Accurate Sensing Technology: Using Qubits And Machine Learning

- Jun 07, 2019-

Recently, a research team composed of researchers from the Aalto University in Finland, the Swiss Federal Institute of Technology in Zurich, and the Moscow Institute of Physics and Technology in Russia challenged the limit and proposed a method for measuring magnetic fields using quantum systems. The accuracy exceeds the standard quantum limit. .


The accuracy with which we measure things is limited. In the case of an X-ray image, it is likely to be ambiguous and can only be properly interpreted by an expert physician. The contrast between different tissues is small, but can be improved by longer exposure times, higher illumination intensity, or by taking several images and superimposing them.

A well-established rule of thumb is the so-called "standard quantum limit": the accuracy of the measurement is inversely proportional to the square root of the available resources. In other words, the more resources you use (time, radiation power, number of images, etc.), the more accurate your measurements will be. However, this only allows your understanding to reach this level: extreme precision means using a lot of resources.


Recently, a research team composed of researchers from Aalto University in Finland, ETH Zurich, and the Moscow Institute of Physics and Technology (MIPT) challenged the limit and proposed a measurement using quantum systems. The method of magnetic field exceeds the standard quantum limit. Their paper was published in the prestigious magazine Npj Quantum Information.

qubits and machine learning


Sorin Paraoanu, leader of the Kvantti research group at Aalto University in Finland, said: “We want to design an efficient but minimally invasive measurement technique. For example, for extremely sensitive samples, we must either observe the lowest possible magnetic field strength. These samples either minimize the measurement time."

However, this paper describes how to use the coherence of superconducting artificial atoms (a qubit) to improve the accuracy of magnetic field measurements. It is a tiny device made up of overlapping aluminum strips evaporating on a silicon chip. This technology is similar to the technology used to make mobile phones and cell phone processors.

Artificial atoms released from the aluminum strip on the silicon chip can be used to detect magnetic fields

Artificial atoms released from the aluminum strip on the silicon chip can be used to detect magnetic fields

When the device is cooled to very low temperatures, the incredible thing happens: the flow of current in it is not blocked and begins to exhibit quantum mechanical properties similar to those of real atoms.

When irradiated with microwave pulses (different from microwaves in domestic microwave ovens), the state of the artificial atoms changes. The results show that this change depends on the externally applied magnetic field: by measuring the atom, you can calculate the magnetic field.

But in order to go beyond the standard quantum limit, another approach must be taken, that is, a technique similar to that of a widely used branch of machine learning: pattern recognition.

Andrey Lebedev, author of ETH Zurich, who works at MIPT, Moscow, Russia, said: "We have adopted an adaptive technique. First, we take measurements and then let our pattern recognition algorithm decide how to change the next step based on the measurement results. The control parameters used to achieve the fastest magnetic field measurement."

Magnetic field sensing: The probability distribution defined in successive steps of the algorithm (the two algorithms used in the study are shown in red and blue, respectively), which provide accurate identification of magnetic flux values. The green curve is the standard quantum limit distribution and the background is the interference pattern feature of the device.

machine learning and magnetic


In a range of fields, from geological exploration to imaging of brain activity, magnetic field detection is very important. Researchers believe that their work is the first step toward the goal of sensing technology using quantum enhancement methods. In addition, the rapid extraction of information from quantum states is essential for future quantum processors and ultra-sensitive detectors in the prior art.
Lebedev said: "This is a very good application of quantum technology. By combining quantum phenomena with measurement techniques based on supervised machine learning, we can improve the sensitivity of magnetic field detectors into a new realm that breaks through the standard quantum limits."

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