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MFTcalibrationTestWorkflow MFT calibration workflows

MFT calibration workflows

This will read data from raw data file, produces clusters and write a noise map to a local CCDB running on port 8080:

o2-raw-file-reader-workflow -b --delay ${DELAY_S} --nocheck-missing-stop --nocheck-starts-with-tf --nocheck-packet-increment --nocheck-hbf-jump --nocheck-hbf-per-tf --detect-tf0 --configKeyValues "HBFUtils.nHBFPerTF=${HBF_PER_TF}" --input-conf ${CFGFILE} | \
o2-itsmft-stf-decoder-workflow -b --nthreads ${N_THREAD} --runmft --decoder-verbosity ${DECODER_VERBOSITY} | \
o2-calibration-mft-calib-workflow --path "/MFT/test_CCDB/" --meta "Description=MFT;Author=Maurice Coquet;Uploader=Maurice Coquet" -b | \
o2-calibration-ccdb-populator-workflow --ccdb-path="http://localhost:8080" -b

The same as before but uses digits instead of clusters:

o2-raw-file-reader-workflow -b --delay ${DELAY_S} --nocheck-missing-stop --nocheck-starts-with-tf --nocheck-packet-increment --nocheck-hbf-jump --nocheck-hbf-per-tf --detect-tf0 --configKeyValues "HBFUtils.nHBFPerTF=${HBF_PER_TF}" --input-conf ${CFGFILE} | \
o2-itsmft-stf-decoder-workflow -b --nthreads ${N_THREAD} --runmft --digits --no-clusters --no-cluster-patterns --decoder-verbosity ${DECODER_VERBOSITY} | \
o2-calibration-mft-calib-workflow --useDigits --path "/MFT/test_CCDB/" --meta "Description=MFT;Author=Maurice Coquet;Uploader=Maurice Coquet" -b | \
o2-calibration-ccdb-populator-workflow --ccdb-path="http://localhost:8080" -b

Additional options to the mft-calib DPL :

--path "/path/in/CCDB/" : defines path to write to in CCDB (default : "/MFT/Calib/NoiseMap")
--meta "Description=...;Author=...;Uploader=..." : add meta data to the input in the CCDB
--tstart <start timestamp> : defines the start of validity timestamp of the file written in the CCDB (default is -1 : current timestamp)
--tend <end timestamp> : defines the start of validity timestamp of the file written in the CCDB (defult is -1 : one year from the current timestamp)
--prob-threshold <proba> : defined probability threshold for noisy pixels (default : 3e-6)

The Muon Forward Tracker

This documentation describes the main workflows used for MFT standalone reconstruction and global forward matching. The MFT is a Silicon pixel tracking detector designed to add vertexing capabilities to the MUON spectrometer. More details about the MFT are available on the Technical Design Report for the Muon Forward Tracker.

MFT Standalone workflows in O2

o2-mft-reco-workflow is the main workflow used in MFT standalone tracking, reconstructing MFT tracks stored in mfttracks.root. The workflow options are defined in mft-reco-workflow.cxx and tracking configurable parameters at MFTTrackingParam.h. During normal data taking periods, this workflows find and fit tracks from clusters provided by upstream devices. For simulated data this workflows reads simulated digits, runs clusterization, track-finding and track-fitting.

Running MFT Standalone reconstruction from a simulation

# 0) Enter O2 environment
alienv enter O2/latest-dev-o2
# 1) Run MFT standalone simulation of 10 pp events
o2-sim -n 10 -g pythia8pp -m MFT
# 2) Run MFT digitizer: produces `mftdigits.root`
o2-sim-digitizer-workflow -b
# 3) Run MFT reconstruction workflow from digits
# produces mftclusters.root and mfttracks.root
o2-mft-reco-workflow --configKeyValues "MFTTracking.forceZeroField=false;MFTTracking.LTFclsRCut=0.0100;"

MFT Standalone reconstruction from CTFs

Workflow: CTF reader workflow -> MFT reconstruction workflow

Example:

o2-ctf-reader-workflow --onlyDet MFT --ctf-input o2_ctf_run00000000_orbit0000000000_tf0000000001.root | o2-mft-reco-workflow --clusters-from-upstream --disable-mc -b

Reconstruction from MFT clusters (real data)

Workflow: MFT cluster reader workflow -> MFT reconstruction workflow

Example:

o2-mft-cluster-reader-workflow | o2-mft-reco-workflow --clusters-from-upstream --disable-mc --mft-cluster-writer "--outfile /dev/null"

MFT Assessment

The o2-mft-assessment-workflow evaluates MFT standalone tracking. By default the workflow operates in data collection mode and stores MFTAssessment.root.

Usage modes:

  1. Piped with matching workflow:
    • o2-mft-reco-workflow | o2-mft-assessment-workflow
  2. Reading data on disk:
    • o2-global-track-cluster-reader --track-types MFT --cluster-types MFT | o2-mft-assessment-workflow

Analysis of collected data can be executed calling the workflow with --, producing objects that cannot be merged. For grid-compatible workflows, data collected in several files can be merged with hadd and the finalization of merged objects can be steered by a macro as bellow.

void finalizeMFTAssessment()
{
o2::mft::MFTAssessment analyser(true);
analyser.loadHistos(); // loads MFFAssessment.root produced by the DPL workflow
analyser.finalizeAnalysis();
TFile *fout = new TFile("MFTAssessmentFinalized.root", "RECREATE");
TObjArray objarOut;
analyser.getHistos(objarOut); // Output objects
objarOut.Write();
fout->Close();
}

MFT in Global Forward Workflows

Global forward workflows produce tracks by matching different detector systems:

  • Standalone reconstruction workflows: MFT, MCH and MID
  • Matching workflows: MCH-MID and MFT-MCH-MID

A compreensive execution of ALICE workflows from simulation up to AOD files is implemented on sim_challenge.sh. Bellow a summary of the reconstruction workflows used to produce global forward tracks.

MCH and MID reconstruction workflows

  • MCH reconstruction workflow:
    • o2-mch-reco-workflow
    • produces mchtracks.root
  • MID reconstruction workflow:
    • o2-mid-digits-reader-workflow | o2-mid-reco-workflow
    • produces mid-reco.root

More details about these workflows are available at the documentation for MCH and the MID.

MCH-MID matching

o2-muon-tracks-matcher-workflow runs MCH-MID matching, using MCH tracks (mchtracks.root) and MID tracks (mid-reco.root). By default it produces muontracks.root, which contains only track-matching information, as defined in TrackMCHMID.h.

MFT-MCH-MID matching

o2-globalfwd-matcher-workflow runs MFT-MCH-MID matching, using MFT tracks (mfttracks.root), MCH Tracks (mchtracks.root) and MCH-MID matches (muontracks.root). MID information is used to identify GlobalMuonTracks. By default o2-globalfwd-matcher-workflow produces globalfwdtracks.root which contains matched forward tracks.

Global forward matching can be configured at runtime with options defined in MatchGlobalFwdParam.h. Example:

o2-globalfwd-matcher-workflow --configKeyValues "FwdMatching.useMIDMatch=true"

Global Forward Assessment Workflow

The o2-globalfwd-assessment-workflow evaluates reconstruction performance, the pairing efficiency and purity of global muon tracks. By default the workflow only collects data, creating mergeable objects.

Usage modes:

  1. Piped with matching workflow:
    • o2-globalfwd-matcher-workflow | o2-globalfwd-assessment-workflow
  2. Reading data on disk:
    • o2-global-track-cluster-reader --track-types MFT,MCH,MFT-MCH | o2-globalfwd-assessment-workflow

Analysis of collected data can be executed calling the workflow with --finalize-analysis, producing objects that cannot be merged. The finalization of merged objects can be steered by a macro as bellow.

void finalizeGlobalFwdAssessment()
{
o2::globaltracking::GloFwdAssessment analyser(true);
analyser.loadHistos(); // loads GlobalForwardAssessment.root produced by the DPL workflow
analyser.finalizeCutConfig(1., 15., 15); // finalizeCutConfig(float minCut, float maxCut, int nSteps)
analyser.finalizeAnalysis();
TFile *fout = new TFile("GlobalForwardAssessmentFinalized.root", "RECREATE");
TObjArray objarOut;
analyser.getHistos(objarOut);
objarOut.Write();
fout->Close();
}

Acknowlegements

This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 896850.