Sample with jet, track and secondary vertex properties for Hbb tagging ML studies HiggsToBBNTuple_HiggsToBB_QCD_RunII_13TeV_MC

Description

The dataset consists of particle jets extracted from simulated proton-proton collision events at a center-of-mass energy of 13 TeV generated with Pythia 8. It has been produced for developing machine-learning algorithms to differentiate jets originating from a Higgs boson decaying to a bottom quark-antiquark pair (Hbb) from quark or gluon jets originating from quantum chromodynamic (QCD) multijet production.

The reconstructed jets are clustered using the anti-kT algorithm with R=0.8 from particle flow (PF) candidates (AK8 jets). The standard L1+L2+L3+residual jet energy corrections are applied to the jets and pileup contamination is mitigated using the charged hadron subtraction (CHS) algorithm. Features of the AK8 jets with transverse momentum pT > 200 GeV and pseudorapidity |η| < 2.4 are provided. Selected features of inclusive (both charged and neutral) PF candidates with pT > 0.95 GeV associated to the AK8 jet are provided. Additional features of charged PF candidates (formed primarily by a charged particle track) with pT > 0.95 GeV associated to the AK8 jet are also provided. Finally, additional features of reconstructed secondary vertices (SVs) associated to the AK8 jet (within ∆R < 0.8) are also provided.

Related datasets

This dataset was derived from:

/BulkGravTohhTohbbhbb_narrow_M-600_13TeV-madgraph/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM

/BulkGravTohhTohbbhbb_narrow_M-1000_13TeV-madgraph/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM

/BulkGravTohhTohbbhbb_narrow_M-1200_13TeV-madgraph/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/BulkGravTohhTohbbhbb_narrow_M-1400_13TeV-madgraph/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/BulkGravTohhTohbbhbb_narrow_M-1600_13TeV-madgraph/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/BulkGravTohhTohbbhbb_narrow_M-1800_13TeV-madgraph/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/BulkGravTohhTohbbhbb_narrow_M-2000_13TeV-madgraph/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/BulkGravTohhTohbbhbb_narrow_M-2000_13TeV-madgraph/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM

/BulkGravTohhTohbbhbb_narrow_M-2500_13TeV-madgraph/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/BulkGravTohhTohbbhbb_narrow_M-3000_13TeV-madgraph/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM

/BulkGravTohhTohbbhbb_narrow_M-4000_13TeV-madgraph/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/BulkGravTohhTohbbhbb_narrow_M-4500_13TeV-madgraph/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/QCD_Pt_300to470_TuneCUETP8M1_13TeV_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/QCD_Pt_470to600_TuneCUETP8M1_13TeV_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/QCD_Pt_600to800_TuneCUETP8M1_13TeV_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/QCD_Pt_800to1000_TuneCUETP8M1_13TeV_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/QCD_Pt_1000to1400_TuneCUETP8M1_13TeV_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/QCD_Pt_1400to1800_TuneCUETP8M1_13TeV_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/QCD_Pt_1800to2400_TuneCUETP8M1_13TeV_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/QCD_Pt_2400to3200_TuneCUETP8M1_13TeV_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM

/QCD_Pt_3200toInf_TuneCUETP8M1_13TeV_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v3/MINIAODSIM

Dataset characteristics

182 files. 228.1 GiB in total.

Dataset semantics

Variable	Type	Description
event_no	UInt_t	Event number
npv	Float_t	Number of reconstructed primary vertices (PVs)
ntrueInt	Float_t	True mean number of the poisson distribution for this event from which the number of interactions in each bunch crossing has been sampled
rho	Float_t	Median density (in GeV/A) of pile-up contamination per event; computed from all PF candidates of the event
sample_isQCD	Int_t	Boolean that is 1 if the simulated sample corresponds to QCD multijet production
label_H_bb	Int_t	Boolean that is 1 if a Higgs boson is matched and at least two b quarks are found within the AK8 jet
label_QCD_bb	Int_t	Boolean that is 1 if no resonances are matched and at least two b quarks are found within the AK8 jet
label_QCD_b	Int_t	Boolean that is 1 if no resonances are matched and only one b quark is found within the AK8 jet
label_QCD_cc	Int_t	Boolean that is 1 if no resonances are matched and at least two c quarks are found within the AK8 jet
label_QCD_c	Int_t	Boolean that is 1 if no resonances are matched and only one c quark is found within the AK8 jet
label_QCD_others	Int_t	Boolean that is 1 if no resonances are matched and no b or c quarks are found within the AK8 jet
fj_doubleb	Float_t	Double-b tagging discriminant based on a boosted decision tree calculated for the AK8 jet (see CMS-BTV-16-002)
fj_eta	Float_t	Pseudorapidity η of the AK8 jet
fj_gen_eta	Float_t	Pseudorapidity η of the generator-level, matched heavy particle: H, W, Z, top, etc. (default = -999)
fj_gen_pt	Float_t	Transverse momentum of the generator-level, geometrically matched heavy particle: H, W, Z, t, etc. (default = -999)
fj_isBB	Int_t	Boolean that is 1 if two or more b hadrons are clustered within the AK8 jet (see SWGuideBTagMCTools)
fj_isNonBB	Int_t	Boolean that is 1 if fewer than two b hadrons are clustered within the AK8 jet (see SWGuideBTagMCTools)
fj_nbHadrons	Int_t	Number of b hadrons that are clustered within the AK8 jet (see SWGuideBTagMCTools)
fj_ncHadrons	Int_t	Number of c hadrons that are clustered within the AK8 jet (see SWGuideBTagMCTools)
fj_isH	Int_t	Boolean that is 1 if a generator-level Higgs boson and its daughters are geometrically matched to the AK8 jet
fj_isTop	Int_t	Boolean that is 1 if a generator-level top quark and its daughters are geometrically matched to the AK8 jet
fj_isW	Int_t	Boolean that is 1 if a generator-level W boson and its daughters are geometrically matched to the AK8 jet
fj_isZ	Int_t	Boolean that is 1 if a generator-level Z boson and its daughters are geometrically matched to the AK8 jet
fj_isQCD	Int_t	Boolean that is 1 if none of the above matching criteria are satisfied (H, top, W, Z)
fj_label	Int_t	Integer label: `Invalid=0, Top_all=10, Top_bcq=11, Top_bqq=12, Top_bc=13, Top_bq=14, W_all=20, W_cq=21, W_qq=22, Z_all=30, Z_bb=31, Z_cc=32, Z_qq=33, H_all=40, H_bb=41, H_cc=42, H_qqqq=43, QCD_all=50, QCD_bb=51, QCD_cc=52, QCD_b=53, QCD_c=54, QCD_others=55`
fj_labelJMAR	Int_t	Alternative integer label from the CMS Jet/MET and Resolution (JMAR) group: `Default=0, Top=1, W=2, Z=3, H=4`
fj_labelLegacy	Int_t	Alternative (legacy) integer label: `Default=0, Top=1, W=2, Z=3, H=4`
fj_jetNTracks	Float_t	Number of tracks associated with the AK8 jet
fj_nSV	Float_t	Number of SVs associated with the AK8 jet (∆R < 0.7)
fj_n_sdsubjets	Float_t	Number of soft drop subjets in the AK8 jet (up to 2)
fj_mass	Float_t	Ungroomed mass of the AK8 jet
fj_phi	Float_t	Azimuthal angle ϕ of the AK8 jet
fj_pt	Float_t	Transverse momentum of the AK8 jet
fj_tau1	Float_t	N-subjettiness variable for a 1-prong jet hypothesis
fj_tau2	Float_t	N-subjettiness variable for a 2-prong jet hypothesis
fj_tau3	Float_t	N-subjettiness variable for a 3-prong jet hypothesis
fj_tau21	Float_t	N-subjettiness variable for 2-prong vs 1-prong jet discrimination (`fj_tau2/fj_tau1`)
fj_tau32	Float_t	N-subjettiness variable for 3-prong vs 2-prong jet discrimination (`fj_tau3/fj_tau2`)
fj_sdmass	Float_t	Soft drop mass of the AK8 jet
fj_ptDR	Float_t	Transverse momentum times the ΔR between the two soft drop subjets
fj_relptdiff	Float_t	Absolute relative difference between the transverse momenta of the two softdrop subjets
fj_sdn2	Float_t	Fraction of second subjet transverse momentum times ∆R squared
fj_sdsj1_axis1	Float_t	First axis of the first subjet
fj_sdsj1_axis2	Float_t	Second axis of the first subjet
fj_sdsj1_csv	Float_t	Combined secondary vertex (CSV) b-tagging discriminant for the first subjet
fj_sdsj1_eta	Float_t	Pseudorapidity η of the first subjet
fj_sdsj1_mass	Float_t	Mass of the first subjet
fj_sdsj1_mult	Float_t	Particle multiplicity of the first subjet
fj_sdsj1_phi	Float_t	Azimuthal angle ϕ of the first subjet
fj_sdsj1_pt	Float_t	Transverse momentum of the first subjet
fj_sdsj1_ptD	Float_t	ptD variable, defined as the square root of the sum in quadrature of the transverse momentum of the subjet constituents divided by the scalar sum of the transverse momentum of the subjet constituents, for the first subjet (see CMS-PAS-JME-13-002)
fj_sdsj2_axis1	Float_t	First axis of the first subjet
fj_sdsj2_axis2	Float_t	Second axis of the first subjet
fj_sdsj2_csv	Float_t	Combined secondary vertex (CSV) b-tagging discriminant for the first subject
fj_sdsj2_eta	Float_t	Pseudorapidity η of the second subjet
fj_sdsj2_mass	Float_t	Mass of the second subjet
fj_sdsj2_mult	Float_t	Particle multiplicity of the second subjet
fj_sdsj2_phi	Float_t	Azimuthal angle ϕ of the second subjet
fj_sdsj2_pt	Float_t	Transverse momentum of the second subjet
fj_sdsj2_ptD	Float_t	ptD variable, defined as the square root of the sum in quadrature of the transverse momentum of the subjet constituents divided by the scalar sum of the transverse momentum of the subjet constituents, for the second subjet (see CMS-PAS-JME-13-002)
fj_z_ratio	Float_t	z ratio variable as defined in CMS-BTV-16-002
fj_trackSipdSig_0	Float_t	First largest track 3D signed impact parameter significance (see CMS-BTV-16-002)
fj_trackSipdSig_1	Float_t	Second largest track 3D signed impact parameter significance (see CMS-BTV-16-002)
fj_trackSipdSig_2	Float_t	Third largest track 3D signed impact parameter significance (see CMS-BTV-16-002)
fj_trackSipdSig_3	Float_t	Fourth largest track 3D signed impact parameter significance (see CMS-BTV-16-002)
fj_trackSipdSig_0_0	Float_t	First largest track 3D signed impact parameter significance associated to the first N-subjettiness axis
fj_trackSipdSig_0_1	Float_t	Second largest track 3D signed impact parameter significance associated to the first N-subjettiness axis
fj_trackSipdSig_1_0	Float_t	First largest track 3D signed impact parameter significance associated to the second N-subjettiness axis
fj_trackSipdSig_1_1	Float_t	Second largest track 3D signed impact parameter significance associated to the second N-subjettiness axis
fj_trackSip2dSigAboveCharm_0	Float_t	Track 2D signed impact parameter significance of the first track lifting the combined invariant mass of the tracks above the c hadron threshold mass (1.5 GeV)
fj_trackSip2dSigAboveBottom_0	Float_t	Track 2D signed impact parameter significance of the first track lifting the combined invariant mass of the tracks above b hadron threshold mass (5.2 GeV)
fj_trackSip2dSigAboveBottom_1	Float_t	Track 2D signed impact parameter significance of the second track lifting the combined invariant mass of the tracks above b hadron threshold mass (5.2 GeV)
fj_tau0_trackEtaRel_0	Float_t	Smallest track pseudorapidity ∆η, relative to the jet axis, associated to the first N-subjettiness axis
fj_tau0_trackEtaRel_1	Float_t	Second smallest track pseudorapidity ∆η, relative to the jet axis, associated to the first N-subjettiness axis
fj_tau0_trackEtaRel_2	Float_t	Third smallest track pseudorapidity ∆η, relative to the jet axis, associated to the first N-subjettiness axis
fj_tau1_trackEtaRel_0	Float_t	Smallest track pseudorapidity ∆η, relative to the jet axis, associated to the second N-subjettiness axis
fj_tau1_trackEtaRel_1	Float_t	Second smallest track pseudorapidity ∆η, relative to the jet axis, associated to the second N-subjettiness axis
fj_tau1_trackEtaRel_2	Float_t	Third smallest track pseudorapidity ∆η, relative to the jet axis, associated to the second N-subjettiness axis
fj_tau_vertexMass_0	Float_t	Total SV mass for the first N-subjettiness axis, defined as the invariant mass of all tracks from SVs associated with the first N-subjettiness axis
fj_tau_vertexMass_1	Float_t	Total SV mass for the second N-subjettiness axis, defined as the invariant mass of all tracks from SVs associated with the second N-subjettiness axis
fj_tau_vertexEnergyRatio_0	Float_t	SV vertex energy ratio for the first N-subjettiness axis, defined as the total energy of all SVs associated with the first N-subjettiness axis divided by the total energy of all the tracks associated with the AK8 jet that are consistent with the PV
fj_tau_vertexEnergyRatio_1	Float_t	SV energy ratio for the second N-subjettiness axis, defined as the total energy of all SVs associated with the first N-subjettiness axis divided by the total energy of all the tracks associated with the AK8 jet that are consistent with the PV
fj_tau_flightDistance2dSig_0	Float_t	Transverse (2D) flight distance significance between the PV and the SV with the smallest uncertainty on the 3D flight distance associated to the first N-subjettiness axis
fj_tau_flightDistance2dSig_1	Float_t	Transverse (2D) flight distance significance between the PV and the SV with the smallest uncertainty on the 3D flight distance associated to the second N-subjettiness axis
fj_tau_vertexDeltaR_0	Float_t	Pseudoangular distance ∆R between the first N-subjettiness axis and SV direction
n_pfcands	Int_t	Number of particle flow (PF) candidates associated to the AK8 jet with transverse momentum greater than 0.95 GeV
npfcands	Float_t	Number of particle flow (PF) candidates associated to the AK8 jet with transverse momentum greater than 0.95 GeV
pfcand_VTX_ass	Int_t	PV association quality for the PF candiate: `UsedInFitTight=7`, the track is used in the PV fit and the weight is above 0.5; `UsedInFitLoose=6`, the track is used in the PV fit and the weight is below 0.5; `CompatibilityDz=5` the track is not used in fit but is very close in `dz` to the PV (`dzsig` < 5 or `dz` < 300 um); `CompatibilityBTag=4`, the track is not compatible with the PV but it is close to the nearest jet axis starting from the PV (distance to jet axis < 700 um); `NotReconstructedPrimary=0`, the track is not associated to any PV and is compatible with the beam spot hence it is likely to be originating from an interaction for which we did not reconstruct the PV (beam spot compatibility: `dxysig` < 2 and `dxy` < 200 um); `OtherDeltaZ=1`, none of the above criteria is satisfied, hence the closest in `dz` vertex is associated)
pfcand_charge	Float_t	Electric charge of the PF candidate
pfcand_deltaR	Float_t	Pseudoangular distance ∆R between the PF candidate and the AK8 jet axis
pfcand_drminsv	Float_t	Minimum pseudoangular distance ∆R between the associated SVs and the PF candidate
pfcand_drsubjet1	Float_t	Pseudoangular distance ∆R between the PF candidate and the first soft drop subjet
pfcand_drsubjet2	Float_t	Pseudoangular distance ∆R between the PF candidate and the second soft drop subjet
pfcand_dxy	Float_t	Transverse (2D) impact paramater of the PF candidate, defined as the distance of closest approach of the PF candidate trajectory to the beam line in the transverse plane to the beam
pfcand_dxysig	Float_t	Transverse (2D) impact paramater significance of the PF candidate
pfcand_dz	Float_t	Longitudinal impact parameter, defined as the distance of closest approach of the PF candidate trajectory to the PV projected on to the z direction
pfcand_dzsig	Float_t	Longitudinal impact parameter significance of the PF candidate
pfcand_erel	Float_t	Energy of the PF candidate divided by the energy of the AK8 jet
pfcand_etarel	Float_t	Pseudorapidity of the PF candidate relative to the AK8 jet axis
pfcand_phirel	Float_t	Azimuthal angular distance ∆ϕ between the PF candidate and the AK8 jet axis
pfcand_ptrel	Float_t	Transverse momentum of the PF candidate divided by the transverse momentum of the AK8 jet
pfcand_fromPV	Float_t	Integer indicating whether the PF candidate is consistent with the PV: `PVUsedInFit=3`, if the track is used in the PV fit; `PVTight=2` if the track is not used in the fit of any of the other PVs and is closest in z to the PV, `PVLoose=1` if the track is closest in z to a PV other then the PV; `NoPV=0` if the track is used in the fit of another PV
pfcand_hcalFrac	Float_t	Fraction of energy of the PF candidate deposited in the hadron calorimeter
pfcand_isChargedHad	Float_t	Boolean that is 1 if the PF candidate is classified as a charged hadron
pfcand_isEl	Float_t	Boolean that is 1 if the PF candidate is classified as an electron
pfcand_isGamma	Float_t	Boolean that is 1 if the PF candidate is classified as an photon
pfcand_isMu	Float_t	Boolean that is 1 if the PF candidate is classified as an muon
pfcand_isNeutralHad	Float_t	Boolean that is 1 if the PF candidate is classified as a neutral hadron
pfcand_lostInnerHits	Float_t	Integer with information related to inner silicon tracker hits for the PF candidate: `validHitInFirstPixelBarrelLayer=-1`, if the track has a valid hit in the first pixel barrel layer; `noLostInnerHits=0` if it does not have such hit because of geometrical or detector inefficiencies (i.e. the hit wasn't expected to be there); `oneLostHit=1`, if the track extrapolation towards the beam line crosses an active detector but no hit is found there; `moreLostHits=2` if there are at least two missing expected inner hits
pfcand_mass	Float_t	Mass of the PF candidate
pfcand_puppiw	Float_t	Pileup per-particle identification (PUPPI) weight indicating whether the PF candidate is pileup-like (0) or not (1)
n_tracks	Int_t	Number of tracks associated with the AK8 jet
ntracks	Float_t	Number of tracks associated with the AK8 jet
trackBTag_DeltaR	Float_t	Pseudoangular distance ∆R between the track and the AK8 jet axis
trackBTag_Eta	Float_t	Pseudorapidity η of the track
trackBTag_EtaRel	Float_t	Pseudorapidity ∆η of the track relative the AK8 jet axis
trackBTag_JetDistVal	Float_t	Minimum track approach distance to the AK8 jet axis
trackBTag_Momentum	Float_t	Momentum of the track
trackBTag_PPar	Float_t	Component of track momentum parallel to the AK8 jet axis
trackBTag_PParRatio	Float_t	Component of track momentum parallel to the AK8 jet axis, normalized to the track momentum
trackBTag_PtRatio	Float_t	Component of track momentum perpendicular to the AK8 jet axis, normalized to the track momentum
trackBTag_PtRel	Float_t	Component of track momentum perpendicular to the AK8 jet axis
trackBTag_Sip2dVal	Float_t	Transverse (2D) signed impact paramater of the track
trackBTag_Sip2dSig	Float_t	Transverse (2D) signed impact paramater significance of the track
trackBTag_Sip3dSig	Float_t	3D signed impact parameter significance of the track
trackBTag_Sip3dVal	Float_t	3D signed impact parameter of the track
track_VTX_ass	Float_t	PV association quality for the track: `UsedInFitTight=7`, the track is used in the PV fit and the weight is above 0.5; `UsedInFitLoose=6`, the track is used in the PV fit and the weight is below 0.5; `CompatibilityDz=5` the track is not used in fit but is very close in `dz` to the PV (`dzsig` < 5 or `dz` < 300 um); `CompatibilityBTag=4`, the track is not compatible with the PV but it is close to the nearest jet axis starting from the PV (distance to jet axis < 700 um); `NotReconstructedPrimary=0`, the track is not associated to any PV and is compatible with the BeamSpot hence it is likely to be originating from an interaction for which we did not reconstruct the PV (beam spot compatibility: `dxysig` < 2 and `dxy` < 200 um); `OtherDeltaZ=1`, none of the above criteria is satisfied, hence the closest in dZ vertex is associated)
track_charge	Float_t	Electric charge of the charged PF candidate
track_deltaR	Float_t	Pseudoangular distance (∆R) between the charged PF candidate and the AK8 jet axis
track_detadeta	Float_t	Track covariance matrix entry (eta, eta)
track_dlambdadz	Float_t	Track covariance matrix entry (lambda, dz)
track_dphidphi	Float_t	Track covariance matrix entry (phi, phi)
track_dphidxy	Float_t	Track covariance matrix entry (phi, xy)
track_dptdpt	Float_t	Track covariance matrix entry (pT, pT)
track_dxydxy	Float_t	Track covariance matrix entry (dxy, dxy)
track_dxydz	Float_t	Track covariance matrix entry (dxy, dz)
track_dzdz	Float_t	Track covariance matrix entry (dz, dz)
track_drminsv	Float_t	Minimum pseudoangular distance ∆R between the associated SVs and the charged PF candidate
track_drsubjet1	Float_t	Pseudoangular distance ∆R between the charged PF candidate and the first soft drop subjet
track_drsubjet2	Float_t	Pseudoangular distance ∆R between the charged PF candidate and the second soft drop subjet
track_dxy	Float_t	Transverse (2D) impact parameter of the track, defined as the distance of closest approach of the track trajectory to the beam line in the transverse plane to the beam
track_dxysig	Float_t	Transverse (2D) impact parameter significance of the track
track_dz	Float_t	Longitudinal impact parameter, defined as the distance of closest approach of the track trajectory to the PV projected on to the z direction
track_dzsig	Float_t	Longitudinal impact parameter significance of the track
track_erel	Float_t	Energy of the charged PF candidate divided by the energy of the AK8 jet
track_etarel	Float_t	Pseudorapidity ∆η of the track relative to the jet axis
track_fromPV	Float_t	Integer indicating whether the charged PF candidate is consistent with the PV: `PVUsedInFit=3`, if the track is used in the PV fit; `PVTight=2` if the track is not used in the fit of any of the other PVs and is closest in z to the PV, `PVLoose=1` if the track is closest in z to a PV other then the PV; `NoPV=0` if the track is used in the fit of another PV
track_isChargedHad	Float_t	Boolean that is 1 if the charged PF candidate is classified as a charged hadron
track_isEl	Float_t	Boolean that is 1 if the charged PF candidate is classified as an electron
track_isMu	Float_t	Boolean that is 1 if the charged PF candidate is classified as a muon
track_lostInnerHits	Float_t	Integer with information related to inner silicon tracker hits for the track: `validHitInFirstPixelBarrelLayer=-1`, if the track has a valid hit in the first pixel barrel layer; `noLostInnerHits=0` if it does not have such hit because of geometrical or detector inefficiencies (i.e. the hit wasn't expected to be there); `oneLostHit=1`, if the track extrapolation towards the beam line crosses an active detector but no hit is found there; `moreLostHits=2` if there are at least two missing expected inner hits
track_mass	Float_t	Mass of the charged PF candidate
track_normchi2	Float_t	Normalized χ2 of the track fit
track_phirel	Float_t	Azimuthal angular distance ∆ϕ between the charged PF candidate and the AK8 jet axis
track_pt	Float_t	Transverse momentum of the charged PF candidate
track_ptrel	Float_t	Transverse momentum of the charged PF candidate divided by the transverse momentum of the AK8 jet
track_puppiw	Float_t	Pileup per-particle identification (PUPPI) weight indicating whether the PF candidate is pileup-like (0) or not (1)
track_quality	Float_t	Track quality: `undefQuality=-1`; `loose=0`; `tight=1`; `highPurity=2`; `confirmed=3`, if track found by more than one iteration; `looseSetWithPV=5`; `highPuritySetWithPV=6`, `discarded=7` if a better track found; `qualitySize=8`
n_sv	Int_t	Number of secondary vertices (SV) associated with the AK8 jet (∆R < 0.8)
nsv	Float_t	Number of secondary vertices (SV) associated with the AK8 jet (∆R < 0.8)
sv_chi2	Float_t	χ2 of the vertex fit
sv_ndf	Float_t	number of degrees of freedom of the vertex fit
sv_normchi2	Float_t	χ2 divided by the number of degrees of freedom for the vertex fit
sv_costhetasvpv	Float_t	Cosine of the angle cos(θ) between the SV and the PV
sv_d3d	Float_t	3D flight distance of the SV
sv_d3derr	Float_t	3D flight distance uncertainty of the SV
sv_d3dsig	Float_t	3D flight distance significance of the SV
sv_dxy	Float_t	Transverse (2D) flight distance of the SV
sv_dxyerr	Float_t	Transverse (2D) flight distance uncertainty of the SV
sv_dxysig	Float_t	Transverse (2D) flight distance significance of the SV
sv_deltaR	Float_t	Pseudoangular distance ∆R between the SV and the AK8 jet
sv_erel	Float_t	Energy of the SV divided by the energy of the AK8 jet
sv_etarel	Float_t	Pseudorapidity ∆η of the SV relative to the AK8 jet axis
sv_mass	Float_t	Mass of the SV
sv_ntracks	Float_t	Number of tracks associated with the SV
sv_phirel	Float_t	Azimuthal angular distance ∆ϕ of the SV relative to the jet axis
sv_pt	Float_t	Transverse momentum of the SV
sv_ptrel	Float_t	Transverse momentum of the SV divided by the transverse momentum of the AK8 jet

How were these data selected?

This dataset was produced with the software available in:

HiggsToBBNtupleProducerTool - ROOT ntuple producer for developing machine learning algorithms from CMS Run2 MiniAOD

How can you use these data?

The use of these files does not require any software specific to the CMS experiment. There are two sets of files in two different formats: ROOT and H5. For the H5 files, only information for up to 100 particle candidates, up to 60 charged particles or tracks, and up to 5 secondary vertices are stored in zero-padded arrays. An example notebook is provided.