Beyond the quantum limit

Think of an X-ray image: it is likely quite blurry and something only an expert physician can interpret properly. The contrast between different tissues is rather poor but could be improved by longer exposure times, higher intensity, or by taking several images and overlapping them. But there are considerable limitations: humans can safely be exposed to only so much radiation, and imaging takes time and resources.

A well-established rule of thumb is called standard quantum limit: the precision of the measurement varies inversely with the square root of available resources. In other words, the more resources you throw in – in our example, time, radiation power, number of images – the more accurate the measurement will be. But this will only get you so far: by that reasaning, extreme precision also means using excessive resources.

Pushing the envelope

Now, a pan-European team of researchers from Aalto University, ETH Zurich, and MIPT and Landau Institute in Moscow have pushed the envelope and come up with a way to measure magnetic fields using a quantum system – with accuracy beyond the standard quantum limit.

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 of using quantum-enhanced methods for sensor technology.

"We wanted to design a highly efficient but minimally invasive measurement technique," explained Sorin Paraoanu, leader of the Kvantti research group at Aalto University. "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."

The work to improve the accuracy of magnetic field measurements exploits the coherence of a superconducting artificial atom, known as a qubit. It is a tiny device made of overlapping strips of aluminium evaporated on a silicon chip – a technology similar to the one used to fabricate the processors of mobile phones and computers.

An artificial atom realised from superconducting strips of aluminium on a silicon chip can be employed for the detection of magnetic fields. Image: Babi Brasileiro / Aalto University (17)

When the device is cooled to a very low temperature, the electrical current flows in it without resistance. It then starts to display quantum mechanical properties similar to those of real atoms. When irradiated with a microwave pulse – not unlike the ones in household microwave ovens – the state of the artificial atom changes. It turns out that this change depends on the external magnetic field applied. Therefore, measure the atom and you will figure out the magnetic field.

Surpassing the standard

But to surpass the standard quantum limit, another trick had to be performed using a similar technique pattern recognition, a widely-applied branch of machine learning. "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," explains Andrey Lebedev, now at MIPT in Moscow.

Sensing of a magnetic field: probability distributions (shown in red and blue for two algorithms used in the work) narrow in consecutive steps of the algorithms, leading to the precise identification of the magnetic flux value. The green curve is the standard quantum limit distribution, and the background is the interference pattern characteristic of the device. Figure: Sergey Danilin and Sorin Paraoanu (with data from the research)

"This is a nice example of quantum technology at work: by combining a quantum phenomenon with a measurement technique based on supervised machine learning, we can enhance the sensitivity of magnetic field detectors to a realm that clearly breaks the standard quantum limit."

Reference:
S. Danilin, A.V. Lebedev, A. Vepsäläinen, G.B. Lesovik, G. Blatter, and G.S. Paraoanu, Quantum-enhanced magnetometry by phase estimation algorithms with a single artificial atom. npj Quantum Information (2018) 4: 29. doi: 10.1038/s41534-018-0078-y