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VDC Tracking P.E. Ulmer Old Dominion University Expert … or, nobody else wanted to talk about it; You decide Hall A Analysis Workshop December 11, 2001.

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Presentation on theme: "VDC Tracking P.E. Ulmer Old Dominion University Expert … or, nobody else wanted to talk about it; You decide Hall A Analysis Workshop December 11, 2001."— Presentation transcript:

1 VDC Tracking P.E. Ulmer Old Dominion University Expert … or, nobody else wanted to talk about it; You decide Hall A Analysis Workshop December 11, 2001

2 Algorithm description Tracking problems seen in E94-004 My definition of good event Rate dependence of tracking efficiency Hit patterns for a sample of events Possible repair strategies Thanks to Jeff Templon for providing me with his paper: VDC Reconstruction in ESPACE, dated October 22, 2001 Outline

3 LeCroy 1877 multihit TDC TDC Start: wire TDC Stop: trigger 1.496 usec time window 1 st hit has largest TDC value Rough time distance conversion: tdc_cut > 0: cut out negative distances tdc_cut > 1: cut out large positive distances For hits passing cuts: Accept only largest TDC values Load VDC Wire/TDC structure Find clusters Analyze clusters for tracks Algorithm Overview

4 Analysis flow (main VDC routines): scan_file input process_data process_spectrometer spectrometer_reconstruct vdc_presort find_clusters vdc_pattern vdc_tracks find_tracks setup_tree order_paths fill_track Algorithm Details - 1

5 spectrometer_reconstruct: vdc_presort: find_clusters: NGAP_CLUS=2 1 wire gap max vdc_pattern: Determine pivot point per cluster vdc_tracks: Get rough slope/intercept per cluster find_tracks: Find all tracks Fill structure with golden track Algorithm Details - 2

6 setup_tree: Establish all possible links (branches) between clusters Layers ordered as: u1,u2,v1,v2 Fit for u1/u2 and fit for v1/v2: intercept + slope * (x(i) +/- t0) 3 parameters: intercept, slope, t0 x(i): distance including separation between planes Require 4 or more wires in u1+u2 and v1+v2 Algorithm Details - 3

7 order_paths : Define chi-square: Rank paths (roads) by ascending chi- square: Minimum Spanning Tree Algorithm Details - 4

8 fill_track : 1 st track: track with min. chi-square Examine track with next lowest chi- square All clusters distinct from track 1? Yes: this track becomes track 2 No: go to next track and repeat Sort surviving tracks in order of ascending average t0. Lowest t0: golden track Fill structure with golden track (done in spectrometer_reconstruct) Algorithm Details - 5

9 clusters/plane = 1 multiplicity/plane: 3 to 7 angle_diff: -0.4 to +0.5 slope: from 0.4 to 1.0 ( u1, v1, v2) from 0.5 to 0.9 (u2) tracks/spectrometer = 1 (guaranteed by clusters/plane = 1) |th_tra| < 0.15 Analysis flags: tdc_cut=2 tx_cor=1 Cuts: good events

10 Possible Strategies Multi-plane consistency: Angle from single plane determined to ~ 1 deg Track to other, corresponding chamber: ~ 1.5 cm spot (4 wires) Find appropriate cluster Does this cluster point back to our starting cluster? Slope test: Define clusters by group of wires with reasonable delta_t between adj. wires Consistent with scintillator paddles defining trigger? Cause for high multiplicities, even at low rate? Hardware solutions?

11 Figures – from E94-004 H(e,ep) – Run 2591 e_reactz vs. h_reactz (event_type=5) log plot of eu1_slope (event_type=1) eu1_mult < 6 eu1_mult > 5 eu1_mult > 6 log plot of e_miss (event_type=5) mult < 6 (all 8 planes) mult < 8 (all 8 planes) no multiplicity cuts D(e,ep) production runs E-arm efficiency vs. rate (electron.ps) H-arm efficiency vs. rate (hadron.ps) Figures of event hit patterns


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