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HI-MGN introduces a hierarchical multiscale graph neural network to improve long-range communication in mesh-based physics simulations, enhancing accuracy while reducing training time and memory usage compared to existing methods.
Eigendrum is a web tool that allows users to draw shapes and hear them as real drums by solving eigenvalue problems for drumhead vibrations using finite element methods.
MIT CSAIL and Tsinghua University researchers introduce GeoPT, a pre-training approach that uses synthetic dynamics to help AI models learn physics more efficiently for simulating real-world scenarios like vehicle safety and robot testing. It reaches peak performance twice as fast and trains on up to 60% less data.
This post discusses the use of SIMD to optimize collision detection for convex hulls in Box3D, particularly using wide SIMD and the Separating Axis Test to improve performance for hulls with many edges.
The Well is an open-source project providing 15TB of high-precision physics simulation results, which would normally cost millions of dollars and weeks on a supercomputer at a national lab, now 100% free and open source, making a huge impact on the scientific research field.
An interactive app that simulates the microscopic physics of a stylus tracing a vinyl groove, using realistic contact mechanics, noise sources, and tracing distortion, calibrated to real-world orders of magnitude.
SimWorlds is a multi-agent framework that generates dynamic, editable 4D scenes from natural language, using Blender-specific procedural knowledge and a planner-coder-reviewer workflow, outperforming prior baselines.
This article presents a detailed benchmark comparing ECS and OOP architectures in JavaScript for a 2D physics simulation, testing memory locality and performance across multiple dimensions including broad-phase algorithms and sorting strategies, with results on an M4 Mac.
A comparison of four AI models (Fable 5, Opus 4.8, GLM 5.2, GPT 5.5) on generating HTML5 canvas physics demos shows Fable 5 outperforms others in quality but costs significantly more per test.
NVIDIA research presents Generative Pretrained Controllers (GPC), a method to pretrain motor control using discrete tokens and transformer-based next-token prediction, enabling fine-tuning for new tasks. Trained on 600+ hours of motion, GPC runs in real-time physics simulation for interactive control.
PhysiFormer uses coordinate-space diffusion to generate physically-plausible 3D object motions without explicit inductive biases, enabling efficient multi-object reasoning and generalization to complex materials and geometries.
Introduces Neural Particle Automata, a method for learning self-organizing particle dynamics using smooth particle hydrodynamics perception, enabling particles to have local perception vectors for an update rule, analogous to Neural Cellular Automata but on continuous particle positions.
This article introduces Environments AI, a tool that generates and runs code for physics simulations, enabling easier creation of simulation environments.
Z.ai releases GLM-5.2, an open-weights AI model with improved coding and agentic performance, demonstrated by beating Kimi K2.7 Code on a physics simulation benchmark across three tasks.
AdaVoMP uses a sparse adaptive voxel structure and transformer encoder-decoder to predict spatially-varying mechanical properties for 3D objects, enabling high-resolution deformable simulations with improved accuracy and efficiency.
A new arena lets LLMs control physics ragdolls in weapon duels where users define weapon damage zones, vote blind, and models battle for Elo. Free models like Llama 3.3 and GPT-OSS compete, with self-hostable infrastructure.
Proposes the first application of split conformal prediction to neural operator-based physics simulation, providing distribution-free prediction intervals with finite-sample coverage guarantees and adaptive-width intervals using MC Dropout uncertainty.
PhyGenHOI is a novel framework that generates physically accurate 4D human-object interactions by coupling motion diffusion models with material point method simulations using 3D Gaussian representations.
A blog post tutorial explaining how to implement Navier-Stokes fluid simulation in the Godot game engine, including code and mathematical explanations for learning purposes.
An experiment feeding GPT-4o, Claude 3.5 Sonnet, and other models the same double pendulum prompt reveals they pick opposite angle conventions, causing immediate visible mismatch in a shared renderer. The convention split, non-random across model families, suggests a bias in training data distribution for classical mechanics problems.