1 / 34

Behaviour of MicroMega chambers in magnetic field : analysis of H2 June data

This study examines the impact of magnetic fields on electron drift in the behaviour of micro megachambers using H2 June data. The analysis covers cluster size, mTPC behaviour, space resolutions, and offsets. The data set used and noise filtering techniques are detailed alongside insights into cluster lengths and holes. Observation of cluster charges, strip numbers, and event spectra provide valuable insights into the performance of micro megachambers in magnetic fields.

sheba
Download Presentation

Behaviour of MicroMega chambers in magnetic field : analysis of H2 June data

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. BehaviourofMicroMegachambers in magneticfield: analysisof H2 June data Outline: (0) Introduction (1) Data set used and noisefiltering (2) Cluster size and length (3) mTPCbehaviour (4) Spaceresolutions and offsets.

  2. (0) Introduction • Effectof the magneticfield on electron drift: wherev0dis the driftvelocitywhenB = 0. IfB perp. to E(H2 data) at the nominalMMworkingpoint. 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

  3. (1) Data set used and noisefiltering side view T3 – T4 T1 – T2 B field  beam: p=150 GeV/c • Magnetic field orthogonal to Electric field • Xstrip 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 93-7 • T3, T4: 400 mm pitch, 10 mm gap, HVmesh = 500(?) V; HVdrift = 600 V , Ar-CO2 93-7

  4. Full datasetused (Junetest-beam) •  Pre-filter done based on FFT recipe (see following) • Strips are selectedusing the standard selection: • (chargethreshold = 80) • Timesobtainedusingrisetimefit • (slope > 0.15) • Extended cluster definition(seefollowing) • Resolution: score(T1-T3)/√2 (not completely correct…)

  5. NoiseFilter • CGattiNoiseFilterextractsan FFT value per chamber. High FFT means “noisy” event. Typicaldistributions are shownhere (run 7453): T1 T2 T3 T4

  6. June H2 data are “more noisy” than H8 July data Junetest-beam (run 7353) T1 T2 Julytest-beam (run 7486) T1 T2

  7. FFT tails in differentchambers are correlated : cut based on T1 and T3 chambersonly:Events are acceptedif FFT(T1)<4.5 && FFT(T3)<4.5 Typical rejection ≈ 20%: 20kevts  15-16 kevts FFT(T1) FFT(T3)

  8. Dataset A: bending “track-side” -10° and -20° data DatasetB: bending “opposite-side” +10° and +20° data Mostplots in the following: |B| = 0 |B| = 0.2 T (average NSW) |B| = 0.5 T (extreme NSW) |B| = 1T (“crash” test)

  9. (2) Numberofstrips: dataset A -10° T3 T1 average#strips • “singular” configuration @ |B|=0.2 T • increase of width •  increase of “empty events” fraction • (particularly strong for T1 data) 0-strips events

  10. Numberofstrips: dataset A -20° T3 T1 average#strips • “singular” configuration • @ 0.2<|B|<0.5 T • increase of width •  increase of “empty events” fraction • but less evident than at 10o. 0-strips events

  11. Numberofstrips: datasetB +10° T3 T1 average#strips 0-strips events • No “singular” configuration • average #strips almost constant • BUT increase of width • increase of “empty events” fraction • (particularly strong for T1 data)

  12. Average cluster charge vs. |B|: Generaldecreasewithincreasing |B|. Dataset A DatasetB

  13. Cluster length and #holes: T3 –datasetB +10° cluster length Numberofholes The cluster definitionhastobechangedto include “scattered” clusters. FormTPC (seefollowing) I require 2<#strips<16 nholes<15 CONCLUSION: clusters are spread butmaintainsapproximately the same numberofstrips; the overallchargedecreases

  14. DatasetB: T3 timespectraGeneral trend: increaseofdrifttime +10° data: +20° data:

  15. Maximumdrifttime: summary T3 T1 Effectofsingluaritiesevident in Dataset A data (-10° and -20°) N.B. In mTPC the vdriftisheld at itsnominalvalueof 47 mm/ns (itshouldbeadjustedaccordingly)

  16. (3) mTPCevent gallery-1: |B|=1, q=+10o

  17. mTPCevent gallery-2: |B|=1, q=+10o

  18. mTPC T1 angles: Dataset A – T1 -10° data: -20° data: “Angle inversion”: at 0.2 T @ -10° at 0.2 ÷ 0.5 T @ -20°

  19. mTPC T3 angles: Dataset A – T3 -10° data: -20° data: “Angle inversion”: at 0.2 T @ -10° at 0.2 ÷ 0.5 T @ -20°

  20. mTPC T3 angles: DatasetB– T3 +10° data: +20° data: Increaseof the angle due toLorentz angle effect

  21. Peak angle frommTPC vs. |B| (DatasetB data –previous slide). Data (redpoints) are comparedwithexpectionsbased on geometrical considerations: +20° data +10° data |B| (T) |B| (T)

  22. (4) mTPCxhalfresolution: Dataset A -10° data: -20° data: Bad xhalfresolution: @-10° |B| = 0.2 T @-20° |B| = 0.5 T

  23. mTPCxhalfresolution: DatasetB +10° data: +20° data: @20° resolution is worsening for |B|≥0.5 T

  24. Centroidresolutions: Dataset A -10° data: -20° data: Goodcentroidresolution: @-10° |B| = 0.2 T @-20° |B| = 0.5 T

  25. xhalf and centroidresolutions: summary DatasetB Dataset A

  26. Summary: a pictorialview “singularbelt” NSW operation regions “Singular belt” = Points where Lorentz Angle ≈ Track inclination

  27. Offset (T1-T3): depends on |B| due to the different gap sizeof T1 and T3 T1 sketch of a track crossing T1 and T3 bothimmersed in the sameB-field T3

  28. xhalf x0 Tryx0 in placeofxhalf xhalfisaffectedby a systematics, the effectof the magneticfield being a rotation of the trackwith x0as “pivot”. x0shouldn’tbeaffected. Since T1 and T3 have a different gap (5mm vs. 10 mm) a B-dependent offset in xhalfisexpectedbutnot in x0.

  29. mTPC: comparisonbtw x0 and xhalfmeasurements (DatasetB data) +10° data +20° data • Offset clearly reduced BUT worse resolution (as expected)

  30. mTPC: comparisonbtw x0 and xhalfmeasurements (Dataset A data) -10° data -20° data

  31. Studyofback-to-backconfiguration: mTPC on the fourchambers, than combine and check. (T1+T2)/2 vs. (T3+T4)/2 l xcomb(1) = (xhalf(T1) + xhalf(T2))/2 xcomb(2) = (xhalf(T3) + xhalf(T4))/2 then: xcomb(1) –xcomb(2) distribution resolution and offset.

  32. Look @ 0T data: resolutionimprovesforcentroid, notforxhalf. Why ? I expect that the resolution on xcomb is roughly √2 times better than resolution on xhalf red = T1 – T3 blue = T1T2 – T3T4

  33. Offsets = averagevaluesofxcomb(1) - xcomb(2): The offset shouldbereducedto the the effectof the particlebending Offset are reducedtotipicalslopesof 350 mm/T: I expectthisslopeif p=150 GeV/c and l = 60 cm. Are thesenumberscorrect ?

  34. 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 x0ratherthanxhalfreduces the offset butspoils the resolution. • Back-to-Back doublets show no improvements on resolution but reduction • of the offset probably consistent with track bending.

More Related