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MEG DCH Analysis

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Title: MEG DCH Analysis


1
MEG DCH Analysis
W. Molzon For the DCH Analysis Working Group
MEG Review Meeting 18 February 2009
2
Outline
  • Impact on MEG performance
  • Analysis algorithms
  • DCH Calibration
  • DCH position resolutions Rf and q
  • Positron reconstruction
  • Momentum
  • Position and angle at target
  • Projection to timing counters
  • DCH efficiency
  • Required improvements in analysis
  • Drift model
  • Reducing noise and its impact on resolution
  • Improved tracking efficiency with lower than
    expected DCH efficiency
  • Fitting

3
Positron Spectrometer Impact on MEG Performance
  • Select on positron energy within interval
    near52.8 MeV
  • For fixed m?eg acceptance, BG/S proportional to
    dp (MEG prediction sRMS180 keV/c)
  • Select on qeg near p
  • For fixed acceptance, BG/S proportional to df x
    dq (MEG prediction sRMS 8x8 mrad2)
  • photon position resolution 6 mm sRMS ? 9
    mrad both f and q
  • Track fitting angle uncertainty
    ? 12 mrad f, 6 mrad q
  • Position of stopping target uncertainty 0.5 mm
    ? 6 mrad f
  • Project to target and timing counter and correct
    te for propagation delay
  • For fixed acceptance, BG/S proportional to dt
    (MEG prediction sRMS 64 ps, 2 cm)
  • Projection to target has negligible uncertainty
  • Uncertainty in timing counter projection
    dominated by scattering and E loss after
    spectrometer
  • Improvements needed from incorporating position
    at timing counter and material between
    spectrometer and timing counter into fit.
  • For all effects, tails in resolution function ?
    loss of acceptance proportional to integral in
    tail, small increase in background because source
    of background is uniform

4
Tracking Analysis
  • Outline of algorithms
  • Extract hits from waveform on each cell two
    anode ends, four pads
  • Extract hit position in Rf from hit time and in Z
    from anode and pad charges
  • Form clusters of hits on a particular chamber
    coming from single particle
  • Form track candidates from groups of hits
    consistent with Michel positron
  • Fit the hits from track candidates to form tracks

5
Waveform Analysis
  • Based on waveforms on 2 anode ends and 4 pads
    associated with each cell
  • waveform noise limits resolution
  • DRS voltage calibrated with on-board constant
    voltage presented to input of DRS
  • DRS time calibrated with off-board sine-wave of
    known frequency presented to each board.
    Bin-by-bin time calibration done for each DRS
    channel (2x105 points)
  • Readout rate dependent baseline offset for some
    DRS bins not corrected, trigger waveform
    crosstalk onto DRS not corrected hardware
    improvements anticipated
  • Improvement in noise level would significantly
    improve resolution

6
DCH Calibrations and Corrections
  • Alignment of chambers radial offsets, z
    offsets, chamber tilts
  • All from fits to Michel data
  • Typical systematic residuals after alignment
    small ( lt 100 mm)
  • Calibration of preamp gains, effective wire
    length
  • Use known periodicity of cathode pads to
    calibrate anode preamp gains, input impedance,
    wire resistivity that affects anode z position
  • Calibrate relative gains of cathode pads by ratio
    of signal on two ends of pads to sine function
    with variable relative gain
  • Correct drift times for signal propagation on
    wire reduce dispersion on time difference
    between two ends by 20
  • Identify and correct for incorrect pad cycle
    assignment due to errors in anode Z position
    exceeding 2.5 cm
  • Measure effect of noise on pad charge
    measurements on Z resolution optimize
    integration time to minimize effect of noise

7
Hit Finding
  • Smooth waveforms to reduce high frequency noise
  • Determine constant baseline offset event-by-event
    for each waveform
  • Only time before hit used small slope from
    earlier hits not corrected
  • Find max peak in anode waveform iterate after
    removing signal in peak
  • Integrate around peak in limited time interval to
    get 2 anode, 6 pad charges optimized to minimize
    impact of noise on charge integration typically
    50 ns.
  • Get hit time from simple threshold discriminator
    on unsmoothed waveform correct for propagation
    along wire using Z coordinate
  • Get Z first from anode charge division, then from
    interpolation with pads

Time difference two ends
8
Cluster Finding
  • Find group of hits consistent with coming from
    single charge particle
  • Start with groups of hits in contiguous wires on
    chamber
  • Split clusters that have hits at inconsistent Z
    locations
  • Identify and fix clusters that have hits
    separated in Z by one pad cycle (5 cm) due to
    incorrect anode Z position
  • Reassess assignment of hits to clusters during
    track-finding, when track angle at the cluster is
    known
  • After all clusters with gt 1 hit are found, assign
    unmatched hits as single hit clusters

Single hit clusters
Correct wrong pad cycle
3,4 hit clusters
9
Track Candidate Finding
  • Find group of clusters consistent with coming
    from single charge particle with fixed momentum
    going through spectrometer
  • Self-contained code, independent of TIC (i.e. for
    track time)
  • Start with seed with 3 clusters in 4 adjacent
    chambers at RgtRmin
  • Given a seed, propagate in both directions,
    adding hits within range in dR and dZ consistent
    with Michel momentum
  • At each stage, determine track candidate time
    from drift times
  • Consistent radial coordinate, consistent Z
    coordinate
  • Track time that minimizes residual of hit
    positions to local helix fit
  • L/R resolution by minimizing deviations from
    local helix fit
  • Hits can be removed from clusters at tracking
    stage

10
Track Fitting
  • Kalman filter using hits found by trackfinder
  • Uses fully aligned chamber coordinates from
    optical alignment software alignment
  • Use hit-by-hit uncertainty in Rf and Z
    coordinates parameterized as function of hit
    charge, magnitude of drift distance (determined
    from data)
  • Phenomenological corrections to drift time vs.
    drift distance based on parameterization of data
  • Removes hits that are inconsistent with positron
    trajectory
  • Group of clusters consistent with coming from
    single charge particle with fixed momentum going
    through spectrometer
  • Optimization of fitting algorithm for sparse hits
    to be done
  • Incorporation of TIC position into filter to
    improve trajectory after spectrometer to be done

11
Intrinsic Drift Chamber Performance from Tracking
  • Rf position resolution
  • Look at difference in hits in 2 planes in chamber
    projected to central plane using trajectory
    information insensitive to multiple scattering
  • Typical spatial resolution of 260 microns
  • Systematic effects with drift distance and angle
    ad-hoc corrections applied
  • dr for opposite side more sensitive to errors
    in track time


  • sRMS of central region 260 mm
  • non-Gaussian tails, larger for
    opposite side hits
  • Z position resolution
  • Similar technique to that for Rf resolution

Inferred sz 0.15 cm
Za-Zb
normalized Za-Zb
Za-Zb vs charge
12
Definition of Selection Criteria for Tracking
Efficiency, Resolution
  • Tight Cuts have additional requirements Nhits gt
    9, dE lt 0.0006

13
Momentum Resolution from Monte Carlo
  • No source of fixed momentum particles fit to
    edge of Michel spectrum, first MC
  • Generate Michel spectrum, including radiative
    decays in this study without inefficiencies
  • Fit convolution of generated MC spectrum with
    single Gaussian to reconstructed MC spectrum
  • Fit range (51.5-54.0) MeV/c
  • Done for tight cuts
  • Resolution worse than original MEG predictions
    DRS noise ?
  • Tails from large angle scattering, pattern
    recognition?, others?

14
Momentum Resolution from Data
  • No source of fixed momentum particles to measure
    response function
  • Fit to edge of Michel spectrum to demonstrate
    resolution
  • Generate Michel spectrum with radiative
    corrections
  • Impose momentum dependence of TIC acceptance x
    efficiency measured using DCH triggered data
  • Fit measured energy distribution to convolution
    of acceptance-corrected Michel spectrum and
    hypothetical resolution function
  • Edge of spectrum most sensitive to Gaussian part
    of resolution function fit of high energy tail
    very dependent on model for tail in resolution
    function
  • Currently worse than MC by a factor of 2, but
    inefficiencies not yet in MC resolution fits

early datasRMS 830 keV
tight cuts, early datasRMS 772 keV
late datasRMS 1002 keV
tight cuts, late datasRMS 795 keV
15
Check of Angular Resolution
  • No source of positrons of known direction
  • Fitting provides event-by-event estimate of dq,
    df
  • Target designed with holes to test of resolution
    in projection to the target ? infer dq, df
  • Take slice in target projection around hole, try
    to match depth of dip data to MC
  • Position of hole vs. angle of track with respect
    to target normal sensitive to target position
  • Difficult to quantitatively match distributions

16
Project to TIC, Require Space and Time Match,
Calculate Propagation Time
  • Need to correct for track propagation delay to
    precision of 50 ps ? track length to 1.5 cm
  • Trajectory known from target plane through
    spectrometer to very good precision
  • Projection to TIC complicated by material after
    spectrometer causing scattering, energy loss
  • Currently, project to fixed f of timing counter
    with signal using propagation of Kalman state
    vector
  • No correction for mismatch with reconstructed
    position in timing counter
  • Typical propagation distance is of order 1 m
  • Systematic uncertainties in dR, dZ seen, of order
    1 cm
  • First attempts at simple corrections to
    path-length based on dR, dZ not successful

17
Use DCH Data and Analysis to Study Timing Counter
  • Use DCH trigger data
  • Require 4 hits in 5 contiguous chambers
  • Run standard analysis, positron selection
    criteria
  • Measure probability of having a TIC hit

18
Tracking Efficiency From Monte Carlo
  • Put actual typical patterns of inefficient
    chambers into Monte Carlo
  • Generate signal events over extended region f lt
    1, cos(q) lt 0.45
  • Define efficiency as ( positrons accepted
    in fiducial region)
  • (
    positrons generated in fiducial region)

19
Reconstructed Tracks per Trigger
  • Look at fraction of events with at least one
    reconstructed track at high momentum measure of
    relative (not absolute) tracking efficiency
  • Absolute scale depends on trigger purity, other
    factors not relevant to DCH performance

20
Can We Estimate Tracking Efficiency from Data
  • Use highly pre-scaled timing counter trigger
    data
  • 6000 C total live protons on target 2.8 x 107
    m/s/2mA (assume livetimesame for MEG, other
    triggers Implies 8400
    x 1010 total muon stops
  • Nm?enn 11895 satisfying selection cuts
    counted
  • 8.4x1013 Number of muon
    stops calculated
  • X 107 prescale factor known
  • X 0.30 TIC acceptance x efficiency for
    Michel measured
  • X 0.182 fraction of Michel spectrum gt 48
    MeV calculated
  • X (0.92-1.0) conditional trigger efficiency
    for TIC measured
  • X 0.091 Michel geometric
    acceptance assumed
  • X eDCH drift chamber reconstruction
    cuts unknown
  • eDCH 11895 x 107 / 0.3 / 0.182 / 0.92 / 0.091 /
    8.4 / 1013 0.28-0.31

21
Conclusions
  • Tracking efficiency in current run is poor,
    mostly due to chamber performance
  • Intrinsic resolutions are not as good as expected
  • Rf resolution close to expectations, but tails
    are more than originally anticipated
  • time-distance relationship
  • operation at less than optimal voltages
  • noise
  • perhaps other causes
  • Z resolution significantly worse than planned,
    almost all due to noise
  • Momentum resolution not as good as expected with
    measured Gaussian uncertainties as input to
    fitter
  • reflection of tails in Rf and Z resolution
  • reduced number of hits and shorter tracks
  • full inefficiencies not yet represented in MC

22
Conclusions
  • DCH analysis currently adequate for data with MEG
    sensitivity of order few x 10-12
  • Find radiative decay signal requiring track
    projecting to timing counter hit, timing
    correction for track propagation
  • Trigger on and reconstruct with good precision
    Michel positrons to help with calibration and
    understanding of TIC performance
  • Reduced background rejection due to reduced
    momentum resolution adequate at current MEG
    sensitivity to m?eg
  • Significant improvement in MEG sensitivity per
    day of running can be achieved
  • Improvements in central part of resolution
    function
  • improved chamber efficiency (hardware)
  • some (non-trivial) tuning
  • ? reduction of background by 1/2
  • Improved noise performance (hardware)
  • ? additional background reduction by 1/2
  • Higher chamber efficiency will increase
    reconstruction efficiency
  • ? increase in sensitivity per day by 3
  • Strong effort is needed to achieve MEG
    sensitivity goal
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