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This research establishes a geometric framework for designing optimal probe states in distributed multiparameter quantum sensing, addressing the complexity where single-parameter optimality fails to generalize. By utilizing minimal enclosing balls and ellipsoids of generator eigenvalue vectors, the study provides a systematic method to maximize total quantum Fisher information and minimize weighted covariance. These findings offer a rigorous mathematical approach for advancing precision limits in multi-parameter quantum metrology architectures.
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Geometric construction of optimal probe states in distributed multiparameter quantum sensing

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2609.26608v1 Announce Type: new Abstract: The choice of probe state is essential to achieving ultimate precision in quantum metrology. For a single parameter, an equal superposition of eigenstates associated with the largest and smallest generator eigenvalues is optimal. This simple construction does not directly extend to multiple parameters, since different parameters can favor different probes. We address this difficulty through a geometric construction of optimal probes for multiparameter estimation in distributed quantum sensing. In this setting, the generators commute and share a common eigenbasis, so each common eigenstate defines a vector of generator eigenvalues. We show that the minimal enclosing balls and ellipsoids of these vectors determine the maximal total quantum Fisher information and the minimum weighted covariance, respectively. In both cases, the boundary of the convex body identifies the common eigenstates that can contribute to an optimal probe, and its center and shape specify the conditions that their populations must satisfy. Our results provide a systematic approach to designing optimal probe states, linking the structure of the parameter generators directly to the attainable precision in multiparameter quantum metrology.

Abstract:The choice of probe state is essential to achieving ultimate precision in quantum metrology. For a single parameter, an equal superposition of eigenstates associated with the largest and smallest generator eigenvalues is optimal. This simple construction does not directly extend to multiple parameters, since different parameters can favor different probes. We address this difficulty through a geometric construction of optimal probes for multiparameter estimation in distributed quantum sensing. In this setting, the generators commute and share a common eigenbasis, so each common eigenstate defines a vector of generator eigenvalues. We show that the minimal enclosing balls and ellipsoids of these vectors determine the maximal total quantum Fisher information and the minimum weighted covariance, respectively. In both cases, the boundary of the convex body identifies the common eigenstates that can contribute to an optimal probe, and its center and shape specify the conditions that their populations must satisfy. Our results provide a systematic approach to designing optimal probe states, linking the structure of the parameter generators directly to the attainable precision in multiparameter quantum metrology.

arXiv:2609.26608 [quant-ph]

(or arXiv:2609.26608v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2609.26608 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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