The antenna shower model was initially developed as a standalone plugin (VINCIA), but since Pythia version 8.300 it has been incorporated into the Pythia 8 source code.
The shower evolution is driven by 2→3 antenna functions which have DGLAP kernels as their collinear limits and eikonal factors as their soft limits. They hence should exhibit improved colour coherence effects relative to the old (DGLAP-based) simple shower model. Likewise, the QED antenna-shower module is based on a fully coherent (multipole) treatment of photon radiation patterns. For both QCD and QED, the effects of parton masses (e.g., bottom and top quark masses) are systematically included, and the massive antenna functions have the appropriate quasi-collinear limits.
mode Vincia:nFlavZeroMass
(default = 4; minimum = 2; maximum = 6)flag Vincia:helicityShower
(default = off)
Similarly to PYTHIA, for processes that include at least one quark,
gluon, or photon in the
final state, the default choice in VINCIA is to start the shower from the
factorisation scale used for the hard process (as given by
PYTHIA for internal
processes, or defined by the scale value for Les Houches
input),while processes
that do not include any such partons are allowed to populate the full
phase space. This behaviour can be changed by the following option,
which is anologous to the SpaceShower:PTmaxMatch option
in PYTHIA.
mode Vincia:pTmaxMatch
(default = 0; minimum = 0; maximum = 2)option 0 : Showers off processes that include at least one
final-state quark, gluon, or photon, are started at the factorisation
scale, while processes that do not include any such partons are
started at the phase-space maximum.
option 1 : Showers are always started at the factorisation
scale.
option 2 : Showers are always started at the phase-space
maximum. This option is not recommended for physics runs as it will
lead to unphysical double counting in many cases.
When the first branching is limited by the factorisation scale for the hard process, a multiplicative factor can be applied to either increase or decrease the shower starting scale relative to the factorisation scale:
parm Vincia:pTmaxFudge
(default = 1.0; minimum = 0.1; maximum = 10.0)parm Vincia:pTmaxFudgeMPI
(default = 1.0; minimum = 0.1; maximum = 10.0)Note that for any (combination of) choices that result in ISR showers not using the factorisation scale as the starting scale, the generated Sudakov factor will effectively produce leftover PDF ratios in the exclusive cross sections produced by the shower.
VINCIA's shower evolution can be biased to populate the multi-jet phase space more efficiently and/or enhance the rate of rare processes such as g→bb and g→cc splittings. It is also possible to inhibit radiation (e.g., to focus on Sudakov regions), by choosing enhancement factors smaller than unity. When these options are used, it is important to note that the event weights will be modified, reflecting that some types of events (e.g., multijet events, or events with gluon splittings to heavy quarks) will be "overrepresented" statistically, and others (events with few jets, or events with no gluon splittings to heavy quarks) underrepresented. Averages and histograms will therefore only be correct if computed using the correct weight for each generated event. A description and proof of the algorithm can be found in [MS16]. Note that care has been taken to ensure that the weights remain positive definite; under normal circumstances, VINCIA's enhancement algorithm should not result in any negative weights.
flag Vincia:enhanceInHardProcess
(default = on)flag Vincia:enhanceInResonanceDecays
(default = on)flag Vincia:enhanceInMPIshowers
(default = off)parm Vincia:enhanceFacAll
(default = 1.0; minimum = 0.01; maximum = 100.0)parm Vincia:enhanceFacBottom
(default = 1.0; minimum = 1.0; maximum = 100.0)Vincia:biasAll.
parm Vincia:enhanceFacCharm
(default = 1.0; minimum = 1.0; maximum = 100.0)Vincia:enhanceFacBottom but for charm quarks.
Note: this factor is applied on top of Vincia:biasAll.
parm Vincia:enhanceCutoff
(default = 10.0; minimum = 0.0; maximum = 1000.0)VINCIA has its own set of dedicated tune presets, which can be specified by the user.
mode Vincia:Tune
(default = 0; minimum = -1; maximum = 0)option -1 : None. No VINCIA-specific tune parameter settings
will be used during initialisation.
option 0 : Hadronisation and MPI parameters optimised for use
with the VINCIA shower model, used as default VINCIA parameters
since PYTHIA 8.302.
Note: the requested tune parameters will only be activated when VINCIA is switched on, in order not to interfere with the PYTHIA settings when VINCIA is switched off.
Note 2: as with ordinary Pythia tune parameters, the tuned parameter values will be superseded by any user modifications made in the user's command file or main program. This should allow sufficient flexibility to explore user variations away from the tuned values.
Although there are obviously parameters that it makes more sense to tune than others, there is no explicit restriction imposed on what parameters are allowed to be present in the tune file. This implies some responsibility on the part of the user.
As a guideline, the main parameters that need to be properly tuned are the non-perturbative hadronisation parameters used in PYTHIA's string fragmentation model. Since PYTHIA and VINCIA treat soft radiation somewhat differently, there can be important differences between the two in the soft region that the hadronisation model will not re-absorb automatically and which therefore only a retuning can address.
The strategy used for the default tune of VINCIA is to take the reference value for alphaS from the current world average value in the MSbar scheme, and let the effective shower scheme tuning be done by first translating to the CMW scheme and then fine-tune by modifying the renormalisation-scale prefactors used for shower branchings.
An alternative (but equivalent) strategy that is often used in PYTHIA tunes, is to perceive of the value of the strong coupling itself as a tuning parameter. In this case the interpretation is that extracting alphaS from, e.g., event shapes, can be done equally well using a shower code as with more analytical approaches. The difference is that the alphaS value extracted with the shower code is in an a priori unknown scheme, defined by the shower algorithm. If the shower only includes LO/LL accuracy for the given observable(s), the extraction should be compared with other LO/LL extractions. This typically yields alphaS values ~ 0.13 - 0.14. When explicit NLO corrections are included for the relevant observable(s), values comparable to other NLO extractions should result, around 0.12.
The main references for the current version of VINCIA are:
The name VINCIA stands for "VIrtual Numerical Collider with Interleaved Antennae". The naming of VINCIA is intended to allude to a progression from PYTHIA - a name originating in ancient Greece - to the renaissance era of Leonardo da Vinci. The logo of VINCIA is the "Vitruvian Man", by da Vinci, a choice which also reflects the combination of art and accuracy which is necessary to write a good event generator. Classical antiquity is still indirectly represented, via the namesake of the logo, Vitruvius, a first-century (BC) Roman author, architect, and engineer.
flag Vincia:sectorShower
(default = off)parm Vincia:sectorDamp
(default = 0.0; minimum = 0.0; maximum = 1.0)sectorDamp
parameter produces sector antenna functions which have slightly
smaller magnitudes outside the collinear limits. Strictly speaking
this choice is an ambiguity that should be varied for uncertainty
estimates, in which context we note that we expect it to be
almost entirely degenerate with variations of nonsingular terms.
Within the antenna formalism, the collinear singularity of two gluons j and k is distributed between two neighboring antennae. One contains the singularity for j becoming soft, one the singularity for k becoming soft. In showers based on so-called global antenna functions (as opposed to sector functions, which are no longer implemented in VINCIA), the two antennae share the collinear singularity, j||k, point by point in phase space, and only after summing over both is the full collinear AP splitting kernel recovered. The parameter below controls the repartition ambiguity and gives the value of "half" the gluon splitting function on its finite end.
parm Vincia:octetPartitioning
(default = 0.0; minimum = 0.0; maximum = 1.0)mode Vincia:verbose
(default = 1; minimum = 0; maximum = 9)VINCIA. Settings different from zero and one are intended
for debugging purposes and hence should not be used for normal runs.
option 0 : No runtime output.
option 1 : Normal runtime output. Warnings and errors are
printed, but no additional diagnostic output is given.
option 2 : Enhanced runtime output. As for =1, but limited
additional diagnostic info is given. Some
previously silent warnings are added. Also, internal VINCIA
diagnostics histograms are booked and filled, especially for
matching. These can be printed by the user at any time (e.g., after
a run) using the VinciaPlugin::printHistos()
method.
option 3 : Debug runtime output. As for =2, but as much diagnostic
output as possible is given for each error or warning.
Also, a consistency check is added
to each branching by reclustering the resulting momenta back using the
corresponding inverse kinematics map and checking that the original
momenta are recovered within the desired numerical
precision. Note: the kinematics check will slow down the speed of
event generation.
option 4 : As for =3. And: each prepare()
and pTnext() call is explicitly announced, with system
number and restart scale printed out, respectively. .
option 5 : As for =4. And: momentum listings are printed for
each configuration that violates Paccept <= 1.
option 6 : As for =5. And: each main function call is
explicitly announced with begin and end printed to output.
option 7 : As for =6. And: most function calls are explicitly
announced with begin and end printed to output
(still only partly implemented).
option 8 : As for =7. And: last semi-sensible level of
output.
option 9 : As for =8. And: all possible output.
flag Vincia:CheckAntennae
(default = on)mode Vincia:nPointsCheck
(default = 1000; minimum = 0; maximum = 1e6)parm Vincia:deadZoneAvoidance
(default = 0.0001; minimum = 0.0; maximum = 1.0)