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Characterization of reactor fuel burn-up from antineutrino spectral distortions

ANGRA Neutrinos Project. Characterization of reactor fuel burn-up from antineutrino spectral distortions. E. Kemp, L.F. G. Gonzalez, T.J.C. Bezerra and B. Miguez for the ANGRA Collaboration State University of Campinas - UNICAMP Physics Institute- Cosmic Rays Department. So/Si.

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Characterization of reactor fuel burn-up from antineutrino spectral distortions

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  1. ANGRA Neutrinos Project Characterization of reactor fuel burn-up from antineutrino spectral distortions E. Kemp, L.F. G. Gonzalez, T.J.C. Bezerra and B. Miguezfor the ANGRA Collaboration State University of Campinas - UNICAMPPhysics Institute- Cosmic Rays Department

  2. So/Si

  3. Neutrino Spectra Parametrization: • Precision spectroscopy with reactor anti-neutrinos.Patrick Huber, Thomas Schwetz , hep-ph/0407026

  4. Simulation Steps Isotope Selection Energy draw from selected spectrum 1000 events Weighting by cross-section Static Fuel Energy resolution dE = k.E dE=0 Fitting routine to extract the isotope fraction Fuel evolution

  5. Fitting convergence study:239Pu fraction 239 Pu Fission contribution • Perfect energy resolution • Static Fuel • Assumed rate: 1000/day (Angra expectation) Events

  6. High Statistics (exposure) Needs • Shape comparison: Kolmogorov-Smirnov test • Neutrino spectrum: Composition from normalized Schreckemback’s spectra (235U, 239Pu and 241Pu)

  7. Spectral Distortion:expectations from burn-up • Taking the ratio between the spectra measured in the n-th month and the first one, we can observe the distortion induced by the burn-up

  8. Spectral Distortion:expectations from burn-up

  9. Nucifer Simulations:we are in good agreement Thanks to D. Lhuillier !

  10. The Spectral Ratio Fit: an example 6th Month after reactor starting

  11. Spectral Ratio Fit Red: linear fit Green: 95% C.L. bands

  12. The slope time dependence

  13. Is the slope of R(t) a good indicator for deviations from the expected behavior ? • Let’s assume a diversion of 1/3 of the reactor fuel during the 6th month

  14. Burnup: impact on the spectrum shape with 1/3 of the fuel replaced at half-cycle Fission fraction Day number

  15. Burnup: impact on the spectrum shape with 1/3 of the fuel replaced at half-cycle Fission fraction Day number

  16. The slope time dependence Is it an outlier?

  17. The slope time dependence Yes, with 75% C.L.

  18. Simulation Steps Isotope Selection Experimental Data (Shreckemback’s Spectra) Energy draw from selected spectrum Weighting by cross-section Static Fuel Repeat until Energy resolution dE = k.E Fuel evolution:Poisson-like time interval μ= f.Δt frequency f = f(D,M)D,M: detector distance and mass dE=0 Χ2 – KS tests Null hypothesis: No distortion

  19. Simulation Steps Isotope Selection Experimental Data (Shreckemback’s Spectra) Energy draw from selected spectrum Weighting by cross-section Static Fuel Repeat until Energy resolution dE = k.E Fuel evolution:Poisson-like time interval μ= f.Δt frequency f = f(D,M)D,M: detector distance and mass dE=0 Χ2 – KS tests Null hypothesis: No distortion

  20. Simulation Steps Isotope Selection Experimental Data (Shreckemback’s Spectra) Energy draw from selected spectrum Weighting by cross-section Static Fuel Repeat until Energy resolution dE = k.E Fuel evolution:Poisson-like time interval μ= f.Δt frequency f = f(D,M)D,M: detector distance and mass dE=0 Χ2 – KS tests Null hypothesis: No distortion

  21. Hypothesis Tests Results

  22. Chi^2 vs. KS • Chi^2 (is more optimistic…) • More Type II Errors • KS test • More Type I Errors • See T.J.C. Bezerra, B. Miguez and R.M.Almeida works (poster session) for detailed numbers and generalities on this (including oscillation studies)

  23. Chi^2 vs. KS • Is it possible to profit the better from both of the tests? • Fisher’s method: • Combination of N different results (p-values) of independent statistical tests resulting in a Chi^2 like quantity with 2K degrees of freedom Next step for this study…

  24. Conclusions • Isotopic composition measurements by shape analysis only requires a large number of events • Reduce the time integration: • Large time intervals degrades information • High exposure: source luminosity + detector mass+ time • Recognition of fuel diversion is possible by observing UNEXPECTED spectral distortions (but, how much?) • Required Improvements: • More sophisticated analysis methods to quote the sensitivity in mass of the recognition method • Combining information: • Shape + Counting Rates • different statistical methods working together • Fisher’s method • PCA, LDA: decomposition of a mixed signal (?)

  25. Thank you !

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