pith:YLRDSPAB
Impact-Driven Quantum Decomposition for Traffic Zone Partitioning: A Hybrid Gate-Model Framework
Estimating energy impacts lets quantum processors handle key parts of traffic zone partitioning while classical methods coordinate the rest.
arxiv:2605.01127 v2 · 2026-05-01 · quant-ph · cs.ET
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\pithnumber{YLRDSPAB5HAQC5JCXL62TJH7BQ}
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Record completeness
Claims
Results show that impact-guided decomposition improves convergence behavior and produces more coherent spatial partitions relative to classical refinement, while remaining consistent with hardware constraints.
That the energy impact of decision variables can be estimated accurately enough to selectively assign quantum computation to influential subproblems while the classical coordination loop maintains global feasibility.
Impact-guided hybrid quantum decomposition for traffic zone partitioning improves convergence and spatial coherence over classical refinement but does not outperform direct quantum optimization on IBM hardware.
Receipt and verification
| First computed | 2026-05-20T00:04:33.464509Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
c2e2393c01e9c1017522bafda9a4ff0c19b555ded096b92186a11b8988c9889b
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/YLRDSPAB5HAQC5JCXL62TJH7BQ \
| 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: c2e2393c01e9c1017522bafda9a4ff0c19b555ded096b92186a11b8988c9889b
Canonical record JSON
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"license": "http://creativecommons.org/licenses/by-sa/4.0/",
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