Tootfinder

Comparing the Performance of MC/DC's on-GPU Event-based Processing Methods in Multigroup and Continuous-energy Problems
Braxton Cuneo, Joanna Piper Morgan, Ilham Variansyah, Kyle E. Niemeyer
https://arxiv.org/abs/2506.00263

Comparing the Performance of MC/DC's on-GPU Event-based Processing Methods in Multigroup and Continuous-energy Problems
Monte Carlo / Dynamic Code (MC/DC) is a portable Monte Carlo neutron transport package for rapid numerical methods exploration in heterogeneous and HPC contexts, developed under the auspices of the Center for Exascale Monte Carlo Neutron Transport (CEMeNT). To support execution on GPUs, MC/DC delegates resource and execution management to Harmonize (another CEMeNT software project). In this paper, we describe and compare the performance of the two methods that Harmonize currently provides: a st…

"Woodside boss says young people ‘ideological’ on fossil fuels while ‘happily ordering from Temu’"
#FossilFuels #Climate #ClimateChange

No shit, Sherlock.
https://www.aljazeera.com/news/liveblog/2025/6/24/live-trump-announces-ceasefire-no-confirmation-from-israel-iran?update=3797073

Reconfigurable Intelligent Surfaces for 6G and Beyond: A Comprehensive Survey from Theory to Deployment
Prasetyo Putranto, Anis Amazigh Hamza, Sameh Mabrouki, Nasrullah Armi, Iyad Dayoub
https://arxiv.org/abs/2506.19526

Reconfigurable Intelligent Surfaces for 6G and Beyond: A Comprehensive Survey from Theory to Deployment
As the wireless research community moves toward shaping the vision of sixth-generation (6G) networks, reconfigurable intelligent surfaces (RIS) have emerged as a promising technology for controlling the propagation environment. Although RIS has not yet been standardized, its versatile applications and enabling capabilities have attracted growing attention in both academia and industry. This survey presents a comprehensive review of RIS technology spanning theoretical foundations, design aspects…

Engineering and harnessing long-range interactions for atomic quantum simulators
Arg\"uello-Luengo Javier
https://arxiv.org/abs/2506.07250 https://

Engineering and harnessing long-range interactions for atomic quantum simulators
Interactions between quantum particles, such as electrons, are the source of important effects, ranging from superconductivity, to the formation of molecular bonds, or the stability of elementary compounds at high-energies. In this article, we illustrate how advances in the cold-atom community to further engineer such long-range interactions have stimulated the simulation of new regimes of these fundamental many-body problems. The goal is two-fold: first, to provide a comprehensive review of th…

Graph Neural Networks in Modern AI-aided Drug Discovery
Odin Zhang, Haitao Lin, Xujun Zhang, Xiaorui Wang, Zhenxing Wu, Qing Ye, Weibo Zhao, Jike Wang, Kejun Ying, Yu Kang, Chang-yu Hsieh, Tingjun Hou
https://arxiv.org/abs/2506.06915

Graph Neural Networks in Modern AI-aided Drug Discovery
Graph neural networks (GNNs), as topology/structure-aware models within deep learning, have emerged as powerful tools for AI-aided drug discovery (AIDD). By directly operating on molecular graphs, GNNs offer an intuitive and expressive framework for learning the complex topological and geometric features of drug-like molecules, cementing their role in modern molecular modeling. This review provides a comprehensive overview of the methodological foundations and representative applications of GNN…