VINCIA accepts input of tune presets in the form of a standard PYTHIA 8 command file whose name and location can be specified by the user.
default = default.cmnd)
Note: the requested file will only be read in when VINCIA is switched on, in order not to interfere with the PYTHIA settings when VINCIA is switched off.
Note 2: a special value for this parameter is "none", in which case no tune file will be used (i.e., PYTHIA's parameters will be used as they are).
Note 3: the entries in the tune file will be superseded by any user modifications made in the main command file given to the VINCIA constructor. This should allow sufficient flexibility to explore user variations away from the tuned values.
A particular set of user-defined parameters can easily be made into a tune set by simply copying the relevant parts of the user's normal command file (i.e., omitting the process-specific and program control parameters) into a new file that can then be shared and/or submitted to the VINCIA authors for possible inclusion in future distributions. In order to make tunings more stable against possible changes in the program defaults (be it PYTHIA or VINCIA), it is advisable to include all relevant parameter values explicitly in the tune file, rather than letting parameters that retain their (version-specific) default values be defined implicitly.
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. However, for best results, be aware that an (N)NLO extraction of alphaS should still ideally be combined with explicit (N)NLO matrix-element corrections to the shower.
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.