Diffusion updates – mainly MC simulations
Thomas Karl Warburton, with help from Michelle Stancari and Dom Brailsford
Diffusion updates mainly MC simulations Thomas Karl Warburton, - - PowerPoint PPT Presentation
Diffusion updates mainly MC simulations Thomas Karl Warburton, with help from Michelle Stancari and Dom Brailsford What Ive shown before Want to determine interaction times using diffusion. Use the change in RMS and the change in
Thomas Karl Warburton, with help from Michelle Stancari and Dom Brailsford
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Want to determine interaction times using diffusion.
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Use the change in RMS and the change in RMS/Charge of the hits along the track.
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Make look-up tables using tracks with known angles (using the counter coincidences).
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Use these look-up tables on a set of tracks to predict an interaction time for the track.
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This interaction time can then be compared with the time of the counter coincidence.
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I did this for both a sample of data runs, and an MC sample at 250 V.
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Predicted times using the RMS metric
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s) µ Difference in predicted and reconstructed interaction time ( 1000 − 500 − 500 1000 1500 2000 Number 20 40 60 80 100 120 140
35t data 35t CRY MC
s) µ Difference in predicted and reconstructed interaction time ( 1000 − 500 − 500 1000 1500 2000 Number 10 20 30 40 50 60 70 80 90 100
35t data 35t CRY MC
Predicted times using the RMS/Q metric
✤ Increased width of data predictions. ✤ Tighter distribution around 0 difference for RMS/Q ✤ When converted to a drift distance this times are < 5 cm.
✤ I made some MC challenge like samples with
✤ Diffusion consts. 0, 50, 100, 200 ✤ Electron lifetimes: 1, 2, 3, 5, 8 ✤ Electric fields: 250, 275, 500 ✤ Didn’t want to make LOADS of samples, so only
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Hit RMS 1.6 1.8 2 2.2 2.4 2.6 2.8 3 Number 5000 10000 15000 20000 25000 30000
3ms 500V 0Diff 3ms 500V 0Diff 3ms 500V 50Diff 3ms 500V 50Diff 3ms 500V 100Diff 3ms 500V 100Diff 3ms 500V 200Diff 3ms 500V 200Diff
Hit RMS divided by hit charge 0.005 0.01 0.015 0.02 0.025 0.03 Number 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000 22000 24000
3ms 500V 0Diff 3ms 500V 0Diff 3ms 500V 50Diff 3ms 500V 50Diff 3ms 500V 100Diff 3ms 500V 100Diff 3ms 500V 200Diff 3ms 500V 200Diff
Drift Distance (cm) 20 40 60 80 100 120 140 160 180 200 Mean value for hit RMS (ticks, 500 ns) 1.8 1.9 2 2.1 2.2 2.3 2.4 2.5 2.6
3ms 500V 0Diff 3ms 500V 0Diff 3ms 500V 50Diff 3ms 500V 50Diff 3ms 500V 100Diff 3ms 500V 100Diff 3ms 500V 200Diff 3ms 500V 200Diff
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) ° Track Angle ( 5 10 15 20 25 30 35 40 Intercept of fit (ticks) 1.8 1.85 1.9 1.95 2 2.05
3ms 500V 0Diff 3ms 500V 50Diff 3ms 500V 100Diff 3ms 500V 200Diff
Time (ms) 600 − 400 − 200 − 200 400 600 Number 500 1000 1500 2000 2500 3000 3500
3ms 500V 0Diff 3ms 500V 0Diff 3ms 500V 50Diff 3ms 500V 50Diff 3ms 500V 100Diff 3ms 500V 100Diff 3ms 500V 200Diff 3ms 500V 200Diff
Time (ms) 600 − 400 − 200 − 200 400 600 Number 500 1000 1500 2000 2500 3000
3ms 500V 0Diff 3ms 500V 0Diff 3ms 500V 50Diff 3ms 500V 50Diff 3ms 500V 100Diff 3ms 500V 100Diff 3ms 500V 200Diff 3ms 500V 200Diff
Top Left – RMS MPV at 0 cm Top Right – AvDiff in predicted and counter time for RMS Bottom left – AvDiff in predicted and counter time for RMS/Q
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Hit RMS 1.6 1.8 2 2.2 2.4 2.6 2.8 3 Number 2000 4000 6000 8000 10000 12000 14000 16000
1ms 500V 100Diff 1ms 500V 100Diff 2ms 500V 100Diff 2ms 500V 100Diff 3ms 500V 100Diff 3ms 500V 100Diff 5ms 500V 100Diff 5ms 500V 100Diff 8ms 500V 100Diff 8ms 500V 100Diff
Hit RMS divided by hit charge 0.005 0.01 0.015 0.02 0.025 0.03 Number 2000 4000 6000 8000 10000 12000
1ms 500V 100Diff 1ms 500V 100Diff 2ms 500V 100Diff 2ms 500V 100Diff 3ms 500V 100Diff 3ms 500V 100Diff 5ms 500V 100Diff 5ms 500V 100Diff 8ms 500V 100Diff 8ms 500V 100Diff
Drift Distance (cm) 20 40 60 80 100 120 140 160 180 200 Mean value for hit RMS (ticks, 500 ns) 1.8 1.85 1.9 1.95 2 2.05 2.1 2.15 2.2 2.25 2.3
1ms 500V 100Diff 1ms 500V 100Diff 2ms 500V 100Diff 2ms 500V 100Diff 3ms 500V 100Diff 3ms 500V 100Diff 5ms 500V 100Diff 5ms 500V 100Diff 8ms 500V 100Diff 8ms 500V 100Diff
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Top Left – RMS MPV at 0 cm Top Right – AvDiff in predicted and counter time for RMS Bottom left – AvDiff in predicted and counter time for RMS/Q
) ° Track Angle ( 5 10 15 20 25 30 35 40 Intercept of fit (ticks) 1.82 1.84 1.86 1.88 1.9 1.92 1.94 1.96 1.98 2 2.02
1ms 500V 100Diff 2ms 500V 100Diff 3ms 500V 100Diff 5ms 500V 100Diff 8ms 500V 100Diff
Time (ms) 600 − 400 − 200 − 200 400 600 Number 500 1000 1500 2000 2500 3000 3500
1ms 500V 100Diff 1ms 500V 100Diff 2ms 500V 100Diff 2ms 500V 100Diff 3ms 500V 100Diff 3ms 500V 100Diff 5ms 500V 100Diff 5ms 500V 100Diff 8ms 500V 100Diff 8ms 500V 100Diff
Drift Distance (cm) 100 − 50 − 50 100 Number 500 1000 1500 2000 2500 3000
1ms 500V 100Diff 1ms 500V 100Diff 2ms 500V 100Diff 2ms 500V 100Diff 3ms 500V 100Diff 3ms 500V 100Diff 5ms 500V 100Diff 5ms 500V 100Diff 8ms 500V 100Diff 8ms 500V 100Diff
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Hit RMS 1.6 1.8 2 2.2 2.4 2.6 2.8 3 Number 2000 4000 6000 8000 10000 12000 14000 16000 3ms 250V 100Diff 3ms 250V 100Diff 3ms 375V 100Diff 3ms 375V 100Diff 3ms 500V 100Diff 3ms 500V 100Diff Hit RMS divided by hit charge 0.005 0.01 0.015 0.02 0.025 0.03 Number 2000 4000 6000 8000 10000 12000 14000 3ms 250V 100Diff 3ms 250V 100Diff 3ms 375V 100Diff 3ms 375V 100Diff 3ms 500V 100Diff 3ms 500V 100Diff Drift Distance (cm) 20 40 60 80 100 120 140 160 180 200 Mean value for hit RMS (ticks, 500 ns) 1.8 2 2.2 2.4 2.6 2.8 3
3ms 250V 100Diff 3ms 250V 100Diff 3ms 375V 100Diff 3ms 375V 100Diff 3ms 500V 100Diff 3ms 500V 100Diff
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Top Left – RMS MPV at 0 cm Top Right – AvDiff in predicted and counter time for RMS Bottom left – AvDiff in predicted and counter time for RMS/Q
) ° Track Angle ( 5 10 15 20 25 30 35 40 Intercept of fit (ticks) 1.8 1.9 2 2.1 2.2 2.3 2.4 2.5
3ms 250V 100Diff 3ms 375V 100Diff 3ms 500V 100Diff
Drift Distance (cm) 100 − 50 − 50 100 Number 500 1000 1500 2000 2500 3000 3500 3ms 250V 100Diff 3ms 250V 100Diff 3ms 375V 100Diff 3ms 375V 100Diff 3ms 500V 100Diff 3ms 500V 100Diff Drift Distance (cm) 100 − 50 − 50 100 Number 500 1000 1500 2000 2500 3000 3500 3ms 250V 100Diff 3ms 250V 100Diff 3ms 375V 100Diff 3ms 375V 100Diff 3ms 500V 100Diff 3ms 500V 100Diff
✤ I need to sort out the placing of the legends… ✤ The RMS/Q method is more accurate, even when the
✤ The distributions are not centered around 0. ✤ This is because of averaging numbers found by
✤ The first two plots for each sample aren’t symmetric but
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✤ I also want to make a sample which has increased noise
✤ Only using EW counters for this, so a very narrow range of
✤ Only using collection plane wires, so not sensitive to
✤ I don’t have time to expand the angular range used for
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