The charge transfer (ionization) of hydrogen Rydberg atoms (n = 25 − 34) at a Cu(100) surface is investigated. Unlike fully metallic surfaces, where the Rydberg electron energy is degenerate with the conduction band of the metal, the Cu(100) surface has a projected bandgap at these energies, and only discrete image states are available through which charge transfer can take place. Resonant enhancement of charge transfer is observed for Rydberg states whose energy matches one of the image states, and the integrated surface ionization signals (signal versus applied field) show clear periodicity as a function of n as the energies come in and out of resonance with the image states. The surface ionization dynamics show a velocity dependence; decreased velocity of the incident H atom leads to a greater mean distance of ionization and a lower field required to extract the ion. The surface-ionization profiles for 'on resonance' n values show a changing shape as the velocity is changed, reflecting the finite field range over which resonance occurs.The collision of a Rydberg atom in the gas phase with a solid surface typically leads to transfer of the Rydberg electron to the surface at distances less than 5n 2 a 0 , where n is the Rydberg electron principal quantum number. This is especially true for metallic surfaces, where the Rydberg electron energy is degenerate with the conduction band so that resonant charge transfer (RCT) can occur. Experimental and theoretical studies of this phenomenon have focused on the effects of varying the n quantum number, the parabolic quantum number k, the velocity of the incoming particle and the applied fields [1,2], and observing how the rate of ionization varies as a function of distance from the surface [3]. For nonhydrogenic atoms, adiabatic and non-adiabatic passage through surface-induced energy level crossings leads to behavior that varies with the Rydberg species [4]. Thus, such studies reveal important information about the Rydberg states and their dynamics near surfaces.An equally important question for such studies is what they reveal about the nature of the surface. Experimental studies have been primarily conducted with flat-metal surfaces for which the ionization dynamics are almost independent of the material because of the generic behavior of RCT to the conduction band. However, there have also been some experimental and/or theoretical investigations of the effects of adlayers and thin insulating films [5], interaction with doped semiconductor surfaces [6] and dielectric materials [7], effects of corrugation and of patch charges [8,9]. Related theoretical calculations were used to investigate the variation of ionization rate of ground state H -with the thickness of a metal film substrate [10]. All these studies point to a degree of sensitivity of the charge transfer process to the surface characteristics. The mean radius of a hydrogenic Rydberg orbit is of order n 2 a 0 (e.g., ∼ 20 nm for n = 20) and charge transfer typically occurs at a Rydberg-surface distance of 3 − 5...
Abstract. The interface of neutral Rydberg atoms in the gas phase with a solid surface is of interest in many fields of modern research. This interface poses a particular challenge for any application in which Rydberg atoms are close to a substrate but also opens up the possibility of studying properties of the surface material itself through the atomic response. In this review the focus is on the process of electron tunneling from the excited state into the substrate that occurs when a Rydberg atom is located in front of a surface at a range of a few hundred nm and is demonstrated with a metallic surface. It is shown how variations in this ionisation mechanism can provide a powerful tool to probe imagecharge effects, measure small superficial electric stray or patch fields and how charge transfer from the Rydberg atom can be in resonance with energetically discrete surface states. Rydberg atoms at surfaces and interfacesWhen atoms are excited into states of high principal quantum number n their properties are exaggerated and long-range interactions lead to a strong coupling with their environment. The electron cloud is greatly expanded compared to the ground state (∝ n 2 ) which results in a large polarisability of a Rydberg state (∝ n 7 ) causing a strong response to electric fields [1]. In terms of a classical dipole, the positive core and negative electron are widely separated giving these excited states a large dipole moment, by which Rydberg atoms exhibit interactions over great distances (∼ μm), where the interactions can be controlled externally. The range of exotic properties makes them an interesting subject in various fields of research, Rydberg atoms are used in cavity quantum electrodynamics [2,3], in controlled chemical reactions by mechanical manipulation [4], serve as a model system for dipole-mediated energy transport in biological systems [5], can be used as a non-linear medium to mediate single-photon interactions [6,7] and have been proposed in several ways for quantum information processing [9][10][11][12]. However, this also means that the strong interaction will not be limited to surrounding atoms but that they also couple to condensed matter, bulk surfaces, in the vicinity. See Fig. 1 for an overview of Rydberg-surface interactions.a
To systematically validate the safe behavior of automated vehicles (AV), the aim of scenario-based testing is to cluster the infinite situations an AV might encounter into a finite set of functional scenarios. Every functional scenario, however, can still manifest itself in a vast amount of variations. Thus, metamodels are often used to perform analyses or to select specific variations for examination. However, despite the safety criticalness of AV testing, metamodels are usually seen as a part of an overall approach, and their predictions are not further examined. In this paper, we analyze the predictive performance of Gaussian processes (GP), deep Gaussian processes, extra-trees (ET), and Bayesian neural networks (BNN), considering four scenarios with 5 to 20 inputs. Building on this, we introduce and evaluate an iterative approach to efficiently select test cases. Our results show that regarding predictive performance, the appropriate selection of test cases is more important than the choice of metamodels. While their great flexibility allows BNNs to benefit from large amounts of data and to model even the most complex scenarios, less flexible models like GPs can convince with higher reliability. This implies that relevant test cases have to be explored using scalable virtual environments and flexible models so that more realistic test environments and more trustworthy models can be used for targeted testing and validation.
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