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Issues on -Decay Total Absorption Spectroscopy

Issues on -Decay Total Absorption Spectroscopy. J.L. Tain Jose.Luis.Tain@ific.uv.es http://ific.uv.es/gamma/ Instituto de Física Corpuscular C.S.I.C - Univ. Valencia. IAEA Specialists Meeting Vienna, 12-14 December , 2005.

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Issues on -Decay Total Absorption Spectroscopy

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  1. Issues on -Decay Total Absorption Spectroscopy J.L. Tain Jose.Luis.Tain@ific.uv.es http://ific.uv.es/gamma/ Instituto de Física Corpuscular C.S.I.C - Univ. Valencia IAEA Specialists Meeting Vienna, 12-14 December, 2005

  2. Total absorption spectroscopy: how, why • How reliable are the results from TAS ? • -delayed neutron emission: a problem for TAS?

  3. -decay • Total absorption gamma-ray spectroscopy is the best technique to measure the -decay strength distribution over the entire energy window in particular for nuclei far from the stability. • Total absorption spectroscopy, using large 4 scintillation detectors, aims to detect the full -ray cascade rather than individual -rays as in high resolution spectroscopy, using Ge detectors. • Total absorption spectroscopy avoids the “Pandemonium effect” (misplacement of -strength) when constructing level schemes in high resolution spectroscopy.

  4. T P Efficiency The Pandemonium effect in 150Ho decay: CLUSTER-CUBE: 6 EUROBALL Clusters in cubic geometry CLUSTER: 7 Ge detectors, 60% each CLUSTER-CUBE at GSI

  5. How do we extract the -strength from the measured TAS spectra? • How reliable is the result? -decay Statement of the problem: Relation between -strength S and -intensity I: Relation between TAS data and the -intensity distribution: Rij: probability that for decay to level j we register a count in channeli Solution: f=R-1·d

  6. 3 2 1 0 The response matrix R can be constructed by recursive convolution: gjk: -response for j  k transition Rk: response for level k bjk: branching ratio for j  k transition • Problem: • number of levels 104-106 • also: spectrometer resolution • Solution: rebin the levels into E • New problems: • bjkcannot be rebinned • mismatch on energies Caution: convolution of discretized continuous distributions Problem:bjkare in general unknown Solution:bjk as externally introduced parameters ASUME VALIDITY & CHECK SYSTEMATICDEVIATIONS

  7. Monte Carlo simulation of TAGS -ray (and -ray,…) response GEANT3 and Geant4 simulations with detailed geometry, light production and PMT response NIM A430 (1999) 333 NIM A430 (1999) 488

  8. Problem: • statistical nature of the problem • numerical difficulties of the inversion • Solution: • reproduce the data in 2 or maximum-likelihood sense • use a priori information on the solution Solution of linear inverse problems: d = R · f is not f = R-1 · d ill-posed or ill-conditioned problems

  9. Solution of linear inverse problems: d = R · f • Linear Regularization (LR) method: • solution must be smooth: polynomial : Lagrange multiplier, B: regularization matrix, Vd: data covariance Algorithm: • Maximum Entropy (ME) method: • solution must maximize entropy S(f): entropy, Algorithm: • Expectation Maximization (EM) method: • modify knowledge on causes from effects Algorithm: NIM A, submitted

  10. Results of the EM algorithm

  11. Comparison of the three algorithms LINEAR REGULARIZATION MAXIMUM ENTROPY EXPECTATION-MAXIMIZATION • LR gives strong oscillations and negative values for low statistics • uncertainties for LR and ME depend on Lagrange multiplier • ME and EM give very similar results • differences in averaged and/or accumulated strengths are bellow few percent

  12. In the case of a real decay how much depends the solutionon: • approximations used in the construction of the response matrix? • the assumption on branching ratios? • Use the nuclear statistical model to define a realistic decay: • level density formula + Wigner fluctuations: nuclear levels • -ray strength functions + Porter-Thomas fluctuations: branching ratios • -strength function + Porter-Thomas fluctuations: feeding probability

  13. Average branching ratio matrix (based on statistical model parameters) Results: ME algorithm

  14. “Flat” branching ratio matrix Average branching ratio matrix LR, ME and EM algorithms

  15. : average b.r. : flat b.r. : reference strength

  16. The main source of systematic uncertainty in TAS are contamination/background signals • For decay-heat problems we want to measure the -strength of - decaying nuclei • To clean spectra from isobarcontamination at on-line separators we can use half-lifes, chemical selectivity or laser ionization • A particular challenge is the application of this technique at the neutron rich side, due to the beta delayed neutrons The beta-delayed neutrons and the subsequently emitted gamma-rays (may) become a contamination source

  17. n  NE213 moderator +3He count implantation Grand-daughter -rays are prompt with daughter -rays • Solution: “subtract” from data • Measure them with high resolution (Ge array + neutron-detector array) • Measure them with low resolution (TAS + neutron detector): MC simulations + test measurements planned

  18. Are the neutrons a problem ? • Neutrons interact through: • elastic scattering • inelastic scattering -rays • capture  -rays • Recoils with very low energies and -rays • Long interaction times (>s)  delayed signals Available MC codes do not treat properly the generation of secondaries in inelastic and capture processes  MC simulations

  19. -rays neutrons Pulse shape Rocinante (Surrey-Valencia) ~10 ns Inelastic & capture interaction time distribution BaF2 scintillator: • Direct neutron interaction: • pulse shape depends on particle • recoils have low energies ( Emax=4A/(A+1)2En ) • their light is quenched (~3-5) •  ETHR=100 keV  20 MeV n

  20. capture 0.5 % inelastic 30 % BaF2 scintillator: 19F 135Ba 136Ba 134Ba

  21. 638 63 1454 62

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