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Register a new userAtomic scale electron vortices for nanoresearch
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Electron vortex beams were only recently discovered and their potential as a probe for magnetism in materials was shown. Here we demonstrate a new method to produce electron vortex beams with a diameter of less than 1.2 AA. This unique way to prepare free electrons to a state resembling atomic orbitals is fascinating from a fundamental physics point of view and opens the road for magnetic mapping with atomic resolution in an electron microscope.
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Electronic nearsightedness is one of the fundamental principles governing the behavior of condensed matter and supporting its description in terms of local entities such as chemical bonds. Locality also underlies the tremendous success of machine-learning schemes that predict quantum mechanical observables -- such as the cohesive energy, the electron density, or a variety of response properties -- as a sum of atom-centred contributions, based on a short-range representation of atomic environments. One of the main shortcomings of these approaches is their inability to capture physical effects, ranging from electrostatic interactions to quantum delocalization, which have a long-range nature. Here we show how to build a multi-scale scheme that combines in the same framework local and non-local information, overcoming such limitations. We show that the simplest version of such features can be put in formal correspondence with a multipole expansion of permanent electrostatics. The data-driven nature of the model construction, however, makes this simple form suitable to tackle also different types of delocalized and collective effects. We present several examples that range from molecular physics, to surface science and biophysics, demonstrating the ability of this multi-scale approach to model interactions driven by electrostatics, polarization and dispersion, as well as the cooperative behavior of dielectric response functions.
We investigate numerically the dynamics of optical vortex beams carrying different topological charges, launched in a dissipative three level ladder type nonlinear atomic vapor. We impose the electromagnetically induced transparency (EIT) condition on the medium. Linear, cubic, and quintic susceptibilities, considered simultaneously with the dressing effect, are included in the analysis. Generally, the beams slowly expand during propagation and new vortices are induced, commonly appearing in oppositely charged pairs. We demonstrate that not only the form and the topological charge of the incident beam, but also its growing size in the medium greatly affect the formation and evolution of vortices. We formulate common rules for finding the number of induced vortices and the corresponding rotation directions, stemming from the initial conditions of various incident beams, as well as from the dynamical aspects of their propagation. The net topological charge of the vortex is conserved during propagation, as it should be, but the total number of charges is not necessarily same as the initial number, because of the complex nature of the system. When the EIT condition is lifted, an enhancement region of beam dynamics if reached, in which the dynamics and the expansion of the beam greatly accelerate. In the end, we discuss the liquid like behavior of light evolution in this dissipative system and propose a potential experimental scheme for observing such a behavior.
We propose and theoretically analyze a new vibrational spectroscopy, termed electron- and light-induced stimulated Raman (ELISR) scattering, that combines the high spatial resolution of electron microscopy with the molecular sensitivity of surface-enhanced Raman spectroscopy. With ELISR, electron-beam excitation of plasmonic nanoparticles is utilized as a spectrally-broadband but spatially-confined Stokes beam in the presence of a diffraction-limited pump laser. To characterize this technique, we develop a numerical model and conduct full-field electromagnetic simulations to investigate two distinct nanoparticle geometries, nanorods and nanospheres, coated with a Raman-active material. Our results show the significant ($10^6$-$10^7$) stimulated Raman enhancement that is achieved with dual electron and optical excitation of these nanoparticle geometries. Importantly, the spatial resolution of this vibrational spectroscopy for electron microscopy is solely determined by the nanoparticle geometry and the plasmon mode volume. Our results highlight the promise of ELISR for simultaneous high-resolution electron microscopy with sub-diffraction-limited Raman spectroscopy, complementing advances in superresolution microscopy, correlated light and electron microscopy, and vibrational electron energy loss spectroscopy.
Atomic systems have long provided a useful material platform with unique quantum properties. The efficient light-matter interaction in atomic vapors has led to numerous seminal scientific achievements including accurate and precise metrology and quantum devices. In the last few decades, the field of thin optical elements with miniscule features has been extensively studied demonstrating an unprecedented ability to control photonic degrees of freedom, both linearly and non-linearly, with applications spanning from photography and spatial light modulators to cataract surgery implants. Hybridization of atoms with such thin devices may offer a new material system allowing traditional vapor cells with enhanced functionality. Here, we fabricate and demonstrate chip-scale, quantum diffractive optical elements which map atomic states to the spatial distribution of diffracted light. Two foundational diffractive elements, lamellar gratings and Fresnel lenses, are hybridized with atomic channels containing hot atomic vapors which demonstrate exceptionally strong frequency dependent behaviors. Providing the design tools for chip-scale atomic diffractive optical elements develops a path for a variety of compact thin quantum-optical elements.
This chapter discusses the importance of incorporating three-dimensional symmetries in the context of statistical learning models geared towards the interpolation of the tensorial properties of atomic-scale structures. We focus on Gaussian process regression, and in particular on the construction of structural representations, and the associated kernel functions, that are endowed with the geometric covariance properties compatible with those of the learning targets. We summarize the general formulation of such a symmetry-adapted Gaussian process regression model, and how it can be implemented based on a scheme that generalizes the popular smooth overlap of atomic positions representation. We give examples of the performance of this framework when learning the polarizability and the ground-state electron density of a molecule.
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