dorsal/arxiv
View SchemaDouble Markovity for quantum systems
| Authors | Masahito Hayashi, Jinpei Zhao |
|---|---|
| Categories | |
| ArXiv ID | 2601.09995vv1 |
| URL | https://arxiv.org/abs/2601.09995 |
| License | http://creativecommons.org/licenses/by/4.0/ |
Abstract
The subadditivity-doubling-rotation (SDR) technique is a powerful route to Gaussian optimality in classical information theory and relies on strict subadditivity and its equality-case analysis, where double Markovity is a standard tool. We establish quantum analogues of double Markovity. For tripartite states, we characterize the simultaneous Markov conditions A-B-C and A-C-B via compatible projective measurements on B and C that induce a common classical label J yielding A-J-(BC). For strictly positive four-party states, we show that A-(BD)-C and A-(CD)-B hold if and only if A-D-(BC) holds. These results remove a key bottleneck in extending SDR-type arguments to quantum systems.
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"date_created": "2026-02-17T05:53:24.105000Z",
"date_modified": "2026-02-17T05:53:24.105000Z",
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"abstract": "The subadditivity-doubling-rotation (SDR) technique is a powerful route to Gaussian optimality in classical information theory and relies on strict subadditivity and its equality-case analysis, where double Markovity is a standard tool. We establish quantum analogues of double Markovity. For tripartite states, we characterize the simultaneous Markov conditions A-B-C and A-C-B via compatible projective measurements on B and C that induce a common classical label J yielding A-J-(BC). For strictly positive four-party states, we show that A-(BD)-C and A-(CD)-B hold if and only if A-D-(BC) holds. These results remove a key bottleneck in extending SDR-type arguments to quantum systems.",
"arxiv_id": "2601.09995",
"authors": [
"Masahito Hayashi",
"Jinpei Zhao"
],
"categories": [
"quant-ph"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"title": "Double Markovity for quantum systems",
"url": "https://arxiv.org/abs/2601.09995",
"version": "v1"
},
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"source": {
"execution_id": "fb6c2866-0915-4faa-bdaa-289ac372157e",
"id": "arXiv Dataset",
"type": "Model",
"variant": "snapshot-2026-01-17",
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