pith:TALNI6PB
Circula-based multivariate distributions on the flat torus, with applications in structural biology
A low-rank latent variable model yields the first closed-form normalized distributions on the flat torus that carry explicit covariance structure.
arxiv:2605.12577 v1 · 2026-05-12 · stat.AP
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Claims
using a low rank covariance structure to define circulae based on a latent variable model, we design the first closed-form normalized distribution on the flat torus T^d--with covariance structure. ... we propose the first models for joint distributions of torsion angles (backbone and side-chains) for neighboring amino-acids in proteins.
That the low-rank covariance structure in the latent variable model adequately captures the true dependencies among torsion angles on the flat torus without significant loss of fidelity or introduction of artifacts for protein data.
Presents the first closed-form normalized distributions on the flat torus with covariance structure via circula and latent models, then applies them to model joint torsion angles in proteins with SOTA likelihood and sparsity.
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Receipt and verification
| First computed | 2026-05-18T03:10:01.600357Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
9816d479e1b67658b8b9499670e6d690d3ed2be5c0a86cdf498a91a38dffb175
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/TALNI6PBWZ3FROFZJGLHBZWWSD \
| 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: 9816d479e1b67658b8b9499670e6d690d3ed2be5c0a86cdf498a91a38dffb175
Canonical record JSON
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