Reshaping Metrology with Quantum Information Processing

Sisi Zhou examines how quantum information methods can improve the precision of physical measurements. Qubit examples distinguish noise that quantum error correction can suppress from noise indistinguishable from the signal. The discussion extends to several qubits, phase estimation, many-body measurements and distributed sensors. A second part applies quantum-learning tools, including tomography, certification and purification, to estimation of several parameters. Because incompatible observables prevent all parameters from being measured optimally together, designing measurements is difficult. The talk presents practical protocols for several such sensing tasks that combine efficient implementation with sensitivity close to the optimum.