English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We present a Bayesian analysis of renormalization-group invariantnucleon-nucleon interactions at leading order in chiral effective field theory($\chi$EFT) with momentum cutoffs in the range 400--4000 MeV. We use historymatching to identify relevant regions in the parameter space of low-energyconstants (LECs) and subsequently infer the posterior probability density oftheir values using Markov chain Monte Carlo. All posteriors are conditioned onexperimental data for neutron-proton scattering observables and we estimate the$\chi$EFT truncation error in an uncorrelated limit. We do not detect anysignificant cutoff dependence in the posterior predictive distributions fortwo-nucleon observables. For all cutoff values we find a multimodal LECposterior with an insignificant mode harboring a bound $^1{S}_0$ state. The$^3P_0$ and $^3P_2$ phase shifts emerging from the Bayesian analysis are lessconstrained and typically more repulsive compared to the results of a phaseshift optimization. We expect that our inference will impact predictions fornuclei. This work demonstrates how to perform inference in the presence oflimit-cycle-like behavior and spurious bound states, and lays the foundationfor a Bayesian analysis of renormalization-group invariant $\chi$EFTinteractions beyond leading order.

Bayesian Analysis of $\chi$EFT at Leading Order in a Modified Weinberg Power Counting Approach