Machine-learned, finite temperature Fermi-operator expansions suitable for GPUs and AI-hardware

arXiv:2605.08523 · quant-ph · Submitted 2026-05-08 · Read on arXiv

quant-ph

Submitted: 2026-05-08

Updated: 2026-09-22

Code: https://github.com/lanl/sedacs

Terminology

• Accuracy — 30× in this paper · explained in 1 episode
• Core — 17× in this paper · explained in 2 episodes
• Trace — 7× in this paper · explained in 2 episodes
• Activation Function — 6× in this paper · explained in 1 episode
• Generalization — 6× in this paper · explained in 13 episodes
• Density Functional Theory (DFT) — 2× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Gauge Freedom — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Symmetry Breaking — 1× in this paper · explained in 3 episodes

Sources

• Improvements to the Levenberg-Marquardt algorithm for nonlinear least-squares minimization
• Muon is Scalable for LLM Training
• Deep Residual Learning for Image Recognition

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