A platform for the next-generation of nuclear data evaluations


Bayesian Optimization • Version Control • Modularized with Containers • Python 3+


Matthew Mumpower

Theoretical Division

Mike Herman, Toshihiko Kawano, Amy Lovell, Ionel Stetcu,
Patrick Talou

Los Alamos National Laboratory Caveat

The submitted materials have been authored by an employee or employees of Triad National Security, LLC (Triad) under contract with the U.S. Department of Energy/National Nuclear Security Administration (DOE/NNSA).

Accordingly, the U.S. Government retains an irrevocable, nonexclusive, royaltyfree license to publish, translate, reproduce, use, or dispose of the published form of the work and to authorize others to do the same for U.S. Government purposes.

Example evaluation workflow

Our current workflow combines many distinct codes and data

The problem: we need to integrate all of these interrelated parts together

NEXUS provides

code structures and marshalling that allow theory, data and evaluation to seemlessly communicate

Pu suite evaluation

Focus on consistency in evaluating all reaction channels together

Figure: $^{239}$Pu(n,f) cross section. Regularization procedure maps model to experimental data (redblue)

Parsed ENDF, EXFOR, ran reaction model, optimized model parameters all with less than 50 lines of Python3 code!

Evaluation effort now capable of utilizing HPC machines; combination of CPU / GPU based emulators

What's new?

Focus on consistency throughout evaluation

Figure: Bayesian opt. of optical model parameters with the NEXUS code

New Data

New ChiNu data for Pompt Fission Neutron Spectrum (PFNS)

TPC data for fission cross section (in coordination with IAEA)

New Theory (model improvements)

Evaluate prompt-nu and FPY in a consistent way with the PFNS evaluation [CGMF / BeoH]

Include prompt fission $\gamma$-rays (PFGS) [BeoH]

New inelastic scattering model using the Engelbrecht-Weidenmuller transformation [CoH]