Related papers: Machine Learning Assisted Vector Atomic Magnetomet…
An experimentally feasible magnetometer based on a dual-coupling optomechanical system is proposed, where the radiation-pressure coupling transduces the magnetic signal to the optical phase, and the quadratic optomechanical interaction…
Electric and magnetic fields are inherently coupled in an electromagnetic wave. However, structured light beams enable their spatial separation. In particular, azimuthally polarized laser beams exhibit a localized magnetic field on-axis…
Quantum sensing exploits the strong sensitivity of quantum systems to measure small external signals. The nitrogen-vacancy (NV) center in diamond is one of the most promising platforms for real-world quantum sensing applications,…
We present an experimental and theoretical study of a scalar atomic magnetometer using an oscillating field-driven Zeeman resonance in a high-density optically-pumped potassium vapor. We describe an experimental implementation of an atomic…
Because of the unlimited range of state space, orbital angular momentum (OAM) as a new degree of freedom of light has attracted great attention in optical communication field. Recently there are a number of researches applying deep learning…
With the introduction of x-ray free electron laser sources around the world, new scientific approaches for visualizing matter at fundamental length and time-scales have become possible. As it relates to magnetism and "magnetic-type"…
Magnetic fields generated by human and animal organs, such as the heart, brain and nervous system carry information useful for biological and medical purposes. These magnetic fields are most commonly detected using cryogenically-cooled…
We train a model atom to recognize hand-written digits between 0 and 9, employing intense light--matter interaction as a computational resource. For training, individual images of hand-written digits in the range 0-9 are converted into…
We present a method of optical magnetometry with parts-per-billion resolution that is able to detect biomagnetic signals generated from the human brain and heart in Earth's ambient environment. Our magnetically silent sensors measure the…
We observe velocity-selective two-photon resonances in a cold atom cloud in the presence of a magnetic field. We use these resonances to demonstrate a simple magnetometer with sub-mG resolution. The technique is particularly useful for…
We demonstrate a new method for measuring radio frequency (RF) electric fields based on quantum interference in an atom. Using a bright resonance prepared within an electromagnetically induced transparency window we are able to achieve a…
Vector magnetometry provides more information than scalar measurements for magnetic surveys utilized in space, defense, medical, geological and industrial applications. These areas would benefit from a mobile vector magnetometer that can…
Optomechanical magnetometers enable highly sensitive magnetic field sensing. However, all such magnetometers to date have been optically excited and read-out either via free space or a tapered optical fiber. This limits their scalability…
We present an automated approach for identifying magnetospheric regions using supervised machine learning techniques applied to Magnetospheric MultiScale mission data. Our method utilizes ion energy spectra, total magnetic field, total ion…
Free-induction-decay (FID) magnetometers have evolved as simple magnetic sensors for sensitive detection of unknown magnetic fields. However, these magnetometers suffer from a fundamental problem known as a "dead zone," making them…
We propose a new type of sensor, which uses diamond containing the optically active nitrogen-vacancy (NV$^-$) centres as a laser medium. The magnetometer can be operated at room-temperature and generates light that can be readily fibre…
We study multi-parameter sensing of 2D and 3D vector fields within the Bayesian framework for $SU(2)$ quantum interferometry. We establish a method to determine the optimal quantum sensor, which establishes the fundamental limit on the…
Machine learning methods have nowadays become easy-to-use tools for constructing high-dimensional interatomic potentials with ab initio accuracy. Although machine learned interatomic potentials are generally orders of magnitude faster than…
We demonstrate a magnetometric technique based on nonlinear magneto-optical rotation using amplitude modulated light. The magnetometers can be operated in either open-loop (typical nonlinear magneto-optical rotation with amplitude-modulated…
We report the use of an atomic magnetometer based on nonlinear magneto-optical rotation with frequency modulated light (FM NMOR) to detect nuclear magnetization of xenon gas. The magnetization of a spin-exchange-polarized xenon sample ($1.7…