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Vector atomic magnetometer based on EIT in Rb vapor

Irina V. Novikova, Eugeniy E. Mikhailov, Alex Toyryla, Mario Gonzales, Andrey B. Matsko, Jamie McKelvy, I. Fan, Yang Li, John E. Kitching

Published Jan 1, 2023• 2 citations
Publisher

Abstract

By analyzing the relative frequencies and amplitude of multiple electromagnetically induced transparency resonances in external magnetic field, we achieve scalar magnetometer sensitivity <5pT/Hz, and can determine the B-field direction with angular sensitivity < 1° using machine learning and optical lock techniques in a 100 mm3 atomic vapor cell.

DOI
10.1364/cleo_si.2023.sw4o.4

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By analyzing the relative frequencies and amplitude of multiple electromagnetically induced transparency resonances in external magnetic field, we achieve scalar magnetometer sensitivity <5pT/Hz, and can determine the B-field direction with angular sensitivity < 1° using machine learning and optical lock techniques in a 100 mm3 atomic vapor cell.
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We present a realization of a magnetic sensor based on electromagnetically induced transparency (EIT) resonances observed in hot Rb vapor using lin∥\parallel∥lin polarized dichromatic light and evaluate scalar and vector capabilities of the sensor for measuring Earth-like magnetic fields. We demonstrate scalar measurement sensitivity of 2 pT/Hz^1/2 in the 1-100~Hz spectral frequency band using a cm^3 Rb vapor cell, significantly improving the performance for such a configuration if compared with earlier measurements of large magnetic fields. By using a single linearly polarized dichromatic optical field, we are also able to determine the direction of the magnetic field with respect to the light propagation direction and polarization, taking advantage of the symmetries of the interaction scheme. We accomplish that by combining the polarization-sensitive transmission measurements and sparse sensing machine learning techniques. A path for further improvement of the sensitivity and elimination of systematic effects, such as heading error, is discussed.
We present a realization of a magnetic sensor based on electromagnetically induced transparency (EIT) resonances observed in hot Rb vapor using lin∥\parallel∥lin polarized dichromatic light and evaluate scalar and vector capabilities of the sensor for measuring Earth-like magnetic fields. We demonstrate scalar measurement sensitivity of 2 pT/Hz^1/2 in the 1-100~Hz spectral frequency band using a cm^3 Rb vapor cell, significantly improving the performance for such a configuration if compared with earlier measurements of large magnetic fields. By using a single linearly polarized dichromatic optical field, we are also able to determine the direction of the magnetic field with respect to the light propagation direction and polarization, taking advantage of the symmetries of the interaction scheme. We accomplish that by combining the polarization-sensitive transmission measurements and sparse sensing machine learning techniques. A path for further improvement of the sensitivity and elimination of systematic effects, such as heading error, is discussed.
Here, we describe progress toward realization of a vector magnetometer based on all-optical excitation of an atomic ensemble in a vapor cell under the conditions of electromagnetically induced transparency (EIT). The EIT resonance amplitudes depend on relative orientations of the three key vectors: laser wave-vector, polarization, and the direction of the magnetic field. By analyzing possible two-photon transitions and their combinations, we can, in principle, analytically calculate the amplitude of various EIT resonances as functions of the relative angles between the magnetic field, polarization and laser propagation vectors. By locking the polarization to one of these maxima, one can determine the plane formed by the magnetic field and the light wave vector to the accuracy better than 0.001 rad. Analysis of the relative resonance amplitude may be used to extract the full information about the magnetic field direction.
The precise measurement of magnetic fields is a fundamental tool of remote sensing. However, accurately measuring the direction of magnetic fields is challenging with atomic magnetometers. In this work, we discuss progress on the development of an all-optical vector atomic magnetometer that uses electromagnetically induced transparency (EIT) on87Rb vapor. The magnitude of the magnetic field is evaluated by measuring the separation of the laser transmission peaks of the Zeeman-resolved EIT spectra, and the direction is measured by evaluating the relative peak contrast using a lightweight machine learning algorithm involving principal component analysis (PCA). We have demonstrated a scalar sensitivity of $ < 10pT/\sqrt {Hz} $ in the 1–100 Hz band and an angular accuracy of < 1°. This approach for vector magnetometry does not require an array of sensors or calibration coils, ultimately setting the groundwork for the design of a new magnetometer that is lighter and more accurate than conventional vector magnetometer configurations.