2.1. FCC: Getting started with event generation

2.1.1. Overview

2.1.2. Enabling FCCSW

To configure your environment for the FCC software, just do:

source /cvmfs/sw.hsf.org/key4hep/setup.sh

Nota Bene

For legacy reasons the following is still provided, fully equivalent to the above

source /cvmfs/fcc.cern.ch/sw/latest/setup.sh

Builds exist on CernVM-FS for CentOS7 (this is the Operating System run on lxplus) using gcc11.

The k4run steering application should be available at this point:

which k4run

# The output might differ, but shouldn't be empty and the structure should be similar
/cvmfs/sw.hsf.org/spackages6/k4fwcore/1.0pre15/x86_64-centos7-gcc11.2.0-opt/2q37t/bin/k4run

The application fccrun is still provided, fully equivalent to k4run.

Nota Bene

You will need to source the /cvmfs/sw.hsf.org/key4hep/setup.sh script everytime you want to use the software.

2.1.3. Generators

2.1.3.1. Overview

The physics generators available for FCC typically come from the underlying stack. However, any generator able to generate events in one of the understood formats, e.g. HepMC or EDM4hep or LHEf, can be used in standalone. The recommended formats are HepMC3 and EDM4hep. This pages intend to illustrate the use of a few general purpose generators available when enabling FCCSW: pythia8, whizard, MadGraph5, Herwig, KKMCee, BHLUMI, BabaYaga.

2.1.3.2. Pythia8

Pythia8 is fully intergrated in Key4hep software stack and it provides diverse functionality in addition to event generation, including capability to read events in LHEF format.

To use Pythia8 we need a Gaudi steering file and a configuration file. Examples of configuration files can be obtained from the FCC-config repository.

The Gaudi steering file needs to activate the GaudiAlgorithm that runs Pythia8; the algorithm is available from the k4Gen repository and it is called PythiaInterface.

An example of steering file can be found at https://github.com/HEP-FCC/k4Gen/blob/main/k4Gen/options/pythia.py. The steering file runs the miniaml set of algorithms to run Pythia8 and produce an output in EDM4hep format:

$ wget https://raw.githubusercontent.com/HEP-FCC/k4Gen/main/k4Gen/options/pythia.py
$ k4run pythia.py -h
 -->  Pythia8 -->  HepMCToEDMConverter -->  StableParticles -->  out
...
  -n NUM_EVENTS, --num-events NUM_EVENTS
                        Number of events to run
...
  --out.filename [OUT.FILENAME], --filename.out [OUT.FILENAME]
                        Name of the file to create [PodioOutput]
...
  --Pythia8.PythiaInterface.pythiacard [PYTHIA8.PYTHIAINTERFACE.PYTHIACARD], --pythiacard.Pythia8.PythiaInterface [PYTHIA8.PYTHIAINTERFACE.PYTHIACARD]
                        [PythiaInterface]
...

For example, to generate 500 e⁺e^- → mu⁺mu^- at 91.2 GeV, we can do the following: download the configuration file:

$ wget https://raw.githubusercontent.com/HEP-FCC/FCC-config/main/FCCee/Generator/Pythia8/p8_ee_Zmumu_ecm91.cmd

and run

k4run pythia.py -n 500 --out.filename p8_mumu_500.e4h.root --Pythia8.PythiaInterface.pythiacard p8_ee_Zmumu_ecm91.cmd

2.1.3.3. Whizard

Whizard is available as standalone program:

which whizard

/cvmfs/sw.hsf.org/spackages6/whizard/3.0.1/x86_64-centos7-gcc11.2.0-opt/pmm4s/bin/whizard

Whizard is run as this:

whizard <process_config>.sin

Example of process configuration files are found under

ls /cvmfs/sw.hsf.org/spackages6/whizard/3.0.1/x86_64-centos7-gcc11.2.0-opt/pmm4s/share/whizard/examples/

or at https://gitlab.tp.nt.uni-siegen.de/whizard/public/-/tree/master/share/examples .

Some examples more specific to FCC can be found under

ls /eos/project-f/fccsw-web/www/share/gen/whizard/

or browsing https://fccsw.web.cern.ch/fccsw/share/gen/whizard/Zpole/, if EOS is not available.

Show dimuon example

It is advised to work in a separate directory for each process. For example, for Z_mumu, we have:

 mkdir -p test_whizard/Z_mumu; cd test_whizard/Z_mumu
 wget https://fccsw.web.cern.ch/fccsw/share/gen/whizard/Zpole/Z_mumu.sin
 whizard Z_mumu.sin

| Writing log to 'whizard.log'
|=============================================================================|
|                                                                             |
|    WW             WW  WW   WW  WW  WWWWWW      WW      WWWWW    WWWW        |
|     WW    WW     WW   WW   WW  WW     WW      WWWW     WW  WW   WW  WW      |
|      WW  WW WW  WW    WWWWWWW  WW    WW      WW  WW    WWWWW    WW   WW     |
|       WWWW   WWWW     WW   WW  WW   WW      WWWWWWWW   WW  WW   WW  WW      |
|        WW     WW      WW   WW  WW  WWWWWW  WW      WW  WW   WW  WWWW        |
|                                                                             |
|                                                                             |

...

|=============================================================================|
|                               WHIZARD 3.0.1
|=============================================================================|
| Reading model file '/cvmfs/sw.hsf.org/spackages6/whizard/3.0.1/x86_64-centos7-gcc11.2.0-opt/pmm4s/share/whizard/models/SM.mdl'
| Preloaded model: SM
| Process library 'default_lib': initialized
| Preloaded library: default_lib
| Reading model file '/cvmfs/sw.hsf.org/spackages6/whizard/3.0.1/x86_64-centos7-gcc11.2.0-opt/pmm4s/share/whizard/models/SM_hadrons.mdl'
| Reading commands from file 'Z_mumu.sin'
| Switching to model 'SM', scheme 'default'

...

$description = "A WHIZARD 3.0 Example.
   Z -> mumu @ 91.2 events for FCC ee."
$y_label = "$N_{\textrm{events}}$"
$sample = "z_mumu"
| Starting simulation for process 'zmumu'
| Simulate: using integration grids from file 'zmumu.m1.vg'
| RNG: Initializing TAO random-number generator
| RNG: Setting seed for random-number generator to 22345
| Simulation: requested number of events = 1000
|             corr. to luminosity [fb-1] =   6.6285E-04
| Events: writing to HepMC file 'z_mumu.hepmc'
| Events: writing to raw file 'z_mumu.evx'
| Events: generating 1000 unweighted, unpolarized events ...
| Events: event normalization mode '1'
|         ... event sample complete.
| Events: actual unweighting efficiency =   1.16 %
Warning: Encountered events with excess weight: 6 events (  0.600 %)
| Maximum excess weight = 2.465E+00
| Average excess weight = 4.511E-03
| Events: closing HepMC file 'z_mumu.hepmc'
| Events: closing raw file 'z_mumu.evx'
| There were no errors and    2 warning(s).
| WHIZARD run finished.
|=============================================================================|

The file z_mumu.hepmc contains 100 e⁺e^- → mu⁺mu^-(gamma) events in HepMC 3 format .

2.1.3.4. MadGraph5

MadGraph5 is available as standalone program:

which mg5_aMC

/cvmfs/sw.hsf.org/spackages6/madgraph5amc/2.8.1/x86_64-centos7-gcc11.2.0-opt/3tclk/bin/mg5_aMC

2.1.3.5. Herwig

Herwig is available as standalone program:

which Herwig

/cvmfs/sw.hsf.org/spackages6/herwig3/7.2.3/x86_64-centos7-gcc11.2.0-opt/5d2cb/bin/Herwig

2.1.3.6. KKMCee

KKMCee is an adaptation of the KKMC Monte Carlo generator (the latest version of the Koral generators) to the case of FCC-ee. KKMCee is available as standalone program when using the key4hep stack:

which KKMCee

/cvmfs/sw.hsf.org/spackages6/kkmcee/5.00.02/x86_64-centos7-gcc11.2.0-opt/eodg6/bin/KKMCee

A help function is available:

KKMCee -h

Show help function output

+++ Wrapper around the KKMCee executable  +++

Usage: \tKKMCee -f Mu|Tau|UDS|C|B|Hadrons -e Ecms -n Nevts -o output_file [-s initial_seed] [OPTIONS]
       \tKKMCee -c config_file [-s initial_seed]

Options:
  -c, --config file 		Path to configuration file
  -f, --flavour flavour 	Flavour to be generated (Mu|Tau|UDS|C|B|Hadrons)
  -e, --ecms energy 		Center of Mass energy in GeV
  -n, --nevts events 		Number of events to be generated
  -o, --outfile file 		File with the generated events in HEPMCv3 format [kkmcee.hepmc]
  -s, --initialseed 		Long number to be used for initial seeding (randomly generated, if missing)
  -b, --bessig bessig 		Beam-Energy-Spread of both beams (or of the first beam, if bessig2<0.)
                      		[fraction of Ecms/2, default -1. (no spread)]
  -g, --bessig2 bessig2 	Beam-Energy-Spread of the second beam if different from the first beam; fraction of Ecms/2.
                      		[fraction of Ecms/2, default -1. (no spread or equal to first beam)]
  -r, --besrho rho 		Beam-Energy-Spread correlation [default 0.]
  -d, --debug lvl 		 PrintOut Level 0,1,2 [default 1]

Special options for taus only:
  -t, --taudec t1*1000+t2 	decay channel for the first (t1) and second tau (t2)
                      		 0        Inclusive
                      		 1,2,3    electron,mu,pi
                      		 4,5,6,7  rho,a1,K,K*
                      		 8,9,10,11,12,13  3pip0,pi3pi0,3pi2pi0,5pi,5pip0,3pi3p0
                      		 14, ... (other rare decays see tauola++)
  --tauopt file 		File with tau options (see Tauola section in KKMCee_defaults)
                      		 the file is included as it is and overwrites other settings

Examples:
KKMCee -f Mu -e 91.2 -n 10000 -o kkmu_10000.hepmc -b 0.001
KKMCee -c kkmc_ditau.input
KKMCee -f B -e 91.2 -n 1000 -o kkbb_1000.hepmc

  NB: (1) This wrapper works only for KKMCee versions 5 or newer
      (2) Output is HEPMC v3

Note that the BES (Beam Energy Spread) options are only available in version 4.32.01 and higher.

A configuration example file for taus is available under at

ls `dirname $( which KKMCee )`/../share/KKMCee/examples/kkmc-tauola.input

Show dimuon example

To generate a sample of dimuon events using the example files, do the following

KKMCee -f Mu -e 91.2 -n 1000 -o kkmu_1000.hepmc

The output should look something like this:

Seeds: 29318493 48191772
  29318493      IJKLIN= 29318493  48191772
         0      NTOTIN= 0
         0      NTOT2N= 0
  ------- starting from the scratch ----------
ranmar initialized: ij,kl,ijkl,ntot,ntot2=       974     18625  29318493         0         0
        1000  requested events
 ---------------
 ****************************
 *    KK2f_ReaDataX Starts  *
 ****************************
 ---------------
 ---------------
 ---------------
 ---------------
 ---------------
BeginX
********************************************************************************
*               ACTUAL DATA FOR THIS PARTICULAR RUN
********************************************************************************
*indx_____data______ccccccccc0ccccccccc0ccccccccc0ccccccccc0ccccccccc0ccccccccc0
*     Center-of-mass energy [GeV]
    1    91.0000         CMSene =xpar( 1) Average Center of mass energy [GeV]
********************************************************************************
*     Define process
  413    1.00000          KFfin, muon
  100    1.00000          store lhe file to (LHE_OUT.LHE)
 ---------------          26          36 LHE_OUT.LHE
************************* one can change the lhf file name between brackets
********************************************************************************
EndX
 **************************
 *   KK2f_ReaDataX Ends   *
 **************************
 Tables are READ from DiskFile  dizet/table.down
amz,amh,amtop,swsq,gammz,amw,gammw=
     =  91.1876000 125.1000000 173.0000000   0.2234020   2.4953766  80.3588894   2.0898788
 
 ...
 
 

                            Event listing (summary)

    I particle/jet KS     KF  orig    p_x      p_y      p_z       E        m

    1 !e-!         21      11    0    0.000    0.000   45.500   45.500    0.001
    2 !e+!         21     -11    0    0.000    0.000  -45.500   45.500    0.001
    3 (Z0)         11      23    1    0.039    0.001    0.115   90.879   90.879
    4 gamma         1      22    1    0.000    0.000   -0.001    0.001    0.000
    5 gamma         1      22    1   -0.039   -0.001   -0.114    0.120    0.000
    6 mu-           1      13    3   14.678    0.229   43.067   45.500    0.106
    7 mu+           1     -13    3  -14.639   -0.229  -42.952   45.379    0.106
                   sum:  0.00         0.000    0.000    0.000   91.000   91.000
 iev=          501
  generation finished
  xSecPb, xErrPb =   1442.5021729176829        13.903134156944603
++++++++++++++++++++++++++++++++++++++++++++++++++++++
++    GLK_PRINT: bmin.eq.bmax, id=     50004 ++
++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++
++    GLK_PRINT: bmin.eq.bmax, id=     50005 ++
++++++++++++++++++++++++++++++++++++++++++++++++++++++

real	0m4.043s
user	0m3.777s
sys	0m0.085s

and a file kkmu_1000.hepmc created.

KKMCee creates several files during its run. These are saved into a folder called KKMCee-<date>-<time>, for example KKMCee-12Oct2022-191047. This folder contains the files:

$ ls KKMCee-12Oct2022-191047
DIZET-table1  TabMain77.output  TabMainC.output  mcgen.root  pro.input  pro.output  pro77.output

The file pro.input contains the configuration options and can be used to repeat the run

KKMCee -c KKMCee-12Oct2022-191047/pro.input

and, of course, as base configuration file example for further variations.

2.1.3.7. BHLUMI

BHLUMI is a Monte Carlo generator of Bhabha events used at LEP for luminosity studies. BHLUMI is available as standalone program when using the key4hep stack:

which BHLUMI

/cvmfs/sw.hsf.org/spackages4/bhlumi/4.04-linuxLHE/x86_64-centos7-gcc8.3.0-opt/o7rmcus/bin/BHLUMI

A help function is available:

BHLUMI -h

Show help function output

+++ Wrapper around the BHLUMI.exe executable +++

Usage: 	BHLUMI -e Ecms -n Nevts -f Thmin -t Thmax -x epscms -o output_file [-s seed_file]
       	BHLUMI -c config_file [-s seed_file]

Switches:
  -c, --config file 		Path to configuration file
  -e, --ecms energy 		Center of Mass energy in GeV
  -n, --nevts energy 		Number of events to be generated
  -f, --Thmin theta 		Minimum theta [rad]
  -t, --Thmax theta 		Maximum theta [rad]
  -x, --epscms fraction 	Energy cut-off in  fraction of Ecms
  -o, --outfile file 		File with the generated events in LHE format
  -s, --seedfile file 		File to be used for seeding (randomly generated, if missing)

Examples:
BHLUMI -f 0.022 -t 0.082 -x 0.001 -e 91.2 -n 10000 -o kkmu_10000.LHE
BHLUMI -c bhlumi.input

Additional switches (for experts only):
  -k, --keyopt KEYOPT 		Technical parameters switch [default 3021]
  				KEYOPT = 1000*KEYGEN + 100*KEYREM + 10*KEYWGT + KEYRND
  -r, --keyrad KEYRAD 		Physics parameters switch [default 1021]
  				KEYRAD = 1000*KEYZET + 100*KEYUPD + 10*KEYMOD + KEYPIA
  (Contact BHLUMI authors for details, e.g. through https://github.com/KrakowHEPSoft/BHLUMI)

2.1.3.8. BabaYaga

BabaYaga is a Monte Carlo generator of two-photons events used at LEP. BabaYaga is available as standalone program when using the key4hep stack:

which babayaga

/cvmfs/sw.hsf.org/spackages4/babayaga/fcc-1.0.0/x86_64-centos7-gcc8.3.0-opt/jsgdir7/bin/babayaga

A help function is available:

babayaga -h

Show help function output

+++ Wrapper around the babayaga-fcc.exe executable +++

+++ Process: e+e- -> gamma gamma

Usage: 	babayaga -e Ecms -n Nevts -f Thmin -t Thmax -x epscms -o output_file [-s seed]
       	babayaga -c config_file [-s seed]

Switches:
  -c, --config file 		Path to configuration file
  -e, --ecms energy 		Center of Mass energy in GeV
  -n, --nevts energy 		Number of events to be generated
  -f, --Thmin angle 		Minimum theta [deg]
  -t, --Thmax angle 		Maximum theta [deg]
  -a, --acolmax angle 		Max acollinearity [deg]
  -m, --emin energy 		Min energy in GeV
  -x, --eps fraction 		Soft-photon cut-off
  -o, --outfile file 		File with the generated events in LHE format
  -w, --outdir path 		Path with working space (and residual files)
  -s, --seed number 		Number used for seeding (randomly generated, if missing)
  -d, --debug number 		Debug level (0, 1, 2, ...)

Examples:
babayaga -f 15. -t 165. -e 91.2 -n 10000 -o bbyg_10000.LHE
babayaga -c babayaga.input -o bbyg.LHE

2.1.4. Hands-on case study: ditau events with KKMCee, Pythia8 and Whizard

In this section we describe, with exercises, the generation of an equivalent sample of Monte Carlo events with three diffent generators, KKMCee, Pythia8 and Whizard. The process chosen is e^-e⁺ → tau^-tau⁺ (hereafter referred to as ditaus) at a centre of mass energy of 91.2 GeV. In the three cases 10000 will be generated and saved in ROOT files in EDM4hep format.

2.1.4.1. Generating ditaus with KKMCee

As shown in the KKMCee section, event generation with the KKMCee is controlled through a configuration file. The interface available in key4hep allowed a generation of the configuration file through command line switches. Starting from the command line switches is therefore always a good option when no confguration file is available.

Currently, KKMCee does not have the option to save directly the events in EDM4hep format. In order to get there we need first to generate the events in HepMC format.

2.1.4.1.1. Generating `HepMC` events

What are the commands (options) to generate 10000 ditau events and saved them into the file kk_tautau_10000.hepmc ?

2.1.4.1.2. `HepMC` to `EDM4hep` conversion

In order to get the events in EDM4hep format, we will use Gaudi and the tools available in k4FWCore and k4Gen. We need a Gaudi steering file that reads the HepMC file and writes out the EDM4hep file. A minimal version of such a steering code is available on the tutorial reference page:

wget http://fccsw.web.cern.ch/tutorials/october2020/tutorial1/hepmc2edm.py .

Let’s see what it does: that is shown by the first line of the help function

$ k4run hepmc2edm.py -h
 -->  GenAlg  -->  HepMCToEDMConverter  -->  out
...

2.1.4.1.2.1. Dissection of `hepmc2edm.py`

Expand

The tool that we need is HepMCFileReader, which is a GaudiTool, not a GaudiAlgorithm, which is used as a signal provider (such as a Monte Carlo generator) within the Generator Algorithm (GenAlg). This is done in this part of the code:

from Configurables import HepMCFileReader
hepmcreader = HepMCFileReader()

from Configurables import GenAlg
reader = GenAlg()
reader.SignalProvider = hepmcreader
reader.hepmc.Path = "hepmc"
ApplicationMgr().TopAlg += [reader]

Then we convert the event from HepMC to EDM4hep with the HepMCToEDMConverter:

from Configurables import HepMCToEDMConverter
hepmc_converter = HepMCToEDMConverter()
hepmc_converter.hepmc.Path="hepmc"
hepmc_converter.GenParticles.Path = "GenParticles"
ApplicationMgr().TopAlg += [hepmc_converter]

Finally we write out the converted events into a file with the PodioOutput algorithm:

from Configurables import PodioOutput
out = PodioOutput("out", filename = "hepmc2edm_output.root")
out.outputCommands = ["keep *"]
ApplicationMgr().TopAlg += [out]

2.1.4.1.2.2. Running `hepmc2edm.py`

Among the hepmc2edm switches relevant for the purpose are those controling input an output files:

$ k4run hepmc2edm.py -h
...
  --GenAlg.HepMCFileReader.Filename [GENALG.HEPMCFILEREADER.FILENAME], --Filename.GenAlg.HepMCFileReader [GENALG.HEPMCFILEREADER.FILENAME]
                        Name of the HepMC file to read [HepMCFileReader]
...
  --out.filename [OUT.FILENAME], --filename.out [OUT.FILENAME]
                        Name of the file to create [PodioOutput]
...

We would like the output file to be called kk_tautau_10000.e4h.root . Which command should we use for that?

Check answer

k4run hepmc2edm.py -n 10000 --GenAlg.HepMCFileReader.Filename kk_tautau_10000.hepmc --out.filename kk_tautau_10000.e4h.root

Q: Can you explain why we need to pass the -n 10000 switch and how you could modify hepmc2edm.py to avoid that?

Check answer

Because hepmc2edm.py contains this piece of code:

from Configurables import ApplicationMgr
ApplicationMgr(
               EvtSel='NONE',
               EvtMax=1,
               OutputLevel=INFO,

The setting EvtMax=1 is overwritten by -n <n_evts>. To avoid this one could set EvtMax=10000 inside hepmc2edm.py (try!)

Note en passant that the EDM4hep file is much smaller than the HepMC one:

$ ls -lt
total 43032
-rw-r--r-- 1 ganis vboxsf  3661630 Oct 18  2022 kk_tautau_10000.e4h.root
-rw-r--r-- 1 ganis vboxsf     1232 Oct 18  2022 hepmc2edm.py
drwxr-xr-x 1 ganis vboxsf      288 Oct 18 16:12 KKMCee-18Oct2022-161012
-rw-r--r-- 1 ganis vboxsf 19584017 Oct 18 16:12 kk_tautau_10000.hepmc

Q: Can you explain why?

Check answer

Because kk_tautau_10000.e4h.root is a ROOT file, which binary and compressed.

2.1.4.2. Generating ditaus with Pythia8

As explained in the dedicated Pythia8 section, to use Pythia8 we need a configuration file. To generate ditau events we will use the file p8_ee_Ztautau_ecm91.cmd:

$ wget https://raw.githubusercontent.com/HEP-FCC/FCC-config/main/FCCee/Generator/Pythia8/p8_ee_Ztautau_ecm91.cmd

Q: How will we run it? (hint: check specific section)

Answer

k4run pythia.py -n 10000 --out.filename p8_tautau_10000.d4h.root --Pythia8.PythiaInterface.pythiacard p8_ee_Ztautau_ecm91.cmd

Running will take a few minutes. Among the last lines of the output there should be the total cross-section for the process:

 *-------  PYTHIA Event and Cross Section Statistics  -------------------------------------------------------------*
 |                                                                                                                 |
 | Subprocess                                    Code |            Number of events       |      sigma +- delta    |
 |                                                    |       Tried   Selected   Accepted |     (estimated) (mb)   |
 |                                                    |                                   |                        |
 |-----------------------------------------------------------------------------------------------------------------|
 |                                                    |                                   |                        |
 | f fbar -> gamma*/Z0                            221 |      140682      10000      10000 |   1.458e-06  7.715e-09 |
 |                                                    |                                   |                        |
 | sum                                                |      140682      10000      10000 |   1.458e-06  7.715e-09 |
 |                                                                                                                 |
 *-------  End PYTHIA Event and Cross Section Statistics ----------------------------------------------------------*

i.e. 1458.0 +- 7.7 pb.

Q: How the cross-sections compare?

Answer

The differences of teh corss-section calculated by KKMCee and Pythia8 is (1480.2 - 1458.0) pb = 22.2 pb ; the errors have a statistical and systematic component. Assuming half and half for statistical and systematics, and the systematics fully correlated, the error on the difference is about 8.5 pb, i.e. the two calculatons differ by 2.6 standard deviations. What would you check first?

2.1.4.3. Generating ditaus with Whizard

As explained in the dedicated Whizard section, to use whizard we need a Sindarin configuration file. To generate ditau events we will use the file Z_tautau.sin:

$ wget http://fccsw.web.cern.ch/tutorials/october2020/tutorial1/Z_tautau.sin

and run it in a dedicate directory to not pollute the working one withe the many files produced:

$ mkdir -p whizard/tautau; cd whizard/tautau;
$ whizard ../../Z_tautau.sin

The output created by whizard is LHEf (Les Houches Event format); this is because the curent build does not support writing HepMC; this may change in the future.

Exercise: look at produced LHEf file z_tautau.lhe: what di we notice?

Answer

The taus are not decayed. Investigate if a Sindarin option to decay taus exists.

The first lines of the LHEf file give the total cross-section: 1502 +- 2 pb, which seems dfinetly higher than the othesr.

2.1.4.3.1. `LHEf` to `EDM4hep` conversion

In order to get the events in EDM4hep format, we eploit the fact that Pythia provides LHEf reader functionality. To activate that we will use Gaudi and special .cmd file the consider the input LHEf input file as a Beam. This special .cmd is called Pythia_LHEinput.cmd and it is available under the directory pointed by $K4GEN:

S cp -rp $K4GEN/Pythia_LHEinput.cmd

Please note the lines

! 4) Read-in Les Houches Event file - alternative beam and process selection.
Beams:frameType = 4                      ! read info from a LHEF
Beams:LHEF = Generation/data/events.lhe ! the LHEF to read from

This file needs to be edited to enter the exact locaton of the input file (it could also be a symlink to avoid always editng the file.

As steering we will use the file lhe2edm.py which run the following sequence:

$ wget http://fccsw.web.cern.ch/tutorials/october2020/tutorial1/lhe2edm.py
$ k4run lhe2edm.py -h
 -->  Pythia8 -->  HepMCToEDMConverter -->  HepMCFileWriter -->  StableParticles -->  out

The HepMCFileWriter step is redundant and only serves at converting also in HepMC for controls. The conversion is run by the usual comand:

$ k4run lhe2edm.py -n 10000 --out.filename wz_tautau_10000.e4h.root --HepMCFileWriter.Filename wz_tautau_10000.hepmc 

2.1.4.4. Looking at the produced files: the MCParticle class

Despite being ROOT files, the EDM4hep files are not easily usable, beaue they contain information in EDM4hep classes. A good practie is to use some helper function available in FCAnalyses to create flat ntuple, much more readable.

2.1.4.4.1. Creating flat ntuples with FCCAnalyses

To create flat ntuples using FCCAnalyses we need a Python script to be feed into the framework. An example is available in make_flat.py.

You should have a lok and try to understand what it does. It adds a few event varialbe whihc would be useful to compare.

In order to run it with FCCAnalyses we have to call it like this:

fccanalysis run make_flat.py --test --output kk_tautau_10000.flat.root

and the same the other files.

Exercise: add a variable invmass with the invariant mass of the two taus.

Hint

Look at the the scalarProdNorm.

2.1.4.4.2. Comparing distributions

This is the final exercise: write a ROOT macro, in Python or C++, to compare the global event variables acol, n_charged and cthetauminus, and perhaps also invmass.

Hint

Look at the ROOT tutorials for RDataFrame, TTree and Hist.

What can you say from the comparison?

2.1. FCC: Getting started with event generation

2.1.1. Overview

2.1.2. Enabling FCCSW

2.1.3. Generators

2.1.3.1. Overview

2.1.3.2. Pythia8

2.1.3.3. Whizard

2.1.3.4. MadGraph5

2.1.3.5. Herwig

2.1.3.6. KKMCee

2.1.3.7. BHLUMI

2.1.3.8. BabaYaga

2.1.4. Hands-on case study: ditau events with KKMCee, Pythia8 and Whizard

2.1.4.1. Generating ditaus with KKMCee

2.1.4.1.1. Generating HepMC events

2.1.4.1.2. HepMC to EDM4hep conversion

2.1.4.1.2.1. Dissection of hepmc2edm.py

2.1.4.1.2.2. Running hepmc2edm.py

2.1.4.2. Generating ditaus with Pythia8

2.1.4.3. Generating ditaus with Whizard

2.1.4.3.1. LHEf to EDM4hep conversion

2.1.4.4. Looking at the produced files: the MCParticle class

2.1.4.4.1. Creating flat ntuples with FCCAnalyses

2.1.4.4.2. Comparing distributions

2.1.4.1.1. Generating `HepMC` events

2.1.4.1.2. `HepMC` to `EDM4hep` conversion

2.1.4.1.2.1. Dissection of `hepmc2edm.py`

2.1.4.1.2.2. Running `hepmc2edm.py`

2.1.4.3.1. `LHEf` to `EDM4hep` conversion