Standard Particles

7.1.1. Standard Particles#

Deprecated since version light-2604-jellyfish: stdCharged.stdE, stdCharged.stdMu, stdCharged.stdLep, and most lists in stdPhotons and stdPi0s are deprecated and will be removed at the end of 2026. Use the following replacements or the ‘all’ list instead:

  • stdCharged.stdCharged with listtype='base': thetaInCDCAcceptance and dr < 0.5 and abs(dz) < 2

  • stdPhotons.stdPhotons with listtype='base': inCDCAcceptance and abs(clusterTiming) < 200

  • For pi0s, use reconstructDecay directly with a suitable photon selection, mass window, and any other variables recommended by the performance group.

These lists provide a common baseline; further selections should be optimised based on the requirements of each individual analysis. Please refer to b2help-recommendation: Tool to print analysis recommendations (web version) for further guidance. To provide feedback on the removal, see work item #11641.

Warning

Some standard particle lists are outdated and no longer recommended for use. Please refer to b2help-recommendation: Tool to print analysis recommendations (web version) for recommended selections and the latest updates on what to use.

Tip

The following V0 standard lists are good (i.e. recommended for use):

These standard particle lists provide common selection criteria for final-state particles, and in some cases, for composite particles. 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. If you don’t know that you specifically need these legacy/skim lists, then avoid them.

Default final-state particle list builder functions#

stdPi0s.stdPi0s(listtype='eff60_May2020', path=None, beamBackgroundMVAWeight='', fakePhotonMVAWeight='', biasCorrectionTable='', writeOut=True)[source]#

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

The following lists are deprecated and will be removed at the end of 2026:

  • ‘all’ using gamma:all, no cuts

  • ‘eff10_May2020’ gamma:pi0eff10_May2020, mass range selection, 10% pi0 efficiency list, optimized in May 2020

  • ‘eff20_May2020’ gamma:pi0eff20_May2020, mass range selection, 20% pi0 efficiency list, optimized in May 2020

  • ‘eff30_May2020’ gamma:pi0eff30_May2020, mass range selection, 30% pi0 efficiency list, optimized in May 2020

  • ‘eff40_May2020’ gamma:pi0eff40_May2020, mass range selection, 40% pi0 efficiency list, optimized in May 2020

  • ‘eff50_May2020’ gamma:pi0eff50_May2020, mass range selection, 50% pi0 efficiency list, optimized in May 2020

  • ‘eff60_May2020’ gamma:pi0eff60_May2020, mass range selection, 60% pi0 efficiency list, optimized in May 2020

You can also append “Fit” to the effXX listtype which will run a mass fit and require that the fit did not fail. For example: “pi0:eff50_May2020Fit” is the 50% efficiency list plus a not-failing mass fit. These Fit variants are also deprecated, fits with mass constraint can be performed manually when necessary.

Deprecated since version light-2604-jellyfish: All list types in this function are deprecated and will be removed at the end of 2026. Please use reconstructDecay directly with an appropriate selection optimised for your analysis. Refer to the b2help-recommendation: Tool to print analysis recommendations tool (web version: Performance Recommendations) for guidance. To provide feedback on the removal, see work item #11641.

Parameters:

  • listtype (str) – name of standard list

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

  • beamBackgroundMVAWeight (str) –

    type of weight file for beam background MVA; if empty, beam background MVA will not be used

    Tip

    Please refer to the Performance Recommendations for information on the beam background MVA.

  • fakePhotonMVAWeight (str) –

    type of weight file for fake photon MVA; if empty, fake photon MVA will not be used

    Tip

    Please refer to the Performance Recommendations for information on the fake photon MVA.

  • biasCorrectionTable (str) –

    correction table for the photon energy bias correction (should only be applied to data)

    Tip

    Please refer to the Performance Recommendations for information on the names of available correction tables.

  • writeOut (bool) – whether RootOutput module should save the created ParticleList

stdV0s.stdKshorts(prioritiseV0=True, fitter='TreeFit', path=None, updateAllDaughters=False, writeOut=False, addSuffix=False)[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 by default. If addSuffix is set to True, then a suffix of form _<fitter> is added depending on the chosen fitter. A vertex fit is performed and only candidates with an invariant mass in the range \(0.450 < M < 0.550~GeV\) after the vertex fit, 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

  • updateAllDaughters (bool) –

    see the updateAllDaughters parameter of vertex.treeFit or the daughtersUpdate parameter of vertex.kFit / vertex.raveFit.

    Warning

    The momenta of the daughters are updated only if updateAllDaughters is set to True (i.e. not by default). Some variables, e.g. daughterAngle, will only return meaningful results if the daughters momenta are updated.

    This happens because variables like daughterAngle assume the direction of the daughers momenta at the Ks vertex to be provided, while non-updated daughters will provide their momenta direction at the point-of-closest-approach (POCA) to the beam axis.

  • writeOut (bool) – whether RootOutput module should save the created ParticleList

  • addSuffix (bool) – whether to add a suffix of form _<fitter> to the ParticleList name depending on the chosen fitter

stdV0s.stdLambdas(prioritiseV0=True, fitter='TreeFit', path=None, updateAllDaughters=False, writeOut=False, addSuffix=False)[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 by default. If addSuffix is set to True, then a suffix of form _<fitter> is added depending on the chosen fitter. A vertex fit is performed and only candidates with an invariant mass in the range \(1.10 < M < 1.13~GeV\) after the vertex fit, 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

  • updateAllDaughters (bool) –

    see the updateAllDaughters parameter of vertex.treeFit or the daughtersUpdate parameter of vertex.kFit / vertex.raveFit.

    Warning

    The momenta of the daughters are updated only if updateAllDaughters is set to True (i.e. not by default). Some variables, e.g. daughterAngle, will only return meaningful results if the daughters momenta are updated.

    This happens because variables like daughterAngle assume the direction of the daughers momenta at the Lambda vertex to be provided, while non-updated daughters will provide their momenta direction at the point-of-closest-approach (POCA) to the beam axis.

  • writeOut (bool) – whether RootOutput module should save the created ParticleList

  • addSuffix (bool) – whether to add a suffix of form _<fitter> to the ParticleList name depending on the chosen fitter

stdCharged.stdE(listtype='good', method=None, classification=None, lid_weights_gt=None, release=None, channel_eff='combination', channel_misid_pi='combination', channel_misid_K='combination', inputListName=None, outputListLabel=None, trainingModeMulticlass=(Belle2::ChargedPidMVAWeights::ChargedPidMVATrainingMode::Belle2::ChargedPidMVAWeights::ChargedPidMVATrainingMode::c_Multiclass) : (unsigned int) 1, trainingModeBinary=(Belle2::ChargedPidMVAWeights::ChargedPidMVATrainingMode::Belle2::ChargedPidMVAWeights::ChargedPidMVATrainingMode::c_Classification) : (unsigned int) 0, path=None)[source]#

Function to prepare one of several standardized types of electron lists. See the documentation of stdLep for details.

Deprecated since version light-2604-jellyfish: Please use stdCharged and apply PID cuts manually depending on your analysis. Efficiency corrections are available via the systematic corrections framework. To provide feedback on the removal, see work item #11641.

It also accepts any of the legacy definitions for the listtype parameter (aka working_point in stdLep) to fall back to the stdCharged behaviour:

  • ‘all’

  • ‘good’ (deprecated, will be removed end of 2026)

  • ‘loosepid’ (deprecated, will be removed end of 2026)

  • ‘loose’ (deprecated, will be removed end of 2026)

  • ‘higheff’ (deprecated, will be removed end of 2026)

  • ‘95eff’ (deprecated, will be removed end of 2026)

  • ‘90eff’ (deprecated, will be removed end of 2026)

  • ‘85eff’ (deprecated, will be removed end of 2026)

Returns:

the alias for the electron ID variable, and the list of aliases for the weights.

Return type:

tuple(str, list(str))

stdCharged.stdMu(listtype='good', method=None, classification=None, lid_weights_gt=None, release=None, channel_eff='combination', channel_misid_pi='combination', channel_misid_K='combination', inputListName=None, outputListLabel=None, trainingModeMulticlass=(Belle2::ChargedPidMVAWeights::ChargedPidMVATrainingMode::Belle2::ChargedPidMVAWeights::ChargedPidMVATrainingMode::c_Multiclass) : (unsigned int) 1, trainingModeBinary=(Belle2::ChargedPidMVAWeights::ChargedPidMVATrainingMode::Belle2::ChargedPidMVAWeights::ChargedPidMVATrainingMode::c_Classification) : (unsigned int) 0, path=None)[source]#

Function to prepare one of several standardized types of muon lists. See the documentation of stdLep for details.

Deprecated since version light-2604-jellyfish: Please use stdCharged and apply PID cuts manually depending on your analysis. Efficiency corrections are available via the systematic corrections framework. To provide feedback on the removal, see work item #11641.

It also accepts any of the legacy definitions for the listtype parameter (aka working_point in stdLep) to fall back to the stdCharged behaviour:

  • ‘all’

  • ‘good’ (deprecated, will be removed end of 2026)

  • ‘loosepid’ (deprecated, will be removed end of 2026)

  • ‘loose’ (deprecated, will be removed end of 2026)

  • ‘higheff’ (deprecated, will be removed end of 2026)

  • ‘95eff’ (deprecated, will be removed end of 2026)

  • ‘90eff’ (deprecated, will be removed end of 2026)

  • ‘85eff’ (deprecated, will be removed end of 2026)

Returns:

the alias for the muon ID variable, and the list of aliases for the weights.

Return type:

tuple(str, list(str))

stdCharged.stdLep(pdgId, working_point, method, classification, lid_weights_gt, release=None, channel_eff='combination', channel_misid_pi='combination', channel_misid_K='combination', inputListName=None, outputListLabel=None, trainingModeMulticlass=(Belle2::ChargedPidMVAWeights::ChargedPidMVATrainingMode::Belle2::ChargedPidMVAWeights::ChargedPidMVATrainingMode::c_Multiclass) : (unsigned int) 1, trainingModeBinary=(Belle2::ChargedPidMVAWeights::ChargedPidMVATrainingMode::Belle2::ChargedPidMVAWeights::ChargedPidMVATrainingMode::c_Classification) : (unsigned int) 0, path=None)[source]#

Function to prepare one of several standardized types of lepton (\(e,\mu\)) lists, with the following working points:

Deprecated since version light-2604-jellyfish: Please use stdCharged and apply PID cuts manually depending on your analysis. Efficiency corrections are available via the systematic corrections framework. To provide feedback on the removal, see work item #11641.

  • ‘FixedThresh05’, PID cut of > 0.5 for each particle in the list.

  • ‘FixedThresh09’, PID cut of > 0.9 for each particle in the list.

  • ‘FixedThresh095’, PID cut of > 0.95 for each particle in the list.

  • ‘FixedThresh099’, PID cut of > 0.99 for each particle in the list.

  • ‘UniformEff60’ 60% lepton efficiency list, uniform in a given multi-dimensional parametrisation.

  • ‘UniformEff70’ 70% lepton efficiency list, uniform in a given multi-dimensional parametrisation.

  • ‘UniformEff80’ 80% lepton efficiency list, uniform in a given multi-dimensional parametrisation.

  • ‘UniformEff90’ 90% lepton efficiency list, uniform in a given multi-dimensional parametrisation.

  • ‘UniformEff95’ 95% lepton efficiency list, uniform in a given multi-dimensional parametrisation.

  • ‘UniformPiFR5EM1’ 50% pion to lepton fake rate, uniform in a given multi-dimensional parametrisation.

  • ‘UniformPiFR1EM1’ 10% pion to lepton fake rate, uniform in a given multi-dimensional parametrisation.

  • ‘UniformPiFR5EM2’ 5% pion to lepton fake rate, uniform in a given multi-dimensional parametrisation.

  • ‘UniformPiFR1EM2’ 1% pion to lepton fake rate, uniform in a given multi-dimensional parametrisation.

  • ‘UniformPiFR5EM3’ 0.5% pion to lepton fake rate, uniform in a given multi-dimensional parametrisation.

  • ‘UniformPiFR1EM3’ 0.1% pion to lepton fake rate, uniform in a given multi-dimensional parametrisation.

The function creates a ParticleList, selecting particles according to the chosen working_point, and decorates each candidate in the list with the nominal Data/MC \(\ell\) ID efficiency and \(\pi,K\) fake rate correction factors and their stat, syst uncertainty, reading the info from the Conditions Database (CDB) according to the chosen input global tag (GT).

Note

Particles will not be selected if they are outside the Data/MC efficiency corrections’ phase space coverage for the given working point. In fact, the threshold value for the PID cut in such cases is set to NaN.

Warning

At the moment, the only supported binary lepton identification is against the pion hypothesis. This implies that, if binary classification is chosen, only \(\pi\) fake rate corrections will be added to the resulting particle list.

Parameters:

  • pdgId (int) – the lepton pdg code.

  • working_point (str) – name of the chosen working point that defines the content of the list. Choose among the above values.

  • method (str) – the PID method: ‘likelihood’ or ‘bdt’.

  • classification (str) – the type of classifier: ‘binary’ (one-vs-pion) or ‘global’ (one-vs-all).

  • lid_weights_gt (str) –

    the name identifier of the global tag with the recommended Data/MC correction weights.

    Tip

    Please refer to the Charged PID XWiki page for info about the recommended global tags.

  • release (Optional[int]) –

    the major release number of the data and MC campaigns considered. If specified, it ensures the correct \(\ell\) ID variables are used.

    Tip

    Please refer to the Charged PID XWiki page for info about lepton identification variables and campaigns.

  • channel_eff (Optional[str]) –

    the channel used to derive the \(\ell\) ID efficiency corrections. By default, ‘combination’ is set, meaning they are obtained by combining results of several hadronic and low multiplicity channels, wherever they overlap.

    Tip

    Please refer to the Charged PID XWiki page for other possible choices (if any).

  • channel_misid_pi (Optional[str]) – the channel used to derive the \(\pi\) fake rate corrections.

  • channel_misid_K (Optional[str]) – the channel used to derive the \(K\) fake rate corrections.

  • inputListName (Optional[str]) –

    the name of a pre-existing ParticleList object (defined as a full decayString, e.g. ‘e-:my_input_electrons’) of which the standard lepton list will be a subset. For instance, users might want to apply a Bremsstrahlung correction to electrons first, which modifies their 4-momentum, and only later define the subset passing the PID selection, including the appropriate PID weights and uncertainties (which are \(p\)-dependent). By default, the standard lepton list is created from all Track objects in the event.

    Warning

    Do not apply any PID selection on the input list, otherwise results could be biased.

  • outputListLabel (Optional[str]) – the name of the output lepton list label, i.e., the string that follows the particle identifier (‘e-:’, ‘mu-:’). By default, it is assigned as: '{method}_{classification}_{working_point}'.

  • trainingModeMulticlass (Optional[Belle2.ChargedPidMVAWeights.ChargedPidMVATrainingMode]) – enum identifier of the multi-class (global PID) training mode. See modularAnalysis.applyChargedPidMVA docs for available options.

  • trainingModeBinary (Optional[Belle2.ChargedPidMVAWeights.ChargedPidMVATrainingMode]) – enum identifier of the classification (binary PID) training mode. See modularAnalysis.applyChargedPidMVA docs for available options.

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

Returns:

the alias for the lepton ID variable, and the list of aliases for the weights.

Return type:

tuple(str, list(str))

Other functions available#

Warning

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

stdCharged.stdCharged(particletype, listtype, path, writeOut=True)[source]#

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

  • ‘all’ with no cuts on track

  • ‘base’ tracks passing trackQuality and IP cuts (thetaInCDCAcceptance and dr < 0.5 and abs(dz) < 2), no PID requirement

  • ‘good’ high purity lists for data studies [deprecated, will be removed end of 2026]

  • ‘loosepid’ loose selections for skimming, PID cut only [deprecated, will be removed end of 2026]

  • ‘loose’ loose selections for skimming [deprecated, will be removed end of 2026]

  • ‘higheff’ high efficiency list with loose global ID cut for data studies [deprecated, will be removed end of 2026]

  • ‘mostlikely’ list with the highest PID likelihood [deprecated, will be removed end of 2026]

Note

After end of 2026 only the 'all' and 'base' lists will be available.

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) [deprecated, will be removed end of 2026]

  • ‘95eff’ with 95% selection efficiency (calculated for 1<p<4 GeV) and good track (MC only) [deprecated, will be removed end of 2026]

  • ‘90eff’ with 90% selection efficiency (calculated for 1<p<4 GeV) and good track (MC only) [deprecated, will be removed end of 2026]

  • ‘85eff’ with 85% selection efficiency (calculated for 1<p<4 GeV) and good track (MC only) [deprecated, will be removed end of 2026]

Deprecated since version light-2604-jellyfish: The list types 'good', 'loosepid', 'loose', 'higheff', 'mostlikely', '99eff', '95eff', '90eff', and '85eff' will be removed at the end of 2026. Only 'all' and 'base' will be kept. Please update your analysis accordingly. To provide feedback on the removal, see work item #11641.

Parameters:

  • particletype – type of charged particle to make a list of

  • listtype – name of standard list

  • path – modules are added to this path

  • writeOut – whether RootOutput module should save the created ParticleList

stdCharged.stdMostLikely(pidPriors=None, suffix='', custom_cuts='', path=None, writeOut=True)[source]#

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

Deprecated since version light-2604-jellyfish: Please update your analysis to use the stdCharged 'all' or 'base' lists instead. To provide feedback on the removal, see work item #11641.

Parameters:

  • pidPriors – list of 6 float numbers used to reweight PID likelihoods, for e, mu, pi, K, p and d

  • suffix – string added to the end of particle list names

  • custom_cuts – custom selection cut string, if empty, standard track quality cuts will be applied

  • path – modules are added to this path

  • writeOut – whether RootOutput module should save the created ParticleList

stdPhotons.loadStdGoodBellePhoton(path)[source]#

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

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.loadStdSkimHighEffPi0(path)[source]#

Function to prepare the high-efficiency skim pi0 lists based on eff60_May2020 list.

Warning

Should only be used by skims.

Parameters:

path (basf2.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 \(0.468 < M < 0.528~GeV\) after the vertex fit, and for which the vertex fit did not fail, are kept.

Parameters:

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

stdV0s.scaleErrorKshorts(prioritiseV0=True, fitter='TreeFit', scaleFactors_V0=[1.125927, 1.058803, 1.205928, 1.066734, 1.047513], scaleFactorsNoPXD_V0=[1.125927, 1.058803, 1.205928, 1.066734, 1.047513], d0Resolution_V0=[0.001174, 0.000779], z0Resolution_V0=[0.00135, 0.000583], d0MomThr_V0=0.5, z0MomThr_V0=0.0, scaleFactors_RD=[1.149631, 1.085547, 1.151704, 1.096434, 1.086659], scaleFactorsNoPXD_RD=[1.149631, 1.085547, 1.151704, 1.096434, 1.086659], d0Resolution_RD=[0.00115328, 0.00134704], z0Resolution_RD=[0.00124327, 0.0013272], d0MomThr_RD=0.5, z0MomThr_RD=0.5, addSuffix=False, path=None)[source]#

Reconstruct K_S0 applying helix error correction to K_S0 daughters given by modularAnalysis.scaleError. The ParticleList is named K_S0:scaled by default. If addSuffix is set to True, then a suffix of form _<fitter> is added.

Considering the difference of multiple scattering through the beam pipe, different parameter sets are used for K_S0 decaying outside/inside the beam pipe (K_S0:V0/RD).

Only for TDCPV analysis.

Parameters:

  • prioritiseV0 – If True K_S0 from V0 object is prioritised over RD when merged.

  • fitter – Vertex fitter option. Choose from TreeFit, KFit and Rave.

  • scaleFactors_V0 – List of five constants to be multiplied to each of helix errors (for tracks with a PXD hit)

  • scaleFactorsNoPXD_V0 – List of five constants to be multiplied to each of helix errors (for tracks without a PXD hit)

  • d0Resolution_V0 – List of two parameters, (a [cm], b [cm/(GeV/c)]), defining d0 best resolution as sqrt{ a**2 + (b / (p*beta*sinTheta**1.5))**2 }

  • z0Resolution_V0 – List of two parameters, (a [cm], b [cm/(GeV/c)]), defining z0 best resolution as sqrt{ a**2 + (b / (p*beta*sinTheta**2.5))**2 }

  • d0MomThr_V0 – d0 best resolution is kept constant below this momentum

  • z0MomThr_V0 – z0 best resolution is kept constant below this momentum

  • scaleFactors_RD – List of five constants to be multiplied to each of helix errors (for tracks with a PXD hit)

  • scaleFactorsNoPXD_RD – List of five constants to be multiplied to each of helix errors (for tracks without a PXD hit)

  • d0Resolution_RD – List of two parameters, (a [cm], b [cm/(GeV/c)]), defining d0 best resolution as sqrt{ a**2 + (b / (p*beta*sinTheta**1.5))**2 }

  • z0Resolution_RD – List of two parameters, (a [cm], b [cm/(GeV/c)]), defining z0 best resolution as sqrt{ a**2 + (b / (p*beta*sinTheta**2.5))**2 }

  • d0MomThr_RD – d0 best resolution is kept constant below this momentum

  • z0MomThr_RD – z0 best resolution is kept constant below this momentum

  • addSuffix – Whether to add a suffix of form _<fitter> to the ParticleList name depending on the chosen fitter

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

Warning

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

By default, prepares the ‘K_L0:allklm’ list with no cuts (all KLM clusters are loaded). It’s possible to provide the argument ‘allecl’ to create a list of all ECL clusters loaded as Klong candidates.

Parameters:

  • listtype (str) – name of standard list options (currently only ‘allklm’ and ‘allecl’ are supported/recommended)

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

Deprecated since version light-2604-jellyfish: All functions in stdHyperons (stdXi, stdXi0, stdOmega, goodXi, goodXi0, goodOmega) are deprecated and will be removed at the end of 2026. Please replace them with a custom hyperon reconstruction and selection optimised for your specific analysis. To provide feedback on the removal, see work item #11641.

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', addSuffix=False, path=None)[source]#

Reconstruct the standard \(\Omega^-\) ParticleList named Omega-:std. If addSuffix is set to True, then a suffix of form _<fitter> is added depending on the chosen fitter.

See also

BELLE2-NOTE-PH-2019-011.

Parameters:

  • fitter (str) – specify either KFit or TreeFit for the vertex reconstructions (default TreeFit)

  • addSuffix (bool) – whether to add a suffix of form _<fitter> to the ParticleList name depending on the chosen fitter

  • path (basf2.Path) – modules are added to this path building the Omega-:std list

stdHyperons.stdXi(fitter='TreeFit', addSuffix=False, path=None)[source]#

Reconstruct the standard \(\Xi^-\) ParticleList named Xi-:std by default. If addSuffix is set to True, then a suffix of form _<fitter> is added depending on the chosen fitter.

See also

BELLE2-NOTE-PH-2019-011.

Parameters:

  • fitter (str) – specify either KFit or TreeFit for the vertex reconstructions (default TreeFit)

  • addSuffix (bool) – whether to add a suffix of form _<fitter> to the ParticleList name depending on the chosen fitter

  • path (basf2.Path) – modules are added to this path building the Xi-:std list

stdHyperons.stdXi0(gammatype='eff40', beamBackgroundMVAWeight='', fakePhotonMVAWeight='', biasCorrectionTable='', 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)

  • beamBackgroundMVAWeight (str) –

    type of weight file for beam background MVA; if empty, beam background MVA will not be used

    Tip

    Please refer to the Performance Recommendations for information on the beam background MVA.

  • fakePhotonMVAWeight (str) –

    type of weight file for fake photon MVA; if empty, fake photon MVA will not be used

    Tip

    Please refer to the Performance Recommendations for information on the fake photon MVA.

  • biasCorrectionTable (str) –

    correction table for the photon energy bias correction (should only be applied to data)

    Tip

    Please refer to the Performance Recommendations for information on the names of available correction tables.

  • path (basf2.Path) – modules are added to this path building the Xi0:std list

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