Vaibhav Chahar | Searcharxiv

arXiv2026

Probing Instanton Dynamics in the Pion Vector Form Factor with Wilson Flow

Instanton liquid model is believed to capture the main features of vacuum QCD dynamics. Recently, multiple predictions for hadron structure functions have been derived and compared with experimental measurements and lattice QCD calculations, finding a general agreement. In order to explore the precision of the instanton liquid model, one has to compare its predictions with non-perturbative simulations in a regime dominated by instanton dynamics. This has been performed for two gluon-sensitive observables: the gluon Green's function and the strong running coupling constant. In this contribution, we propose to study a fermionic observable, the pion electromagnetic form factor, for which instanton liquid model predictions have been discussed in Phys.Rev.D 109, 074029. We use the Wilson flow to single out the dominant contribution from the instantons out of a lattice QCD configuration ensemble. We describe the details of our numerical setup, and some first, preliminary results.

hep-lat↗

arXiv2025

Hierarchical autoregressive neural networks in three-dimensional statistical system

Autoregressive Neural Networks (ANN) have been recently proposed as a mechanism to improve the efficiency of Monte Carlo algorithms for several spin systems. The idea relies on the fact that the total probability of a configuration can be factorized into conditional probabilities of each spin, which in turn can be approximated by a neural network. Once trained, the ANNs can be used to sample configurations from the approximated probability distribution and to explicitly evaluate this probability for a given configuration. It has also been observed that such conditional probabilities give access to information-theoretic observables such as mutual information or entanglement entropy. In this paper, we describe the hierarchical autoregressive network (HAN) algorithm in three spatial dimensions and study its performance using the example of the Ising model. We compare HAN with three other autoregressive architectures and the classical Wolff cluster algorithm. Finally, we provide estimates of thermodynamic observables for the three-dimensional Ising model, such as entropy and free energy, in a range of temperatures across the phase transition.

cond-mat.stat-mech↗