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Predicting nuclear masses by image reconstruction

Abstract : The differences between measured masses and Liquid Drop Model (LDM) predictions have well known regularities, which can be analyzed as a two-dimensional texture on the N-Z plane. The remaining microscopic effects, obtained after removing the smooth LDM mass contributions, have proved difficult to model. They contain all the information related to shell closures, nuclear deformation and the residual nuclear interactions, and display a well defined pattern. In the present work the more than 2000 known nuclear masses are studied as an array in the N-Z plane viewed through a mask, behind which the approximately 7000 unknown unstable nuclei that can exist between the proton and neutron drip lines are hidden. Employing a Fourier transform deconvolution method these masses can be predicted. Measured masses are reconstructed with and r.m.s. error of less than 100 keV. Potential applications of the present approach are outlined.
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Contributor : Michel Lion <>
Submitted on : Tuesday, April 3, 2007 - 9:42:12 AM
Last modification on : Thursday, February 1, 2018 - 1:35:48 AM




I. Morales, A. Frank, J.C. Lopez-Viera, J. Barea, J.G. Hirsch, et al.. Predicting nuclear masses by image reconstruction. International Conference on Frontiers of Nuclear Structure (Part II), Jun 2006, Shangai, China. pp.1855-1867, ⟨10.1142/S0218301306005228⟩. ⟨in2p3-00139679⟩



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