aiqbench analysis
This research establishes precise entanglement trade-offs for qutrit stabilizer states, clarifying how specific optimization objectives influence residual entanglement distributions in composite-dimensional systems. By linking entropy-deficit metrics to code weight enumerators, the study provides rigorous analytical bounds that are critical for advancing error correction and resource management in higher-dimensional quantum architectures. These findings offer a foundational reference for researchers designing qutrit-based quantum circuits where maximal entanglement is not uniformly available.
Exact entanglement trade-offs in qutrit and composite-dimensional stabilizer states
arXiv:2605.05167v3 Announce Type: replace Abstract: When absolute maximal entanglement is unavailable in a state family, different objectives can select different distributions of residual entanglement. We determine exact trade-offs for qutrit stabilizer states and binary--ternary product states. For eight qutrits, evaluation of the complete published classification gives three nondominated balanced-cut entanglement profiles, characterized by the probabilities of obtaining three or four maximally entangled qutrit pairs. We relate the squared entropy-deficit objective to code weight enumerators and use a uniformity-forcing bound to prove that its eleven-qutrit minimum is six. The unique minimizing Clifford class is an already classified code, whose entropy profile also attains a sharp bound on average reference--erasure mutual information among four-uniform eleven-qutrit stabilizer states. In local dimension six, explicit sector alignments attain 56 maximally mixed four-party reductions, the maximum for arbitrary binary--ternary product states. Within the stabilizer product family, the exact cost--count Pareto boundary consists of $(44,48)$ and $(48,56)$. These results identify when aggregate optimization determines operational entanglement properties and when it does not. Published classifications supply coverage; analytical bounds, explicit witnesses, and independent arithmetic checks establish the stated consequences.
Abstract:When absolute maximal entanglement is unavailable in a state family, different objectives can select different distributions of residual entanglement. We determine exact trade-offs for qutrit stabilizer states and binary--ternary product states. For eight qutrits, evaluation of the complete published classification gives three nondominated balanced-cut entanglement profiles, characterized by the probabilities of obtaining three or four maximally entangled qutrit pairs. We relate the squared entropy-deficit objective to code weight enumerators and use a uniformity-forcing bound to prove that its eleven-qutrit minimum is six. The unique minimizing Clifford class is an already classified code, whose entropy profile also attains a sharp bound on average reference--erasure mutual information among four-uniform eleven-qutrit stabilizer states. In local dimension six, explicit sector alignments attain 56 maximally mixed four-party reductions, the maximum for arbitrary binary--ternary product states. Within the stabilizer product family, the exact cost--count Pareto boundary consists of $(44,48)$ and $(48,56)$. These results identify when aggregate optimization determines operational entanglement properties and when it does not. Published classifications supply coverage; analytical bounds, explicit witnesses, and independent arithmetic checks establish the stated consequences.
Substantially revised with new results and reproducibility materials. Title and author list updated
arXiv:2605.05167 [quant-ph]
(or arXiv:2605.05167v3 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2605.05167 Focus to learn more arXiv-issued DOI via DataCite
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Full text under the publisher's open licence · 278 words
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