Status of TDR studies NDK t0 reconstruction J. Soto DPPD - - PowerPoint PPT Presentation

Status of TDR studies NDK t0 reconstruction

• J. Soto

DPPD consortium 12th February 2019

Content

• Previous status of the analysis.
• Including MCTruth position.
• Background reduction.
• Matching process.
• Results.
• J. Soto | TDR studies, t0 reconstruction

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Previous status (CM201901)

• We don't reach the 90% of t0

matching efficiency in all volume.

• BUT this study was considering

just the detected light over the background (without considering additional information provided by the trigger).

• Next steps

To consider the → MCTruth position in the PMT plane.

• J. Soto | TDR studies, t0 reconstruction

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• If we consider the center of the maximum reconstructed cluster as the

reconstructed position, we can compare with the montecarlo truth position (expected to be provided by the trigger).

• We observe a smearing of ~5m.

RecoCluster vs MCTruth Position

• Looking at the distance in the PMT plane, most of the events are reconstructed within a

radius of 5m around the MCTruth vertex. This distance distribution is wider as we go up in the drift direction.

• If we reduce our area of interest to this circle of 5m radius around the trigger point, we can

reduce our background.

RecoCluster vs MCTruth Position

*Full 4seconds sample

• The background level is not uniform

along the YZ plane.

• Since we have the YZ position of the

event, we should get only the background events in the vicinity.

• We can define a distance, and take

into account only the background events of the same intensity (#PEs)

• f the signal cluster.

Background reduction

• Since we don't have the mixed sample yet

(signal+background), I compute the matching probability rather than efficiency

• Matching process:

–

I take the number of background clusters in the vicinity, N, with similar intensity to the signal cluster (>0.8 #PEs) in a 16ms window.

–

Vicinity is defined as a circle of radius D, and center the MCTruth position.

–

If the reconstructed cluster of the signal is inside the vicinity, the probability to be well matched is 1/(1+N)

–

If not, Probability = 0.

• I define the Matching efficiency as the average
• f the probability to be well matched.

Matching process

N=0 N=1 N=1

BG cluster Signal Cluster Arrow marks the MCTruth vertex.

Matching probability = 0 Matching probability = 1

Matching probability = 0.5

• A scan in the Matching Distance (D)

parameter has been perform, to find the balance between background rejection and signal detection.

• Red

curve shows the matching efficiency.

• Black curve shows the matching

efficiency with no background, converging with the efficiency for small distances.

• Green curve shows the background

contribution to the matching efficiency, assuming that the signal cluster is always in the vicinity of the MCTruth position.

• We have a maximum around 0.78 in

D~5m (this plot considers 16ms of background).

Matching efficiency

Matching efficiency scan in drift direction

• We are able to match the 80% of the events, with the right cluster.
• We reach up to 8meters of the TPC AV above 90% efficiency.
• (Considering matching distance of 5m, and 8ms of background per event).
• J. Soto | TDR studies, t0 reconstruction

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A possible improvement:

• Introducing a dependency of D with the #PEs:
• J. Soto | TDR studies, t0 reconstruction

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#PE < exp(13.15-d/60.8)