abstract

We have measured reaction cross sections of neutron-rich \(^8\)Li nucleus on proton target at intermediate energies from 40.9 to 105.4 MeV/nucleon using the transmission method. Density distributions of \(^8\)Li are deduced by the use of the Glauber model to fit the experimental data. The matter and neutron radii converted from densities are consistent with other previous measurements. This work suggests that the measurement of the reaction cross section on the proton target can be a method to extract the neutron density distribution or neutron radius.

abstract

Recently, a machine learning approach to Monte-Carlo simulations called Neural Markov Chain Monte Carlo (NMCMC) is gaining traction. In its most popular form, it uses neural networks to construct normalizing flows which are then trained to approximate the desired target distribution. In this contribution, we present a new gradient estimator for the Stochastic Gradient Descent algorithm (and the corresponding PyTorch implementation) and show that it leads to better training results for the \(\phi ^4\) model. For this model, our estimator achieves the same precision in approximately half of the time needed in the standard approach and ultimately provides better estimates of the free energy. We attribute this effect to the lower variance of the new estimator. In contrary to the standard learning algorithm, our approach does not require estimation of the action gradient with respect to the fields, thus has the potential of further speeding up the training for models with more complicated actions.

abstract

The memory effect in electrodynamics, as discovered in 1981 by Staruszkiewicz, and also analysed later, consists of an adiabatic shift of the position of a test particle. The proposed ‘velocity kick’ memory effect, supposedly discovered recently, is in contradiction to these findings. We show that the ‘velocity kick’ memory is an artefact resulting from an unjustified interchange of limits. This example is a warning against drawing uncritical conclusions for spacetime fields, from their asymptotic behavior.

abstract

There exist several ways of expressing the difference \(E_{\mit \Omega }-E_{{\mit \Omega }_0}\) of the ground-state energies of the complete Hamiltonian \(H=H_0+V_\mathrm {int}\) and of its free part \(H_0\). Most of them can be used to generate systematic perturbative expansions of \(E_{\mit \Omega }\). In advanced applications to many-body quantum theory, the successive terms of these expansions are usually visualized in terms of diagrams (Goldstone diagrams, Feynman diagrams) and easily evaluated. Here, we recall these methods, discuss their foundations, and show how their working and their graphical representation can be simply introduced to the beginners on the harmonic oscillator example. In doing this, we will also clarify a delicate point in computing the corrections using the Goldstone diagrams which is somewhat misleadingly presented in textbooks like the one of Fetter and Walecka.