Table of Contents
Fetching ...

Predictive tracking of the NV Center based on external temperature sensors

Manpreet Singh Jattana, Thomas Lippert

Abstract

We report an experimental design where the position and resonance frequency of the Nitrogen Vacancy (NV) in a diamond are correlated with the room temperature. A simple model trained on the interpolated correlation data predicts both quantities. The predictive tracking of the NV's location enables continuous operation of the NV quantum computer under ambient conditions for a week without recalibration.

Predictive tracking of the NV Center based on external temperature sensors

Abstract

We report an experimental design where the position and resonance frequency of the Nitrogen Vacancy (NV) in a diamond are correlated with the room temperature. A simple model trained on the interpolated correlation data predicts both quantities. The predictive tracking of the NV's location enables continuous operation of the NV quantum computer under ambient conditions for a week without recalibration.

Paper Structure

This paper contains 1 equation, 4 figures.

Figures (4)

  • Figure 1: Experimental optical setup of our NV center based quantum computer. The optics table, laser, and liquid cooling temperature control are placed within a weakly thermally isolated room. The optics table consists of a diamond (red) placed close to a magnet. A green beam of light originating at B is shone onto the diamond through the objective O. Emitted red light is detected at detector D. Control equipment consisting of several devices that generate most of the heat are kept outside.
  • Figure 2: (a) The relative change in NV's location (left axis) and temperature T$_2$ (right axis) plotted against a time period of $10$ days. The values in $X$ and $Z$ directions are negated for a better visualisation of the anticorrelation. There are strong linear (anti/)correlations despite the different scales of $X$, $Y$, and $Z$. The axes are not optimized for superimposition. (b) The correlation matrix between the NV's coordinates $X$, $Y$, and $Z$, and temperatures T$_1$ and T$_2$ shows the strength of their linear correlations (red) and anticorrelations (blue). The apparent stronger (anti/)correlation of positions with T$_2$ compared to T$_1$ is due to the measurement sensitivities of the sensors. As is also visible in (a), the measurables $-X$, $Y$, and T$_2$ have near perfect correlation. (c) The percentage difference in the crest and trough of the Rabi oscillations obtained for different driving frequencies at constant temperature is plotted in red square points. A Lorentzian fit to the data is shown in dashed black lines. The full width at half maxima (FWHM) is $1.55$ MHz.
  • Figure 3: The negative of measured resonance frequencies (grey points) in GHz (left axis) and temperature in °C (black line) T$_2$ (right axis) are plotted against time. Each blue point represents one standard deviation of the resonance frequencies.
  • Figure 4: (a) The absolute difference between actual and predicted $X$ (top), $Y$ (middle), and $Z$ (bottom). The units of y-axes is nanometers. (b) The actual $\nu_\mathrm{res}$ (grey) in GHz and the predicted $\nu_\mathrm{res}$ (orange) as a function of time.