• Corpus ID: 238531236

# Bayesian parameter estimation in $\chi$EFT using Hamiltonian Monte Carlo

@inproceedings{Svensson2021BayesianPE,
title={Bayesian parameter estimation in \$\chi\$EFT using Hamiltonian Monte Carlo},
author={Isak Svensson and Andreas Ekstrom and Christian Forss'en},
year={2021}
}
• Published 8 October 2021
• Physics
The number of low-energy constants (LECs) in chiral effective field theory (χEFT) grows rapidly with increasing chiral order, necessitating the use of Markov chain Monte Carlo techniques for sampling their posterior probability density function. For this we introduce a Hamiltonian Monte Carlo (HMC) algorithm and sample the LEC posterior up to next-to-next-to-leading order (NNLO) in the two-nucleon sector of χEFT. We find that the sampling efficiency of HMC is three to six times higher compared…

## References

SHOWING 1-8 OF 8 REFERENCES
Monte Carlo Methods in Statistical Mechanics: Foundations and New Algorithms
These notes are an updated version of lectures given at the Cours de Troisieme Cycle de la Physique en Suisse Romande (Lausanne, Switzerland) in June 1989. We thank the Troisieme Cycle de la Physique
Stan modeling language users guide and reference manual, version 2.26
• 2021
Bayesian data analysis, Texts in statistical science series
• 2014
Python 3 Reference Manual (CreateSpace
• 2009
Stan modeling language users guide and reference manual , version 2 . 26 , ” ( 2021 ) . [ 26 ] M . Betancourt , arXiv : 1701 . 02434 . [ 27 ] A . Griewank
• Acta Numer .
• 2003
Ins data analysis center: SAID
Optim . Method
• Softw . J . Mach . Learn . Res . Comm . App . Math . Com . Sc .
URL will be inserted by publisher] for posterior predictive distributions at LO, NLO, and NNLO for the nucleon-nucleon scattering cross sections in the Granada database