相关论文: Gaussian Process Model for Extrapolation of Scatte…

We show that a Gaussian Process model can be combined with a small number (of order 100) of scattering calculations to provide a multi-dimensional dependence of scattering observables on the experimentally controllable parameters such as…

The predictive capability of a plasma discharge model depends on accurate representations of electron-impact collision cross sections, which determine the key reaction rates and transport properties of the plasma. Although many cross…

Within a Bayesian statistical framework using a Gaussian Process emulator for an isospin-dependent Boltzmann-Uehling-Uhlenbeck (IBUU) transport model simulator of heavy-ion reactions at intermediate energies, we infer from the HADES proton…

Recent work has provided the means to rigorously determine properties of super-hadronic matter from experimental data through the application of broad scale modeling of high-energy nuclear collisions within a Bayesian framework. These…

For applications in chemistry and physics, machine learning (ML) is generally used to solve one of three problems: interpolation, classification or clustering. These problems use information about physical systems in a certain range of…

We apply the Bayesian model selection method (based on the Bayes factor) to optimize $\sqrt{s_\mathrm{NN}}$-dependence in the phenomenological parameters of the (3+1)-dimensional hybrid framework for describing relativistic heavy-ion…

We show that density models describing multiple observables with (i) hard boundaries and (ii) dependence on external parameters may be created using an auto-regressive Gaussian mixture model. The model is designed to capture how observable…

We present a treatment of cold hydrogen-antihydrogen collisions based on the asymptotic properties of atom-antiatom interactions. We derive general formulas for the elastic and inelastic cross sections and for the scattering lengths and…

Being able to rigorously quantify the uncertainties in reaction models is crucial to moving this field forward. Even though Bayesian methods are becoming increasingly popular in nuclear theory, they are yet to be implemented and applied in…

We present a machine-learning method for predicting sharp transitions in a Hamiltonian phase diagram by extrapolating the properties of quantum systems. The method is based on Gaussian Process regression with a combination of kernels chosen…

In a previous work, we studied the momentum fraction and hard--scale dependence of double parton scattering (DPS) in proton--proton collisions and the resulting dependence of the effective cross section on the final--state observables. In…

We revisit the Glauber model to study the heavy ion reaction cross sections and elastic scattering angular distributions at low and intermediate energies. The Glauber model takes nucleon-nucleon cross sections and nuclear densities as…

We perform a comprehensive Bayesian analyses of Au + Au collision data at 1.23 GeV/nucleon using an isospin-dependent Boltzmann-Uehling-Uhlenbeck transport model that incorporates a momentum-dependent mean field and medium-modified…

Accurate prediction of fragmentation cross sections is essential for rare-isotope beam production, planning new-isotope searches, and designing experiments to study the most exotic regions of the nuclear chart. However, existing reaction…

In light of its ubiquitous presence in the interstellar gas, the chemistry and reactivity of the HCO+ ion requires special attention. The availability of up-to-date collisional data between this ion and the most abundant perturbing species…

Currently, quantum scattering calculations cannot be used for quantitative predictions of molecular scattering observables at ultralow temperatures. This is a result of two problems: the extreme sensitivity of the scattering observables to…

Bayesian parameter estimation provides a systematic approach to compare heavy ion collision models with measurements, leading to constraints on the properties of nuclear matter with proper accounting of experimental and theoretical…

Theoretical study of systematics of neutron scattering cross sections on various materials for neutron energies up to several hundred MeV are of practical importance. In this paper, we analysed various cross sections of neutron-nucleus…

We present a model-independent method to reconstruct the impact parameter distributions of experimental data for intermediate energy heavy ion collisions, adapted from a recently proposed approach for ultra-relativistic heavy ion…

The hypothesis of the multi peripheral model is extended to the hadron-nucleus interactions and then generalized to the nucleus-nucleus case. The processing of the model depends on input parameters that are extracted from the features of…