pith:KRFMONNW
Machine Learning Approaches to Building Quantum Circuits for Sets of Matrices
Machine learning parameters directly produce a universal shortest quantum circuit for diagonal matrices of any size.
arxiv:2605.06633 v2 · 2026-05-07 · quant-ph · hep-th
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\usepackage{pith}
\pithnumber{KRFMONNWS4WSZCQ7WH6KRSP57D}
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Record completeness
Claims
By studying the parameters of the machine learning algorithm we were able to construct universal shortest analytic quantum algorithm for arbitrary diagonal matrix of any size.
That the parameters learned by the machine learning model directly translate into the shortest and truly universal analytic quantum circuit without additional unstated optimizations or assumptions about matrix structure.
Interpretable machine learning yields a universal shortest analytic quantum algorithm for arbitrary diagonal matrices of any size.
Receipt and verification
| First computed | 2026-05-21T01:04:27.004673Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
544ac735b6972d2c8a1fb1fca8c9fdf8d3d829403b5931f66bf0a4a159bfce94
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/KRFMONNWS4WSZCQ7WH6KRSP57D \
| 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: 544ac735b6972d2c8a1fb1fca8c9fdf8d3d829403b5931f66bf0a4a159bfce94
Canonical record JSON
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