Behaviour of MicroMega chambers in magnetic field : analysis of H2 June data
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Transcript of Behaviour of MicroMega chambers in magnetic field : analysis of H2 June data
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Behaviour of MicroMega chambers in magnetic field: analysis of H2 June data
Outline:(0) Introduction(1) Data set used and noise filtering(2) Cluster size and length(3) mTPC behaviour(4) Space resolutions and offsets.
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(0) Introduction• Effect of the magnetic field on electron drift:
where v0d is the drift velocity when B = 0. If B perp. to E (H2 data)
at the nominal MM working point. a is the “Lorentz angle”In NSW B<0.3 T l < 0.24 B term can be neglected (unless a sizeable E B is there). Displacements in the ExB direction of typical sizes:
up to hundreds of micron >> typical mechanical systematics
(1) Data set used and noise filtering
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beam: p=150 GeV/c
T1 – T2 T3 – T4
B field
side view
Magnetic field orthogonal to Electric fieldXstrip readout (vertical coordinate)particle bending non-negligible (displacement ≈ 50mm×B(T) btw. T1 and T3)T1, T2: 400 mm pitch, 5mm gap, HVmesh = 500(?) V; HVdrift = 300 V , Ar-CO2 93-7T3, T4: 400 mm pitch, 10 mm gap, HVmesh = 500(?) V; HVdrift = 600 V , Ar-CO2 93-7
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Full dataset used (June test-beam)|B| (T) +10° -10° +20° -20°
0. 7340 7319 7273 7299
0.2 7345 7324 7279 7305
0.5 7348 7327 7286 7308
1 7353 7333 7290 7313
Pre-filter done based on FFT recipe (see following)Strips are selected using the standard selection:
(charge threshold = 80)Times obtained using risetime fit
(slope > 0.15)Extended cluster definition (see following)
Resolution: score(T1-T3)/√2 (not completely correct…)
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NoiseFilter• CGatti NoiseFilter extracts an FFT value per chamber. High FFT
means “noisy” event.Typical distributions are shown here (run 7453):
T1 T2
T3 T4
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June test-beam (run 7353)
July test-beam (run 7486)
June H2 data are “more noisy” than H8 July data
T1
T1
T2
T2
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FFT tails in different chambers are correlated : cut based on T1 and T3 chambers only:
Events are accepted if FFT(T1)<4.5 && FFT(T3)<4.5
FFT(T1)
FFT(T3)
Typical rejection ≈ 20%: 20kevts 15-16 kevts
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Most plots in the following:
|B| = 0 |B| = 0.2 T(average NSW)
|B| = 0.5 T(extreme NSW)
|B| = 1 T(“crash” test)
Dataset A: bending “track-side”-10° and -20° data
Dataset B: bending “opposite-side”+10° and +20° data
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(2) Number of strips: dataset A -10° T1 T3
average #strips 0-strips events“singular” configuration @ |B|=0.2 T
increase of width increase of “empty events” fraction(particularly strong for T1 data)
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Number of strips: dataset A -20° T1 T3
average #strips 0-strips events“singular” configuration @ 0.2<|B|<0.5 T
increase of width increase of “empty events” fractionbut less evident than at 10o.
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Number of strips: dataset B +10° T1 T3
average #strips 0-strips eventsNo “singular” configurationaverage #strips almost constantBUT increase of widthincrease of “empty events” fraction(particularly strong for T1 data)
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Average cluster charge vs. |B|:General decrease with increasing |B|.
Dataset A Dataset B
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Cluster length and #holes: T3 – dataset B +10° cluster length Number of holes
The cluster definition has to be changed to include “scattered” clusters.For mTPC (see following) I require
2<#strips<16nholes<15
CONCLUSION: clusters are spread but maintains approximately the same number of strips; the overall charge decreases
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Dataset B: T3 time spectraGeneral trend: increase of drift time
+10° data: +20° data:
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Maximum drift time: summary
T3 T1
Effect of singluarities evident in Dataset A data (-10° and -20°)N.B. In mTPC the vdrift is held at its nominal value of 47 mm/ns(it should be adjusted accordingly)
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(3) mTPC event gallery-1: |B|=1, q=+10o
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mTPC event gallery-2: |B|=1, q=+10o
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mTPC T1 angles: Dataset A – T1
-10° data: -20° data:
“Angle inversion”: at 0.2 T @ -10° at 0.2 ÷ 0.5 T @ -20°
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mTPC T3 angles: Dataset A – T3
-10° data: -20° data:
“Angle inversion”: at 0.2 T @ -10° at 0.2 ÷ 0.5 T @ -20°
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mTPC T3 angles: Dataset B – T3
+10° data: +20° data:
Increase of the angle due to Lorentz angle effect
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Peak angle from mTPC vs. |B| (Dataset B data – previous slide).Data (red points) are compared with expections based on geometricalconsiderations:
|B| (T) |B| (T)
+20° data +10° data
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(4) mTPC xhalf resolution: Dataset A
-10° data: -20° data:
Bad xhalf resolution: @-10° |B| = 0.2 T @-20° |B| = 0.5 T
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mTPC xhalf resolution: Dataset B
+10° data: +20° data:
@20° resolution is worsening for |B|≥0.5 T
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Centroid resolutions: Dataset A
-10° data: -20° data:
Good centroid resolution: @-10° |B| = 0.2 T @-20° |B| = 0.5 T
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xhalf and centroid resolutions: summary
Dataset B
Dataset A
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NSW operationregions
“singular belt”
Summary: a pictorial view
“Singular belt” = Points where Lorentz Angle ≈ Track inclination
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T1
T3
Offset (T1-T3): depends on |B| due to the different gap size of T1 and T3
sketch of a trackcrossing T1 and T3both immersed in thesame B-field
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Try x0 in place of xhalf
xhalf is affected by a systematics, the effect of the magnetic field being a rotation of the track with x0 as “pivot”. x0 shouldn’t be affected.
Since T1 and T3 have a different gap (5mm vs. 10 mm) a B-dependent offset in xhalf is expected but not in x0.
x0
xhalf
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mTPC: comparison btw x0 and xhalf measurements (Dataset B data)
Offset clearly reduced BUT worse resolution (as expected)
+10° data
+20° data
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mTPC: comparison btw x0 and xhalf measurements (Dataset A data)
-10° data
-20° data
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Study of back-to-back configuration: mTPC on the four chambers, than combine and check.(T1+T2)/2 vs. (T3+T4)/2
lxcomb(1) = (xhalf(T1) + xhalf(T2))/2xcomb(2) = (xhalf(T3) + xhalf(T4))/2then:xcomb(1) – xcomb(2) distribution resolution and offset.
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Look @ 0 T data: resolution improves for centroid, not for xhalf. Why ?I expect that the resolution on xcomb is roughly √2 times better than resolution on xhalf
red = T1 – T3blue = T1T2 – T3T4
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Offsets = average values of xcomb(1) - xcomb(2):The offset should be reduced to the the effect of the particle bending
Offset are reduced to tipical slopes of 350 mm/T: I expect this slope if p=150 GeV/cand l = 60 cm. Are these numbers correct ?
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Summary and conclusions
The operation of MM in magnetic field requires a careful knowledge of the field map and a careful calibration procedure providing O(100 mm) corrections;
mTPC works fine with acceptable resolution in the full |B|-q plane apart from specific “singularities” (q=-10o, |B|=0.2 T and q=-20o, |B|≈0.4T)where the Lorentz angle “compensates” the track inclination.
In the singularities the centroid helps to recover resolution(but the combination should be based on clusterlength rather than #strips);
Using x0 rather than xhalf reduces the offset but spoils the resolution.
Back-to-Back doublets show no improvements on resolution but reduction of the offset probably consistent with track bending.