MET primary dataset in NANOAOD format from RunG of 2016 (/MET/Run2016G-UL2016_MiniAODv2_NanoAODv9-v1/NANOAOD)
/MET/Run2016G-UL2016_MiniAODv2_NanoAODv9-v1/NANOAOD, CMS Collaboration
Cite as: CMS Collaboration (2024). MET primary dataset in NANOAOD format from RunG of 2016 (/MET/Run2016G-UL2016_MiniAODv2_NanoAODv9-v1/NANOAOD). CERN Open Data Portal. DOI:10.7483/OPENDATA.CMS.PW5O.RR4H
Dataset Collision CMS 13TeV pp CERN-LHC
Description
MET primary dataset in NANOAOD format from RunG of 2016. Run period from run number 278820 to 280385.
The list of validated runs, which must be applied to all analyses, either with the full validation or for an analysis requiring only muons, can be found in:
Related datasets
The corresponding MINIAOD dataset:Dataset characteristics
26974131 events. 17 files. 23.8 GiB in total.System details
NANOAOD datasets are in the ROOT tree format and their analysis does not require the use of CMSSW or CMS open data environments. They can be analysed with common ROOT and Python tools.
Recommended container image for analyses is available in the following locations (see guide):
gitlab-registry.cern.ch/cms-cloud/root-vncgitlab-registry.cern.ch/cms-cloud/python-vnc
Dataset semantics
Variable listHow were these data selected?
Events stored in this primary dataset were selected because of the presence of high missing transverse energy.
Data taking / HLT
The collision data were assigned to different RAW datasets using the following HLT configuration.
Data processing
This NANOAOD dataset was processed from the RAW dataset by the following steps:
Step NANO
Release: CMSSW_10_6_26
Global tag: 106X_dataRun2_v35
Configuration file for NANO step ReReco-Run2016G-MET-UL2016_MiniAODv2_NanoAODv9
Output dataset: /MET/Run2016G-UL2016_MiniAODv2_NanoAODv9-v1/NANOAOD
Step PAT
Release: CMSSW_10_6_25
Global tag: 106X_dataRun2_v35
Configuration file for PAT step ReReco-Run2016G-MET-UL2016_MiniAODv2
Output dataset: /MET/Run2016G-UL2016_MiniAODv2-v2/MINIAOD
Step RECO
Release: CMSSW_10_6_8_patch1
Global tag: 106X_dataRun2_v27
Configuration file for RECO step recoskim_Run2016G_MET
Output dataset: /MET/Run2016G-21Feb2020_UL2016-v1/AOD
HLT trigger paths
The possible HLT trigger paths in this dataset are:
HLT_CaloMHTNoPU90_PFMET90_PFMHT90_IDTight_BTagCSV_p067
HLT_CaloMHTNoPU90_PFMET90_PFMHT90_IDTight
HLT_DiCentralPFJet55_PFMET110
HLT_DoubleMu3_PFMET50
HLT_MET200
HLT_MET250
HLT_MET300
HLT_MET600
HLT_MET60_IsoTrk35_Loose
HLT_MET700
HLT_MET75_IsoTrk50
HLT_MET90_IsoTrk50
HLT_MonoCentralPFJet80_PFMETNoMu100_PFMHTNoMu100_IDTight
HLT_MonoCentralPFJet80_PFMETNoMu110_PFMHTNoMu110_IDTight
HLT_MonoCentralPFJet80_PFMETNoMu120_PFMHTNoMu120_IDTight
HLT_MonoCentralPFJet80_PFMETNoMu90_PFMHTNoMu90_IDTight
HLT_Mu14er_PFMET100
HLT_Mu3er_PFHT140_PFMET125
HLT_Mu6_PFHT200_PFMET100
HLT_Mu6_PFHT200_PFMET80_BTagCSV_p067
HLT_PFMET100_PFMHT100_IDTight_BeamHaloCleaned
HLT_PFMET100_PFMHT100_IDTight
HLT_PFMET110_PFMHT110_IDTight
HLT_PFMET120_BTagCSV_p067
HLT_PFMET120_Mu5
HLT_PFMET120_PFMHT120_IDTight
HLT_PFMET170_BeamHaloCleaned
HLT_PFMET170_HBHECleaned
HLT_PFMET170_HBHE_BeamHaloCleaned
HLT_PFMET170_JetIdCleaned
HLT_PFMET170_NoiseCleaned
HLT_PFMET170_NotCleaned
HLT_PFMET300
HLT_PFMET400
HLT_PFMET500
HLT_PFMET600
HLT_PFMET90_PFMHT90_IDTight
HLT_PFMETNoMu100_PFMHTNoMu100_IDTight
HLT_PFMETNoMu110_PFMHTNoMu110_IDTight
HLT_PFMETNoMu120_PFMHTNoMu120_IDTight
HLT_PFMETNoMu90_PFMHTNoMu90_IDTight
HLT_PFMETTypeOne190_HBHE_BeamHaloCleaned
How were these data validated?
During data taking all the runs recorded by CMS are certified as good for physics analysis if all subdetectors, trigger, lumi and physics objects (tracking, electron, muon, photon, jet and MET) show the expected performance. Certification is based first on the offline shifters evaluation and later on the feedback provided by detector and Physics Object Group experts. Based on the above information, which is stored in a specific database called Run Registry, the Data Quality Monitoring group verifies the consistency of the certification and prepares a json file of certified runs to be used for physics analysis. For each reprocessing of the raw data, the above mentioned steps are repeated. For more information see:
The Data Quality Monitoring Software for the CMS experiment at the LHC: past, present and future
How can you use these data?
You can access these data through XRootD protocol or direct download, and they can be analysed with common ROOT and Python tools. See the instructions for getting started in
Files and indexes
Disclaimer
These open data are released under the Creative Commons Zero v1.0 Universal license.
Neither the experiment(s) ( CMS ) nor CERN endorse any works, scientific or otherwise, produced using these data.
This release has a unique DOI that you are requested to cite in any applications or publications.
