied to the fits to the data that used the same estimation.
The correction derived from Monte Carlo simulations could introduce a bias in the result if the \(p_\text {T}\) spectrum of the model differed from the true shape. This is because the extrapolation to full \(p_\text {T}\) phase space is based on the model spectrum. To investigate this effect another hadronic interaction model was used, DPMJet 3.06 [40]. This model also provides \(p_\text {T}\) spectra for each resonance measured in this analysis, and the difference between the correction factors found for DPMJet 3.06 and Epos 1.99 is less than 4%. This suggests that any bias introduced by the extrapolation to full \(p_\text {T}\) phase space is small. The difference between the correction factors is used in the estimate of the systematic uncertainties.
The final measurement is calculated by taking the average of the result using the two different background description methods, charge mixing and Monte Carlo background, with all the correction factors that change calculated separately for the two methods. The difference between these two methods is taken to be a systematic uncertainty.
3.4 Uncertainties and Cross Checks
 (i)
The fitting method used for estimating the background shape and the fit procedure. The systematic uncertainty is taken to be half the difference between the two methods, using either charge mixing or Monte Carlo background, after the respective validation corrections have been applied. This estimate therefore combines the systematic uncertainty due to both the fitting method validation correction and the background estimation used and this is the dominant systematic uncertainty.
 (ii)
Correction factors. The correction factors calculated above were compared with factors found using a different hadronic interaction model, DPMJet 3.06.
 (iii)Track cuts. The effect of the event and track selection cuts were checked by performing the analysis with the following cuts changed, compared to the values shown in Sect. 3.1.
 (a)
The cut on the zposition of the interaction vertex was changed to be between \(590\) and \(570\) cm.
 (b)
The window in which offtime beam particles were not allowed was decreased from 2 to 1.5 \(\upmu \)s.
 (c)
The minimum number of clusters on the track was decreased to 25.
 (d)
The sum of clusters on the track in VTPC1 and VTPC2 was decreased to 12 or increased to 18.
 (e)
The impact parameter cuts were increased to less than 4 cm in the xplane and 2 cm in the yplane.
 (a)
The fraction of target removed tracks is less than \(0.15\%\) in all \(x_\text {F}\) bins. The shape of the target removed distributions, after applying all the track and event cuts, is consistent with the background description so there is no additional correction or systematic uncertainty considered.
3.4.1 Fit range
The default fit range used in this analysis was restricted to the mass ranges of the resonances of interest. We tested an extended fit range by including all data down to the kinematic threshold of \(m_\text {inv} (\pi ^+\pi ^) = 2m_\pi \). For this purpose additional templates needed to be taken into account including electrons and positrons pairproduced in the target by photons from \(\pi ^0\) decays. The sum of all resonances produced by the Epos 1.99 model can however not describe the low \(m_\text {inv} (\pi ^+\pi ^)\) region satisfactorily. In particular, a significant bump at a mass of \({\approx }0.4\,\text{ GeV }{/}\text{ c }^2 \) appears to be in the data that does not have a counterpart in the templates. No resonance, meson or baryon, could be found in Epos 1.99 that could describe this bump. To avoid any bias the region of \(0.35\,\text{ GeV }{/}\text{ c }^2< m_\text {inv} (\pi ^+\pi ^) < 0.4\,\text{ GeV }{/}\text{ c }^2 \) was excluded from the fit. Further discussions about the study of this bump are given in Appendix D.
Once this region is excluded from the fit a reasonable description of the \(m_\text {inv}\) distribution down to the kinematic limit can be achieved, as shown in Fig. 8. However, the fit quality is worse and the agreement between the two background estimates is weaker. The poorer fit quality is most likely a combination of poorer performance of the estimate of the combinatorial background close to the kinematic threshold and the missing template to describe the bump at \({\approx }0.375\,\text{ GeV }{/}\text{ c }^2 \).
The yields obtained with the extended range differ by less than the systematic uncertainties from the yields with the original range, with the exception of one bin, and, to be conservative, the corresponding differences, which are of the order of 10%, are included in the systematic uncertainty.
3.4.2 \(\rho ^0\) mass
The yields of the \(\rho ^0\) when fitting with this Breit–Wigner function differ slightly from the yields calculated using the standard analysis method. These small differences of the order of 3% are included in the systematic uncertainties.
A comparison of the yields from the standard template analysis method, the extended fit range and when fitting a Breit–Wigner function (Eq. (7)) is shown in Fig. 10. As can be seen the differences are within the systematic uncertainties of the standard analysis. These small differences, of the order of 3% for the fits with a Breit–Wigner function and 10% for the extended fit range, are added in quadrature to the systematic uncertainties.
3.4.3 Further checks
 (i)
The data, along with the templates, were split into two equally sized regions of polar angle. If there was any polarangle dependence of the result introduced by insufficient modeling of different parts of the detector, this would appear in a difference between the spectra from these independent data sets. The resulting multiplicity spectra were consistent within statistical uncertainties.
 (ii)
The data set was split according to different time ranges, both a night and day split as well as a first half and second half split in run taking. Any possible systematic differences in the detector which depend on time would result in discrepancies in the spectra from the different time ranges. Both resulting \(x_\text {F}\) spectra were again consistent within statistical uncertainties.
 (iii)
Instead of assuming the pion mass for both tracks, one track was allocated the kaon mass. This means that the number of combinations used has to double, as both combinations of masses have to be taken into account for any given pair of tracks to allow for the kaon to be either of the two charges. This also then increases the background even further and because of the different shape of the background under the \(\pi \) K invariant mass distribution, the systematic uncertainty for this method is larger than for the \(\pi \,\pi \) method. The multiplicity spectra from this method were consistent within statistical and systematic uncertainties of the standard analysis method.
4 Results
The spectra of \(\rho ^0\), \(\omega \), and K\(^{*0}\) mesons produced in production \(\pi ^\) + C interactions are shown in Fig. 11. The average \(x_\text {F} \) in each bin is used to display the data points in this and in the following figures. It is worthwhile noting that this average is not corrected for the detector acceptance within the bin and is calculated from all oppositely charge combinations including combinatorial background, i.e. for each \(x_\text {F} \) bin i the average is given by the arithmetic mean \(\langle x_\text {F} \rangle _{i} = \frac{1}{N_i} \sum _{j=1}^{N_i} (x_\text {F})_j\), where the sum runs over all \(N_i\) track combinations in the bin. For a detailed comparison of this data with model predictions it is therefore recommended to compare to model predictions binned in the same way as the data rather than comparing them at the average \(x_\text {F} \).
The measured spectra are compared to model predictions by QGSJet II04 [58], Epos 1.99 [12], DPMJet 3.06 [40], Sibyll 2.1 [59], Sibyll 2.3 [60] and Epos LHC [50] in Figs. 12 and 13. For the purpose of display, the multiplicities were scaled by \(x_\text {F}\).
It can be seen that in the low \(x_\text {F}\) region (\(<0.3\)) all hadronic interaction models overestimate the \(\rho ^0\) yield with discrepancies of up to +80%. At intermediate \(x_\text {F}\) (\(0.4< x_\text {F} < 0.7\)) the \(\rho ^0\) production is underestimated by up to \(60\)%. It is interesting to note that even if QGSJet II04, Sibyll 2.3 and Epos LHC were tuned to \(\pi ^+\)+p data from NA22 [17], these models cannot reproduce the measurement presented here. The large underestimation in QGSJet II04 is mainly for nonforward \(\rho ^0\) production which is not treated explicitly in the model. This explains the large difference in spectral shape compared to the other hadronic models and the large deviations between the model and the measurement. The best description of our data in the forward range (\(x_\text {F} >0.4\)) is given by Sibyll 2.3, which describes the data within 10%.
The shape of the measured \(\omega \) spectrum is in approximate agreement with all of the models shown (QGSJet II04 does not include \(\omega \) mesons in the model). Also the measured normalisation is approximately reproduced by all models but Epos 1.99, which produces too many \(\omega \) mesons above \(x_\text {F} >0.1\).
The measured multiplicity of K\(^{*0}\) mesons is not reproduced by any of the models over the full \(x_\text {F} \) range. DPMJet 3.06 gives a correct description of the yields only at low \(x_\text {F} \) but underpredicts the multiplicity at large \(x_\text {F} \) and the opposite is true for Epos LHC and Epos 1.99 which are in agreement with the measurement only at \(x_\text {F} \gtrsim 0.6\). Sibyll 2.3 and Sibyll 2.1 predict a too low number of K\(^{*0}\) mesons at all \(x_\text {F} \) values.
The ratio between combinations of the three meson measurements are shown in Fig. 21 in Appendix E, where it can be seen that no model can consistently describe the results.
The comparison between results from this analysis to measurements of other experiments are presented in Fig. 14 for \(\rho ^0\) and \(\omega \) mesons. The two other experiments shown are NA22 [17] and LEBCEHS (NA27) [57], both of which used a hydrogen target. NA22 had a \(\pi ^+\) beam at 250 \(\text{ GeV }{/}\text{ c }\) while LEBCEHS had a \(\pi ^\) beam at 360 \(\text{ GeV }{/}\text{ c }\). The results from NA22 and LEBCEHS are scaled by their measured inelastic cross sections: \(20.94\pm 0.12\,\text{ mb } \) for NA22 [61] and \(21.6\,\text{ mb } \) for LEBCEHS [57]. There is good agreement between the previous measurements with proton targets and the results from this analysis for \(x_\text {F} <0.6\). At larger \(x_\text {F}\) the \(\rho ^0\) yields measured in this analysis show a decrease that is not present in the \(\pi \)+p data and could thus be an effect of the nuclear target used for the measurement presented here. The comparison of the measurements of the \(\omega \) multiplicities shows no significant differences between the other experiments and results from this analysis.
5 Summary
This article presents experimental results on \(\rho ^0\), \(\omega \) and K\(^{*0}\) \(x_\text {F}\)spectra in \(\pi ^\) + C production interactions at \(158\,\text{ GeV }{/}\text{ c } \) and the \(\rho ^0\) spectra at 350 \(\text{ GeV }{/}\text{ c }\) from the NA61/SHINE spectrometer at the CERN SPS. These results are the first \(\pi ^\) + C measurements taken in this energy range and are important to tune hadronic interaction models used to understand the measurements of cosmicray air showers.
The comparisons of the measured spectra to predictions of hadronic interaction models suggests that for all models further tuning is required to reproduce the measured spectra of \(\rho ^0\), \(\omega \) and K\(^{*0}\) mesons in the full range of \(x_\text {F}\). Recent retunes of these models to resonance data in \(\pi +p\) interactions resulted in changes of the muon number at ground of up to 25% [14, 60]. The new data provided here for \(\pi \) + C interactions gives a more adequate reference for pionair interactions relevant for air showers and will help to establish the effect of forward resonance production on muons in air showers with the precision needed for using the muon number to estimate the particle type of primary cosmic rays, as e.g. planned within the upgrade of the Pierre Auger Observatory [62].
Notes
Acknowledgements
We would like to thank the CERN EP, BE and EN Departments for the strong support of NA61/SHINE. This work was supported by the Hungarian Scientific Research Fund (Grants OTKA 68506 and 71989), the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, the Polish Ministry of Science and Higher Education (Grants 667/NCERN/2010/0, NN 202 48 4339 and NN 202 23 1837), the Polish National Center for Science (Grants 2011/03/N/ST2/03691, 2013/11/N/ST2/03879, 2014/13/N/ST2/02565, 2014/14/E/ST2/00018 and 2015/18/M/ST2/00125, 2015/19/N/ST2 /01689), the Foundation for Polish Science — MPD program, cofinanced by the European Union within the European Regional Development Fund, the Federal Agency of Education of the Ministry of Education and Science of the Russian Federation (SPbSU research Grant 11.38.242.2015), the Russian Academy of Science and the Russian Foundation for Basic Research (Grants 080200018, 090200664 and 120291503CERN), the National Research Nuclear University MEPhI in the framework of the Russian Academic Excellence Project (contract No. 02.a03.21.0005, 27.08.2013), the Ministry of Education, Culture, Sports, Science and Technology, Japan, GrantinAid for Scientific Research (Grants 18071005, 19034011, 19740162, 20740160 and 20039012), the German Research Foundation (Grant GA 1480/22), the EUfunded Marie Curie Outgoing Fellowship, Grant PIOFGA2013624803, the Bulgarian Nuclear Regulatory Agency and the Joint Institute for Nuclear Research, Dubna (bilateral contract No. 4418115/17), Bulgarian National Science Fund (Grant DN08/11), Ministry of Education and Science of the Republic of Serbia (Grant OI171002), Swiss Nationalfonds Foundation (Grant 200020117913/1), ETH Research Grant TH01 073 and the US Department of Energy.
Supplementary material
References
 1.R. Engel, D. Heck, T. Pierog, Extensive air showers and hadronic interactions at high energy. Annu. Rev. Nucl. Part. Sci. 61, 467–489 (2011)CrossRefADSGoogle Scholar
 2.J. Abraham et al., Properties and performance of the prototype instrument for the Pierre Auger Observatory. Nucl. Instrum. Methods A 523, 50–95 (2004)CrossRefADSGoogle Scholar
 3.R. Abbasi et al., IceTop: the surface component of IceCube. Nucl. Instrum. Methods A 700, 188–220 (2013)CrossRefGoogle Scholar
 4.G. Navarra et al., KASCADEGrande: a large acceptance, highresolution cosmicray detector up to 10**18eV. Nucl. Instrum. Methods A 518, 207–209 (2004)CrossRefADSGoogle Scholar
 5.T. AbuZayyad et al., The surface detector array of the Telescope Array experiment. Nucl. Instrum. Methods A 689, 87–97 (2012)CrossRefADSGoogle Scholar
 6.T. AbuZayyad et al., Evidence for changing of cosmic ray composition between \({10}^{17}\) and \({10}^{18}\) eV from multicomponent measurements. Phys. Rev. Lett. 84, 4276–4279 (2000)CrossRefADSGoogle Scholar
 7.J.C. ArteagaVelazquez et al., Test of hadronic interaction models with the KASCADEGrande muon data. EPJ Web Conf. 52, 07002 (2013)CrossRefGoogle Scholar
 8.A. Aab et al., Muons in air showers at the Pierre Auger Observatory: mean number in highly inclined events. Phys. Rev. D 91, 032003 (2015)CrossRefADSGoogle Scholar
 9.A. Aab et al., Muons in air showers at the Pierre Auger Observatory: measurement of atmospheric production depth. Phys. Rev. D 90, 012012 (2014)CrossRefADSGoogle Scholar
 10.A. Aab et al., Testing hadronic interactions at ultrahigh energies with air showers measured by the Pierre Auger Observatory. Phys. Rev. Lett. 117(19), 192001 (2016)CrossRefADSGoogle Scholar
 11.J. Matthews, A Heitler model of extensive air showers. Astropart. Phys. 22, 387–397 (2005)CrossRefADSGoogle Scholar
 12.T. Pierog, K. Werner, Muon production in extended air shower simulations. Phys. Rev. Lett. 101, 171101 (2008)CrossRefADSGoogle Scholar
 13.H.J. Drescher, Remnant breakup and muon production in cosmic ray air showers. Phys. Rev. D 77, 056003 (2008)CrossRefADSGoogle Scholar
 14.S. Ostapchenko, QGSJETII: physics, recent improvements, and results for air showers. EPJ Web Conf. 52, 02001 (2013)CrossRefGoogle Scholar
 15.M. Adamus et al. Inclusive \(\pi ^0\) Production in \(\pi ^+ p\), \(K^+ p\) and \(p p\) interactions at 250GeV/c. Z. Phys. C 35, 7 (1987). [Sov. J. Nucl. Phys. 47, 271 (1988)]Google Scholar
 16.I.V. Azhinenko et al., Neutral kaon production in K\(^+\)p and pi\(^+\)p interactions at 250GeV/c. Z. Phys. C 46, 525–536 (1990)CrossRefADSGoogle Scholar
 17.N.M. Agababyan et al., Inclusive production of vector mesons in pi\(^+\)p interactions at 250GeV/c. Z. Phys. C 46, 387–395 (1990)CrossRefGoogle Scholar
 18.H.J. Drescher, G.R. Farrar, Dominant contributions to lateral distribution functions in ultrahigh energy cosmic ray air showers. Astropart. Phys. 19, 235–244 (2003)CrossRefADSGoogle Scholar
 19.I.C. Mariş. Hadron production measurements with the NA61/SHINE experiment and their relevance for air shower simulations. Proc. 31st ICRC, p. 1059 (2009)Google Scholar
 20.T. Eichten et al., Particle production in proton interactions in nuclei at 24 GeV/c. Nucl. Phys. B 44, 333–343 (1972)CrossRefADSGoogle Scholar
 21.T. Abbott et al., Measurement of particle production in proton induced reactions at 14.6GeV/c. Phys. Rev. D 45, 3906–3920 (1992)CrossRefADSGoogle Scholar
 22.G. Ambrosini et al., Pion yield from 450 GeV/c protons on beryllium. Phys. Lett. B 425, 208–214 (1998)CrossRefADSGoogle Scholar
 23.C. Alt et al., Inclusive production of charged pions in p + C collisions at 158 GeV/c beam momentum. Eur. Phys. J. C 49, 897–917 (2007)CrossRefADSGoogle Scholar
 24.M. Apollonio et al., Forward production of charged pions with incident protons on nuclear targets at the CERN PS. Phys. Rev. C 80, 035208 (2009)CrossRefADSGoogle Scholar
 25.M.G. Catanesi et al., Measurement of the production crosssections of in pC and C interactions at 12 GeV/c. Astropart. Phys. 29, 257–281 (2008)CrossRefADSGoogle Scholar
 26.M.G. Catanesi et al., Forward production in p–O\(_2\) and p–N\(_2\) interactions at 12 GeV/c. Astropart. Phys. 30, 124–132 (2008)CrossRefADSGoogle Scholar
 27.D.S. Barton et al., Experimental study of the \(a\)dependence of inclusive hadron fragmentation. Phys. Rev. D 27, 2580 (1983)CrossRefADSGoogle Scholar
 28.M. AguilarBenitez et al., Vector meson production in pi–p interaction at 360GeV/c. Z. Phys. C 44, 531 (1989)CrossRefGoogle Scholar
 29.J.E. Elias et al., Experimental study of multiparticle production in hadron–nucleus interactions at high energy. Phys. Rev. D 22, 13–35 (1980)CrossRefADSMathSciNetGoogle Scholar
 30.N. Abgrall et al., NA61/SHINE facility at the CERN SPS: beams and detector system. JINST 9, P06005 (2014)CrossRefADSGoogle Scholar
 31.M. Unger, Results from NA61/SHINE. EPJ Web Conf. 52, 01009 (2013)CrossRefGoogle Scholar
 32.H. Dembinski. Measurement of hadron–carbon interactions for better understanding of air showers with NA61/SHINE. Proc. 33rd ICRC, p. 0688 (2013)Google Scholar
 33.A. Herve. Results from pion–carbon interactions measured by NA61/SHINE for better understanding of extensive air showers. PoS, ICRC2015, p. 330 (2015)Google Scholar
 34.A.E. Kiryunin et al., GEANT4 physics evaluation with testbeam data of the ATLAS hadronic endcap calorimeter. Nucl. Instrum. Methods A560, 278–290 (2006)CrossRefADSGoogle Scholar
 35.J.V. Damgov. CMS HCAL testbeam results and comparison with GEANT4 simulation. AIP Conf. Proc. 867, 471–478 (2006). [471 (2006)]Google Scholar
 36.C. Adloff et al., Validation of GEANT4 Monte Carlo models with a highly granular scintillatorsteel hadron calorimeter. JINST 8, 07005 (2013)Google Scholar
 37.S. Afanasev et al., The NA49 large acceptance hadron detector. Nucl. Instrum. Methods A430, 210–244 (1999)CrossRefADSGoogle Scholar
 38.C. Bovet, S. Milner, A. Placci, The Cedar Project. Cherenkov differential counters with achromatic ring focus. IEEE Trans. Nucl. Sci. 25, 572–576 (1978)Google Scholar
 39.N. Abgrall et al. Calibration and analysis of the 2007 data. CERNSPSC2008018. SPSCSR033 (2008)Google Scholar
 40.S. Roesler, R. Engel, J. Ranft, The Monte Carlo event generator DPMJETIII (Springer, Berlin, 2001), pp. 1033–1038Google Scholar
 41.T. Pierog, Private communication (2013)Google Scholar
 42.R. Brun et al. GEANT: detector description and simulation tool. CERN, 1993. Long Writeup W5013Google Scholar
 43.N. Abgrall et al., Measurements of cross sections and charged pion spectra in proton–carbon interactions at 31 GeV/c. Phys. Rev. C 84, 034604 (2011)CrossRefADSGoogle Scholar
 44.G. Jancso et al., Evidence for dominant vectormeson production in inelastic proton–proton collisions at 53 GeV cm energy. Nucl. Phys. B 124, 1–11 (1977)CrossRefADSGoogle Scholar
 45.M.K. Köhler et al., Dielectron measurements in pp, p–pb and pb–pb collisions with ALICE at the LHC. Nucl. Phys. A 931, 665–669 (2014)CrossRefADSGoogle Scholar
 46.ATLAS Collaboration. Determination of the top quark mass with a template method in the all hadronic decay channel using 2.04/fb of ATLAS data. ATLASCONF2012030, 2012Google Scholar
 47.A. Abulencia et al., Top quark mass measurement using the template method in the lepton + jets channel at CDF II. Phys. Rev. D 73, 032003 (2006)CrossRefADSGoogle Scholar
 48.S. Chatrchyan et al., Measurement of the topquark mass in \(t\bar{t}\) events with dilepton final states in pp collisions at \(\sqrt{s}\)=7 TeV. Eur. Phys. J. C 72, 2202 (2012)CrossRefADSGoogle Scholar
 49.T. Pierog, C. Baus, R. Ulrich. https://web.ikp.kit.edu/rulrich/crmc.html
 50.T. Pierog et al., EPOS LHC: test of collective hadronization with LHC data. Phys. Rev. C 92, 034906 (2015)CrossRefADSGoogle Scholar
 51.C. Patrignani et al., Review of particle physics. Chin. Phys. C 40(10), 100001 (2016)CrossRefADSGoogle Scholar
 52.R.S. Hayano, T. Hatsuda, Hadron properties in the nuclear medium. Rev. Mod. Phys. 82, 2949 (2010)CrossRefADSGoogle Scholar
 53.X.M. Jin, D.B. Leinweber, Valid QCD sum rules for vector mesons in nuclear matter. Phys. Rev. C 52, 3344–3352 (1995)CrossRefADSGoogle Scholar
 54.C. Adler et al., Coherent rho0 production in ultraperipheral heavy ion collisions. Phys. Rev. Lett. 89, 272302 (2002)CrossRefGoogle Scholar
 55.S. Teis et al., Pion production in heavy ion collisions at SIS energies. Z. Phys. A 356, 421–435 (1997)CrossRefADSGoogle Scholar
 56.J.H. Koch, N. Ohtsuka, E.J. Moniz, Nuclear photoabsorption and compton scattering at intermediateenergy. Ann. Phys. 154, 99–160 (1984)CrossRefADSGoogle Scholar
 57.M. AguilarBenitez et al., Vector meson production in \(\pi \)–p interactions at 360 GeV/c. Z. Phys. C 44, 531–539 (1989)CrossRefGoogle Scholar
 58.Sergey Ostapchenko, Monte Carlo treatment of hadronic interactions in enhanced Pomeron scheme: I. QGSJETII model. Phys. Rev. D 83, 014018 (2011)CrossRefADSGoogle Scholar
 59.E.J. Ahn et al., Cosmic ray interaction event generator SIBYLL 2.1. Phys. Rev. D 80, 094003 (2009)CrossRefADSGoogle Scholar
 60.F. Riehn et al. A new version of the event generator Sibyll. PoS, ICRC2015, p. 558 (2015)Google Scholar
 61.M. Adamus et al., Crosssections and charged multiplicity distributions for pi\(^+\)p, K\(^+\)p and p–p interactions at 250GeV/c. Z. Phys. C 32, 475 (1986)ADSGoogle Scholar
 62.A. Aab et al., The Pierre Auger Observatory upgrade—preliminary design report. 2016Google Scholar
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