Intrinsic and induced quantum quenches for enhancing qubit-based quantum noise spectroscopy

Spatially Resolved Dielectric Loss at the Si/SiO_{2} Interface

The Si/SiO_{2} interface is populated by isolated trap states that modify its electronic properties. These traps are of critical interest for the development of semiconductor-based quantum sensors and computers, as well as nanoelectronic devices. Here, we study the electric susceptibility of the Si/SiO_{2} interface with nm spatial resolution using frequency-modulated atomic force microscopy. The sample measured here is a patterned dopant delta layer buried 2 nm beneath the silicon native oxide interface. We show that charge organization timescales of the Si/SiO_{2} interface range from 1-150 ns, and increase significantly around interfacial traps. We conclude that under time-varying gate biases, dielectric loss in metal-insulator-semiconductor capacitor devices is in the frequency range of MHz to sub-MHz, and is highly spatially heterogeneous over nm length scales.

Selective Detection of Dynamics-Complete Set of Correlations via Quantum Channels

Correlations of fluctuations are essential to understanding many-body systems and key information for advancing quantum technologies. To fully describe the dynamics of a physical system, all time-ordered correlations (TOCs), i.e., the dynamics-complete set of correlations are needed. The current measurement techniques can only access a limited set of TOCs, and there has been no systematic and feasible solution for extracting the dynamic-complete set of correlations hitherto. Here we propose a platform-universal protocol to selectively detect arbitrary types of TOCs via quantum channels. In our method, the quantum channels are synthesized with various controls, and engineer the evolution of a sensor-target system along a specific path that corresponds to a desired correlation. Using nuclear magnetic resonance, we experimentally demonstrate this protocol by detecting a specific type of fourth-order TOC that has never been accessed previously. We also show that the knowledge of the TOCs can be used to significantly improve the precision of quantum optimal control. Our method provides a new toolbox for characterizing the quantum many-body states and quantum noise, and hence for advancing the fields of quantum sensing and quantum computing.

Nonergodic Measurements of Qubit Frequency Noise

Slow fluctuations of a qubit frequency are one of the major problems faced by quantum computers. To understand their origin it is necessary to go beyond the analysis of their spectra. We show that characteristic features of the fluctuations can be revealed using comparatively short sequences of periodically repeated Ramsey measurements, with the sequence duration smaller than needed for the noise to approach the ergodic limit. The outcomes distribution and its dependence on the sequence duration are sensitive to the nature of the noise. The time needed for quantum measurements to display quasiergodic behavior can strongly depend on the measurement parameters.

Detection of Quantum Signals Free of Classical Noise via Quantum Correlation

Extracting useful signals is key to both classical and quantum technologies. Conventional noise filtering methods rely on different patterns of signal and noise in frequency or time domains, thus limiting their scope of application, especially in quantum sensing. Here, we propose a signal-nature-based (not signal-pattern-based) approach which singles out a quantum signal from its classical noise background by employing the intrinsic quantum nature of the system. We design a novel protocol to extract the quantum correlation signal and use it to single out the signal of a remote nuclear spin from its overwhelming classical noise backgrounds, which is impossible to be accomplished by conventional filter methods. Our Letter demonstrates the quantum or classical nature as a new degree of freedom in quantum sensing. The further generalization of this quantum nature-based method opens a new direction in quantum research.