Related papers: Magnetic field regression using artificial neural …
For magnetic field calculations, cylindrical permanent magnets are often approximated as ideal, azimuthally symmetric solenoids. Despite the frequent usage of this approximation, research papers demonstrating the validity and limitations of…
The Muon g-2 Experiment (E989) at Fermilab measures the muon magnetic anomaly, aiming to resolve the greater than 3$\sigma$ discrepancy between the previous measurement and the Standard Model calculation with an improved precision of 140…
The spins, which are accumulated at a boundary of a nanomagnet due to the Spin Hall effect, induce a magnetic field, which tilts the nanomagnet magnetization out of its easy axis. Even though this magnetic field is relatively small (about…
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…
Deep neural networks have been successfully applied in many different fields like computational imaging, medical healthcare, signal processing, or autonomous driving. In a proof-of-principle study, we demonstrate that computational optical…
Electron density is a fundamental quantity, which can in principle determine all ground state electronic properties of a given system. Although machine learning (ML) models for electron density based on either an atom-centered basis or a…
We present an approach to accelerate Neural Field training by efficiently selecting sampling locations. While Neural Fields have recently become popular, it is often trained by uniformly sampling the training domain, or through handcrafted…
We have constructed an imaging device that capable to show a spatio-temporal distribution of magnetic field intensity in real-time. The device employs a set of AMR (Anisotropic Magneto Resistance) 3-axis magnetometers, which are arranged…
We develop a theoretical model for calibrating the absorption imaging of cold atoms under high magnetic fields. Comparing to zero or low magnetic fields, the efficiency of the absorption imaging becomes lower while it requires an additional…
Significant systematic errors in high-precision Penning trap mass spectrometry can result from electric and magnetic field imperfections. An experimental procedure to minimize these uncertainties is presented for the on-line Penning trap…
The magnetic diagnostics subsystem of the LISA Technology Package (LTP) on board the LISA PathFinder (LPF) spacecraft includes a set of four tri-axial fluxgate magnetometers, intended to measure with high precision the magnetic field at…
A novel approach is presented for the solution of instantaneous chemical equilibrium problems. The chemical equilibrium can be considered, due to its intrinsically local character, as a mapping of the three-dimensional parameter space…
We present an all-optical method to measure and compensate for residual magnetic fields present in a cloud of ultracold atoms trapped in an optical dipole trap. Our approach leverages the increased loss from the trapped atomic sample…
Nitrogen vacancy (NV) centers in diamond are optically addressable and versatile light-matter interfaces with practical application in magnetic field sensing, offering the ability to operate at room temperature and reach sensitivities below…
Observational constraints on stellar magnetic fields are essential to both stellar and planetary physics. Recent studies revealed the diversity and evolution of large-scale magnetic fields in low-mass stars. These large-scale fields only…
A properly calibrated longitudinal magnetograph is an instrument that measures circular polarization and gives an estimation of the magnetic flux density in each observed resolution element. This usually constitutes a lower bound of the…
During the last decade, the FORS1 instrument of the ESO VLT has been extensively used to study stellar magnetism. A number of interesting discoveries of magnetic fields in several classes of stars have been announced, many of which obtained…
We investigate the efficient learning of magnetic phases using artificial neural networks trained on synthetic data, combining computational simplicity with physics-informed strategies. Focusing on the diluted Ising model, which lacks an…
Optical microtraps provide a strong spatial confinement for laser-cooled atoms. They can, e.g., be realized with strongly focused trapping light beams or the optical near fields of nano-scale waveguides and photonic nanostructures. Atoms in…
Precise magnetic field modeling is fundamental to the closed-loop control of electromagnetic navigation systems (eMNS) and the analytical Multipole Expansion Model (MPEM) is the current standard. However, the MPEM relies on strict physical…