The Interplay Between the Statistical Correlations of -ray Emission Probabilities and Efficiency Calibration * M. Castro 1,2 , Vito R. Vanin 3 , Paulo R. Pascholati 3 , Nora L. Maidan 1 IEAv - CTA, São José dos Campos, Brasil 2 DMAF - UNITAU, Taubaté, Brasil 3 LAL - IFUSP, São Paulo, Brasil 14 th International Conference on Radionuclide Metrology and its Applications ICRM2003 - Dublin, Ireland Applied Radiation and Isotopes 60 (2004) 185-190 http://dx.doi.org/10.1016/j.apradiso.2003.11.014 * Presented in:
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Ruy M. Castro 1,2 , Vito R. Vanin 3 , Paulo R. Pascholati 3 , Nora L. Maidana 3
The Interplay Between the Statistical Correlations of g -ray Emission Probabilities and Efficiency Calibration *. Ruy M. Castro 1,2 , Vito R. Vanin 3 , Paulo R. Pascholati 3 , Nora L. Maidana 3 1 IEAv - CTA, São José dos Campos, Brasil 2 DMAF - UNITAU, Taubaté, Brasil - PowerPoint PPT Presentation
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The Interplay Between the Statistical Correlationsof -ray Emission Probabilities and
Efficiency Calibration *
Ruy M. Castro 1,2, Vito R. Vanin 3, Paulo R. Pascholati 3, Nora L. Maidana 3
1 IEAv - CTA, São José dos Campos, Brasil2 DMAF - UNITAU, Taubaté, Brasil3 LAL - IFUSP, São Paulo, Brasil
14th International Conference on Radionuclide Metrology and its Applications ICRM2003 - Dublin, Ireland
Applied Radiation and Isotopes 60 (2004) 185-190
http://dx.doi.org/10.1016/j.apradiso.2003.11.014
* Presented in:
Contents
•Are the data correlated?
•Efficiency Calibration
•Example
•Decay parameters
Are the data correlated?
REFRelative P (P1408keV = 100 %)
121 keV 244 keV 344 keV 411 keV
1 145,0 ± 4,1 39,4 ± 1,3 128,2 ± 3,6 10,14 ± 0,54
2 138,5 ± 6,4 36,2 ± 1,8 128,2 ± 5,9 10,32 ± 0,51
3 132,9 ± 4,0 35,8 ± 1,0 128,2 ± 3,8 10,77 ± 0,38
4 144,6 ± 4,7 36,4 ± 1,2 128,2 ± 4,2 10,59 ± 0,27
5 141,0 ± 4,0 36,6 ± 1,1 127,2 ± 1,3 10,71 ± 0,11
6 140,6 ± 2,8 35,8 ± 0,6 128,2 ± 2,6 10,55 ± 0,22
7 136,9 ± 1,3 36,2 ± 0,3 127,1 ± 0,7 10,84 ± 0,07
8 136,7 ± 0,7 36,5 ± 0,4 126,9 ± 0,9 10,73 ± 0,10
Analyzing the 152Eu published data~ 32 experiments with the most intense transitions
Are the data correlated?
RI
RI RINI
30
25
20
15
10
5
010 11
RI411 keVRef
30
25
20
15
10
5
0-3 -2 -1 0 1 2 3
NI411 keV
Are the data correlated?
= 0.6
30
25
20
15
10
5
0-3 -2 -1 0 1 2 3
NI411 keV
0 5 10 15 20 25 30-3
-2
-1
0
1
2
3
NI 34
4 ke
V
Are the data correlated?
Some other cases:
Are the data correlated?
AreaF P
- Efficiency Area - Peak area F - Factor
•Activity•Normalization Constant•Reference area
P - Emission probability Usually:
• Area, F and P are independent• Area is uncorrelated• P are correlated for a multi gamma source, but their correlation coefficients are generally unknown
Efficiency
Efficiency Calibration
0
ln lniN
ii b
Ea
E
Eg – Gamma Energy
Eb – Reference Energy
Typical efficiency curve
For energies above 150-200 keV
Efficiency Calibration
1
2
ln
ln
ln n
Y
0 1ln ln ba a E E
Using a Matrix notation:
For example:
1
2
1 ln
1 ln
1 ln
b
b
n b
E E
E EX
E E
0
1
ap
a
Y X p
Efficiency Calibration
Fitting Procedure
11 1ˆ T Tp X V X X V Y
Problem: How to obtain V?
Variance in YWhat is V?due to: peak area, factor and emission probability
11ˆ
TpV X V X
Y Area Y F Y PV V V V
PF
AreaY lnln
Efficiency Calibration
Variance in Y due to Area: VY-Area
,
ln iArea i j
j i
AreaDArea F P
1
2
1 0 0
10 0
10 0n
Area
AreaD
Area
1
2
2
2
2
0 0
0 0
10 0n
Area
Area
Area
Area
V
TY Area Area Area AreaV D V D
1
2
2
1
2
2
2
0 0
0 0
0 0 n
Area
Area
Y Area
Area
n
Area
V Area
Area
Efficiency Calibration
Variance in Y due to F: VY-F
,
ln iF i j
i
AreaDF F P
1 1 1
1 1 1
1 1 1
F F F
D F F F
F F F
2F FV
TY F F F FV D V D
2 2 2
2 2 2
2 2 2
F F F
F F F
Y F
F F F
F F F
V F F F
F F F
Efficiency Calibration
Variance in Y due to P: VY-P
,
ln iP i j
j i
AreaDP F P
1
2
1 0 0
10 0
10 0
P
n
P
PD
P
1
2
n
2
1 2 1 n
2
2 1 2 n
2
n 1 n 2
cov , cov ,
cov , cov ,
cov , cov ,
P
PP
P
P P P P
P P P PV
P P P P
TY P P P PV D V D
1
2
n
2 1 2 1 n
1 1 2 1 n
2 2 1 2 n
2 1 2 2 n
2 n 1 n 2
n 1 n 2 n
cov , cov ,
cov , cov ,
cov , cov ,
P
P
Y P
P
P P P P
P P P P P
P P P PV P P P P P
P P P P
P P P P P
P
Efficiency Calibration
Fitting Procedure
11 1ˆ T Tp X V X X V Y
11ˆ
TpV X V X
Quality of the fitting: adjT
adj YYVYY 12
Interpolation:pXY
intint ˆT
pY intintintXVXV ˆ
Example
Typical efficiency calibration
• 1 multi gamma-ray source - 152Eu(partially know covariance)
• 2 105 Bq Activity• 20 cm source-detector distance• 2 h of measurement (live time)
Pile-up rejection and dead time correction
0
ln lniN
ii b
Ea
E
REF
AreaArea P
Relative efficiency
Example
Efficiency curve
Example
Calibration Data Energy I Correlation Matrix(keV) 344 411 778 1089 1299344 0,26689(13) 1 0,10 0,32 0,15 -0,07411 0,02229(3) 0,10 1 0,31 0,72 -0,08779 0,1303(8) 0,32 0,31 1 0,45 -0,20
P and correctionsdependents of the decay parameters
N
iif
0 1
1
0
1j
iij
Decay parameters
Decay Scheme
13
13301 1
fP
Constraints
13
13133
01
1330101 11
EffEFA total
Probability& area
Conclusion
• The emission probabilities of a multi gamma source are correlated
• The emission probabilities and efficiencies are dependents.
• Should use branching ratios and feeding fractions instead of gamma intensities.
References
• Ruy M. Castro , Vito R. Vanin , Otaviano Helene , Paulo R. Pascholati , Nora L. Maidana , Mauro S. Dias and Marina F. Koskinas, The Interplay Between the Statistical Correlations of -ray Emission Probabilities and Efficiency Calibration, Applied Radiation and Isotopes 60 (2004) 185-190http://dx.doi.org/10.1016/j.apradiso.2003.11.014
• Vito R. Vanin and Otaviano Helene, Covariance Analysis Within the Framework of the Least-squares Method in Update of X Ray and Gamma Ray Data Standards for Detector Calibration and Other applications, International Atomic Energy Agency, Viena (2007)