Precision Limits of Multiparameter Markovian-Noise Metrology

Quantum Physics [Submitted on 15 Apr 2026] Precision Limits of Multiparameter Markovian-Noise Metrology Anthony J. Brady, Yu-Xin Wang, Luis Pedro García-Pintos, Alexey V. Gorshkov Measuring stochastic signals ("noise metrology") constitutes a central task in quantum sensing and the characterization of open quantum systems. Here we establish ultimate precision bounds for multiparameter estimation of stochastic signals encoded through Markovian Lindblad dynamics, allowing for arbitrary quantum control and noiseless ancillae. Although Markovianity enforces standard-quantum-limit scaling with sensing time T, our bounds reveal Heisenberg-type scaling in the number of dissipative channels, R: when the stochastic signal exhibits high-rank correlations across the R channels and the probe is entangled, the average variance (per parameter) scales no better than \Omega(1/(TR^2)). For collective k-body dissipation, R=\Theta(N^k), signifying super-Heisenberg scaling with the system size N. We further show that, when the unknown parameters enter through the dissipative eigenrates, a Rapid Prepare-and-Measure (RPM) protocol that tracks many distinct quantum jumps in parallel attains these limits. In this regime, the estimation problem reduces to a multi-Poisson counting model, providing a conceptually clean route to optimal quantum noise metrology. We illustrate the breadth of the framework with applications to networked noise metrology, collective many-body dissipation, learning Pauli noise, and subdiffraction quantum imaging. Comments: 39 pages (17 main text + 22 appendices). Comments and feedback are welcome Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2604.14298 [quant-ph]   (or arXiv:2604.14298v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2604.14298 Focus to learn more Submission history From: Anthony Brady PhD [view email] [v1] Wed, 15 Apr 2026 18:00:22 UTC (88 KB) Access Paper: HTML (experimental) view license Current browse context: quant-ph < prev   |   next > new | recent | 2026-04 References & Citations INSPIRE HEP NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)