相关论文: Two-step nuclear reactions: The Surrogate Method, …

Nucleon-nucleon (NN) cross sections are evaluated in neutron-rich matter using a scaling model according to nucleon effective masses. It is found that the in-medium NN cross sections are not only reduced but also have a different isospin…

We present a graph neural network (GNN) based surrogate framework for molecular dynamics simulations that directly predicts atomic displacements and learns the underlying evolution operator of an atomistic system. Unlike conventional…

Neutrino event generators make use of intranuclear cascade models (INCs), to predict the kinematics of hadrons produced in neutrino-nucleus interactions. We perform a consistent comparison of different INCs, by using the same set of events…

Nuclear structure at short $NN$-distances is still poorly understood. In particular, the full quantum structure of the nucleus with a correlated $NN$-pair is a challenge to theory. So far, model descriptions have been limited to the average…

Energy integrated neutrino cross sections are integrals of nuclear responses weighted with kinematic prefactors. We decompose the prefactors into a limited set of functions of energy transfer and show the relevant integrals are the moments…

Indirect methods using nucleus-nucleus reactions at high energies (here, high energies mean $\sim$ 50 MeV/nucleon and higher) are now routinely used to extract information of interest for nuclear astrophysics. This is of extreme relevance…

A Theory-guided Auto-Encoder (TgAE) framework is proposed for surrogate construction and is further used for uncertainty quantification and inverse modeling tasks. The framework is built based on the Auto-Encoder (or Encoder-Decoder)…

Time-dependent Hartree-Fock approach in three dimensions is employed to study the multi-nucleon transfer reaction $^{132}$Sn + $^{208}$Pb at various incident energies above the Coulomb barrier. Probabilities for different transfer channels…

Background: Eclipse effect of the neutron and proton in a deuteron target is essential to correctly describe high-energy deuteron scattering. The nucleus-deuteron scattering needs information not only on the nucleus-proton but also the…

We present the incorporation of a surrogate Gaussian Process Regression (GPR) atomistic model to greatly accelerate the rate of convergence of classical Nudged Elastic Band (NEB) calculations. In our surrogate model approach, the cost of…

Experimental studies of one nucleon knockout from magic nuclei suggest that their nucleon orbits are not fully occupied. This conflicts a commonly accepted view of the shell closure associated with such nuclei. The conflict can be…

A general analytical expression for the double differential cross section of inclusive deuteron stripping reaction on nuclei at intermediate energies of incident particles was obtained in the diffraction approximation. Nucleon-nucleus…

Neutron capture cross sections are one of the most important nuclear inputs to models of stellar nucleosynthesis of the elements heavier than iron. The activation technique and the time-of-flight method are mostly used to determine the…

We analyze quantitatively the interplay between explicit and implicit renormalization in Nuclear Physics. By explicit renormalization we mean to integrate out higher energy modes below a given cutoff scale using the similarity…

In the last years, reinforcement learning received a lot of attention. One method to solve reinforcement learning tasks is Neuroevolution, where neural networks are optimized by evolutionary algorithms. A disadvantage of Neuroevolution is…

This paper proposes a technique for training a neural network by minimizing a surrogate loss that approximates the target evaluation metric, which may be non-differentiable. The surrogate is learned via a deep embedding where the Euclidean…

An established way to improve the transferability of black-box evasion attacks is to craft the adversarial examples on an ensemble-based surrogate to increase diversity. We argue that transferability is fundamentally related to uncertainty.…

Bayesian inference provides a principled framework for probabilistic reasoning. If inference is performed in two steps, uncertainty propagation plays a crucial role in accounting for all sources of uncertainty and variability. This becomes…

Extensive elastic scattering data measured at energies around 10 to 20 MeV/nucleon for some identical systems, like 12C+12C and 16O+16O, exhibit the nuclear rainbow pattern of broad Airy oscillations of the cross section at medium and large…

Before we apply nonlinear techniques, for example those inspired by chaos theory, to dynamical phenomena occurring in nature, it is necessary to first ask if the use of such advanced techniques is justified "by the data". While many…