Search Results for author: Witold Nazarewicz

Found 8 papers, 0 papers with code

Microscopic origin of reflection-asymmetric nuclear shapes

no code implementations11 Dec 2020 Mengzhi Chen, Tong Li, Jacek Dobaczewski, Witold Nazarewicz

Background: The presence of nuclear ground states with stable reflection-asymmetric shapes is supported by rich experimental evidence.

Nuclear Theory

Statistical aspects of nuclear mass models

no code implementations11 Feb 2020 Vojtech Kejzlar, Léo Neufcourt, Witold Nazarewicz, Paul-Gerhard Reinhard

We study the information content of nuclear masses from the perspective of global models of nuclear binding energies.

Quantified limits of the nuclear landscape

no code implementations16 Jan 2020 Léo Neufcourt, Yuchen Cao, Samuel A. Giuliani, Witold Nazarewicz, Erik Olsen, Oleg B. Tarasov

We use microscopic nuclear mass models and Bayesian methodology to provide quantified predictions of proton and neutron separation energies as well as Bayesian probabilities of existence throughout the nuclear landscape all the way to the particle drip lines.

Gaussian Processes

Beyond the proton drip line: Bayesian analysis of proton-emitting nuclei

no code implementations28 Oct 2019 Léo Neufcourt, Yuchen Cao, Samuel Giuliani, Witold Nazarewicz, Erik Olsen, Oleg B. Tarasov

With the help of Bayesian methodology, we mix a family of nuclear mass models corrected with statistical emulators trained on the experimental mass measurements, in the proton-rich region of the nuclear chart.

Gaussian Processes

Neutron drip line in the Ca region from Bayesian model averaging

no code implementations22 Jan 2019 Léo Neufcourt, Yuchen Cao, Witold Nazarewicz, Erik Olsen, Frederi Viens

In particular, considering the current experimental information and current global mass models, we predict that $^{68}$Ca has an average posterior probability ${p_{ex}\approx76}$% to be bound to two-neutron emission while the nucleus $^{61}$Ca is likely to decay by emitting a neutron (${p_{ex}\approx 46}$ %).

Bayesian approach to model-based extrapolation of nuclear observables

no code implementations1 Jun 2018 Léo Neufcourt, Yuchen Cao, Witold Nazarewicz, Frederi Viens

The increase in the predictive power is quite astonishing: the resulting rms deviations from experiment on the testing dataset are similar to those of more phenomenological models.

Gaussian Processes

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