6.1.1. Standard Particles¶

Warning

At the moment, the standard particle lists are not recommended for use with recent data processings. This will improve, but for now we recommend only using the lists in MC studies and for benchmarking.

The goal is that the standard particle lists will provide recommended selection criteria for final-state particles, and in some cases, for composite particles. The recommended selections will be provided by the performance group(s). Furthermore systematics will be provided centrally for these recommended lists. For information about their status, please see BII-4105.

There are also some skimming, development and legacy lists available. These are specifically for use in skims, for study, or for comparison with Belle and old simulations.

At the moment they are only to be used for benchmarking, and for studies in MC.

Not (yet) recommended final-state particle list builder functions¶

Warning

Unfortunately these lists are not yet recommended for use with recent data processings.

stdPhotons.stdPhotons(listtype='loose', path=None)[source]¶

Function to prepare one of several standardized types of photon lists:

‘gamma:all’ with no cuts this will be polluted by tracks from outside the acceptance
‘gamma:cdc’ all clusters inside the CDC tracking acceptance
‘gamma:loose’ (default) with some loose quality selections
‘gamma:tight’ like loose but with higher energy cuts depending on detector regions
‘gamma:pi0eff60_Jan2020’ gamma list for 60% pi0 efficiency list, optimized in January 2020
‘gamma:pi0eff50_Jan2020’ gamma list for 50% pi0 efficiency list, optimized in January 2020
‘gamma:pi0eff40_Jan2020’ gamma list for 40% pi0 efficiency list, optimized in January 2020
‘gamma:pi0eff30_Jan2020’ gamma list for 30% pi0 efficiency list, optimized in January 2020
‘gamma:pi0eff20_Jan2020’ gamma list for 20% pi0 efficiency list, optimized in January 2020
‘gamma:pi0eff10_Jan2020’ gamma list for 10% pi0 efficiency list, optimized in January 2020
‘gamma:pi0’ gamma list for pi0 list
‘gamma:pi0highE’ gamma list for pi0 list, high energy selection
For latest pi0 recommendations see https://confluence.desy.de/display/BI/Neutrals+Performance

Parameters

listtype – name of standard list
path – modules are added to this path

stdPi0s.stdPi0s(listtype='eff60_Jan2020', path=None)[source]¶

Function to prepare one of several standardized types of pi0 lists:

‘all’ using gamma:all
‘eff10_Jan2020’ gamma:pi0eff10_Jan2020, mass range selection, 10% pi0 efficiency list, optimized in January 2020
‘eff20_Jan2020’ gamma:pi0eff20_Jan2020, mass range selection, 20% pi0 efficiency list, optimized in January 2020
‘eff30_Jan2020’ gamma:pi0eff30_Jan2020, mass range selection, 30% pi0 efficiency list, optimized in January 2020
‘eff40_Jan2020’ gamma:pi0eff40_Jan2020, mass range selection, 40% pi0 efficiency list, optimized in January 2020
‘eff50_Jan2020’ gamma:pi0eff50_Jan2020, mass range selection, 50% pi0 efficiency list, optimized in January 2020
‘eff60_Jan2020’ gamma:pi0eff60_Jan2020, mass range selection, 60% pi0 efficiency list, optimized in January 2020

You can also append “Fit” to the listtype which will run a mass fit and require that the fit did not fail. For example: “pi0:eff50_Jan2020Fit” is the 50% efficiency list plus a not-failing mass fit.

Parameters

listtype (str) – name of standard list
path (basf2.Path) – modules are added to this path

stdV0s.stdKshorts(prioritiseV0=True, fitter='TreeFit', path=None)[source]¶

Load a combined list of the Kshorts list from V0 objects merged with a list of particles combined using the analysis ParticleCombiner module.

The ParticleList is named K_S0:merged. A vertex fit is performed and only candidates with an invariant mass in the range \(0.450 < M < 0.550~GeV\), and for which the vertex fit did not fail, are kept.

The vertex fitter can be selected among TreeFit, KFit, and Rave.

Parameters

prioritiseV0 (bool) – should the V0 mdst objects be prioritised when merging?
fitter (str) – vertex fitter name, valid options are TreeFit, KFit, and Rave.
path (basf2.Path) – the path to load the modules

stdV0s.stdLambdas(prioritiseV0=True, fitter='TreeFit', path=None)[source]¶

Load a combined list of the Lambda list from V0 objects merged with a list of particles combined using the analysis ParticleCombiner module.

The ParticleList is named Lambda0:merged. A vertex fit is performed and only candidates with an invariant mass in the range \(1.10 < M < 1.13~GeV\), and for which the vertex fit did not fail, are kept.

The vertex fitter can be selected among TreeFit, KFit, and Rave.

Parameters

prioritiseV0 (bool) – should the V0 mdst objects be prioritised when merging?
fitter (str) – vertex fitter name, valid options are TreeFit, KFit, and Rave.
path (basf2.Path) – the path to load the modules

stdCharged.stdPi(listtype='good', path=None)[source]¶

Function to prepare standard pion lists, refer to stdCharged for details

Parameters

listtype – name of standard list
path – modules are added to this path

stdCharged.stdK(listtype='good', path=None)[source]¶

Function to prepare standard kaon lists, refer to stdCharged for details

Parameters

listtype – name of standard list
path – modules are added to this path

stdCharged.stdPr(listtype='good', path=None)[source]¶

Function to prepare standard proton lists, refer to stdCharged for details

Parameters

listtype – name of standard list
path – modules are added to this path

stdCharged.stdE(listtype='good', path=None)[source]¶

Function to prepare standard electron lists, refer to stdCharged for details

Parameters

listtype – name of standard list
path – modules are added to this path

stdCharged.stdMu(listtype='good', path=None)[source]¶

Function to prepare standard muon lists, refer to stdCharged for details

Parameters

listtype – name of standard list
path – modules are added to this path

Other functions available¶

These other functions are not recommended for normal use without some study of the selection, or if you are working on skimming. If you improve these lists, please report in a performance meeting and make a pull request.

stdCharged.stdCharged(particletype, listtype, path)[source]¶

Function to prepare one of several standardized types of charged particle lists:

‘all’ with no cuts on track
‘good’ high purity lists for data studies
‘loosepid’ loose selections for skimming, PID cut only
‘loose’ loose selections for skimming
‘higheff’ high efficiency list with loose global ID cut for data studies
‘mostlikely’ list with the highest PID likelihood

Also the following lists, which may or may not be available depending on the release

‘99eff’ with 99% selection efficiency (calculated for 1<p<4 GeV) and good track (MC only)
‘95eff’ with 95% selection efficiency (calculated for 1<p<4 GeV) and good track (MC only)
‘90eff’ with 90% selection efficiency (calculated for 1<p<4 GeV) and good track (MC only)
‘85eff’ with 85% selection efficiency (calculated for 1<p<4 GeV) and good track (MC only)

Parameters

particletype – type of charged particle to make a list of
listtype – name of standard list
path – modules are added to this path

stdCharged.stdMostLikely(pidPriors=None, suffix='', path=None)[source]¶

Function to prepare most likely particle lists according to PID likelihood, refer to stdCharged for details

Parameters

pidPriors – list of 5 float numbers used to reweight PID likelihoods
suffix – string added to the end of particle list names
path – modules are added to this path

stdPhotons.loadStdGoodBellePhoton(path)[source]¶

Load the Belle goodBelle list. Creates a ParticleList named ‘gamma:goodBelle’ with ‘0.5 < goodBelleGamma < 1.5’

Warning

Should only be used for Belle analyses using B2BII.

Parameters: path (basf2.Path) – the path to load the modules

stdPhotons.loadStdSkimPhoton(path)[source]¶

Function to prepare the skim photon lists.

Warning

Should only be used by skims.

Parameters: path (basf2.Path) – modules are added to this path

stdPi0s.loadStdSkimPi0(path)[source]¶

Function to prepare the skim pi0 lists.

Warning

Should only be used by skims.

Parameters: path (basf2.Path) –

stdV0s.goodBelleKshort(path)[source]¶

Load the Belle goodKshort list. Creates a ParticleList named K_S0:legacyGoodKS. A vertex fit is performed and only candidates that satisfy the goodBelleKshort criteria, with an invariant mass in the range \(0.468 < M < 0.528~GeV\), and for which the vertex fit did not fail, are kept

Parameters: path (basf2.Path) – the path to load the modules

stdKlongs.stdKlongs(listtype='allklm', path=None)[source]¶

Warning

This function is a placeholder for Klong selections. Currently everything but the ‘allklm’ list is disabled pending study.

Prepares the ‘K_L0:allklm’ list with no cuts (all KLM clusters are loaded).

Parameters

listtype (str) – name of standard list options (currently only ‘all’ is supported/recommended)
path (basf2.Path) – modules are added to this path

stdHyperons.goodOmega(omegatype='loose', path=None)[source]¶

Select the standard good \(\Omega^-\) ParticleList named Omega-:veryloose, Omega-:loose, or Omega-:tight from the reconstructed Omega-:std.

See also

BELLE2-NOTE-PH-2019-011.

Parameters

omegatype (str) – specify either veryloose, loose, or tight for good ParticleList selection (default veryloose)
path (basf2.Path) – modules are added to this path building the Omega-:veryloose, Omega-:loose, or Omega-:tight, list

stdHyperons.goodXi(xitype='loose', path=None)[source]¶

Select the standard good \(\Xi^-\) ParticleList named Xi-:veryloose, Xi-:loose, or Xi-:tight from the reconstructed Xi-:std.

See also

BELLE2-NOTE-PH-2019-011.

Parameters

xitype (str) – specify either veryloose, loose, or tight for good ParticleList selection (default loose)
path (basf2.Path) – modules are added to this path building the Xi-:veryloose, Xi-:loose, or Xi-:tight, list

stdHyperons.goodXi0(xitype='loose', path=None)[source]¶

Select the standard good \(\Xi^0\) ParticleList named Xi0:veryloose, Xi0:loose, or Xi0:tight from the reconstructed Xi0:std.

See also

BELLE2-NOTE-PH-2019-011.

Parameters

xitype (str) – specify either veryloose, loose, or tight for good ParticleList selection (default loose)
path (basf2.Path) – modules are added to this path building the Xi0:veryloose, Xi0:loose, or Xi0:tight, list

stdHyperons.stdOmega(fitter='TreeFit', path=None)[source]¶

Reconstruct the standard \(\Omega^-\) ParticleList named Omega-:std.

See also

BELLE2-NOTE-PH-2019-011.

Parameters

fitter (str) – specify either KFit or TreeFit for the vertex reconstructions (default TreeFit)
path (basf2.Path) – modules are added to this path building the Omega-:std list

stdHyperons.stdXi(fitter='TreeFit', path=None)[source]¶

Reconstruct the standard \(\Xi^-\) ParticleList named Xi-:std.

See also

BELLE2-NOTE-PH-2019-011.

Parameters

fitter (str) – specify either KFit or TreeFit for the vertex reconstructions (default TreeFit)
path (basf2.Path) – modules are added to this path building the Xi-:std list

stdHyperons.stdXi0(gammatype='eff40', path=None)[source]¶

Reconstruct the standard \(\Xi^0\) ParticleList named Xi0:std.

See also

BELLE2-NOTE-PH-2019-011.

Parameters

gammatype (str) – specify either eff60, eff50, eff40, eff30, or eff20 to select the signal efficiency of the photons used in the pi0 reconstruction (default eff40)
path (basf2.Path) – modules are added to this path building the Xi0:std list