IWM-EC International Conference on Multi facets of EoS and Clustering

Use of a machine learning algorithm to reduce the global computational time for a Bayesian analysis based on the AMD model

May 28, 2026, 10:40 AM

25m

Sala Blu (Il Fuligno (Firenze, Italy))

Oral contribution Nuclear EOS and multi-messenger astronomy

Speaker

Silvia Piantelli (Istituto Nazionale di Fisica Nucleare)

Description

A Bayesian analysis aimed at tuning two parameters of the AMD model related to the dynamical cluster formation and the in-medium nucleon-nucleon cross section was performed. The adopted technique required to produce a huge number of time-consuming simulations varying the relevant model parameters. A very preliminary attempt at making the parameter grid more rarefied in order to reduce the global calculation time for the simulation production for the Bayesian analysis by means of a machine learning algorithm is presented.

Presentation materials

amd2026.pdf