pith:XL4BQDF2
Spectral Flattening Is All Muon Needs: How Orthogonalization Controls Learning Rate and Convergence
Muon orthogonalizes its momentum buffer to flatten the gradient spectrum, allowing stable learning rates scaled to the average singular value rather than the largest.
arxiv:2605.13079 v1 · 2026-05-13 · cs.LG · cs.AI
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Claims
We prove that Muon's maximal stable step size scales with the average singular value of the gradient rather than the largest, which bottlenecks standard gradient descent.
The improvement in effective convergence factor is shown under a Kronecker-factored curvature model for the loss landscape.
Muon achieves faster convergence and larger stable learning rates by flattening the singular value spectrum of the momentum buffer through orthogonalization, scaling step size with average rather than maximum singular values.
References
Receipt and verification
| First computed | 2026-05-18T03:08:58.726066Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
baf8180cbaaf4354eb6fa5f78621d8da28d3455fd710fefd1cd6db22c9a8caae
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/XL4BQDF2V5BVJ23PUX3YMIOY3I \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: baf8180cbaaf4354eb6fa5f78621d8da28d3455fd710fefd1cd6db22c9a8caae
Canonical record JSON
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