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arXiv:1403.4506 · Physical Review B

Optimizing phase-estimation algorithms for diamond spin magnetometry

Naufer Nusran, M. V. Gurudev Dutt

Published Jul 25, 2014• 16 citations
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Abstract

We present a detailed theoretical and numerical study discussing the application and optimization of phase-estimation algorithms (PEAs) to diamond spin magnetometry. We compare standard Ramsey magnetometry, the nonadaptive PEA (NAPEA), and quantum PEA (QPEA) incorporating error checking. Our results show that the NAPEA requires lower measurement fidelity, has better dynamic range, and greater consistency in sensitivity. We elucidate the importance of dynamic range to Ramsey magnetic imaging with diamond spins, and introduce the application of PEAs to time-dependent magnetometry.

DOI
10.1103/physrevb.90.024422

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We present a detailed theoretical and numerical study discussing the application and optimization of phase-estimation algorithms (PEAs) to diamond spin magnetometry. We compare standard Ramsey magnetometry, the nonadaptive PEA (NAPEA), and quantum PEA (QPEA) incorporating error checking. Our results show that the NAPEA requires lower measurement fidelity, has better dynamic range, and greater consistency in sensitivity. We elucidate the importance of dynamic range to Ramsey magnetic imaging with diamond spins, and introduce the application of PEAs to time-dependent magnetometry.
Precision measurements of weak magnetic fields with nanoscale spatial resolution is an outstanding challenge in many fields including medicine, biology, material science and physical science. It has already been demonstrated that a single electronic spin formed by a defect color center in diamond, known as the nitrogen-vacancy (NV) center, can serve as a highly sensitive magnetometer with nanoscale resolution, even under ambient conditions. However, standard quantum sensing methods have significant drawbacks. These include the limited dynamic range due to quantum phase ambiguity, the non-linearity in sensitivity over the detectable field range, the requirement of prior knowledge of a working point for accurate deconvolution, etc. This thesis explores novel quantum control techniques such as the use of phase estimation algorithms (PEA) for magnetic field detection to address these issues. Unlike in the standard approach, PEA readout is linearly dependent on the field being sensed. PEA employed on oscillating (AC) magnetic fields can not only detect unknown field amplitudes but also allows detection of the field phase. The thesis also compares the performance of nonadaptive-PEA (NAPEA) with that of adaptive-PEA (QPEA) and conclude that NAPEA is superior to QPEA due to (a) better sensitivity on average, (b) consistency in sensitivity throughout the full field range, (c) comparatively less demanding measurement fidelity, and (d) for simplicity in its experimental realization. The techniques developed here can potentially have broad applicability to a wide variety of solid-state quantum systems and in the field of quantum control and measurement.
Quantum information protocols, such as quantum error correction and quantum phase estimation, have been widely used to enhance the performance of quantum sensors. While these protocols have relied on single-shot detection, in most practical applications only an averaged readout is available, as in the case of room-temperature sensing with the electron spin associated with a nitrogen-vacancy center in diamond. Here, we theoretically investigate the application of the quantum phase estimation algorithm for high dynamic-range magnetometry, when single-shot readout is not available. We show that, even in this case, Bayesian estimation provides a natural way to efficiently use the available information. We apply Bayesian analysis to achieve an optimized sensing protocol for estimating a time-independent magnetic field with a single electron spin associated to a nitrogen-vacancy center at room temperature and show that this protocol improves the sensitivity over previous protocols by more than a factor of 3. Moreover, we show that an extra enhancement can be achieved by considering the timing information in the detector clicks.
We present an experimental method to perform dual-channel lock-in magnetometry of time-dependent magnetic fields using a single spin associated with a nitrogen-vacancy color center in diamond. We incorporate multipulse quantum sensing sequences with phase estimation algorithms to achieve linearized field readout and constant, nearly decoherence-limited sensitivity over a wide dynamic range. Furthermore, we demonstrate unambiguous reconstruction of the amplitude and phase of the magnetic field. We show that our technique can be applied to measure random phase jumps in the magnetic field, as well as phase-sensitive readout of the frequency.
We propose a protocol to estimate magnetic fields using a single nitrogen-vacancy (N-V) center in diamond, where the estimate precision scales inversely with time, $\ensuremath{\delta}B~1/T$, rather than the square-root of time, $\ensuremath{\delta}B~1/\sqrt{T}$. The method is based on converting the task of magnetometry into phase estimation, performing quantum phase estimation on a single N-V nuclear spin using either adaptive or nonadaptive feedback control, and the recently demonstrated capability to perform single-shot readout within the N-V [P. Neumann et al., Science 329, 542 (2010)]. We present numerical simulations to show that our method provides an estimate whose precision scales close to  ~ 1/T1/T1/T (T T~T  the total estimation time), and moreover will give an unambiguous estimate of the static magnetic field experienced by the N-V. By combining this protocol with recent proposals for scanning magnetometry using an N-V, our protocol will provide a significant decrease in signal acquisition time while providing an unambiguous spatial map of the magnetic field.
We develop the quantum approach to magnetometry utilizing phase estimation algorithms, demonstrating improvements in the estimation of magnetic flux in both precision and dynamical range. We propose the modifications to conventional algorithms including the signal modulation and proximity time measurements. We demonstrate that our approach extends the dynamical range and improves the precision of magnetic flux detection. We show that our approach enhances performance of superconducting qubits and enables higher information gain without compromising dynamical range, paving the way toward achieving the Heisenberg limit. Combining adaptive algorithms with device-specific calibration, our methods bridge the gap between theoretical advancements and practical quantum sensing applications, offering a powerful framework for metrology using superconducting qubits.
A key challenge of magnetometry lies in the simultaneous optimization of magnetic field sensitivity and maximum field range. In interferometry-based magnetometry, a quantum two-level system acquires a dynamic phase in response to an applied magnetic field. However, due to the 2π periodicity of the phase, increasing the coherent interrogation time to improve sensitivity reduces field range. Here we introduce a route towards both large magnetic field range and high sensitivity via measurements of the geometric phase acquired by a quantum two-level system. We experimentally demonstrate geometric-phase magnetometry using the electronic spin associated with the nitrogen vacancy (NV) color center in diamond. Our approach enables unwrapping of the 2π phase ambiguity, enhancing field range by 400 times. We also find additional sensitivity improvement in the nonadiabatic regime, and study how geometric-phase decoherence depends on adiabaticity. Our results show that the geometric phase can be a versatile tool for quantum sensing applications.