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Neural Particle Automata: Extending Self-Organizing Neural Networks to Particle Systems

Self-organizing particle systems driven by neural networks, where particles move and change state to grow morphologies and form texture patterns.

Insighttechnologysciencemachine learning

selforg-npa.github.io·Hacker News: Front Page·25d ago·2 min read

Tensor network compression method for fluid dynamics data using matrix product states

High performance computers produce extreme-scale data sets that require sampling or compression if they are to be used to their full potential. Existing data compression techniques typically exploit features such as sparsity in the data, homogeneity in th

Insighttechnologyscience

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arxiv.org1mo ago

Machine Learning Reduces Computational Steps in Dynamical System Simulations

Newstechnologyscience

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physics.aps.org1mo ago

Quantum algorithm enables simulation of strongly nonlinear stochastic differential equations

Stochastic nonlinear dynamics underlie many models in engineering and computational physics, yet accurate high-dimensional simulation remains challenging. We present a quantum algorithm for a broad class of $N$-dimensional stochastic differential equation

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arxiv.org1mo ago

Quantum Signal Processing Enables Accurate PDE Solutions on IBMQ Hardware

Quantum algorithms offer new avenues for solving partial differential equations (PDEs). While the potential for end-to-end quantum advantage is at present not well understood, recent literature presents explicit circuit constructions for solving certain c

Newstechnologysciencequantum computing

iq.fp2.dev·Tech by Flipboard·1mo ago·2 min read

WebGPU-Based 2D Coulomb Gas Simulator: Visualizing Electron Interactions and Log-Gas Hamiltonian

Each dot represents an electron experiencing pairwise Coulomb repulsion with every other electron while being confined by an external potential $Q$. The energy of a configuration $z_1, \dots, z_n$ is given by the 2D log-gas Hamiltonian $$H(z_1

Insighttechnologysciencecomputational physicssimonhalvdansson.github.io·Hacker News: Front Page·5mo ago·2 min read

VortexNet: Neural Computing Using Fluid Dynamics Principles

VortexNet: Neural Computing through Fluid Dynamics - samim23/vortexnet

Codetechnologymachine learningprogramming

github.com·Hacker News: Front Page·8mo ago·3 min read

General Physics Transformer Achieves Foundation Model Capabilities for Multiple Physical Systems

Foundation models have revolutionized natural language processing through a ``train once, deploy anywhere'' paradigm, where a single pre-trained model adapts to countless downstream tasks without retraining. Access to a Physics Foundation Model (PFM) woul

Insighttechnologyscience

arxiv.org10mo ago