Geometric construction of optimal probe states in distributed multiparameter quantum sensing

@misc{chen2026geometric,
  title = {{Geometric construction of optimal probe states in distributed multiparameter quantum sensing}},
  author = {Hongzhen Chen and Lingna Wang and Haidong Yuan},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.26608},
  eprint = {2609.26608},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.26608},
}

TY  - UNPB
TI  - Geometric construction of optimal probe states in distributed multiparameter quantum sensing
AU  - Hongzhen Chen
AU  - Lingna Wang
AU  - Haidong Yuan
PY  - 2026
DA  - 2026/09/22
PB  - arXiv
DO  - 10.48550/arxiv.2609.26608
UR  - https://arxiv.org/abs/2609.26608
AB  - 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.
ER  -