Monitoring DT trigger rates using online lumi Luminosity - - PowerPoint PPT Presentation

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Monitoring DT trigger rates using online lumi Luminosity - - PowerPoint PPT Presentation

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Monitoring DT trigger rates using online lumi Luminosity monitoring using DT trigger rates? 24/09/2012 Ignacio Redondo Fernndez & Jessica Turner I.Redondo (CIEMAT) 1 Monitoring DT trigger rates Scaler data is stored in DB with

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24/09/2012 I.Redondo (CIEMAT) 1

Luminosity monitoring using DT trigger rates? Monitoring DT trigger rates using

  • nline lumi

Ignacio Redondo Fernández & Jessica Turner

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24/09/2012 I.Redondo (CIEMAT) 2

Monitoring DT trigger rates

  • Scaler data is stored in DB with 5 min granularity.

– flashlist granularity is 30 s (I believe). – Larger granularity requires online SW changes – An ntuple including other beam related variables is being produced daily for easy analysis

  • Observed early last year (as soon as collision

muons started to dominate rate) that DT triger rates were remarkably linear with online luminosity.

– See https://indico.cern.ch/getFile.py/access?contribId=5&resId=0&materialId=slides&confId=135091

  • Estimate saturation effects <1% at lumi< LHC_design

– Double BS muon rates or a pt threshold could be implemented above

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24/09/2012 I.Redondo (CIEMAT) 3

Monitoring

  • Data

>1 year ago

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Monitoring DT trigger rates

  • Fitted parameters (per chamber) up to

250E30 have been used as an online monitoring tool

– Predict chamber rates from online HFlumi – Plot ratio of measured over expected – Chamber rates typically well within 5%

2012: Castor removal reduce neutron rates MB1 MB2 MB3 MB4 Ratio of Measured over Extrapolated (from early 2011 fit)

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24/09/2012 I.Redondo (CIEMAT) 5

BS rate: counting muon tracks

  • Let´s concentrate in the Barrel Sorter rate:

– input to GMT from DTTF – coincidence of triggers from at least 2 out of 4 chambers in sector – Match DTTF algorithm – Survive sorters ghost-killing

  • Relatively high level

– no time dependent pt-cut (just geometry and magnetic field) – does not depend on RPC, midly on CSC – tipically within 3% of extrapolation based on online HF lumi (fit <250E30) up to – Precision limited by bad vacuum fills which results in halo muon rate in the barrel.(~KHz)

  • This can be substracted IF we would sample the rate before

collisions (and after DT HV is turned on at squeeze)

  • In fact, potential for vacuum monitor. Q: List of bad vacuum fills?
  • Further effects worth checking would be dependence with pressure

via vdrift

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24/09/2012 I.Redondo (CIEMAT) 6

Excellent linear correlation (<1%)

  • ver 3 orders of magnitude up to 3.5E33

“Cosmics” 305 Hz

2011: DT rate vs. HFonline lumi expected at same time stamp (from DB)

Histogram is projection of Fit-Point DT fitted lumi minus HFonline lumi

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24/09/2012 I.Redondo (CIEMAT) 7

“Cosmics” 238 Hz

2011: DT rate vs. HFoffline lumi(Calc2) expected at same time stamp

DT fitted lumi minus HFoffline lumi Excellent correlation (<1%) up to 4E33 Narrower and more gaussian residuals

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Excellent correlation (<1%) up to 4E33 Narrower and more gaussian residuals “Cosmics” 238 Hz

2011: DT rate vs. HFoffline lumi(Calc2) expected at same time stamp

DT fitted lumi minus HFonline lumi DT fitted lumi minus HFoffline lumi

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“Cosmics” 284 Hz Excellent correlation (<1%) up to 4E33 Slope vs. HFoffline and vs. pixelLumi equal (+-0.5%)

2011: DT rate vs. Pixel offline lumi expected at same time stamp

DT fitted lumi minus Pixel offline lumi Larger scatter from Pixel lumi

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2011 Lumi_DT (pixel calibrated) vs. time

  • 2. 21/5/2012

DT Resynchronization ~+3 % 11/June/2012 During TS

  • 1. Major HF redefinition

8.5 % effect

  • 2. Loss of DT eff due to

Vdrif change ~<2% Ratio to pixelLumi stable over 2011 6/April/2011 20/Oct/2011

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Summary ca Summer

  • BS rate correlates linearly very well with pixel lumi, HF online& offline lumi over a

few orders of magnitud.

  • A BS rate based lumi estimator:

– would probably need less recalibrations than HF online lumi. – seems to suffer less from statistical fluctuations than pixel lumi and lives naturally

  • nline.
  • Q: What to do with it is up to Lumi POG

– Could automatize to produce weekly (daily if DB values) crosscheck plot – Could provide pixel calibrated lumi online with time granularity :

  • 5 min (reading from DB) => small job, available in short time
  • 30 s (build xdaq app. that reads flash list) => need help,,available in longer time
  • 23.35 s (modifying publishing in DTTF supervisor)

=> not in my hands

  • Correlation with pixel 2012 pending to fully clarify 2012 data
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24/09/2012 I.Redondo (CIEMAT) 12

Status now

  • BS rate correlates linearly very well with pixel lumi, HF online& offline lumi over a

few orders of magnitud.

  • A BS rate based lumi estimator:

– would probably need less recalibrations than HF online lumi. – seems to suffer less from statistical fluctuations than pixel lumi and lives naturally

  • nline.
  • Q: What to do with it is up to Lumi POG

– Could automatize to produce weekly (daily if DB values) crosscheck plot – Could provide pixel calibrated lumi online with time granularity :

  • Find out GMT stores BS rate with lumi section granularity!
  • Use this to publish a BS based DT lumi in WBM

2011 calibration ok waiting for WBM plots to be done Used End of Fill VdM scan 2710 to calibrated 2012 a+b data 2012 c data is off probably due to change in CSC input to BS (horns) J. Turner Study alternative estimators as, for instance, MB3 only rate.

  • Correlation with pixel 2012 pending to fully clarify 2012 data
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  • 5-7 % offest
  • Intriguing fill dependence
  • wrt. HF online
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Is BS rate still linear with lumi in 2012?

  • Bellow 4E33 at 7 TeV, yes, we all agreed.
  • Deviation after April 2012 TS seen

– Effect in fact correlated with the correction (8.5 %)

  • f the normalization of HF data in DB after the TS

– Effect not present if:

  • the online data previous to the TS is corrected
  • r if
  • the correlation is done vs. HF offline lumi (lumiCalc2.py)
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Red: after April TS Black: before April TS Red: after April TS Black: before April TS/1.085

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Larger spread but still Linear correlation (<3%) up to 7E33

2012: DT rate vs. HFoffline lumi(Calc2) expected at same time stamp

DT fitted lumi minus HF offline lumi Low B fill

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Using 2011 (vs. pixel calibration) on 2012 data

4/April/2012

  • 2. 21/5/2012

DT Resynchronization ~+3 % 11/June/2012 During TS

  • 1. Major HF redefinition

8.5 % effect

  • 2. Loss of DT eff due to

Vdrif change ~<2%

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Crosschecking Timestamp Matching

  • DB and offline lumi timestamps match:

description of lumi timeline features (i.e. fills)

  • Pixel lumi (at lumi section level) show

larger statistical(?) scatter

  • HFonline lower normalization

Sampling coincide within ~[-23,23] s CALC2_time-DB_time (s)

CALC2_time-DB_time (s)

September 7 2011

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MB3s Factor of ~2, MB4s ~unaffected 1.7 KHz BS rate vs. usual cosmic background (~260 Hz) MB1s factor of ~10 MB2s factor of ~15 Azimutahl angle Azimutahl angle Wheel

Potential as Vacuum monitor: Fill 1901 18/07/2011

Between squeeze (DT HV on) and collisions Cosmics adter dump

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Saturating the rate

LHC design 20 x LHC design (Wrong assumption: double muon uncorrelated)

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Ratio of slopes 7TeV/8TeV = 0.895? However similar slope to offline lumi Expect more muon rate at a given lumi

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2011

Time since 01/01/2010 BS rate over prediceted BS rate

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Monitoring DT trigger rates

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Monitoring DT trigger rates

BKG in MB4s (“neutrons”) BKG in external wheel MB1s (“punchthrough”)

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2012

HF online lumi

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Pixel offline lumi HF offline lumi

  • Investigate off diagonal points
  • Quantify correlation
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Pixel offline lumi HF offline lumi

  • Investigate off diagonal points
  • Quantify correlation