7. A posteriori scale variations¶
There are several ways to compute the effects of changing the scales and PDFs of any event produced by Sherpa. They can computed explicitly, cf. Explicit scale variations, on-the-fly, cf. Scale and PDF variations (restricted to multiplicative factors), or reconstructed a posteriori. The latter method needs plenty of additional information in the event record and is (depending on the actual calculation) available in two formats:
7.1. A posteriori scale and PDF variations using the HepMC GenEvent Output¶
Events generated in a LO, LOPS, NLO, NLOPS, MEPS@LO, MEPS@NLO or
MENLOPS calculation can be written out in the HepMC format including
all infomation to carry out arbitrary scale variations a
posteriori. For this feature HepMC of at least version 2.06 is
necessary and both HEPMC_USE_NAMED_WEIGHTS: true
and
HEPMC_EXTENDED_WEIGHTS: true
have to enabled. Detailed
instructions on how to use this information to construct the new event
weight can be found here
https://sherpa.hepforge.org/doc/ScaleVariations-Sherpa-2.2.0.pdf.
7.2. A posteriori scale and PDF variations using the ROOT NTuple Output¶
Events generated at fixed-order LO and NLO can be stored in ROOT NTuples that allow arbitrary a posteriori scale and PDF variations, see Event output formats. An example for writing and reading in such ROOT NTuples can be found here: Production of NTuples. The internal ROOT Tree has the following Branches:
id
Event ID to identify correlated real sub-events.
nparticle
Number of outgoing partons.
E/px/py/pz
Momentum components of the partons.
kf
Parton PDG code.
weight
Event weight, if sub-event is treated independently.
weight2
Event weight, if correlated sub-events are treated as single event.
me_wgt
ME weight (w/o PDF), corresponds to ‘weight’.
me_wgt2
ME weight (w/o PDF), corresponds to ‘weight2’.
id1
PDG code of incoming parton 1.
id2
PDG code of incoming parton 2.
fac_scale
Factorisation scale.
ren_scale
Renormalisation scale.
x1
Bjorken-x of incoming parton 1.
x2
Bjorken-x of incoming parton 2.
x1p
x’ for I-piece of incoming parton 1.
x2p
x’ for I-piece of incoming parton 2.
nuwgt
Number of additional ME weights for loops and integrated subtraction terms.
usr_wgt[nuwgt]
Additional ME weights for loops and integrated subtraction terms.
7.2.1. Computing (differential) cross sections of real correction events with statistical errors¶
Real correction events and their counter-events from subtraction terms are highly correlated and exhibit large cancellations. Although a treatment of sub-events as independent events leads to the correct cross section the statistical error would be greatly overestimated. In order to get a realistic statistical error sub-events belonging to the same event must be combined before added to the total cross section or a histogram bin of a differential cross section. Since in general each sub-event comes with it’s own set of four momenta the following treatment becomes necessary:
An event here refers to a full real correction event that may contain several sub-events. All entries with the same id belong to the same event. Step 2 has to be repeated for each event.
Each sub-event must be checked separately whether it passes possible phase space cuts. Then for each observable add up
weight2
of all sub-events that go into the same histogram bin. These sums \(x_{id}\) are the quantities to enter the actual histogram.To compute statistical errors each bin must store the sum over all \(x_{id}\) and the sum over all \(x_{id}^2\). The cross section in the bin is given by \(\langle x\rangle = \frac{1}{N} \cdot \sum x_{id}\), where \(N\) is the number of events (not sub-events). The \(1-\sigma\) statistical error for the bin is \(\sqrt{ (\langle x^2\rangle-\langle x\rangle^2)/(N-1) }\)
Note: The main difference between weight
and weight2
is that they
refer to a different counting of events. While weight
corresponds to
each event entry (sub-event) counted separately, weight2
counts events
as defined in step 1 of the above procedure. For NLO pieces other than the real
correction weight
and weight2
are identical.
7.2.2. Computation of cross sections with new PDF’s¶
7.2.2.1. Born and real pieces¶
Notation:
f_a(x_a) = PDF 1 applied on parton a, F_b(x_b) = PDF 2 applied on
parton b.
The total cross section weight is given by:
weight = me_wgt f_a(x_a)F_b(x_b)
7.2.2.2. Loop piece and integrated subtraction terms¶
The weights here have an explicit dependence on the renormalization and factorization scales.
To take care of the renormalization scale dependence (other than via
alpha_S
) the weight w_0
is defined as
w_0 = me_wgt + usr_wgts[0] log((\mu_R^new)^2/(\mu_R^old)^2) +
usr_wgts[1] 1/2 [log((\mu_R^new)^2/(\mu_R^old)^2)]^2
To address the factorization scale dependence the weights w_1,...,w_8
are given by
w_i = usr_wgts[i+1] + usr_wgts[i+9] log((\mu_F^new)^2/(\mu_F^old)^2)
The full cross section weight can be calculated as
weight = w_0 f_a(x_a)F_b(x_b)
+ (f_a^1 w_1 + f_a^2 w_2 + f_a^3 w_3 + f_a^4 w_4) F_b(x_b)
+ (F_b^1 w_5 + F_b^2 w_6 + F_b^3 w_7 + F_b^4 w_8) f_a(x_a)
where
f_a^1 = f_a(x_a) (a=quark), \sum_q f_q(x_a) (a=gluon),
f_a^2 = f_a(x_a/x'_a)/x'_a (a=quark), \sum_q f_q(x_a/x'_a)x'_a (a=gluon),
f_a^3 = f_g(x_a),
f_a^4 = f_g(x_a/x'_a)/x'_a
The scale dependence coefficients usr_wgts[0]
and usr_wgts[1]
are normally obtained from the finite part of the virtual correction
by removing renormalization terms and universal terms from dipole
subtraction. This may be undesirable, especially when the loop
provider splits up the calculation of the virtual correction into
several pieces, like leading and sub-leading color. In this case the
loop provider should control the scale dependence coefficients, which
can be enforced with option USR_WGT_MODE: false
.
Warning
The loop provider must support this option or the scale dependence coefficients will be invalid!