Extracting information quickly from quantum states is necessary for future quantum technologies, processors and super-sensitive detectors in existing technologies.
Researchers from Aalto University, Finland, ETH Zurich, Switzerland, and MIPT and Landau Institute, Moscow, have developed a way to measure magnetic fields using quantum technologies. They have demonstrated a new method that combines quantum phenomena and machine learning to realise a magnetometer with accuracy beyond the standard quantum limit.
There are currently limits to how we can measure things. A well-established rule is the so-called standard quantum limit: the precision of the measurement scales inversely with the square root of available resources.
The more resources – time, radiation power, number of images, etc. – you have access to, the more accurate your measurement will be. This will, however, only get you so far: extreme precision also means using excessive resources.
Detecting a magnetic force
The detection of magnetic fields is important in a variety of fields, from geological prospecting to imaging brain activity. The researchers believe that their work is a first step towards using quantum technologies for sensors.
Sorin Paraoanu, leader of the research group at Aalto University, said: “We wanted to design a highly efficient but minimally invasive measurement technique. Imagine, for example, extremely sensitive samples: we have to either use as low intensities as possible to observe the samples or push the measurement time to a minimum.”
According to Aalto University, the research shows how to improve the accuracy of magnetic field measurements by exploiting the coherence of a superconducting artificial atom, a qubit.
Using devices to detect a magnetic force
When the device is cooled to a very low temperature, the electrical current flows in without any resistance, it then starts to display quantum mechanical properties similar to those of real atoms. When irradiated with a microwave pulse, the state of the artificial atom changes. This change, however, depends on the external magnetic field applied.
Yet to surpass the standard quantum limit, the researchers had to use a technique similar to a widely-applied area of machine learning: pattern recognition.
Andrey Lebedev, corresponding author from ETH Zurich (now at MIPT), concluded: “We use an adaptive technique: first, we perform a measurement, and then, depending on the result, we let our pattern recognition algorithm decide how to change a control parameter in the next step in order to achieve the fastest estimation of the magnetic field.
“This is a nice example of quantum technology at work.”