Embedding experimental quantum states into high-distance codes enables exponential speedups in fault-tolerant shadow tomography and cubic observable estimation over unencoded adaptive strategies.
Ansatz-free learning of lindbladian dynamics in situ
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Ultimate precision bounds for multiparameter Markovian noise metrology show average variance scaling as Ω(1/(T R²)) with Heisenberg scaling in dissipative channels R when using entangled probes and high-rank signal correlations, attainable via rapid prepare-and-measure protocols.
A randomized algorithm detects dissipation of magnitude at least epsilon in unknown Lindbladian dynamics with optimal total evolution time O(epsilon^{-1}) under bounded strength and locality assumptions.
citing papers explorer
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Exponential speedups in fault-tolerant processing of quantum experiments
Embedding experimental quantum states into high-distance codes enables exponential speedups in fault-tolerant shadow tomography and cubic observable estimation over unencoded adaptive strategies.
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Precision Limits of Multiparameter Markovian-Noise Metrology
Ultimate precision bounds for multiparameter Markovian noise metrology show average variance scaling as Ω(1/(T R²)) with Heisenberg scaling in dissipative channels R when using entangled probes and high-rank signal correlations, attainable via rapid prepare-and-measure protocols.
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Optimal detection of dissipation in Lindbladian dynamics
A randomized algorithm detects dissipation of magnitude at least epsilon in unknown Lindbladian dynamics with optimal total evolution time O(epsilon^{-1}) under bounded strength and locality assumptions.