MIT Chinese doctoral student develops new quantum sensor that can detect electromagnetic signals of any frequency

Harnessing the power of quantum coherence and entanglement, quantum sensors enable sensitive measurements of various signal fields, such as electric and magnetic fields, with atomic-scale spatial resolution . Physicists use them to study exotic states of matter, such as time crystals, topological phases; and to characterize practical devices such as experimental quantum memory or computing devices. However, the accessible frequency range of these signals is still limited by the sensor resonant frequency or the achievable control field amplitude, which is a major obstacle to their practicality .

To this end, the team of Professor Paola Cappellaro at the Massachusetts Institute of Technology (MIT) has developed a new method: using integrated sensors and mixers based on the same quantum device to sense signal fields of arbitrary frequencies without losing the ability to measure nanoscale features .

Specifically, the team exploited nonlinear effects in periodically driven (Floquet) quantum systems to achieve quantum frequency mixing of the signal and an applied bias AC field. It is further shown that the frequency mixing can distinguish the vector components of the oscillating signal field, thus realizing the vector magnetometry of any frequency. Finally, the versatility of the quantum mixer sensing technique is experimentally demonstrated with nitrogen-vacancy color centers in diamond to sense 150 MHz signal fields.

On June 17, the research results were published in the journal "Physical Review X" under the title "Sensing Arbitrary Frequency Fields Using Quantum Mixers" [1].

MIT Chinese doctoral student Wang Guoqing is the first author and corresponding author of the paper, and another Chinese doctoral student, Liu Yixiang, also participated in this work. The other three co-authors are from Lincoln Laboratory.

The strategy for enabling quantum sensors to measure fields of arbitrary frequency is to convert the frequency of the field to a frequency accessible to the sensor, which can be achieved by combining the signal field with a bias field using circuits called "mixers." But this circuit reduces the spatial resolution of the sensor, and the MIT team avoided this problem by using qubits in the sensor to perform a quantum simulation of frequency mixing: When a bias field is applied to the qubit, the qubit converts the signal field converted to accessible frequencies .

Specifically, the team designed a new system called a "Quantum Mixer" that uses a microwave beam to inject a second frequency into the detector [2]. This operation converts the frequency of the field under study into a different frequency, the difference between the original frequency and the added signal, tuned to the specific frequency for which the detector is most sensitive. This simple process enables the detector to be fully adapted to any desired frequency without losing the nanoscale spatial resolution of the sensor.

(a) Schematic of quantum mixing. The effective Hamiltonian (red) comes from the frequency mix of the signal (purple) and biased (green) Hamiltonians. The effective Hamiltonian frequency ω T can be probed experimentally. (b) Probing electron spin resonance (ESR) experiments for ω T using an ensemble of NV color centers. The researchers scan the bias field frequency ω b to detect the signal field at ω s = (2π)150  MHz, although this is not within the reach of typical sensing methods. Finally, it is observed that the resonance ω T =±( ω s − ω b ) matches the probe driver amplitude Ω=(2π)3  MHz.

The signal field can then be analyzed using well-established sensing techniques. In the experiment, the team used a specific device based on a diamond nitrogen-vacancy color center array as a quantum sensing system, and successfully demonstrated the detection frequency of 150 using a qubit detector with a frequency of 2.2 GHz using a quantum multiplexer. MHz signal. Then, by deriving a theoretical framework based on Floquet's theory, the team performed a detailed analysis of the process, testing the theory's numerical predictions in a series of experiments.

Characterization of the effective Hamiltonian predicted by Floquet theory. (a) Schematic showing Rabi oscillations and AC Stark Shift mediated by virtual Floquet states. (b) |0 ⟩ state qubit population as a function of bias field frequency at fixed time t = 1.875 μs , similar to electron spin resonance (ESR) experiments. (c) Signal as a function of time under resonance conditions.

Vector AC magnetometry. (a) Principle of quantum-mixing vector AC magnetometry. (b) Experiment sequence. (c) Environmental and radiation monitoring measurements. (d) Time evolution measurements under resonance conditions. (e) Signal amplitude sweeps at different offset amplitudes. The Rabi frequency for longitudinal component detection was measured as a function of signal amplitude at three different bias field amplitudes. The slopes of the signal sweeps at different offset amplitudes are plotted in the insets and fitted to a linear trend. (f) Measured coherence time T2ρρ measuring the time evolution caused by the effective lateral and longitudinal signals in a rotating coordinate system.

Wang Guoqing said, "The same principle can also be applied to any type of sensor or quantum device. The system will be self-contained, with the detector and the second frequency source all packaged in one device." Talking about the potential uses of this system, Wang Guoqing said it could be used to characterize the performance of microwave antennas in detail: "It can characterize the distribution of the field [generated by the antenna] at nanoscale resolution, so it is very promising in this direction."

MIT doctoral student Wang Guoqing

Other methods can alter the frequency sensitivity of some quantum sensors, but these require the use of large devices and strong magnetic fields that blur details and prevent the very high resolution offered by the new system. In this regard, Wang Guoqing said, "The current system needs to use a strong magnetic field to adjust the sensor, but the magnetic field may destroy the properties of quantum materials, which may affect the phenomenon you want to measure."

MIT engineers have expanded the capabilities of these ultrasensitive nanoscale detectors with potential uses in quantum computing and biosensing.

Professor Paola Cappellaro said the system could potentially open up new applications in the biomedical field, as it can deliver a range of frequencies of electrical or magnetic activity at the level of individual cells. Useful resolution of these signals is difficult to obtain with current quantum sensing systems, and the new system can be used to detect output signals from individual neurons in response to certain stimuli: for example, stimuli that often include a lot of noise can make the signal difficult to isolate .

The system can also be used to characterize the behavior of special materials in detail, such as 2D materials whose electromagnetic, optical and physical properties are being studied in depth.

In future work, the team is exploring the possibility of extending the system's approach to be able to detect a range of frequencies at a time, rather than the current system's single frequency target. In the future, the team will continue to use Lincoln Laboratory's more powerful quantum sensing devices to define the capabilities of the system.

Reference link:

[1] https://journals.aps.org/prx/abstract/10.1103/PhysRevX.12.021061

[2] https://news.mit.edu/2022/quantum-sensor-frequency-0621