6. Tips and tricks

6.1. Shell completion

Sherpa will install a file named $prefix/share/SHERPA-MC/sherpa-completion which contains tab completion functionality for the bash shell. You simply have to source it in your active shell session by running

$ .  $prefix/share/SHERPA-MC/sherpa-completion

and you will be able to tab-complete any parameters on a Sherpa command line.

To permanently enable this feature in your bash shell, you’ll have to add the source command above to your ~/.bashrc.

6.2. Rivet analyses

Sherpa is equipped with an interface to the analysis tool Rivet [B+20]. To enable it, Rivet and HepMC [DH01] have to be installed (e.g. using the Rivet bootstrap script) and your Sherpa compilation has to be configured with the following options:

$ cmake -DHepMC3_DIR=/path/to/hepmc3 -DRIVET_DIR=/path/to/rivet

(Note: Both paths are equal if you used the Rivet bootstrap script.) In the case that the packages are installed in standard locations, you can instead use -DSHERPA_ENABLE_HEPMC3=ON and -DSHERPA_ENABLE_RIVET=ON, respectively.

To use the interface, you need to enable it using the ANALYSIS option and to configure it it using the RIVET settings group as follows:

    - D0_2008_S7662670
    - CDF_2007_S7057202
    - D0_2004_S5992206
    - CDF_2008_S7828950

The analyses list specifies which Rivet analyses to run and the histogram output file can be changed with the normal ANALYSIS_OUTPUT switch.

Further Rivet options can be passed through the interface. The following ones are currently implemented:

    - MC_ZINC
  --ignore-beams: 1
  --skip-weights: 0
  --match_weights: ".*MUR.*"
  --unmatch-weights: "NTrials"
  --nominal-weight: "Weight"
  --weight-cap: 100.0
  --nlo-smearing: 0.1

You can also use rivet-mkhtml (distributed with Rivet) to create plot webpages from Rivet’s output files:

$ source /path/to/rivetenv.sh   # see below
$ rivet-mkhtml -o output/ file1.yoda [file2.yoda, ...]
$ firefox output/index.html &

If your Rivet installation is not in a standard location, the bootstrap script should have created a rivetenv.sh which you have to source before running the rivet-mkhtml script. If you want to employ custom Rivet analyses you might need to set the corresponding Rivet path variable, for example via

$ export RIVET_ANALYSIS_PATH=$RIVET_ANALYSIS_PATH:<path to custom analysis lib>

The RIVET: block can be used with further options especially suitable for detailed studies. Adding JETCONTS: 1 will create separate histograms split by jet multiplicity as created by the hard process. SPLITSH: 1 creates histograms split by soft and hard events, and SPLITPM: 1 creates histograms split by events with positive and negative event weights. Finally, SPLITCOREPROCS: 1 will split by different processes if multiple ones are specified in the runcard.

6.3. MCFM interface

Sherpa is equipped with an interface to the NLO library of MCFM for dedicated processes. To enable it, MCFM has to be installed and compiled into a single library @code{libmcfm.so} by using the -Dwith_library=ON flag when configuring MCFM using CMake.

Finally, your Sherpa compilation has to be configured with the following option:

$ cmake -DMCFM_DIR=/path/to/MCFM

Or, if MCFM is installed in a standard location:


To use the interface, specify

Loop_Generator: MCFM

in the process section of the run card and add it to the list of generators in ME_GENERATORS. MCFM’s process.DAT file should automatically be copied to the current run directory during initialisation.

Note that for unweighted event generation, there is also an option to choose different loop-amplitude providers for the pilot run and the accepted events via the Pilot_Loop_Generator option.

6.4. Debugging a crashing/stalled event

6.4.1. Crashing events

If an event crashes, Sherpa tries to obtain all the information needed to reproduce that event and writes it out into a directory named


If you are a Sherpa user and want to report this crash to the Sherpa team, please attach a tarball of this directory to your email. This allows us to reproduce your crashed event and debug it.

To debug it yourself, you can follow these steps (Only do this if you are a Sherpa developer, or want to debug a problem in an addon library created by yourself):

  • Copy the random seed out of the status directory into your run path:

    $ cp  Status__<date>_<time>/random.dat  ./
  • Run your normal Sherpa commandline with an additional parameter:

    $ Sherpa [...] 'STATUS_PATH: ./'

    Sherpa will then read in your random seed from “./random.dat” and generate events from it.

  • Ideally, the first event will lead to the crash you saw earlier, and you can now turn on debugging output to find out more about the details of that event and test code changes to fix it:

    $ Sherpa [...] --output 15 'STATUS_PATH: ./'

6.4.2. Stalled events

If event generation seems to stall, you first have to find out the number of the current event. For that you would terminate the stalled Sherpa process (using Ctrl-c) and check in its final output for the number of generated events. Now you can request Sherpa to write out the random seed for the event before the stalled one:

$ Sherpa [...] --events <#events - 1> 'SAVE_STATUS: Status/'

(Replace <#events - 1> using the number you figured out earlier.)

The created status directory can either be sent to the Sherpa developers, or be used in the same steps as above to reproduce that event and debug it.

6.5. Versioned installation

If you want to install different Sherpa versions into the same prefix (e.g. /usr/local), you have to enable versioning of the installed directories by using the configure option -DSHERPA_ENABLE_VERSIONING=ON. Optionally you can even pass an argument to this parameter of what you want the version tag to look like.

6.6. NLO calculations

6.6.1. Choosing DIPOLES ALPHA

A variation of the parameter DIPOLES:ALPHA (see Dipole subtraction) changes the contribution from the real (subtracted) piece (RS) and the integrated subtraction terms (I), keeping their sum constant. Varying this parameter provides a nice check of the consistency of the subtraction procedure and it allows to optimize the integration performance of the real correction. This piece has the most complicated momentum phase space and is often the most time consuming part of the NLO calculation. The optimal choice depends on the specific setup and can be determined best by trial.

Hints to find a good value:

  • The smaller DIPOLES:ALPHA is the less dipole term have to be calculated, thus the less time the evaluation/phase space point takes.

  • Too small choices lead to large cancellations between the RS and the I parts and thus to large statistical errors.

  • For very simple processes (with only a total of two partons in the initial and the final state of the born process) the best choice is typically DIPOLES: {ALPHA: 1}. The more complicated a process is the smaller DIPOLES:ALPHA should be (e.g. with 5 partons the best choice is typically around 0.01).

  • A good choice is typically such that the cross section from the RS piece is significantly positive but not much larger than the born cross section.

6.6.2. Integrating complicated Loop-ME

For complicated processes the evaluation of one-loop matrix elements can be very time consuming. The generation time of a fully optimized integration grid can become prohibitively long. Rather than using a poorly optimized grid in this case it is more advisable to use a grid optimized with either the born matrix elements or the born matrix elements and the finite part of the integrated subtraction terms only, working under the assumption that the distributions in phase space are rather similar.

This can be done by one of the following methods:

  1. Employ a dummy virtual (requires no computing time, returns a finite value as its result) to optimise the grid. This only works if V is not the only NLO_Part specified.

    1. During integration set the Loop_Generator to Dummy. The grid will then be optimised to the phase space distribution of the sum of the Born matrix element and the finite part of the integrated subtraction term, plus a finite value from Dummy.


      The cross section displayed during integration will also correspond to these contributions.

    2. During event generation reset Loop_Generator to your generator supplying the virtual correction. The events generated then carry the correct event weight.

  2. Suppress the evaluation of the virtual and/or the integrated subtraction terms. This only works if Amegic is used as the matrix element generator for the BVI pieces and V is not the only NLO_Part specified.

    1. During integration add AMEGIC: { NLO_BVI_MODE: <num> } to your configuration. <num> takes the following values: 1-B, 2-I, and 4-V. The values are additive, i.e. 3-BI.


      The cross section displayed during integration will match the parts selected by NLO_BVI_MODE.

    2. During event generation remove the switch again and the events will carry the correct weight.


this will not work for the RS piece!

6.6.3. Avoiding misbinning effects

Close to the infrared limit, the real emission matrix element and corresponding subtraction events exhibit large cancellations. If the (minor) kinematics difference of the events happens to cross a parton-level cut or analysis histogram bin boundary, then large spurious spikes can appear.

These can be smoothed to some extend by shifting the weight from the subtraction kinematic to the real-emission kinematic if the dipole measure alpha is below a given threshold. The fraction of the shifted weight is inversely proportional to the dipole measure, such that the final real-emission and subtraction weights are calculated as:

w_r -> w_r + sum_i [1-x(alpha_i)] w_{s,i}
foreach i: w_{s,i} -> x(alpha_i) w_{s,i}

with the function \(x(\alpha)=(\frac{\alpha}{|\alpha_0|})^n\) for \(\alpha<\alpha_0\) and \(1\) otherwise.

The threshold can be set by the parameter NLO_SMEAR_THRESHOLD: <alpha_0> and the functional form of alpha and thus interpretation of the threshold can be chosen by its sign (positive: relative dipole kT in GeV, negative: dipole alpha). In addition, the exponent n can be set by NLO_SMEAR_POWER: <n>.

6.6.4. Enforcing the renormalisation scheme

Sherpa takes information about the renormalisation scheme from the loop ME generator. The default scheme is MSbar, and this is assumed if no loop ME is provided, for example when integrated subtraction terms are computed by themselves. This can lead to inconsistencies when combining event samples, which may be avoided by setting AMEGIC: { LOOP_ME_INIT: 1 }.

6.6.5. Checking the pole cancellation

To check whether the poles of the dipole subtraction and the interfaced one-loop matrix element cancel for each phase space point, specify AMEGIC: { CHECK_POLES: true } and/or COMIX: { CHECK_POLES: true }.

In the same way, the finite contributions of the infrared subtraction and the one-loop matrix element can be checked using CHECK_FINITE, and the Born matrix element via CHECK_BORN. The accuracy to which the poles, finite parts and Born matrix elements are checked is set via CHECK_THRESHOLD. These three settings are only supported by Amegic and are thus set using AMEGIC: { <PARAMETER>: <VALUE> }, where <VALUE> is false or true for CHECK_FINITE/CHECK_BORN, or a number specifying the desired accuracy for CHECK_THRESHOLD.

6.7. 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. On-the-fly event weight 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:

6.7.1. 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 information 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.

6.7.2. 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:


Event ID to identify correlated real sub-events.


Number of outgoing partons.


Momentum components of the partons.


Parton PDG code.


Event weight, if sub-event is treated independently.


Event weight, if correlated sub-events are treated as single event.


ME weight (w/o PDF), corresponds to ‘weight’.


ME weight (w/o PDF), corresponds to ‘weight2’.


PDG code of incoming parton 1.


PDG code of incoming parton 2.


Factorisation scale.


Renormalisation scale.


Bjorken-x of incoming parton 1.


Bjorken-x of incoming parton 2.


x’ for I-piece of incoming parton 1.


x’ for I-piece of incoming parton 2.


Number of additional ME weights for loops and integrated subtraction terms.


Additional ME weights for loops and integrated subtraction terms.

6.7.3. 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:

  1. 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.

  2. 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.

  3. 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.

6.7.4. Computation of cross sections with new PDF’s Born and real pieces


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) Loop piece and integrated subtraction terms

The weights here have an explicit dependence on the renormalisation and factorization scales.

To take care of the renormalisation 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)


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 renormalisation 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.


The loop provider must support this option or the scale dependence coefficients will be invalid!