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arXiv:2005.05995 · npj Quantum Information

Optimal control for quantum detectors

Paraj Titum, Kevin Schultz, Alireza Seif, Gregory Quiroz, B. D. Clader

Published Mar 25, 2021• 17 citations
arXivHTMLPDF

Abstract

Abstract Quantum systems are promising candidates for sensing of weak signals as they can be highly sensitive to external perturbations, thus providing excellent performance when estimating parameters of external fields. However, when trying to detect weak signals that are hidden by background noise, the signal-to-noise ratio is a more relevant metric than raw sensitivity. We identify, under modest assumptions about the statistical properties of the signal and noise, the optimal quantum control to detect an external signal in the presence of background noise using a quantum sensor. Interestingly, for white background noise, the optimal solution is the simple and well-known spin-locking control scheme. Using numerical techniques, we further generalize these results to the case of background noise with a Lorentzian spectrum. We show that for increasing correlation time, pulse based sequences, such as CPMG, are also close to the optimal control for detecting the signal, with the crossover dependent on the signal frequency. These results show that an optimal detection scheme can be easily implemented in near-term quantum sensors without the need for complicated pulse shaping.

DOI
10.1038/s41534-021-00383-5

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Abstract Quantum systems are promising candidates for sensing of weak signals as they can be highly sensitive to external perturbations, thus providing excellent performance when estimating parameters of external fields. However, when trying to detect weak signals that are hidden by background noise, the signal-to-noise ratio is a more relevant metric than raw sensitivity. We identify, under modest assumptions about the statistical properties of the signal and noise, the optimal quantum control to detect an external signal in the presence of background noise using a quantum sensor. Interestingly, for white background noise, the optimal solution is the simple and well-known spin-locking control scheme. Using numerical techniques, we further generalize these results to the case of background noise with a Lorentzian spectrum. We show that for increasing correlation time, pulse based sequences, such as CPMG, are also close to the optimal control for detecting the signal, with the crossover dependent on the signal frequency. These results show that an optimal detection scheme can be easily implemented in near-term quantum sensors without the need for complicated pulse shaping.
Quantum sensors can show unprecedented sensitivities, provided they are controlled in a very specific, optimal way. Here, we consider a spin sensor of time-varying fields in the presence of dephasing noise, and we show that the problem of finding the pulsed control field that optimizes the sensitivity (i.e., the smallest detectable signal) can be mapped to the determination of the ground state of a spin chain. We find an approximate but analytic solution of this problem, which provides a lower bound for the sensitivity and a pulsed control very close to optimal, which we further use as initial guess for realizing a fast simulated annealing algorithm. We experimentally demonstrate the sensitivity improvement for a spin-qubit magnetometer based on a nitrogen-vacancy center in diamond.
A key challenge in quantum sensing is the detection of weak time dependent signals, particularly those that arise as specific frequency perturbations over a background field. Conventional methods usually demand complex dynamical control of the quantum sensor and heavy classical post-processing. We propose a quantum sensor that leverages time independent interactions and entanglement to function as a passive, tunable, thresholded frequency filter. By encoding the frequency selectivity and thresholding behavior directly into the dynamics, the sensor is responsive only to a target frequency of choice whose amplitude is above a threshold. This approach circumvents the need for complex control schemes and reduces the post-processing overhead.
Many control and detection applications require real-time analysis of signals from sensors, in order to quickly and accurately act upon events revealed by the sensors. Such signal analysis benefits from statistical models of signal and sensor behavior. This creates a need for data analysis methods that are simultaneously model based, computationally efficient, and causal, in the sense that they employ only sensor data available prior to a specific point in time. In this work, we implement sequential data analysis techniques on a spin-noise-based quantum sensor to perform two key tasks: hypothesis testing and quickest change-point detection. These online protocols allow us to detect weak magnetic fields by adaptively collecting measurement data until a predefined confidence threshold is reached. We demonstrate these methods in a realistic experimental setting and derive performance bounds for the achievable precision and response time. Our approach has potential utility when detecting small perturbations to the magnetic field, in both applied and fundamental contexts including biomagnetism, geophysical surveys, detection of concealed materials, searches for dark matter candidates, and exotic spin interactions. Our results demonstrate that sequential techniques enable faster and more sensitive detection, making them a powerful tool for quantum sensing.
Abstract Quantum sensors can show unprecedented sensitivities, provided they are controlled in a very specific, optimal way. Here, we consider a spin sensor of time-varying fields in the presence of dephasing noise, and we show that the problem of finding the optimal pulsed control field can be mapped to the determination of the ground state of a spin chain. We find an approximate but analytic solution of this problem, which provides a \emph{lower bound} for the sensor sensitivity, and a pulsed control very close to optimal, which we further use as initial guess for realizing a fast simulated annealing algorithm. We experimentally demonstrate the sensitivity improvement for a spin-qubit magnetometer based on a nitrogen-vacancy center in diamond.
Quantum sensors take advantage of the inherent sensitivity of quantum systems to external environment perturbations to precisely measure target signals. The same interaction with the environment, however, limits the device sensitivity by reducing the coherence of the quantum states. Quantum control can play a crucial role in improving the sensor performance. We explore quantum control tools to improve the performance of a NitrogenVacancy (NV) center as a single-qubit sensor of ultra-weak magnetic fields in noisy environments. We present a method to obtain a precise spectroscopic characterization of the NV environment, instrumental to design robust sensing strategies with improved noise protection. Then, we exploit optimal quantum control based on a set of numerical methods to optimize the temporal dependence of the sensor driving field adapted to quantum sensing purposes, and prove its advantage to achieve best compromises between signal acquisition and noise cancellation.