Myopic Entropy Scheduling for Ramsey Magnetometry

TL;DR

This paper introduces an entropy-based adaptive measurement strategy for quantum magnetic field sensing, improving efficiency and accuracy by reducing the number of measurements needed, demonstrated through simulations with nitrogen vacancy centers.

Contribution

The paper presents a novel entropy reduction technique for designing measurement sequences in quantum sensing, applicable to various quantum sensors and validated through simulation comparisons.

Findings

Improved sensing performance over existing methods

Reduced number of measurements for target accuracy

Analytical connection to established measurement strategies

Abstract

This paper presents an entropy based adaptive measurement sequence strategy for quantum sensing of magnetic fields. To physically ground our ideas we consider a sensor employing a nitrogen vacancy center in diamond, however our approach is applicable to other quantum sensor arrangements. The sensitivity and accuracy of these sensors typically rely on long sequences of rapidly occurring measurements. We introduce a new technique for designing these measurement sequences aimed at reducing the number of measurements required for a specified accuracy as measured by entropy, by selecting measurement parameters that optimally reduce entropy at each measurement. We compare, via simulation, the efficiency and sensitivity of our new method with several existing measurement sequence design strategies. Our results show quantifiable improvements in sensing performance. We also show analytically that our entropy reduction approach, reduces, under certain simplified conditions, to a well-known and widely used measurement strategy.