We establish the ultimate precision limits for estimating a function of multiple Hamiltonian parameters in the presence of Markovian noise. By reducing multiparameter function estimation to an optimization over effective single-parameter embeddings, we derive tight bounds on the quantum Fisher information. We identify...
E. Abbasgholinejad, Lorcán O. Conlon, S. R. Muleady et al.· 0 citations
Open quantum systems can exhibit inherently mixed quantum orders, such as strong-to-weak spontaneous symmetry breaking (SW-SSB), which have no analogue in pure states. It is generally expected that a finite-depth local quantum channel cannot induce a phase transition to SW-SSB in one spatial dimension. We circumvent th...
Christopher Fechisin, Tsung-Cheng Lu, Zhi-Yuan Wei et al.· 0 citations
Hamiltonian learning provides a systematic framework for reconstructing unknown quantum dynamics. However, existing protocols typically assume direct measurement access to the entire system. With fast single-qubit control and a connected reference backbone, we show that a single measurable qubit suffices to learn all $...
Su-Ying Liu, Zi-Tai Xu, Alexey V. Gorshkov et al.· 0 citations
This work considers a qubit noise model where the probability of phase-flip errors is exponentially smaller (in qubit number) compared to the probability of bit-flip errors that occur with probability p, and demonstrates that Heisenberg scaling can be attained for times up to T\propto 1/p^{(N+1)/2} for a N-qubit repeti...
Lorcán O. Conlon, Yu-Xin Wang, E. Abbasgholinejad et al.· 1 citation
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