RS algorithm for 3D localization of g interactions in segmented HPGe detectors: tests with calculated and
experimental signal basis.
FABIO CRESPI - University of MILANO / INFN
OUTLINE:
g -ray tracking detectors (AGATA array)
Recursive Subtraction 3D (RS_3D) Algorithm for interaction position determination.
Tests with Calculated and Experimental
Signal Basis.
In gamma spectroscopy experiments with radioactive ion beams the reconstruction of the gamma radiation path inside the detectors allows the correction of the Doppler broadening effect and the suppression of the background radiation not coming from the target position.
Ingredients of g -Tracking
Pulse Shape Analysis to decompose recorded traces Highly segmented
HPGe detectors
· ·
· ·
Identified interaction
points (x, y, z, E, t )i
Reconstruction of tracks e.g. by evaluation of
permutations of interaction points
Digital electronics to record and process segment
signals
g
1
2 3
4
reconstructed g-rays
g
Target Particle
Detectors
Particle Detector
g
The Advanced Gamma ray Tracking Array (AGATA)
AGATA Demonstrator Array
In gamma spectroscopy experiments with radioactive ion beams the reconstruction of the gamma radiation path inside the detectors allows the correction of the Doppler broadening effect and the suppression of the background radiation not coming from the target position.
Ingredients of g -Tracking
Pulse Shape Analysis to decompose recorded traces Highly segmented
HPGe detectors
· ·
· ·
Identified interaction
points (x, y, z, E, t )i
Reconstruction of tracks e.g. by evaluation of
permutations of interaction points
Digital electronics to record and process segment
signals
g
1
2 3
4
reconstructed g-rays
g
Target Particle
Detectors
Particle Detector
g
The Advanced Gamma ray Tracking Array (AGATA)
AGATA Demonstrator Array
RS_3D
Recursive Subtraction* 3D (RS_3D) Algorithm
The XYZ Position of the interactions is extracted comparing the detector signal shape with reference shapes included in a database (―Signal Basis‖).
The Signals in the ―Basis‖ are ordered according to specific parameters (e.g.
position of the derived net-charge signal maximum) in order to minimize CPU time.
For each net charge collecting segment the following operations are performed:
the Signals (transients or net charge) which are likely to have a shape that depends on only one interaction are selected.
these signals are compared with the Basis elements.
the element that best matches is subtracted from the detector signal.
0 0.001 0.002 0.003 0.004 0.005 0.006
0 100 200 300 400 500 600
Time (ns)
0 0.001 0.002 0.003 0.004 0.005 0.006
0 100 200 300 400 500 600
Time (ns)
Amplitude (A.U.)
max at 100 ns max at 200 ns max at 300 ns max at 400 ns
0 0.001 0.002 0.003 0.004 0.005 0.006
0 100 200 300 400 500 600
Time (ns)
Amplitude (A.U.)
max at 100 ns max at 200 ns max at 300 ns max at 400 ns
0 0.001 0.002 0.003 0.004 0.005 0.006
0 100 200 300 400 500 600
Time (ns)
Amplitude (A.U.)
max at 100 ns max at 200 ns max at 300 ns max at 400 ns
*F.C.L. Crespi, Nucl. Instr. and Meth. A570 (2007), p. 459
35 5 11 17 23 29 35 34 4 10 16 22 28 34 33 3 9 15 21 27 33 32 2 8 14 20 26 32 31 1 7 13 19 25 31
30 0
72 keV6 12 18 24 30
446 keV 144 keV
662 keV
Recursive Subtraction 3D (RS_3D) Algorithm Example: 662 keV* F.E.P. simulated event** ,
Segment multiplicity =3.
*137Cs source, used in tests with experimental data presented in the following.
** Geant 4 AGATA code used
(E. Farnea, D. Bazzacco, LNL-INFN(REP)—202 (2004) 158 website: http://agata.pd.infn.it.)
35 5 11 17 23 29 35 34 4 10 16 22 28 34 33 3 9 15 21 27 33 32 2 8 14 20 26 32 31 1 7 13 19 25 31 30 0 6 12 18 24 30
72 keV 446 keV
144 keV
Recursive Subtraction 3D (RS_3D) Algorithm
662 keV
Example: 662 keV F.E.P. simulated event, Segment multiplicity =3
-100 400 900 1400 1900 2400 2900
0 10 20 30 40 50 60
TIME (10*ns)
AMPLITUDE (A.U.)
Net Charge Signals Transient Signals
(1 N.C. segment neighbor only)
“Superimposed” Transient Signals
(influenced by multiple N.C. Segments)
35 5 11 17 23 29 35 34 4 10 16 22 28 34 33 3 9 15 21 27 33 32 2 8 14 20 26 32 31 1 7 13 19 25 31 30 0 6 12 18 24 30
72 keV 446 keV
144 keV
-50 -40 -30 -20 -10 0 10
0 10 20 30 40 50 60
-50 -40 -30 -20 -10 0 10
0 10 20 30 40 50 60
-50 -40 -30 -20 -10 0 10
0 10 20 30 40 50 60
Recursive Subtraction 3D (RS_3D) Algorithm
Example: 662 keV F.E.P. simulated event, Segment multiplicity =3
TIME (10*ns)
TIME (10*ns)
TIME (10*ns)
AMPLITUDE (A.U.)AMPLITUDE (A.U.)AMPLITUDE (A.U.)
662 keV
AMPLITUDE (A.U.)AMPLITUDE (A.U.)AMPLITUDE (A.U.)
35 5 11 17 23 29 35 34 4 10 16 22 28 34 33 3 9 15 21 27 33 32 2 8 14 20 26 32 31 1 7 13 19 25 31 30 0 6 12 18 24 30
72 keV 446 keV
144 keV
-50 -40 -30 -20 -10 0 10
0 10 20 30 40 50 60
-50 -40 -30 -20 -10 0 10
0 10 20 30 40 50 60
-50 -40 -30 -20 -10 0 10
0 10 20 30 40 50 60
TIME (10*ns)
TIME (10*ns)
TIME (10*ns)
Recursive Subtraction 3D (RS_3D) Algorithm
Example: 662 keV F.E.P. simulated event, Segment multiplicity =3
662 keV
35 5 11 17 23 29 35 34 4 10 16 22 28 34 33 3 9 15 21 27 33 32 2 8 14 20 26 32 31 1 7 13 19 25 31 30 0 6 12 18 24 30
72 keV
144 keV
35 5 11 17 23 29 35 34 4 10 16 22 28 34 33 3 9 15 21 27 33 32 2 8 14 20 26 32 31 1 7 13 19 25 31 30 0 6 12 18 24 30
72 keV
Recursive Subtraction 3D (RS_3D) Algorithm
Example: 662 keV F.E.P. simulated event, Segment multiplicity =3
Net Charge Signals Transient Signals
(1 N.C. segment neighbor only)
―Superimposed‖ Transient Signals
(influenced by multiple N.C. Segments)
662 keV
35 5 11 17 23 29 35 34 4 10 16 22 28 34 33 3 9 15 21 27 33 32 2 8 14 20 26 32 31 1 7 13 19 25 31
30 0
72 keV6 12 18 24 30
446 keV 144 keV
662 keV
Recursive Subtraction 3D (RS_3D) Algorithm
Example: 662 keV F.E.P. simulated event, Segment multiplicity =3
-100 400 900 1400 1900 2400 2900
0 10 20 30 40 50 60
TIME (10*ns)
AMPLITUDE (A.U.)
-500 0 500 1000 1500 2000 2500 3000 3500
1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596010 20 30 40 50 60
Reconstructed Signal
Conclusions
PSCS scan Calculated Basis
Pos X [0.1*mm]
PosY [0.1*mm]
-30 -10 10 30 50 70 90 110
0 60 120 180 240 300 360
1 2 3 4 5 6
TIME [10*ns]
AMPLITUDE [a.u.]
882 493 806 513
883 523 839 504
883 554 873 500
884 585 906 500
885 616 940 504
886 646 973 513
887 677
888 708
889 739
Pos Y [0.1*mm]
Pos X [0.1*mm]
Pos X [0.1*mm]
Pos Y [0.1*mm]
1 56 3 24
-30 -10 10 30 50 70 90 110
0 60 120 180 240 300 360
1 2 3 4 5 6
TIME [10*ns]
AMPLITUDE [a.u.]
-30 -10 10 30 50 70 90 110
0 60 120 180 240 300 360
1 2 3 4 5 6
TIME [10*ns]
AMPLITUDE [a.u.]
-30 -10 10 30 50 70 90 110
0 60 120 180 240 300 360
1 2 3 4 5 6
TIME [10*ns]
AMPLITUDE [a.u.]
Experimental Basis: extracted using PSCS scan****recently developed technique, still under test. (4 segments available) (see dedicated NSS 2010 Poster)
Signal Basis: Calculated and Experimental
Calculated Basis*: currently implemented and used in AGATA experiments with
GRID SEARCH** PSA algorithm. (C001 Asymmmetric Detector, used for experimental data acquisition in Liverpool University***)
Conclusions
PSCS scan Calculated Basis
Pos X [0.1*mm]
PosY [0.1*mm]
-30 -10 10 30 50 70 90 110
0 60 120 180 240 300 360
1 2 3 4 5 6
TIME [10*ns]
AMPLITUDE [a.u.]
882 493 806 513
883 523 839 504
883 554 873 500
884 585 906 500
885 616 940 504
886 646 973 513
887 677
888 708
889 739
Pos Y [0.1*mm] Pos X [0.1*mm]
Pos X [0.1*mm]
Pos Y [0.1*mm]
1 56 3 24
-30 -10 10 30 50 70 90 110
0 60 120 180 240 300 360
1 2 3 4 5 6
TIME [10*ns]
AMPLITUDE [a.u.]
-30 -10 10 30 50 70 90 110
0 60 120 180 240 300 360
1 2 3 4 5 6
TIME [10*ns]
AMPLITUDE [a.u.]
-30 -10 10 30 50 70 90 110
0 60 120 180 240 300 360
1 2 3 4 5 6
TIME [10*ns]
AMPLITUDE [a.u.]
Conclusions
PSCS scan Calculated Basis
Pos X [0.1*mm]
PosY [0.1*mm]
-30 -10 10 30 50 70 90 110
0 60 120 180 240 300 360
1 2 3 4 5 6
TIME [10*ns]
AMPLITUDE [a.u.]
882 493 806 513
883 523 839 504
883 554 873 500
884 585 906 500
885 616 940 504
886 646 973 513
887 677
888 708
889 739
Pos Y [0.1*mm]
Pos X [0.1*mm]
Pos X [0.1*mm]
Pos Y [0.1*mm]
1 56 3 24
-30 -10 10 30 50 70 90 110
0 60 120 180 240 300 360
1 2 3 4 5 6
TIME [10*ns]
AMPLITUDE [a.u.]
-30 -10 10 30 50 70 90 110
0 60 120 180 240 300 360
1 2 3 4 5 6
TIME [10*ns]
AMPLITUDE [a.u.]
-30 -10 10 30 50 70 90 110
0 60 120 180 240 300 360
1 2 3 4 5 6
TIME [10*ns]
AMPLITUDE [a.u.] Z(0.1*mm)
Y (0.1*mm)
X (0.1*mm) X’ (0.1*mm)
*Bart Bruyneelet al., NIMA599 (2009), p. 196
**R. Venturelli, D. Bazzacco, LNL-INFN(REP)—204 (2005) 220
***A. Boston et al., Nucl. Instr. and Meth.
B 261 (2007), p. 1098
****F.C.L. Crespi
et al.
,NIMA
593 (2008), p.440Tests with Calculated Signal Basis
Y Position (mm) Y Position (mm)
X Position (mm)
Y Position (mm)
X Position (mm)
Y Position (mm) Z Position (mm)
Z Position (mm)
Y Position (mm)
Counts (A.U.)
662 keV pencil beam moved along Y direction – 5 mm steps
(Geant4 + Calculated Signals + preamp response + 5 keV FWHM noise)
Original Distribution
Original Distribution
RS_3D output Distribution
RS_3D Output Distribution
Tests with Calculated Signal Basis
X Position (mm)
Y Position (mm)
X Position (mm)
Y Position (mm)
Y Position (mm)
Z Position (mm) Z Position (mm)
Y Position (mm) Y Position (mm)
Counts (A.U.)
662 keV pencil beam moved along X direction – 5 mm steps
(Geant4 + Calculated Signals + preamp response + 5 keV FWHM noise)
Original Distribution RS_3D output Distribution
Original Distribution RS_3D Output
Distribution
X (mm)
Counts
Y (mm)
Counts
1 5 6 3 2 4
137Cs
Tests with Experimental Signal Basis
137Cs (662 keV) collimated data*
Experimental Signal Basis extracted with PSCS technique** for Segment A1.
**F.C.L. Crespiet al., NIMA593 (2008), p.440 and NSS- 2010 (N29-226) Poster Presentation
*
A. Boston et al., Nucl. Instr. and Meth. B261 (2007), p.1098
Conclusions
A new version of RS algorithm (RS_3D) providing 3D localization of gamma interaction points inside a segmented HPGe detector (disentangling also multiple hits in a single segment) has been developed and tested with both calculated and experimental signals. 5 mm position resolution (necessary for performing gamma ray tracking) is reached.
RS_3D CPU time consumption still has to be decreased for allowing the algorithm application on-line:
currently in AGATA the GRID SEARCH algorithm is implemented (it is fast but can not disentangle multiple hits in a single segment).
Perspectives
Further test the RS_3D algorithm with experimentally extracted PSCS basis, using all the scanned segments. (e.g. n looking at the reconstructed energy relaese distributon along Z axis).
Improving further RS_3D algorithm CPU time performancies
