Hlt calibration
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HLT & Calibration. HLT as Calibration Data Source. Among the main tasks of HLT (especially in the first years) Monitoring of the detector performance Analysing calibration data (real events and calibration triggers) Calculation of a (first) set of calibration parameters

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HLT & Calibration

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Hlt calibration

HLT & Calibration


Hlt as calibration data source

HLT as Calibration Data Source

  • Among the main tasks of HLT (especially in the first years)

    • Monitoring of the detector performance

    • Analysing calibration data (real events and calibration triggers)

    • Calculation of a (first) set of calibration parameters

    • Applying calibration to online event reconstruction

    • Storing parameters in relevant databases

  • Procedures are being developed in collaboration with TPC, TRD, PHOS, and Dimuon detector

  • HLT is open for calibration tasks for all participating detectors

    • Compatibility w. Computing Power / Financial Budget


Hlt databases

HLT & Databases

  • The HLT will have contact to different databases, which are for different purposes as well as under different administration.

  • For now, it is foreseen to have contact to three different DBs:

    • Configuration DB (DCS)

    • Condition DB (DCS)

    • Calibration DB (Detector Specific)


Hlt db remarks

HLT DB Remarks

  • Use of dedicated HLT portal nodes to contact DBs

  • Redundancy of these nodes to avoid single-point-of-failures

  • Data of the DBs is cached (where possible) and distributed to the appropriate places inside the HLT cluster (using its publisher-subscriber framework)

  • Output data to DBs will be written from the global layer of the HLT cluster.

  • Contact to the databases will be performed via ODBC or similar techniques.


Tpc calibration example 1

TPC Calibration Example (1)

  • Pedestal run analysis and download

  • Pulser runs

    • Accumulation of pulser events

    • Gain calibration and timing alignment

    • Map hot/dead pads

  • Laser runs

    • Online reconstruction of laser tracks

    • Drift velocity map

    • ExB map

    • static E-field distortion map

  • Electron attachment / gas contamination

    • Online reconstruction of particle tracks / laser tracks

    • Cluster charge loss per drift length


Tpc calibration example 2

TPC Calibration Example (2)

  • Drift velocity map

    • Nuclear collisions

    • Accumulate charge per timebin

    • Calculate charge step at central electrode

    • E.g. NA49 data

NA49

charge step


Tpc calibration example 3

TPC Calibration Example (3)

  • Space charge effects

    • Online reconstruction of tracks

    • Histogram of track impact parameters

    • E.g. STAR TPC – fluctuations on second timescale


Tpc calibration example 4

TPC Calibration Example (4)

  • Histogram of track residuals

    • E.g. STAR TPC – grid leak distortions

      • Ion leakage at gating grid gap


Phos calibration example

PHOS Calibration Example

  • Pedestal run analysis and download

  • LED runs

    • Accumulation of pulser events

    • Gain calibration and timing alignment

    • Map hot/dead channels

  • Gain/energy calibration

    • Nuclear collisions

    • Online pulse shape analysis

    • Timing alignment (using fastest particles)

    • Online reconstruction and accumulating of showers

    • Relative gain calibration by equalizing channels

    • Absolute energy calibration by monitoring pi0-peak


Hlt questions open points

HLT Questions/Open Points

To plan connections from HLT to DBs, HLT needs to know:

  • At which places (processing steps) in the HLT cluster is DB data needed?

  • What is the estimated processing budget for online calibration?

  • What data for or/and from which databases?

  • Which detector needs what data?

  • How large is which data?

    • (different for different data -> detailed list wanted)

  • How often is data updated? (once (caching)  regular requests to DB)

  • Output data

    • General

      • e.g. Drift Velocity:

  • Type of measurement (once, continuous spectrum, every X sec., average, ...)

  • Write to DB (continously, at end of run, ...)

  • Who has access to data (online, offline)?


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