Sharp transitions in low-number quantum dots Bayesian magnetometry

TL;DR

This paper investigates Bayesian magnetometry using a few-electron quantum dot system, revealing sudden transitions in optimal measurement strategies and highlighting the limited benefit of environmental memory effects at low magnetic fields.

Contribution

It uncovers abrupt changes in optimal states and measurements in quantum dot magnetometry and emphasizes the importance of occupation level measurements and entanglement.

Findings

Sudden transitions among optimal states and measurements.

Occupation level measurements are useful throughout the evolution.

Limited metrological advantage from memory effects at low magnetic fields.

Abstract

We consider Bayesian estimate of static magnetic field, characterized by a prior Gaussian probability distribution, in systems of a few electron quantum dot spins interacting with infinite temperature spin environment via hyperfine interaction. Sudden transitions among optimal states and measurements are observed. Usefulness of measuring occupation levels is shown for all times of the evolution, together with the role of entanglement in the optimal scenario. For low values of magnetic field, memory effects stemming from the interaction with environment provide limited metrological advantage.