A Bayesian protocol identifies single- and two-source neutron configurations from spectra with greater than 4 sigma significance at event counts as low as 1000.
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Under hub-preferential node removal, networks can match a scale-free degree distribution by KL divergence yet fail finite-size scaling collapse, showing the two tests capture complementary aspects of structural degradation.
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Identifying Neutron Sources using Recoil and Time-of-Flight Spectroscopy
A Bayesian protocol identifies single- and two-source neutron configurations from spectra with greater than 4 sigma significance at event counts as low as 1000.
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Scale-freeness under node removal: a finite-size scaling perspective
Under hub-preferential node removal, networks can match a scale-free degree distribution by KL divergence yet fail finite-size scaling collapse, showing the two tests capture complementary aspects of structural degradation.