1 Introduction

The strong coupling constant \(\alpha _s\) is the least well known coupling in the gauge sector of the Standard Model. The latest Particle Data Group (PDG) average of \(\alpha _s\) has an uncertainty of about 1% [1, 2], considerably larger than the error in the other gauge coupling determinations. Given the importance of QCD at LHC collider experiments, and rapid progress in perturbative calculations [3] and experimental accuracy, the uncertainty on \(\alpha _{s}\) is becoming increasingly critical for precision collider phenomenology. However, the headline figure of 1% uncertainty from the PDG average masks significant discrepancies between different extractions. In particular two of the most precise \(\alpha _{s}\) determinations come from event-shapes studies: \(\alpha _{s}= 0.1135\pm 0.0010\) [4] from fitting thrust data and \(\alpha _{s}= 0.1123\pm 0.0015\) [5] from C-parameter data. These results are several standard deviations away from the world average of \(0.1179 \pm 0.0010\) [2, 6] and from other individual precise extractions, such as \(0.1185\pm 0.0008\) from lattice step scaling [7] and \(0.1188\pm 0.0013\) from jet rates [8].

These particular event-shape and jet-rate fits are among the most precise of a wide variety of fits to \(e^+e^-\) hadronic final-state data [4, 5, 8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23]. Many of them use high-precision perturbative calculations, however they also all require input on non-perturbative (hadronisation) effects. These can be estimated either using Monte Carlo (MC) event generators [8, 11, 14, 17, 20] or via analytic non-perturbative models [4, 5, 13, 18, 24]. The use of MC event generators has long been criticised on two main grounds: they are tuned on less accurate perturbative (shower) calculations, and the separation between perturbative and non-perturbative components cannot easily be related to today’s highest-accuracy perturbative calculations. Conversely the analytic models fit a non-perturbative parameter and the perturbative coupling in a single, consistent framework. The low \(\alpha _{s}\) values from Refs. [4, 5, 18] use the latter method. The price to pay in this approach is that the non-perturbative component is not controlled beyond the first order in an expansion in powers of 1/Q (the centre-of-mass energy) and furthermore only in the 2-jet limit, while fits cover both the 2 and 3-jet regions.

In this article we examine specifically the issue of going beyond the 2-jet limit for the hadronisation correction. In principle one might attempt a full calculation as carried out for top-quark production in the large-\(n_f\) limit in Ref. [25]. Before embarking on such a calculation, we believe however that it is worth establishing whether 3-jet hadronisation corrections bring a phenomenologically relevant effect. To do so simply, we consider the example of the C-parameter. This observable is special in that it has two singular points, one at \(C=0\) and the other at a Sudakov shoulder at \(C=3/4\) [26, 27]. Existing fits calculate the hadronisation correction around the first singular point, \(C=0\) and extend it to the whole C-parameter spectrum. Here we point out that one can also quite straightforwardly calculate the power correction at the other singular point \(C=3/4\). One can then consider a range of schemes for interpolating between the two singular points and examine their impact on strong coupling fits.

This letter is structured as follows: in Sect. 2 we briefly recall the framework for perturbative fits with analytic hadronisation estimates. In Sect. 3 we then review the determination of the C-parameter hadronisation correction in the 2-jet limit and extend it to the symmetric 3-jet case (\(C=3/4\)). Section 4 presents the results of our new fits and we then conclude in Sect. 5.

2 The C-parameter and its distribution

The C-parameter variable for a hadronic final state in \(e^+e^-\) annihilation is defined as follows [28],

$$\begin{aligned} C = 3 \left( \lambda _1\lambda _2 + \lambda _2\lambda _3 + \lambda _3\lambda _1\right) , \end{aligned}$$
(1)

in terms of the eigenvalues \(\lambda _i\) of the linearised momentum tensor \(\varTheta ^{\alpha \beta }\) [29, 30],

$$\begin{aligned} \varTheta ^{\alpha \beta } = \frac{1}{\sum _i |\varvec{p}_i|} \sum _i \frac{{\varvec{p}}_i^\alpha {\varvec{p}}_i^\beta }{|\mathbf {p}_i|} , \end{aligned}$$
(2)

where \(|\varvec{p}_i|\) is the modulus of the three momentum of particle i and \({\varvec{p}}_i^\alpha \) is its momentum component along spatial dimension \(\alpha \) (\(\alpha = 1,2,3\)). In events where all particles are massless, this can also be written as

$$\begin{aligned} C&= 3 - \frac{3}{2}\sum _{i,j} \frac{(p_i\cdot p_j)^2}{(p_i\cdot Q) (p_j\cdot Q)}=\frac{3}{8}\sum _{i,j} x_i x_j \sin ^2\theta _{ij} , \end{aligned}$$
(3)

where Q is the centre-of-mass energy, \(p_i\) denotes the four-momentum of particle i, \(x_i = 2 (p_i\cdot Q)/Q^2\), and \(\theta _{ij}\) is the angle between particles i and j. We introduce the cumulative distribution \({\varSigma }\) defined as

$$\begin{aligned} {\varSigma }(C)\equiv \frac{1}{\sigma }\int _0^{C}\hbox {d}C' \frac{\hbox {d}\sigma }{\hbox {d}C'} . \end{aligned}$$
(4)

The differential distribution \(\hbox {d}\sigma \) is known to next-to-next-to-leading order (NNLO) in massless QCD [31,32,33], which can be combined with the total cross section \(\sigma \) [34] to obtain a \(\hbox {N}^3\hbox {LO}\) prediction for Eq. (4). The effects of heavy-quark (notably the bottom quark) masses on event shape distributions [35], as well as electroweak corrections [36], are known to NLO, but we do not consider them in our study. Their omission does not affect in any way the conclusions of this article. In the following we consider the massless-QCD NNLO predictions for the differential distribution from Ref. [33].

In the two-jet region, the fixed-order expansion is spoiled by large logarithms of infrared and collinear origin, which must be consistently resummed at all perturbative orders to obtain a physical prediction. The resummation for the C-parameter distribution has been carried out in different formalisms [27, 37, 38] and it is known up to \(\hbox {N}^3\hbox {LL}\) [37]. In our analysis we adopt the analytic next-to-next-leading logarithmic (NNLL) calculation from the appendix of Ref. [38], which is sufficient to illustrate our findings.

To obtain a perturbative prediction that is accurate across the whole physical spectrum, we need to match the resummed NNLL calculation to the fixed order result. This is done by combining the \(\hbox {N}^3\hbox {LO}\) calculation \({{\varSigma }^{\mathrm{N}}}^\mathrm{3}{LO}(C)\) with the resummed prediction \({\varSigma }^{\mathrm{NNLL}}(C)\) according to the log-R scheme [39] as

$$\begin{aligned} \varSigma ^\text {pert.}(C) \equiv e^{\ln {\varSigma }^{\mathrm{NNLL}}(C) + \ln {\varSigma }^{\mathrm{N^3LO}}(C) - \ln {\varSigma }^{\mathrm{Exp.}}(C)} , \end{aligned}$$
(5)

where \({\varSigma }^{\mathrm{Exp.}}(C)\) is the fixed-order expansion of \({\varSigma }^{\mathrm{NNLL}}(C)\) to \(\mathcal{O}(\alpha _s^3)\). Detailed formulae are reported in Ref. [40]. Note that specific choices need to be made to limit the impact of the resummation in regions where C is not small. Our choices are discussed in Appendix D.

The hadronisation corrections to the C parameter distribution can be described in terms of an expansion in negative powers of the centre of mass energy Q. The leading correction in this sense leads to a shift of the cumulative distribution of the form

$$\begin{aligned} \varSigma ^\text {hadr.}(C) = \varSigma ^\text {pert.}(C - \langle \delta C\rangle (C)) , \end{aligned}$$
(6)

where \(\langle \delta C\rangle (C) \propto 1/Q\) is the mean change in the C parameter’s value due to the emission of soft non-perturbative radiation. In most work, the power correction is taken to be independent of the value of the observable, \(\langle \delta C\rangle (C) \equiv \langle \delta C\rangle (0)\). In this work we will be investigating the consequences of having \(\langle \delta C\rangle (C)\) vary with C.

We adopt the following form for \(\langle \delta C\rangle (C)\),

$$\begin{aligned} \langle \delta C\rangle&\simeq \zeta (C)\,\mathcal{M}\,\frac{\mu _{I}}{Q}\frac{4 \,C_F}{\pi ^2} \left[ \alpha _{0}(\mu _{I}^{2})-\alpha _{s}(\mu _{R}^2)\right. \nonumber \\&\quad -\alpha _{s}^{2}(\mu _{R}^2)\frac{\beta _{0}}{\pi }\left( 2\ln \frac{\mu _{R}}{\mu _{I}}+\frac{K^{(1)}}{2\beta _{0}}+2\right) \nonumber \\&\quad -\alpha _{s}^{3}(\mu _{R}^2)\frac{\beta _{0}^2}{\pi ^2}\bigg (4\ln ^{2}\frac{\mu _{R}}{\mu _{I}}+4\bigg (\ln \frac{\mu _{R}}{\mu _{I}}+1\bigg )\nonumber \\&\quad \times \left. \bigg (2+\frac{\beta _{1}}{2\beta _{0}^2}+\frac{K^{(1)}}{2\beta _{0}}\bigg )+\frac{K^{(2)}}{4\beta _{0}^2}\bigg )\right] , \end{aligned}$$
(7)

where \(\zeta (C)\) encodes the C-dependence of the correction. In Eq. (7) we include the Milan factor \(\mathcal{M}(n_f=3) \simeq 1.490\) [41,42,43] to account for the non-inclusive correction. Eq. (7) involves the mean value of the strong coupling constant in the soft physical scheme \({\tilde{\alpha }}_s\) (see also Appendix A) at infrared scales \(\mu \le \mu _I\), above which the prediction is assumed to be dominantly perturbative [44],

$$\begin{aligned} \alpha _0(\mu _I^2) \equiv \frac{1}{\mu _I}\int _0^{\mu _I}\hbox {d}\mu \,{\tilde{\alpha }}_s(\mu ^2) . \end{aligned}$$
(8)

Equation (7) also includes terms to subtract the contributions already accounted for in the perturbative calculation [13, 18, 45]. The determination of the latter is not without subtleties, in that it assumes that non-inclusive corrections to such renormalon subtraction are described by the same multiplicative \(\mathcal{M}\) factor as for the coefficient of \(\alpha _0(\mu _I^2)\). However these subtleties are numerically subdominant relative to other effects that we will be discussing here.

The core of this article relates to the coefficient \(\zeta (C)\), which entirely determines the C dependence of Eq. (7). The calculation of \(\zeta (C)\) at specific values of C is the subject of the next section.

3 Non-perturbative corrections

The calculation of \(\langle \delta C\rangle \) near a singular configuration requires the amplitudes describing the emission of a “gluer” [44] k off the hard partonic system defined by the set of momenta \(\{p_i\}\). We can then calculate the mean change in the observable caused by the emission of k, i.e.

$$\begin{aligned} \varDelta C (\{p'_i\},\{p_i\}; k) \equiv C (\{p'_i\}; k) - C(\{p_i\}) . \end{aligned}$$
(9)

where the momenta \(\{p_i\}\) (\(\{p'_i\}\)) describe the hard configuration before (after) the emission of the gluer. One can construct a range of prescriptions for mapping \(\{p_i\} \rightarrow \{p'_i\}\) and in general \(\varDelta C (\{p'_i\},\{p_i\}; k)\) depends on the choice that is made. However, in the immediate vicinity of a singular configuration, it turns out that \(\varDelta C (\{p'_i\},\{p_i\}; k)/k_t\) is independent of that prescription in the limit of \(k_t \rightarrow 0\), where \(k_t\) is the transverse momentum of k. For the C-parameter, the singular points correspond to the 2-jet limit and the symmetric 3-jet limit. At these points the dependence on the choice of recoil scales as \(k_t^2\) and so vanishes in the \(k_t \rightarrow 0\) limit of \(\varDelta C (\{p'_i\},\{p_i\}; k)/k_t\).

Under such conditions, one can write

$$\begin{aligned} \zeta (C)= & {} \lim _{\epsilon \rightarrow 0} \frac{\pi Q}{2\alpha _{s}C_F} \int [dk] \, M^2(k) \nonumber \\&\times \varDelta C (\{p'_i\},\{p_i\}; k)\, \delta (k_t - \epsilon ) , \end{aligned}$$
(10)

where \([\hbox {d}k] M^2(k)\) is the phase space and eikonal squared amplitude describing the emission of the gluer, and the \(\{p_i\}\) are the hard momenta associated with the singular configuration. The coupling, colour factor and a dimensional factor Q are divided out, since these are included in Eq. (7).

For an emission from a dipole \(\{ij\}\), stretching between particles with momenta \(p_i\) and \(p_j\), the matrix element and phase space are

$$\begin{aligned}{}[dk] \, M^2(k) = \frac{2C_F}{\pi } \alpha _{s}\frac{dk_t}{k_t} \frac{d\phi }{2\pi } d\eta , \end{aligned}$$
(11)

where \(k_t\), \(\eta \) and \(\phi \) are to be understood with respect to the dipole; \(k_t\) in the \(\delta (k_t-\epsilon )\) factor in Eq. (10) is also to be understood with respect to the emitting dipole.

3.1 Calculation of \(\zeta (0)\) (2-jet limit)

Let us start by considering the two-jet limit \(C=0\). The shift in the C-parameter induced by a small-\(k_t\) gluer is [27, 39]

$$\begin{aligned} \varDelta C(k) = \frac{k_t}{Q} \frac{3}{\cosh (\eta )} + \mathcal{O}\left( \frac{k_t^2}{Q^2}\right) , \end{aligned}$$
(12)

where, for brevity, we have omitted the \(\{p\}\) and \(\{p'\}\) arguments in \(\varDelta C(k)\). This leads us to

$$\begin{aligned} \zeta (0) = \int _{-\infty }^{\infty }\hbox {d}\eta \, \frac{3}{\cosh (\eta )}= 3 \pi \simeq 9.42478 , \end{aligned}$$
(13)

where the rapidity limits can be taken to infinity because the integral is convergent. This coincides (to within conventions for normalisations) with the result that was given in [27, 45, 46].

3.2 Calculation of \(\zeta (3/4)\) (Sudakov shoulder)

The leading order (LO) C-parameter distribution has an endpoint at 3/4. Just below this endpoint, the distribution tends to a non-zero constant [26],

$$\begin{aligned} \frac{1}{\sigma }\frac{\hbox {d}\sigma }{\hbox {d}C}\left( \frac{3}{4}^- \right) = \frac{\alpha _s}{2\pi } C_F\,\frac{256}{243}\pi \sqrt{3} + \mathcal{O}(\alpha _s^2) , \end{aligned}$$
(14)

while above the endpoint the distribution is zero at order \(\alpha _{s}\). This structure is known as a Sudakov shoulder. Parametrising the energies of the two quarks and the gluon as \(Q/2 (2/3 - \epsilon _q)\), \(Q/2 (2/3 - \epsilon _{{\bar{q}}})\), \(Q/2 (2/3 + \epsilon _q + \epsilon _{{\bar{q}}})\) one obtains

$$\begin{aligned} C = \frac{3}{4} - \frac{81}{16}\left( \epsilon _q^2 + \epsilon _q\epsilon _{{\bar{q}}} + \epsilon _{{\bar{q}}}^2 \right) + \mathcal{O}\!\left( \epsilon ^3\right) , \end{aligned}$$
(15)

and the shoulder arises because of the absence of linear dependence on the \(\epsilon \)’s. This absence of linear dependence on \(\epsilon \) is also the reason that the choice of recoil prescription affects \(\varDelta C\) only at order \(k_t^2/Q^2\). Considering emission of a gluon with momentum k from an \(\{i j\}\) dipole (with ij chosen among \(q,\bar{q},g\)), one can then derive

$$\begin{aligned} \varDelta C(k) = \frac{3\sqrt{3}}{2}\,\frac{\sin ^2(\phi )}{2 \cosh (\eta ) - \cos (\phi )} \,\frac{ k_t}{Q} + \mathcal{O}\left( \frac{k_t^2}{Q^2}\right) , \end{aligned}$$
(16)

in terms of the \(k_t\), \(\eta \) and \(\phi \) of the emission with respect to the dipole (taken in the dipole’s centre of mass). The \(\mathcal{O}\!\left( k_t/Q\right) \) contribution arises only when k is out of the 3-jet plane.

The squared matrix element times phase space can be written as a sum over three dipoles

$$\begin{aligned}{}[dk]M^2(k) = \frac{2\alpha _{s}}{\pi } \!\!\! \sum _{\text {dip}=qg,{\bar{q}}g,q{\bar{q}}} \!\!\!\! C_\text {dip} \frac{dk_t^{[\text {dip}]}}{k_t^{[\text {dip}]}} \frac{d\phi ^{[\text {dip}]}}{2\pi } d\eta ^{[\text {dip}]}, \end{aligned}$$
(17)

where \(C_{qg} = C_{{\bar{q}} g} = C_A/2\) and \(C_{q{\bar{q}}} = C_F - C_A/2\). Note that for each dipole we will use the corresponding kinematic variables (\(k_t^\text {[dip]}\), etc.) in Eq. (16). This is equivalent to the procedure used to calculate the power correction to the D-parameter for arbitrary 3-jet configurations [47].

Integrating over \(\eta ^\text {[dip]}\) and \(\phi ^\text {[dip]}\), and summing over dipoles, we then obtain

$$\begin{aligned} \zeta (3/4)&= \frac{3\sqrt{3}}{4}\frac{C_A+2 C_F}{C_F}\!\int _{-\infty }^{\infty }\!\!\!\!d\eta \int _{0}^{2\pi }\!\frac{d\phi }{2\pi }\frac{\sin ^2\phi }{2\cosh \eta -\cos \phi }\nonumber \\&= \frac{3\sqrt{3}}{4}\, \frac{C_A + 2 C_F}{C_F}\left( 4\, E(1/4) -3\, K(1/4)\right) . \end{aligned}$$
(18)

The functions K and E are the complete elliptic integrals of the first and second kind

$$\begin{aligned} K(t)&= \int _0^{\pi /2} d \theta (1-t \sin ^2\theta )^{-1/2} , \end{aligned}$$
(19a)
$$\begin{aligned} E(t)&= \int _0^{\pi /2} d \theta (1-t \sin ^2\theta )^{1/2} . \end{aligned}$$
(19b)

The numerical value of \(\zeta (3/4)\) reads

$$\begin{aligned} \zeta (3/4) \simeq 4.48628 , \end{aligned}$$
(20)

which provides the leading non-perturbative correction at the shoulder.Footnote 1 This simple result reveals that the leading (\(\sim 1/Q\)) hadronisation correction at the (symmetric three-jet) Sudakov shoulder is less than half that in the two-jet limit (\(\zeta (0) = 3\pi \)).

3.3 Modelling of the \(0\!<\! C\! <\! 3/4\) region

Our calculations of \(\zeta (0)\) and \(\zeta (3/4)\) relied critically on the fact that recoil from the gluer emission had an impact that was quadratic in the gluer momentum. Away from these special points, the methods used here do not give us control over the value of the power correction, because the result depends on the prescription that we adopt for recoil (the impact of the hard parton’s recoil becomes linear in the gluer momentum). One could conceivably extend the methods of Ref. [25] to attempt to determine the general dependence of \(\zeta (C)\) on C, however such a calculation is highly non-trivial. So here, we want to establish whether such a calculation would be phenomenologically important. To do so, we consider a range of models that interpolate the power correction between the known values at \(C=0\) and \(C=3/4\), some of which depend on a parameter \(n \ge 0\). These are:

$$\begin{aligned} \zeta _0(C)&= \zeta (0) \end{aligned}$$
(21a)
$$\begin{aligned} \zeta _{a,n}(C)&= \zeta (0) (1-u^n) + \zeta (3/4)u^n ,\quad u = \frac{4C}{3} , \end{aligned}$$
(21b)
$$\begin{aligned} \zeta _{b,n}(C)&= \zeta (0) (1-u)^n + \zeta (3/4)\left( 1 - (1-u)^n\right) , \end{aligned}$$
(21c)
$$\begin{aligned} \zeta _c(C)&= \zeta (0) + (\zeta (3/4)-\zeta (0)) g(u), \end{aligned}$$
(21d)

where g(u) has the property that it is 0 (1) for \(u=0\) (1) and its first derivative is zero at \(u=0,1\),

$$\begin{aligned} g(u) = -1 + (1-u)^3 + 3u -u^3 . \end{aligned}$$
(21e)

The different forms for \(\zeta (C)\) are shown in Fig. 1.

Fig. 1
figure 1

Different functional forms for \(\zeta (C)\) function interpolating between the results at \(C=0\) and \(C=3/4\)

The \(\zeta _0\) choice corresponds to using a constant shift, i.e. the standard approach for earlier studies. For both \(\zeta _{a,n}\) and \(\zeta _{b,n}\), using \(n=1\) corresponds to a linear interpolation between the \(\zeta (0)\) and \(\zeta (3/4)\) values. For larger n, \(\zeta _{a,n}\) is flat close to \(C=0\), while \(\zeta _{b,n}\) is flat close to \(C = 3/4\). Finally \(\zeta _{c}\) is flat near both \(C=0\) and \(C=3/4\). We stress that the variations in Eq. (21) are not normally taken into account when estimating hadronisation with analytic models, which effectively all assume the \(\zeta _0\) model, corresponding to a constant shift across the whole differential distribution. In Sect. 4 we will see what impact this has on fits for the strong coupling from experimental data.

In order to gain some insight on how \(\zeta (C)\) depends on the recoil scheme, in Appendix B we carry out a fixed-order calculation of this quantity within different schemes to distribute the recoil due to the emission of the gluer among the remaining three partons. In reality, however, the behaviour that we find at fixed order in Appendix B can be substantially modified by the emission of multiple perturbative radiation (as also discussed in Appendix B). Therefore we do not rely on these calculations to assess the impact of \(\zeta (C)\) on the fits, but rather use them as an insightful picture of how the leading non-perturbative correction scales across the spectrum of the event shape. We do however note that the concrete recoil schemes all yield shapes that fall below the \(\zeta _{a,1}\equiv \zeta _{b,1}\) line.

4 Fit of \(\alpha _s\) and hadronisation uncertainties

To test how our results affect the extraction of \(\alpha _s\), we perform a simultaneous fit of the strong coupling and of the non-perturbative parameter \(\alpha _0(\mu _I^2)\), using data at different centre-of-mass energies from the ALEPH [49] and JADE [50] experiments, as summarised in Table 1. This dataset is smaller than that considered for a similar fit in Ref. [5], but is largely sufficient for determining how the \(\alpha _{s}\) fit result depends on \(\zeta (C)\).

Table 1 Data set considered for the simultaneous \(\chi ^{2}\) fit of \(\alpha _s\) and \(\alpha _0\)

The theory predictions are obtained using 50 bins in the \(0\le C \le 1\) range, subsequently interpolated in order to be evaluated in correspondence to the experimental data bins. The fit is performed by minimising the \(\chi ^2\) function defined as

$$\begin{aligned} \chi ^2 =&\sum _{i,j} \left( \left. \frac{1}{\sigma }\frac{\hbox {d}\sigma }{\hbox {d}C}(C_i)\right| ^\mathrm{data}-\left. \frac{1}{\sigma }\frac{\hbox {d}\sigma }{\hbox {d}C}(C_i)\right| ^\mathrm{th}\right) V^{-1}_{ij}\nonumber \\&\times \left( \left. \frac{1}{\sigma }\frac{\hbox {d}\sigma }{\hbox {d}C}(C_j)\right| ^{\mathrm{data}}-\left. \frac{1}{\sigma }\frac{\hbox {d}\sigma }{\hbox {d}C}(C_j)\right| ^{\mathrm{th}}\right) \, , \end{aligned}$$
(22)

where \(V_{ij}\) is the covariance matrix that encodes the correlation between the bins \(C_i\) and \(C_j\). The general form of the covariance matrix is \(V_{ij}= S_{ij}+E_{ij}\), where \(S_{ij}=\delta \sigma _{\mathrm{stat},\,i}^2\delta _{ij}\) is the diagonal matrix of the (uncorrelated) statistical errors in the experimental differential distribution, while \(E_{ij}\) contains the experimental systematic covariances. The diagonal entries of \(E_{ii}=\delta \sigma _{\mathrm{syst},i}^2\) are given by the experimental systematic uncertainty on the i-th bin. For the off-diagonal elements, which are not publicly available, a common choice (used also in Refs. [4, 5, 18]) is to consider a minimal-overlap model, which defines \(E_{ij}\) as

$$\begin{aligned} E_{ij} = \mathrm{min} (\delta \sigma _{\mathrm{syst},i}^2,\delta \sigma _{\mathrm{syst},j}^2 ). \end{aligned}$$
(23)

For ease of comparison, we adopt the same choice, though we note that for the normalised distributions that we fit here, the true covariance matrix would also include some degree of anti-correlation. The \(\chi ^2\) minimisation is carried out with the TMinuit routine distributed with ROOT and the whole analysis was implemented in the C++ code used for a similar fit in Ref. [18]. Results with a diagonal covariance matrix, i.e. without any correlations, are given in Appendix C. They yield almost identical central results for \(\alpha _{s}\) and \(\alpha _0\), smaller \(\chi ^2\) values, and an increase in the experimental errors of \(\mathcal{O}\) (10–20%), which however remain small compared to theoretical uncertainties.

Fig. 2
figure 2

Fit results for \(\alpha _s\) and \(\alpha _0\) for different models of \(\zeta (C)\). The points indicate the fit corresponding to the central setup of scales and parameters for a given model. The ellipses show the \(\varDelta \chi ^2=1\) contours associated with the experimental uncertainty. The shaded areas represent the theory uncertainties due to the variation of additional theoretical parameters as described in the text

Table 2 Results of fits for \(\alpha _{s}\) and \(\alpha _0\) using the different functional forms for \(\zeta (C)\) reported in Eq. (21). The quoted uncertainties encode the total (statistical and systematic) experimental uncertainty (first number) and the total theoretical uncertainty (second number) estimated as described in the text. The \(\chi ^2\) values are those obtained with central scales and setup. The results have been obtained with the minimum overlap model, Eq. (23), for correlations between experimental systematic uncertainties

In order to estimate the theoretical uncertainties, we perform the following variations:

  • the renormalisation scale \(\mu _R\) is randomly varied in the range \(Q/2\le \mu _R \le 2\,Q\), while the infrared scale \(\mu _I\) is set to 2 GeV;

  • for \(\mu _R = Q\), the resummation scale fraction \(x_C\) defined in Appendix D (default value \(x_C=1/2\)) is randomly varied by a factor 3/2 in either direction, namely in the range \(1/3 \le x_C \le 3/4\), following the prescription of Ref. [9];

  • for \(\mu _R = Q\) and \(x_C = 1/2\), the Milan factor \({\mathcal {M}}\) is randomly varied within \(20\%\) of its central value [41] (\(\mathcal{M}\simeq 1.49\)) to account for non-inclusive effects in the \(\langle \delta C\rangle \) shift (7) beyond \(\mathcal{O}(\alpha _s^2)\);

  • keeping all of the above parameters at their central values, the parameter p in the modified logarithm defined in Eq. (41) of Appendix D (default value \(p=6\)) is replaced by \(p=5\) and \(p=7\). This choice for p is discussed in Appendix D.

The theory error is defined as the envelope of all the above variations. When we quote overall results below, we add the theoretical and experimental errors in quadrature.

We test several models for \(\zeta (C)\) as given in Eq. (21) and shown in Fig. 1. Specifically, we consider the constant \(\zeta _0\) choice, the \(\zeta _{a,n}\) model for \(n=1,2,3\), the \(\zeta _{b,n}\) model for \(n=1,2,3\), and the \(\zeta _{c}\) model (recall \(\zeta _{a,1} \equiv \zeta _{b,1}\)).

The results of the fits are given in Fig. 2 and Table 2. Figure 2 shows results for \(\alpha _{s}\) and \(\alpha _0\): the points give the central result for each \(\zeta (C)\) choice, while the corresponding shaded areas represent the envelope of results obtained varying scales and parameters in the theoretical calculation, i.e. our overall theoretical uncertainty. Each point is accompanied by the \(\varDelta \chi ^2=1\) ellipse, whose projection along each of the axes defines the \(1\,\sigma \) experimental uncertainty. Table 2 provides the numerical values of the central results and overall errors for each \(\zeta (C)\) choice, and additionally includes the \(\chi ^2\) result from the fit, Eq. (22), divided by the number of degrees of freedom.

The results with the \(\zeta _0\) model correspond to the standard implementation of the leading non-perturbative correction, which is assumed to amount to a constant shift across the whole C spectrum. The fit returns

$$\begin{aligned} \zeta _0: \ \alpha _s(M_Z^2) = 0.1121^{+0.0024}_{-0.0016} ,\quad \alpha _0(\mu _I^2) = 0.53^{+0.07}_{-0.05} , \end{aligned}$$

and agrees well with that of Ref. [5], albeit with larger uncertainties, in part due to our use of NNLL+NNLO rather than \(\hbox {N}^3\hbox {LL+NNLO}\) theory predictions. We observe that several models lead to a \(\chi ^2\) value that is the same as, or smaller than, that for the \(\zeta _0\) shape. In particular, the \(\zeta _{b,2}\) model returns

$$\begin{aligned} \zeta _{b,2}: \ \alpha _s(M_Z^2) = 0.1163^{+0.0028}_{-0.0018} ,\quad \alpha _0(\mu _I^2) = 0.51^{+0.06}_{-0.04} , \end{aligned}$$

with a \(\chi ^2\) that is similar to that of the \(\zeta _0\) fit. This corresponds to an increase in \(\alpha _s(M_Z^2)\) of about \(3.7\%\). In a number of models (\(\zeta _{a,1}\equiv \zeta _{b,1}\), \(\zeta _{b,2}\), \(\zeta _{b,3}\), and \(\zeta _{c}\)) the values of \(\alpha _s\) become compatible with the world average [2] \(\alpha _s^\mathrm{W.A.} = 0.1179 \pm 0.0010\). The result with the smallest \(\chi ^2\) is the \(\zeta _{a,2}\) model, which yields a rather small value of \(\alpha _{s}= 0.1121^{+0.0024}_{-0.0016}\). However the investigations of Appendix B, with a variety of concrete recoil-scheme prescriptions, seem to disfavour the \(\zeta _{a,2}\) shape, suggesting that yet other factors may be relevant for maximising the fit quality.

Overall, the results suggest that one should allow for a 3–4% uncertainty in \(\alpha _s\) extractions from \(e^+e^-\) C-parameter data, associated with limitations in our current ability to estimate hadronisation corrections.

5 Conclusions

In this letter we have pointed out that the presence of a Sudakov shoulder in the differential distribution of some event-shape observables, such as the C parameter, can be exploited to gain insight on the observable dependence of the leading (\(\sim 1/Q\)) hadronisation correction to the spectrum. We found that the leading hadronisation correction at the Sudakov shoulder (\(C=3/4\)) is over a factor of two smaller than the corresponding value in the two-jet (\(C=0\)) limit.

In order to assess the impact of this observation on the fit of the strong coupling constant, we performed a set of fits using different assumptions on the scaling of the non-perturbative correction between the two points.

Our study is by no means exhaustive, and the inclusion of additional physical effects (such as the impact of bottom-mass effects) as well as a careful assessment of other sources of systematic uncertainty (such as the dependence on the fit range and the choice of correlation model) is necessary. However, it clearly reveals that current uncertainties in the modelling of hadronisation corrections can arguably impact the extractions of the strong coupling from event shapes at the several percent level. In particular, some of the models tested here lead to an increase in the extracted value of the strong coupling by 3–4%, which then becomes compatible with the world average to within uncertainties.

This necessarily raises the question of whether such observables should still be adopted for percent-accurate determinations of the strong coupling at LEP energies. Similar considerations may apply to extractions of \(\alpha _s\) obtained with jet observables, for instance those relying on accurate calculations for jet rates [32, 51,52,53,54] (e.g. the fits of Refs. [8, 21]) or modifications of \(e^+e^-\) event shapes by means of grooming techniques [55,56,57] (an example being the analysis of Ref. [58]). Further studies are certainly warranted to investigate whether it is possible to better understand hadronisation for such observables across their whole spectrum, for example exploiting the large-\(n_f\) calculational methods of Ref. [25].