Non-asymptotic Heisenberg scaling: experimental metrology for a wide resources range
arXiv:2110.02908 · doi:10.1038/s41534-023-00691-y
Abstract
Adopting quantum resources for parameter estimation discloses the possibility to realize quantum sensors operating at a sensitivity beyond the standard quantum limit. Such approach promises to reach the fundamental Heisenberg scaling as a function of the employed resources in the estimation process. Although previous experiments demonstrated precision scaling approaching Heisenberg-limited performances, reaching such regime for a wide range of remains hard to accomplish. Here, we show a method which suitably allocates the available resources reaching Heisenberg scaling without any prior information on the parameter. We demonstrate experimentally such an advantage in measuring a rotation angle. We quantitatively verify Heisenberg scaling for a considerable range of by using single-photon states with high-order orbital angular momentum, achieving an error reduction greater than dB below the standard quantum limit. Such results can be applied to different scenarios, opening the way to the optimization of resources in quantum sensing.
References in corpus (13)
- Optical spin-to-orbital angular momentum conversion in inhomogeneous anisotropic media
- Beating the Standard Quantum Limit with Four Entangled Photons
- Entanglement-free Heisenberg-limited phase estimation
- Optimal Quantum Phase Estimation
- Efficient Toffoli Gates Using Qudits
- Quantum entanglement of angular momentum states with quantum numbers up to 10010
- Entanglement-enhanced measurement of a completely unknown phase
- Heisenberg-limited ground state energy estimation for early fault-tolerant quantum computers
- Distributed quantum phase estimation with entangled photons
- Photonic angular super-resolution using twisted N00N states
- Bayesian Quantum Multiphase Estimation Algorithm
- Experimental multiparameter quantum metrology in adaptive regime
- Beating the classical phase precision limit using a quantum neuromorphic platform
Cited by in corpus (8)
- Current Trends in Global Quantum Metrology
- Estimation of Hamiltonian parameters from thermal states
- Optimizing quantum-enhanced Bayesian multiparameter estimation of phase and noise in practical sensors
- Applications of model-aware reinforcement learning in Bayesian quantum metrology
- Model-aware reinforcement learning for high-performance Bayesian experimental design in quantum metrology
- Quantum-enhanced mean value estimation via adaptive measurement
- Photonic cellular automaton simulation of relativistic quantum fields: observation of Zitterbewegung
- Quantum multiphase estimation