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An implementation of this input-selection algorithm is
available in the
FinalPartons and TauFinder projections
in Rivet [14] from version 2.2.1 onwards.
4 Associating labels to jets
After applying the QCD-aware clustering to the partonic (and
prompt lepton and photon) inputs discussed above, and nor-
mal flavour-blind clustering to the final state truth particles,
we have two distinct jet collections: flavoured partonic label-
jets, and standard particle jets. We aim to label the latter using
the former.
Arguably the simplest labelling algorithm is to assign each
particle jet the label of the closest parton jet, i.e. that which
minimises R
jet-label
. This has the drawback, however, that
distinct particle jets can share the same closest parton jet:
should the particle jets share the same label, or should some
additional matching criterion be introduced to assign the par-
ton jet to just one particle jet, e.g. the nearer of the two?
In this study we have hence used the ghost association [15]
method to non-invasively cluster the parton jets into the par-
ticle jets, guaranteeing that no parton label will be associated
to multiple particle jets.
5
A second ambiguity now arises, because more than one
parton jet can be ghost-associated to a given particle jet. Since
the QCD-aware clustering forbids combination of some par-
ton flavours, having multiple unclustered partons within a
particle jet’s clustering radius is a fairly frequent occurrence –
moreso than the many-particle-to-one-parton ambiguity that
ghost association resolves. Hence a disambiguation measure
is required among the associated parton jets, and for simplic-
ity we have chosen the label which minimises R
jet-label
,
within an inner core of the jet radius: if all R > 0.2, the jet
remains unlabelled. This restriction to R < 0.2 was added
to remove long, low rate tails observed in initial runs of the
algorithm. This may certainly be improved, and we suggest
either a combined R and p
T
matching measure (although
this is a little like adding apples and oranges), to favour high-
p
T
or well-matched p
T
labels within the jet cone, and/or to
assign weights rather than absolute labels – but we do not
consider such extensions in this paper.
5 Performance of QCD-aware labelling
In this section we will make performance comparisons of the
above-described labelling algorithm for two hard processes,
5
Note that this is for the purposes of definiteness more than abso-
lute physical correctness: in such ambiguous circumstances there is no
guarantee that ghost association has picked the physically “correct”
assignment, or that such a thing even exists.
dijet and γ -jet, with various parton shower event generators,
and with several systematic variations to both the labelling
scheme and to the simulation:
Shower generators: Pythia 8.201, Herwig++ 2.7.1, Sherpa
2.1.1
Clustering variants: max- p
T
(no clustering)/k
T
QCD-aware
/anti-k
T
QCD-aware
Simulation variants: normal/without MPI/raised shower
cutoff/ME max multiplicity
Association variants: all labels/reclustered labels
A minimum p
T
requirement of 25 GeV has been imposed
on the particle jets in these studies, and a p
T
> 5GeV
requirement on the partonic label jets. Both types of jets were
clustered with an R parameter of 0.4. All jet clustering was
restricted to within |η| < 2.5.
For comparison to the QCD-aware approach, we will
present a “maximum p
T
” partonic jet labelling scheme,
where the label assigned to a final-state truth jet is the flavour
of the highest- p
T
parton within its radius. This label is dis-
covered by looping over all partons, including those in the
hard process final state (typically in the partonic centre-of-
mass frame of the matrix element calculation), through all
the intermediate stages of the parton shower and MPI, down
to the final partons described in Sect. 3. Since the highest-p
T
parton is used, this tends to be from the hard process or shortly
after, before it has radiated significant virtuality via shower
branchings. The measures that we use for labelling kinematic
performance would be biased in this scheme, hence we will
only show it in direct comparisons either of label assignments
or in ratios of flavour label rates.
5.1 MC generator families
A key motivation for the QCD-aware approach to partonic
truth-jet labelling is for the method to be portable between
different MC generators. Each plot in most of the following
studies is hence shown with three MC lines, for the three
major parton shower MC generator families; the exact ver-
sions are given above.
In principle, the QCD-aware method should be robust
enough for use both with fixed-order codes (producing a few-
body partonic final state) and parton shower codes in which
the final-state partonic multiplicity is much higher. Substan-
tial differences between the Herwig and Pythia generator
families have been seen in q/g rate prediction studies using
the max- p
T
labelling scheme [16,17], so some level of varia-
tion is to be expected between generator shower formalisms,
but we expect broad qualitative agreement of labelling both
between generators and with the expectations for each hard
process type.
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