arXiv (All)
open access
FLARE: Flow Matching with Local Axis-Angle Representations for Stochastic Micromagnetic Evolution
Long-horizon micromagnetic simulation remains expensive because conventional and learned solvers typically propagate Landau--Lifshitz--Gilbert (LLG) dynamics step by step. Existing learned approaches generally retain stepwise integration or model deterministic evolution, leaving full-field, direct-h
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Magnum.np.distributed: Accelerating Finite Difference Micromagnetic Simulations with Multiple GPUs#246525
- Super-Chandrasekhar white dwarfs by the evolution of magnetized main-sequence stars: New mass-limits from STARS simulation#1037120
- MAGNETIC TUNNEL JUNCTION-BASED STOCHASTIC HARDWARE FOR NEURAL AND ARTIFICIAL INTELLIGENCE SYSTEMS#254783
- Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems#10360
- Walk-on-Spheres Monte Carlo and deep neural network approximations of elliptic PDEs with drift and killing#441819
Record · ID 1119143
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive