We present the latest release of PANNA 2.0 (Properties from Artificial Neural Network Architectures), a code for the generation of neural network interatomic potentials based on local atomic descriptors and multilayer perceptrons. Built on a new back end, this new release of PANNA features improved tools for customizing and monitoring network training, better GPU support including a fast descriptor calculator, new plugins for external codes and a new architecture for the inclusion of long-range electrostatic interactions through a variational charge equilibration scheme. We present an overview of the main features of the new code, and several benchmarks comparing the accuracy of PANNA models to the state of the art, on commonly used benchmarks as well as richer datasets.

翻译：我们发布了最新版本的PANNA 2.0（基于人工神经网络架构的物性计算程序），该程序基于局部原子描述符和多层感知器生成神经网络原子间势。新版本PANNA建立在全新后端架构之上，具备以下改进功能：训练过程定制与监控的增强工具、包含快速描述符计算器的GPU支持优化、外部代码新插件，以及通过变分电荷均衡方案纳入长程静电相互作用的新架构。本文概述了新代码的主要功能，并在常用基准测试及更丰富的数据集上，将PANNA模型的精度与当前最先进技术进行了多项基准对比。