Multiplexed scanning microscopy with dual-qubit spin sensors

Abstract

Scanning probe microscopy with multi-qubit sensors offers the potential to improve imaging speed and measure previously inaccessible quantities, such as two-point correlations. We develop a multiplexed quantum sensing approach with scanning probes containing two nitrogen-vacancy (NV) centers at the tip apex. A shared optical channel is used for simultaneous qubit initialization and readout, while phase- and frequency-dependent microwave spin manipulations are leveraged for de-multiplexing the optical readout signal. Scanning dual-NV magnetometry is first demonstrated by simultaneously imaging multiple field projections of a ferrimagnetic racetrack device. Then, we record the two-point covariance of spatially correlated field fluctuations across a current-carrying wire. Our multiplex framework establishes a method to investigate a variety of spatio-temporal correlations, including phase transitions and electronic noise, with nanoscale resolution.

Figures (4)

• Figure 1: Concept of dual-NV scanning microscopy. (a) Schematic of the scanning probe microscope. As the sample is moved under the probe, NV centers in the diamond tip sense their local magnetic (or electric) environment. A single optical channel is used for laser excitation and PL readout, while separate microwave frequencies simultaneously control both spins. (b) Detail showing the correlated ($\vec{B}_\mathrm{c}$, solid field lines) and uncorrelated ($\vec{B}_{\mathrm{uc},1}$, $\vec{B}_{\mathrm{uc},2}$, dashed) magnetic fields experienced by NV1 and NV2. The dashed black lines indicate the measurement axes $\vec{e}_i$. (c) Time trace of the global magnetic signal $\vec{B}_\mathrm{c}(t)$ (arbitrary projection shown) and its projection onto every NV center ($B_i$). (d) Pulse sequence schematic. Laser pulses are used to polarize NV centers and prompt PL emission. Fixed microwave frequencies (MW$_i$) are used to simultaneously address a spin transition for each NV center. $\pi/2$ denotes the spin rotation angle and $\Phi_i \in \{0, 90^\circ, 180^\circ, 270^\circ\}$ denotes the relative phase shifts between first and second pulse. An avalanche photodiode (APD) converts the PL emission into sixteen photon counts signals $C_{\Phi_{1}\Phi_{2}}$ that are used to recover the mean phases and count covariances in (e) and (f), respectively. (e) Readout matrix for de-multiplexing of mean phases $\bar{\phi}_1$ and $\bar{\phi}_2$. Each matrix element represents a photon count $C_{\Phi_{1}\Phi_{2}}$. Mean phases are obtained by partial summation (arrows) followed by application of Eq. (\ref{['eq:mean_phases']}). (f) Readout matrix for covariance sensing. Each matrix element represents the difference $V_{\Phi_{1}\Phi_{2}} - E_{\Phi_{1}\Phi_{2}}$, where $V$ and $E$ are the variance and expectation values computed across $n$ measurement repetitions, respectively. Covariances are obtained by subtracting the readout combination connected by dashed arrows. Four covariances can be computed, $\mathrm{Cov}_{xx}$ (green), $\mathrm{Cov}_{xy}$ (red), $\mathrm{Cov}_{yx}$ (yellow), $\mathrm{Cov}_{yy}$ (blue).
• Figure 2: Characterization of dual-NV probes. (a) Log-scale confocal image of the collected PL recorded by scanning the excitation laser across the diamond probe. Multiple bright spots indicate multiple NV centers and a fainter halo outlines the pillar structure. Scale bar, $1\,\mathrm{\mu m}$. (b) Optically-detected magnetic resonance (ODMR) spectra identifying four spin transitions, confirming the presence of two NV centers. The spectra are recorded while focusing the laser at the position indicated by the cross in panel (b). (c) Schematic of two NV centers inside the scanning tip showing their orientation (defined by $\vartheta$ and $\varphi$) and relative positions (defined by $\Delta x$, $\Delta y$, and $\Delta z$). (d) ODMR frequency shifts while scanning across orthogonal step edges of a magnetic stripe. $\Delta x$ and $\Delta y$ (indicated with black arrows) are determined from the position of the fitted edges of the sample (gray lines). The gray line widths (indicated with gray arrows) is twice the fitted standoff distance ($z_1=47\pm1\,\mathrm{nm}$ and $z_2=58\pm2\,\mathrm{nm}$ for the plotted data), which determines $\Delta z$ and the spatial resolution. Data recorded on tip #2.
• Figure 3: Multiplexed imaging of a ferrimagnetic GdCo racetrack. (a) Experimental PL count data, $C_{\Phi_{1}\Phi_{2}}$, for the sixteen readout combinations forming the readout matrix in Fig. \ref{['fig1']}(e). The mean PL across all phase combinations has been subtracted. (b,c) Phase images $\bar{\phi}_1$ (NV1) and $\bar{\phi}_2$ (NV2), computed using Eq. (\ref{['eq:mean_phases']}). Scale bars, $2\,\mathrm{\mu m}$. Data recorded on tip #4.
• Figure 4: Sensing of spatial correlations using covariance detection. (a) Topography of the current-carrying wire device. Scale bar, $1\,\mathrm{\mu m}$. (b) Dual-NV magnetometry line scans taken across the wire (white-dashed line in (a)). A DC current through the wire produces a static magnetic field. (c) Phase contrasts $c_{r1}$ and $c_{r2}$ for three covariance imaging measurements where an asynchronous AC current ($f = 35.211430\,\mathrm{kHz}$) is passed through the wire. The dips in the signal reflect the magnetic field noise seen by each NV center leading to decoherence. Data point shapes (square, circle, and diamond) indicate different experimental runs. (d) Covariance signal computed from the averaged measurements of (c). Error bars are the standard deviation between the measurements. Gray curve is a Monte Carlo simulation of the expected phase covariance $\mathrm{Cov}_{yy}$ using the measurements in panel (b) as input. Data recorded on tip #4.