English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Quantum metrology exploits quantum resources and strategies to improvemeasurement precision of unknown parameters. One crucial issue is how toprepare a quantum entangled state suitable for high-precision measurementbeyond the standard quantum limit. Here, we propose a scheme to find optimalpulse sequence to accelerate the one-axis twisting dynamics for entanglementgeneration with the aid of deep reinforcement learning (DRL). We consider thepulse train as a sequence of $\pi/2$ pulses along one axis or two orthogonalaxes, and the operation is determined by maximizing the quantum Fisherinformation using DRL. Within a limited evolution time, the ultimate precisionbounds of the prepared entangled states follow the Heisenberg-limited scalings.These states can also be used as the input states for Ramsey interferometry andthe final measurement precisions still follow the Heisenberg-limited scalings.While the pulse train along only one axis is more simple and efficient, thescheme using pulse sequence along two orthogonal axes show better robustnessagainst atom number deviation. Our protocol with DRL is efficient and easy tobe implemented in state-of-the-art experiments.

Efficient and Robust Entanglement Generation with Deep Reinforcement Learning for Quantum Metrology