Magnetic field measurement is a critical component in many disciplines, including fundamental physics, space exploration, and medical biophysics. Accurate measurements of magnetic field are essential for understanding physical phenomena, navigating spacecraft, and conducting advanced medical diagnostics. Despite the development of advanced quantum magnetometers (quantum devices to measure magnetic field), enhancing their efficiency and resilience to noise has remained a persistent challenge.
We focused on employing symmetric graph states, a special type of entangled state represented by graphs, to improve the accuracy of quantum magnetometry. By modeling an ensemble of spin particles in a star-graph structure, we created a sensor that could measure Larmor frequencies—key indicators of magnetic fields—with unprecedented precision.
Our study showcases how graph states can significantly enhance measurement accuracy, even in the presence of noise. This breakthrough has the potential to revolutionize how we measure and understand magnetic fields in various environments.
One of the major challenges in quantum magnetometry is dealing with noise, which can distort measurements and reduce accuracy. We examined the performance of our method under both time-homogeneous  and time-inhomogeneous noises. Our findings revealed that the new method not only improved precision for single Larmor frequency measurements but also surpassed standard limits for multiple Larmor frequencies in both noise environments.
(left) A star-graph structure functions as a quantum sensor, exposed to an external field that induces noise. (right) A proposed measurement framework utilizes Helmholtz coils, driven by laser light and microwaves, with sensing data collected through fluorescence signals.
This is the first time we’ve observed such significant improvements under time-homogeneous noise. Our approach offers a new level of robustness, making it practical for real-world applications where noise is a major concern.
This breakthrough has far-reaching implications for a wide range of applications. In fundamental physics, it could lead to more accurate experiments and discoveries. In space exploration, improved magnetic field measurements can enhance navigation and data collection. In medical biophysics, more precise measurements can improve imaging techniques and diagnostic tools.
Our findings demonstrate the immense potential of graph state-based techniques to transform magnetic field measurements. We believe this advancement will drive further innovation and application in numerous fields.
The detailed findings of this research are published in Scientific Reports. The manuscript provides an in-depth analysis of the methodology, results, and implications of this groundbreaking study.