# Helicity antenna showers for hadron colliders

- 209 Downloads
- 1 Citations

## Abstract

We present a complete set of helicity-dependent \(2\rightarrow 3\) antenna functions for QCD initial- and final-state radiation. The functions are implemented in the Vincia shower Monte Carlo framework and are used to generate showers for hadron-collider processes in which helicities are explicitly sampled (and conserved) at each step of the evolution. Although not capturing the full effects of spin correlations, the explicit helicity sampling does permit a significantly faster evaluation of fixed-order matrix-element corrections. A further speed increase is achieved via the implementation of a new fast library of analytical MHV amplitudes, while matrix elements from Madgraph are used for non-MHV configurations. A few examples of applications to QCD \(2\rightarrow 2\) processes are given, comparing the newly released Vincia 2.200 to Pythia 8.226.

## 1 Introduction

The description of bremsstrahlung processes in parton-shower event generators typically starts from the probability density for unpolarised partons to emit unpolarised radiation, i.e., DGLAP kernels or dipole/antenna functions summed over outgoing and averaged over incoming polarisations/helicities. One way of incorporating nontrivial polarisation effects, used in Pythia [1], is to correlate the plane in which a gluon is produced, with the plane in which it subsequently branches, taking linear-polarisation effects into account on the intermediate propagator, and casting the result in terms of a non-uniform selection of the azimuthal \(\varphi \) angle around the direction of the branching gluon, see, e.g., [2]. A more complete, but also more cumbersome, alternative, used in Herwig [3], is to keep track of spin correlations explicitly, using a spin-density matrix formalism [4, 5, 6]. In both cases, the nontrivial angular correlations ultimately arise from dot products between reference vectors expressing *linear* polarisations.

By contrast, a *helicity* basis does not rely on any external reference vectors, and hence helicity-dependence in and of itself does not generate any nontrivial angular correlations. Nonetheless, helicity-dependent radiation functions, as used for final-state radiation in Vincia for a few years [7], do have some advantages: helicity conservation can be made explicit, allowing to trace helicities through the shower; unphysical helicity configurations are prevented from contributing to sums and averages; and the explicit helicity assignments allow faster evaluations of matrix-element correction (MEC) factors, since only a single (or a few) helicity amplitudes need to be evaluated for each ME-corrected parton state [7].

*R*” in Powheg notation) and \(\mathrm {PS}\) represents the (sum of) parton-shower contributions to the given phase-space point.

The limitation to single emissions was lifted by the development of iterated ME corrections [16],^{1} implemented in Vincia [17, 18], again first in the context of \(e^+e^-\rightarrow \mathrm {jets}\) [16] and subsequently for hadron collisions [18, 19]. Importantly, the most recent study in [19] extended the formalism to strongly-ordered and non-Markovian shower algorithms, expanding its applicability to essentially any shower algorithm in modern MC generators. Although a helicity-dependent (and hence computationally faster) version of the iterated-MEC algorithm was developed for final-state radiation [7], a fully-fledged helicity-dependent version for hadron collisions (and for strongly-ordered non-Markovian showers) has so far been missing. The aim of this paper is to develop this missing piece, while simultaneously presenting a complete set of helicity-dependent (and positive-definite) antenna functions for \(2\rightarrow 3\) branchings for both initial- and final-state radiation. In addition, some helicity configurations (called “maximally helicity violating”) can be expressed in compact analytical forms, hence we use such amplitudes for QCD \(2\rightarrow n\) processes whenever possible to speed up the calculation further. For non-MHV configurations, we use matrix elements from Madgraph 4 [20]. (Note that the use of Madgraph 4 puts some limitations on the configurations for which the relevant information for MEC factors can be extracted easily from the matrix elements. In particular, this is the case for amplitudes with multiple quark pairs. These limitations will be lifted by a new interface to Madgraph 5 which is currently under development [21].)

This article is organised as follows. In Sect. 2, we give an overview over the helicity-dependent shower in Vincia, including the extension to initial-state radiation The matrix-element correction formalism is reviewed in short in Sect. 3 together with a brief introduction to the MHV amplitudes in Vincia. Results are presented in Sect. 4, before giving some concluding remarks in Sect. 5. The helicity-dependent antenna functions are given in Appendix A. Appendix B summarises a few changes in the Vincia code which we deem relevant to ensure that results obtained with the new implementation may be interpreted correctly, in particular in comparison with results obtained with earlier versions.

## 2 Helicity-dependent showers

*i*and a set of helicities

*h*,

*i*. We also make use of the notation

*i*.

*h*is simplest to define in terms of the redefined LC matrix elements,

*unpolarised*trial-antenna function overestimates. After generating the post-branching kinematics (see, e.g., [17, 18]), the total probability for accepting a branching (denoting pre-branching partons by

*AB*and post-branching ones by

*ijk*)

^{2}is:

*ijk*partons, with each term, \(\mathcal {A}\left( h_{A},h_{B};h_{i},h_{j},h_{k}\right) \), being a helicity-dependent antenna function. To avoid clutter, and for ease of reference, we collect the precise forms for these functions in the appendix. We note that some of the functions differ (by nonsingular terms) from those used in previous versions of Vincia, in particular those in [7, 18]. We also note that the accept probability defined by Eq. (7) is in general identical to the unpolarised one (i.e., where one averages over \(h_{A}\) and \(h_{B}\) as well), up to nonsingular terms. In case of initial-state radiation, Eq. (7) will be multiplied with the accept probability for the PDF ratios, just as in the unpolarised case [18].

Helicity conservation implies that, for gluon emission off (massless) quarks or final-state gluons, the parent partons do not change their helicities. A subtlety arises, however, for emissions off initial-state gluons. In the perspective of forwards evolution, such a branching looks like \(g_{i}^\mathrm {\,I}\rightarrow g_{A}^\mathrm {\,I} g_{j}^\mathrm {\,F}\), where superscript *I* (*F*) denotes an initial-state (final-state) parton; clearly, the helicity of parton *i* can be inherited by either parton *j* or parton *A* without violating helicity conservation. Hence the reader should not be confused by the appearance of physical initial-state antenna functions for which \(h_A \ne h_i\) in Appendices A.3 and A.4, with corresponding DGLAP limits given in Appendix A.6.

*nonsingular terms*of the antenna functions to estimate how close a given branching is to the logarithmically-dominated region, and (2) variations of the antenna-function

*renormalisation scale*to estimate the potential impact of subleading-logarithmic terms. We emphasise that both types of variations are performed so that they preserve the total cross section (i.e., the variations appear with equal and opposite signs in real and virtual corrections, respectively [22]). The technical implementation in Vincia is quite similar to that in Pythia 8; see the respective HTML User Manuals and Appendix B. The variation of the renormalisation scale in a helicity-dependent shower is performed just as for an unpolarised shower,

*t*and \(m_\mathrm {ant}\) the mass of the parent antenna. The prefactor

*z*is \(s_{ik}/m^2_\mathrm {ant}\) for final-final and \(m^2_\mathrm {ant}/\mathrm {max}(s_{ik},m^2_\mathrm {ant}+s_{jk})\) for initial-initial and initial-final branchings, with the post-branching invariants \(s_{ij}\), \(s_{jk}\), and \(s_{ik}\), The variation of the antenna functions by nonsingular terms,

For any given (bin of a) physical observable, a large dependence on \(C_\mathrm {NS}\) indicates that corrections from hard matrix elements with higher numbers of legs are needed, while a significant dependence on the renormalisation scale indicates a need for further corrections at the loop level.

Finally, it is worth emphasising that the statistical fluctuations of the uncertainty variations are generally larger than for the central (non-varied) predictions. This is due to the central prediction being unweighted (in our setup) and the variations being computed by reweighting. See [23] for an example of how weighting (“biasing”) the central distribution can improve the relative statistical precision of the uncertainty bands.

## 3 Matrix-element corrections and MHV amplitudes in Vincia

### 3.1 Matrix-element corrections

The GKS formalism for iterated matrix-element corrections [16] was originally based on so-called smoothly ordered showers, with a Markovian (history-independent) choice of restart scale after each branching. This allows the shower algorithm to generate phase-space points that violate the nominal ordering condition of the shower, at a suppressed but still non-zero rate, thus filling previously inaccessible regions of phase space; the correct (tree-level) emission rates can then be obtained via matrix-element corrections just as in the ordered part of phase space. However, general arguments indicate that the effective Sudakov factors for the non-ordered histories, are probably not correct [18, 24, 25]. Recent efforts [19, 25] have therefore shifted focus back to filling the phase space for multiple hard emissions while remaining within the paradigm of strong ordering. In particular, we take the strongly-ordered iterated-MEC formalism presented in [19] as our starting point, and adapt it to include explicit helicities.

The question of Markovian vs non-Markovian behaviour comes about since the value of the shower evolution parameter in conventional strongly-ordered showers depends on which parton was the last one to be emitted. This cannot be uniquely determined merely by considering a given parton configuration; the value is a function of what shower history (or path) led to the configuration in question; a non-Markovian aspect. In the context of iterated ME corrections, non-Markovianity implies that the MEC factors contain nested sums over shower histories involving clusterings all the way back to the Born configuration (while a Markovian algorithm only requires a single level of clusterings [16]).

For a helicity-dependent correction, we modify Eq. (12) such that, for a given polarised \(\Phi _n\) state, the sums over the intermediate states \(\Phi _{n-1}\cdots \Phi _0\) are extended to include all possible helicity configurations. As an example, consider a possible clustering of a final-state \(q\bar{q}\) pair to a gluon. In the unpolarised case, one term corresponding to the clustering \(q\bar{q}\rightarrow g\) contributes with the respective unpolarised antenna function and matrix element (which both implicitly involve helicity sums of course). For a polarised \(q_+\bar{q}_-\) pair, two different clustered helicity states are possible, \(q_+\bar{q}_-\rightarrow g_+\) and \(q_+\bar{q}_-\rightarrow g_-\), each contributing according to their antenna function and matrix element. The evolution variable, however, is the same as in the unpolarised case. This concludes our discussion of helicity-dependent matrix element corrections.

### 3.2 MHV basics

For fast evaluation of certain types of helicity configurations Vincia uses maximally helicity violating (MHV) amplitudes. MHV amplitudes have the advantage of being compact analytical expressions which are independent of Feynman diagrams; see [26, 27] for reviews. In this section, we briefly introduce the concepts and notation relevant to understanding the conventions and properties of the small library of MHV amplitudes implemented in Vincia.

*ij*] is used for inner products of such spinors:

In the all-outgoing convention, helicity conservation implies that at least two pairs of opposite-helicity partons must exist for an *n*-parton amplitude to be nonzero.^{3} If the remaining \(n-4\) partons are all chosen to be of the same helicity (\(+\) or −), the amplitude is called maximally helicity violating (MHV), and has a remarkably simple structure. The first MHV amplitude to be discovered was the all-gluon Parke-Taylor amplitude [29]. In the following years this was extended to include one [30, 31] and two [32, 33, 34] quark pairs, as well as to the case of a quark pair and a massive vector boson which decays leptonically [35, 36].

*All-gluon amplitudes:*To use these amplitudes we first note that the colour information can be factorised from the kinematics. In the

*n*-point all-gluon case we use:

*SU*(3), \(p_i\) is the gluon momentum, \(h_i\) the gluon helicity, \(\text {Tr} ( t^{a_{\sigma (1)}} \cdots t^{a_{\sigma (1)}})\) the colour factor and \(A_n(\sigma (p_1^{h_1}), \ldots , \sigma (p_n^{h_n}))\) the kinematic part of the amplitude. The sum is over all non-cyclic permutations \(\sigma \) of the particles. The Parke–Taylor amplitude then describes the kinematic part of Eq. (16) and is given by:

*i*and

*j*have negative helicity, and all other particles have positive helicity.

*One quark pair:*If we add a \(q\bar{q}\) pair we require that the quark and antiquark have opposite helicities (consistent with the gluon having spin 1), and use the following colour basis:

*q*, \(h_q\), and

*i*(\(\bar{q}\), \(h_{\bar{q}}\), and

*j*) are respectively the quark (anti-quark) momentum, helicity, and colour index; and the sum is over all permutations of the gluons. If the quark and gluon

*i*each have negative helicity and all other particles positive helicity, then the kinematic amplitude is the given by:

*Two quark pairs:*The four-quark, \(n-4\) gluon colour structure is given by:

*q*and

*Q*label the two quark lines; \(A_0(h_q,h_Q,h_g)\) is a kinematic function which depends on the helicities of the two quarks and the gluons,with opposite-helicity cases obtained using parity transformation \(\langle ij \rangle \leftrightarrow [ji]\); and the two functions \(A_n^{(0)}\) and \(A_n^{(1)}\) are kinematic amplitudes, for which we have used the short-hand notation \(q \equiv q^{h_q}\), \(i \equiv \sigma (p_i^{h_i})\) etc.:

*Drell-Yan, DIS, and hadronic Z decays:*To create MHV amplitudes with a single quark pair, a single lepton pair, and an arbitrary number of gluons, the four-quark amplitude can be recycled with all gluons coming from a single quark line. The second quark line is now equivalent to a \(l \bar{l}\) pair up to couplings and an overall propagator factor. The amplitude then has the form

*l*(quark

*q*) with helicity \(h_l\) (\(h_q\)) to vector

*V*, and \(M_V\) and \(\Gamma _V\) are the mass and width of the vector boson respectively.

Finally, we remark that in all of the above expressions, flipping the helicity of every particle is equivalent to exchanging each \(\langle i j \rangle \leftrightarrow [j i]\). This concludes our brief recapitulation of the basics of the MHV formalism and convention choices.

### 3.3 MHV within Vincia

The types of processes available in Vincia ’s MHV library

Type of process | Number of particles |
---|---|

All-gluon | 4–6 |

1 quark pair plus gluons | 4–7 |

2 quark pairs plus gluons | 4, 5 |

1 lepton pair, 1 quark pair plus gluons | 4–9 |

By default, Vincia uses MHV amplitudes wherever possible to compute its matrix-element correction factors, thus ensuring the fastest possible run time. However, this can be turned off (e.g., for cross checks with amplitudes from Madgraph) using the flag vincia:useMHVamplitudes. To calculate an MHV ME correction, Vincia actively crosses the initial-state partons into the final state, rearranges the partons into the correct colour order, calculates all of the explicit spinor products needed, and then calculates the matrix element squared.

The calculation of ME corrections for MHV configurations exhibits the nice feature that all clustered states in Eq. (12) are MHV configurations as well. Helicity conservation does not allow \(++\rightarrow -\) nor \(--\rightarrow +\) clusterings (in the all-outgoing convention). This results in clustered states being either MHV configurations themselves or unphysical states with a vanishing amplitude. Consider *n* positive- and 2 negative-helicity outgoing partons as an example. Here clustered states contain either \(n-1\) positive- and 2 negative-helicity partons (MHV) or *n* positive- and 1 negative-helicity partons (unphysical).

For instructions on how to use Vincia for calculating spinor products or MHV amplitude in a standalone context, see the online user guide [37].

### 3.4 Polarising events with MHV

*h*is a label denoting the helicity assignments, \(M_n^h \equiv |A_n^h(1, \ldots , n)|^2\) is some function of the helicities and momenta, \(\sigma \) is the relevant set of permutations, CF is the relevant colour factor at the amplitude level, and \(\left| \sum _{\sigma } F(\sigma ) \right| ^2\) is the square of the sum over colour permutations. For example, in the all-gluon amplitude \(A_n^h(1, \ldots , n)\) could be \(\langle i j \rangle ^4\). We have therefore factored out the helicity information \(M_n^h\) from the colour information. This also works for the LC matrix elements \(\mathrm {LC}^h_i\) which are given by Eq. (29) above without the sum of permutations. That is, \(\mathrm {LC}^h_i = M_n^h \left| F(\sigma _i) \right| ^2\). Recall that the conditional probability defined in (6) used to pick helicities for configurations that already have colour assignments has the form:

### 3.5 Speed comparisons

At the level of a pure shower (before ME corrections are imposed), the change from helicity-summed to helicity-sampling radiation functions requires the generation of one more random number per \(n \rightarrow n+1\) branching, to select the helicity of the emitted parton. This comes in addition to at least three random numbers for the one-particle phase space. All else being equal, a helicity-sampling shower should therefore not be more than a factor 4/3 slower than a helicity-summed one. (Similar arguments hold for the initial polarisation step for the hard process). However, since there are many common components which must be computed regardless of the choice of helicity treatment, one expects the effective slowdown of the full shower algorithm to be milder than this upper limit. This is also borne out by explicit tests with Vincia, which exhibit slowdowns of less than 10% when switching on helicity-sampling. (See also the first bin of Fig. 1 below.)

*pp*collisions with \(E_\mathrm {cm} = 10~\mathrm {TeV}\). A technical point is that, for this comparison, we switch \(g\rightarrow q\bar{q}\) branchings off in the shower, so that the generated shower configurations are all of the simple \(qg\rightarrow qg + \mathrm {gluons}\) type. This allows us to illustrate speeds of ME corrections with up to three additional legs while, if \(g\rightarrow q\bar{q}\) branchings had been switched on, the current version of Vincia is restricted to ME corrections with up to two additional legs. (This restriction will be lifted in a future update.)

^{4}For 0 or 1 corrected emissions, the helicity-summed shower is actually slightly faster, since the Born-level polariser and the helicity selection in the shower take a little extra time and the first-order ME corrections are very quick to evaluate even when summing over helicities. At two legs, however, the helicity-dependent formalism is up to 30% quicker (with the MHV library switched on) than the helicity-summed one. At three legs, the difference is a factor 4, with the MHV library allowing to shave an extra \(\sim 15\%\) off the shower-generation time relative to using only MG4 matrix elements.

One also notices that by two corrected legs, the showering time is becoming comparable to the time it takes to generate MPI and hadronisation for the events, hence this is the point at which the showering speed would start to be felt in the context of generating full events. By three corrected legs, the ME corrections dominate the event-generation time. The default in the current version of Vincia is that ME corrections are enabled for QCD \(2\rightarrow 2\) processes up to two additional legs; the event-generation time should therefore stay within roughly a factor 2 of that of the uncorrected algorithm. The complete set of matrix elements required for 3rd-order corrections will be provided in a future update. For hadronic *Z*, *W*, and *H* production or decay, the full set of 3rd-order matrix elements are already available in the current version. (We note that the implementation of the iterated-MEC algorithm itself is general and could in principle handle any number of legs, if provided with the required matrix elements.)

## 4 Example application

- 1.
*Early branchings*the 3-jet resolution scale, \(d_{23}\), using the longitudinally invariant \(k_\perp \)-jet algorithm [38] with \(R = 0.4\). The implementation of the algorithm is adapted from the code used in [39], originally written by S. Höche. - 2.
*Late branchings*the 6-jet \(k_\perp \) resolution scale, \(d_{56}\), with the same jet algorithm as above. - 3.
*Gluon polarisation*the angle between the event plane (characteristic of the original \(gg\rightarrow gg\) Born-level event) and the plane of a subsequent \(g\rightarrow b\bar{b}\) splitting. Here, the FastJet [40] implementation of the anti-\(k_\perp \) jet algorithm [41] is used, with \(R=0.2\) (so that the*b*jets can be resolved down to small separations), and we impose a minimum jet \(p_\perp \) of \(50\,\mathrm {GeV}\). (For further ideas on how to exploit heavy-flavour tags to probe \(g\rightarrow q\bar{q}\) splittings at colliders, see e.g. [42, 43].)

To obtain dimensionless variables, the jet resolution measures \(d_{23}\) and \(d_{56}\) are normalised by a factor \(1/d_{12}\), i.e., they are effectively measured relative to a scale representing the \(\hat{p}_\perp ^2\) scale of the underlying Born process.^{5} The resulting quantities exhibit a fixed-order behaviour for large values and a Sudakov suppression for low values. Especially for well-resolved radiation, we therefore expect these observables to be sensitive to low-order ME corrections, and hence the uncertainty associated with nonsingular-term variations should be reduced when Vincia ’s ME corrections are switched on. (Note: Pythia does not incorporate ME corrections for QCD \(2\rightarrow 2\) processes.) Parton-level results for showered \(gg\rightarrow gg\) events are presented in Fig. 2 with uncertainty bands.

The ME corrections in strongly-ordered events exhibit a modest effect of up to \(20\%\) for large values of \(d_{23}/d_{12}\) and \(d_{56}/d_{12}\), with the ME-corrected rate being larger than that of the pure Vincia shower. Shape differences between the predictions of Pythia and Vincia are visible throughout most of the distributions, with the uncorrected Vincia shower generating a somewhat harder \(d_{23}/d_{12}\) spectrum than Pythia. ME corrections increase the rate for large \(d_{56}/d_{12}\) values, bringing the predictions of Vincia closer to that of Pythia. Given the different choices of shower \(\alpha _s\) parameters, evolution variable, and radiation functions, we do not consider this level of disagreement between the two models surprising. The evolution of the hard process starts at the factorisation scale for both showers. However, depending on the form of evolution variable, the hardest possible scales correspond to different values of \(d_{23}\).

All predictions exhibit some rather large fluctuations in the uncertainty bands. The dijet system with the cut \(\hat{p}_\perp \ge 500\,\mathrm {GeV}\) as underlying hard process is typically accompanied by a large number of additional jets. Given the nature of the reweighting algorithm of [22] (and similarly for [23, 44]) this may easily result in fluctuating weights. In addition we expect larger fluctuations in the nonsingular-term variations for the helicity shower, compared to the helicity-independent one. As discussed in Sect. 2, the additional nonsingular terms are distributed evenly between all helicity configurations. This results in a larger spread of weights, when considering helicity configurations that constitute either a large or a small fraction of the helicity-summed antenna functions. To mitigate the effects of weight fluctuations, we conclude that further development of these reweighting methods would be useful, in particular for large phase spaces (long shower chains). E.g., the authors in [23] have demonstrated that combining biasing with reweighting can improve the relative statistical precision of the uncertainty variations, at the price of generating some reasonably well-behaved weights for the central (non-varied) event sample.

We now turn to an observable where polarisation effects are expected to contribute. In events with two *b*-jets a plane is defined by the two jets. A second plane is defined by the gluon-jet (the sum of the two *b*-jets) and the beam axis. In Fig. 3 the angle between the two planes is shown. A flat distribution is obtained with Pythia without gluon polarisation effects in the final-state shower and Vincia without ME corrections. However, Vincia produces an around \(15\%\) higher total rate, compared to Pythia. We note that both codes generate a similar total rate of \(g\rightarrow b\bar{b}\) splittings in the shower, where the gluon splittings occur “later” in the evolution in Pythia (i.e., preceded by a larger number of other branchings). The *b*-quarks are therefore more likely to obtain a smaller invariant mass and might be clustered within the same jet. Together with the \(p_\perp \) and invariant mass cuts on the jets, this may cause a smaller rate of events with two *b*-jets. The polarisation effects in Pythia leave the total rate unchanged, but increase the amount of events where the angle is close to \(\pi /2\). The ME corrections in Vincia change the total rate by decreasing the number of events with splitting angles near 90\(^\circ \). The qualitative effect is therefore the *opposite* of that in Pythia, where the total shower rate is preserved, but the region around 90\(^\circ \) is enhanced by the polarisation effect. We conclude that a measurement of this observable, and the development of alternative strategies for corrections beyond fixed order (e.g., along the lines proposed in [25]), would be desirable.

## 5 Conclusions

We have presented a helicity-dependent antenna shower for QCD initial- and final-state radiation, implemented in the Vincia shower model. The iterated ME correction formalism of [7, 16, 18, 19] has been extended to cope with helicity-dependent clusterings and splitting kernels involving initial-state legs, and in this work has been applied to strongly ordered showers in a direct extension of the formalism presented in [19]. We further reported on new, user-specifiable uncertainty variations in Vincia, including renormalisation-scale and splitting-kernel variations.

The new approach and a library for tree-level MHV amplitudes enable a faster evaluation of MEC factors, as illustrated explicitly for the process \(qg\rightarrow qg\,+\) gluons. While the pure shower is slightly slower due to the additional step of helicity selection, the evaluation of ME corrections can be done significantly faster when only a single or a few helicity matrix elements need to be evaluated per trial branching, relative to when helicity-summed matrix elements are used.

To illustrate the effect of the iterated ME corrections and uncertainty variations within the helicity-dependent shower, we considered a few representative observables, based on showered \(gg\rightarrow gg\) Born-level events. As expected, ME corrections reduce the overall amount of variation considerably in regions of relatively hard emissions, where process-dependent nonsingular terms (captured by the matrix elements) dominate over the universal logarithmic terms (captured by the showers). In regions of large scale hierarchies, the uncertainty due to renormalisation-scale variations dominates and remains uncompensated by tree-level ME corrections.

We also showed a more complex example, the angle between a Born-level \(gg\rightarrow gg\) event plane and the plane of a subsequent \(g\rightarrow b\bar{b}\) splitting. In Pythia, a general implementation of gluon polarisation effects implies an enhancement of such splittings at 90 degrees to the original event plane (while the total shower rate of \(g\rightarrow b\bar{b}\) splittings is preserved); while in Vincia, ME corrections dominantly act to suppress the overall rate of \(g\rightarrow b\bar{b}\) splittings. Moreover, the suppression is most active for the most well-resolved branchings (at 90 degrees), leading to an opposite-sign effect than the one in Pythia. We conclude that there is a complex interplay between the rate and the angular dependence of these branchings, and intend to investigate this further in future studies.

## Footnotes

- 1.
We note that a form of iterated ME corrections is also used throughout the Pythia showers to impose quark-mass corrections [11], but the resulting process-dependent nonsingular terms will still only be fully correct for the first emission.

- 2.
This is the same labelling convention as used in the Vincia reference for final-state helicity showers [7].

- 3.
E.g., think of \(++ \rightarrow ++\) and cross the two incoming positive helicities to be outgoing negative ones.

- 4.
The thickness of the dashed line reflects that the helicity-dependent showers result in slightly longer MPI generation times due to the slightly slower showering off the MPI systems.

- 5.
This is similar to how, e.g., \(m_Z^2\) is used to normalise corresponding observables in \(e^+e^-\) collisions at the

*Z*pole. - 6.
Additional with respect to the final-state antenna functions.

- 7.
Additional with respect to the final-state antenna functions.

## Notes

### Acknowledgements

AL and PS acknowledge support from the Monash–Warwick Alliance Development Fund Project “Collider Physics”. PS is the recipient of an Australian Research Council Future Fellowship, FT130100744.

## References

- 1.T. Sjöstrand, S. Ask, J.R. Christiansen, R. Corke, N. Desai, P. Ilten, S. Mrenna, S. Prestel, C.O. Rasmussen, P.Z. Skands, An introduction to PYTHIA 8.2. Comput. Phys. Commun.
**191**, 159–177 (2015). arXiv:1410.3012 ADSCrossRefMATHGoogle Scholar - 2.B.R. Webber, Monte Carlo simulation of hard hadronic processes. Ann. Rev. Nucl. Part. Sci.
**36**, 253–286 (1986)ADSCrossRefGoogle Scholar - 3.J. Bellm et al., Herwig 7.1 release note. arXiv:1705.06919
- 4.I.G. Knowles, Spin correlations in parton–parton scattering. Nucl. Phys. B
**310**, 571–588 (1988)ADSCrossRefGoogle Scholar - 5.I.G. Knowles, A linear algorithm for calculating spin correlations in hadronic collisions. Comput. Phys. Commun.
**58**, 271–284 (1990)ADSCrossRefGoogle Scholar - 6.P. Richardson, Spin correlations in Monte Carlo simulations. JHEP
**11**, 029 (2001). arXiv:hep-ph/0110108 ADSCrossRefGoogle Scholar - 7.A.J. Larkoski, J.J. Lopez-Villarejo, P. Skands, Helicity-dependent showers and matching with VINCIA. Phys. Rev. D
**87**(5), 054033 (2013). arXiv:1301.0933 - 8.M. Bengtsson, T. Sjöstrand, Coherent parton showers versus matrix elements: implications of PETRA–PEP data. Phys. Lett. B
**185**, 435 (1987)ADSCrossRefGoogle Scholar - 9.M. Bengtsson, T. Sjöstrand, A comparative study of coherent and noncoherent parton shower evolution. Nucl. Phys. B
**289**, 810 (1987)ADSCrossRefGoogle Scholar - 10.G. Miu, T. Sjostrand, \(W\) production in an improved parton shower approach. Phys. Lett. B
**449**, 313–320 (1999). arXiv:hep-ph/9812455 ADSCrossRefGoogle Scholar - 11.E. Norrbin, T. Sjostrand, QCD radiation off heavy particles. Nucl. Phys. B
**603**, 297–342 (2001). arXiv:hep-ph/0010012 ADSCrossRefGoogle Scholar - 12.M.H. Seymour, Matrix element corrections to parton shower algorithms. Comput. Phys. Commun.
**90**, 95 (1995). arXiv:hep-ph/9410414 ADSCrossRefGoogle Scholar - 13.G. Corcella, M.H. Seymour, Matrix element corrections to parton shower simulations of heavy quark decay. Phys. Lett. B
**442**, 417 (1998). arXiv:hep-ph/9809451 ADSCrossRefGoogle Scholar - 14.P. Nason, A New method for combining NLO QCD with shower Monte Carlo algorithms. JHEP
**11**, 040 (2004). arXiv:hep-ph/0409146 ADSCrossRefGoogle Scholar - 15.S. Frixione, P. Nason, C. Oleari, Matching NLO QCD computations with parton shower simulations: the POWHEG method. JHEP
**11**, 070 (2007). arXiv:0709.2092 ADSCrossRefGoogle Scholar - 16.W.T. Giele, D.A. Kosower, P.Z. Skands, Higher-order corrections to timelike jets. Phys. Rev. D
**84**, 054003 (2011). arXiv:1102.2126 ADSCrossRefGoogle Scholar - 17.W.T. Giele, D.A. Kosower, P.Z. Skands, A simple shower and matching algorithm. Phys. Rev. D
**78**, 014026 (2008). arXiv:0707.3652 ADSCrossRefGoogle Scholar - 18.N. Fischer, S. Prestel, M. Ritzmann, P. Skands, Vincia for hadron colliders. Eur. Phys. J. C
**76**(11), 589 (2016). arXiv:1605.06142 - 19.N. Fischer, S. Prestel, Combining states without scale hierarchies with ordered parton showers. arXiv:1706.06218
- 20.J. Alwall, P. Demin, S. de Visscher, R. Frederix, M. Herquet, F. Maltoni, T. Plehn, D.L. Rainwater, T. Stelzer, MadGraph/MadEvent v4: the new web generation. JHEP
**09**, 028 (2007). arXiv:0706.2334 ADSCrossRefGoogle Scholar - 21.V. Hirschi et al., (2017, work in progress)Google Scholar
- 22.S. Mrenna, P. Skands, Automated parton-shower variations in Pythia 8. Phys. Rev. D
**94**(7), 074005 (2016). arXiv:1605.08352 - 23.J. Bellm, S. Plätzer, P. Richardson, A. Siódmok, S. Webster, Reweighting parton showers. Phys. Rev. D
**94**(3), 034028 (2016). arXiv:1605.08256 - 24.L. Hartgring, E. Laenen, P. Skands, Antenna showers with one-loop matrix elements. JHEP
**10**, 127 (2013). arXiv:1303.4974 ADSCrossRefGoogle Scholar - 25.H.T. Li, P. Skands, A framework for second-order parton showers. Phys. Lett. B
**771**, 59–66 (2017). arXiv:1611.00013 - 26.M.L. Mangano, S.J. Parke, Multiparton amplitudes in gauge theories. Phys. Rep.
**200**, 301 (1991). arXiv:hep-th/0509223 ADSCrossRefGoogle Scholar - 27.L.J. Dixon, Calculating scattering amplitudes efficiently. in
*QCD and beyond. Proceedings, Theoretical Advanced Study Institute in Elementary Particle Physics, TASI-95, Boulder, USA, June 4–30, 1995*, pp. 539–584 (1996). arXiv:hep-ph/9601359 - 28.L.J. Dixon, A brief introduction to modern amplitude methods. in
*Proceedings, 2012 European School of High-Energy Physics (ESHEP 2012): La Pommeraye, Anjou, France, June 06–19, 2012*, pp. 31–67 (2014). arXiv:1310.5353 - 29.S.J. Parke, T. Taylor, An amplitude for \(n\) gluon scattering. Phys. Rev. Lett.
**56**, 2459 (1986)ADSCrossRefGoogle Scholar - 30.Z. Kunszt, Combined use of the Calkul method and N=1 supersymmetry to calculate QCD six parton processes. Nucl. Phys. B
**271**, 333 (1986)ADSCrossRefGoogle Scholar - 31.M.L. Mangano, S.J. Parke, Quark—gluon amplitudes in the dual expansion. Nucl. Phys. B
**299**, 673 (1988)ADSCrossRefGoogle Scholar - 32.Z. Xu, D.-H. Zhang, L. Chang, Helicity amplitudes for multiple Bremsstrahlung in massless nonabelian gauge theories. Nucl. Phys. B
**291**, 392 (1987)ADSCrossRefGoogle Scholar - 33.J.F. Gunion, Z. Kunszt, Four jet processes: gluon-gluon scattering to nonidential quark–anti-quark pairs. Phys. Lett. B
**159**, 167 (1985)ADSCrossRefGoogle Scholar - 34.J.F. Gunion, Z. Kunszt, Addendum concerning the four quark two gluon subprocess. Phys. Lett. B
**176**, 477 (1986)ADSCrossRefGoogle Scholar - 35.F.A. Berends, W.T. Giele, Recursive calculations for processes with n gluons. Nucl. Phys. B
**306**, 759 (1988)ADSCrossRefGoogle Scholar - 36.M.L. Mangano, The color structure of gluon emission. Nucl. Phys. B
**309**, 461 (1988)ADSCrossRefGoogle Scholar - 37.P. Skands et al., VINCIA user reference (2017). http://vincia.hepforge.org/current/share/Vincia/htmldoc/
- 38.S.D. Ellis, D.E. Soper, Successive combination jet algorithm for hadron collisions. Phys. Rev. D
**48**, 3160–3166 (1993). arXiv:hep-ph/9305266 ADSCrossRefGoogle Scholar - 39.S. Höche, S. Prestel, The midpoint between dipole and parton showers.
*Eur. Phys. J. C***75**(9), 461 (2015). arXiv:1506.05057 - 40.M. Cacciari, G.P. Salam, G. Soyez, FastJet user manual. Eur. Phys. J. C
**72**, 1896 (2012). arXiv:1111.6097 ADSCrossRefGoogle Scholar - 41.M. Cacciari, G.P. Salam, G. Soyez, The anti-k(t) jet clustering algorithm. JHEP
**04**, 063 (2008). arXiv:0802.1189 ADSCrossRefMATHGoogle Scholar - 42.B. Nachman, \(g \rightarrow b \bar{b}\) studies at the LHC. in
*Proceedings, Parton Radiation and Fragmentation from LHC to FCC-ee: CERN, Geneva, Switzerland, November 22–23, 2016*, pp. 139–143 (2017). arXiv:1702.01329 - 43.P. Ilten, N.L. Rodd, J. Thaler, M. Williams, Disentangling heavy flavor at colliders. arXiv:1702.02947
- 44.E. Bothmann, M. Schönherr, S. Schumann, Reweighting QCD matrix-element and parton-shower calculations. Eur. Phys. J. C
**76**(11), 590 (2016). arXiv:1606.08753 - 45.L. Lönnblad, ARIADNE version 4: a program for simulation of QCD cascades implementing the color dipole model. Comput. Phys. Commun.
**71**, 15 (1992)ADSCrossRefGoogle Scholar - 46.S. Catani, B.R. Webber, G. Marchesini, QCD coherent branching and semiinclusive processes at large
*x*. Nucl. Phys. B**349**, 635 (1991)ADSCrossRefGoogle Scholar - 47.T. Plehn, D. Rainwater, P.Z. Skands, Squark and gluino production with jets. Phys. Lett. B
**645**, 217–221 (2007). arXiv:hep-ph/0510144 ADSCrossRefGoogle Scholar - 48.L. Lönnblad, S. Prestel, Matching tree-level matrix elements with interleaved showers. JHEP
**03**, 019 (2012). arXiv:1109.4829 CrossRefGoogle Scholar

## Copyright information

**Open Access**This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Funded by SCOAP^{3}