Active Learning Metamodels for ATM Simulation Modeling

Transportation systems are particularly prone to exhibiting overwhelming complexity on account of the numerous involved variables and their interrelationships, unknown stochastic phenomena, and ultimately human behavior. Simulation approaches are commonly used tools to describe and study such intricate real-world systems. Despite their obvious advantages,simulation models can still end up being quite complex themselves. The field of Air Traffic Management (ATM) modeling is no stranger to such concerns, as it traditionally involves laborious and systematic analyses built upon computationally heavy simulation models. This rather frequent shortcoming can be addressed by employing simulation metamodels combined with active learning strategies to approximate the input-output mappings inherently defined by the simulation models in an efficient way. In this work, we propose an exploration framework that integrates active learning and simulation metamodeling in a single unified approach to address recurrent computational bottlenecks typically associated with intense performance impact assessments within the field of ATM. Our methodology is designed to systematically explore the simulation input space in an efficient and self-guided manner, ultimately providing ATM practitioners with meaningful insights concerning the simulation models under study. Using a fully developed state-of-the-art ATM simulator and employing a Gaussian Process as a metamodel, we show that active learning is indeed capable of enhancing both the modeling and performances of simulation metamodeling by strategically avoiding redundant computer experiments and predicting simulation outputs values

Active Learning for Air Traffic Management Simulation Metamodeling

Transportation systems are particularly prone to exhibiting overwhelming complexity on account of the numerous involved variables, corresponding interrelationships, and the unpredictability of human behavior. Simulation approaches are commonly used tools to describe and study such intricate real-world systems. Despite their clear advantages, these models can too suffer from high complexity and computational hindrances, especially when designed along with fine detail. The field of Air Traffic Management (ATM) modeling is no stranger to such concerns, as it traditionally involves exhausting and manual-driven intense analyses built upon computationally heavy simulation models. This rather frequent shortcoming can be addressed by employing simulation metamodels combined with active learning strategies to approximate, via fast functions, the input-output mappings inherently defined by the simulation models in an efficient way. In this work, we propose an exploration framework that integrates active learning and simulation metamodeling in a single unified approach to address recurrent computational bottlenecks typically associated with intense performance impact assessments within the field of ATM. Our methodology is designed to systematically explore the simulation input space in an efficient and self-guided manner, ultimately providing ATM practitioners with meaningful insights concerning the simulation models under study. Using a fully developed state-of-the-art ATM simulator and employing a Gaussian Process as a metamodel, we show that active learning is indeed capable of enhancing both the modeling and performances of simulation metamodeling by strategically avoiding redundant computer experiments and predicting simulation outputs values given a pre-specified input region

Spherical-box approach for resonances in presence of Coulomb interaction

The spherical-box approach is extended to calculate the resonance parameters and the real part of the wave function for single particle resonances in a potential containing the long-range Coulomb interaction. A model potential is taken to demonstrate the ability and accuracy of this approach. The calculated resonance parameters are compared with available results from other methods. It is shown that in the presence of the Coulomb interaction, the spherical-box approach works well for not so broad resonances. In particular, for very narrow resonances, the present method gives resonance parameters in a very high precision.Comment: 10 pages, 5 EPS figures; to be published in J. Phys.

Delta-Function Potential with a Complex Coupling

We explore the Hamiltonian operator H=-d^2/dx^2 + z \delta(x) where x is real, \delta(x) is the Dirac delta function, and z is an arbitrary complex coupling constant. For a purely imaginary z, H has a (real) spectral singularity at E=-z^2/4. For \Re(z)<0, H has an eigenvalue at E=-z^2/4. For the case that \Re(z)>0, H has a real, positive, continuous spectrum that is free from spectral singularities. For this latter case, we construct an associated biorthonormal system and use it to perform a perturbative calculation of a positive-definite inner product that renders H self-adjoint. This allows us to address the intriguing question of the nonlocal aspects of the equivalent Hermitian Hamiltonian for the system. In particular, we compute the energy expectation values for various Gaussian wave packets to show that the non-Hermiticity effect diminishes rapidly outside an effective interaction region.Comment: Published version, 14 pages, 2 figure

The association between real-life markers of phone use and cognitive performance, health-related quality of life and sleep

INTRODUCTION: The real-life short-term implications of electromagnetic fields (RF-EMF) on cognitive performance and health-related quality of life have not been well studied. The SPUTNIC study (Study Panel on Upcoming Technologies to study Non-Ionizing radiation and Cognition) aimed to investigate possible correlations between mobile phone radiation and human health, including cognition, health-related quality of life and sleep. METHODS: Adult participants tracked various daily markers of RF-EMF exposures (cordless calls, mobile calls, and mobile screen time 4 h prior to each assessment) as well as three health outcomes over ten study days: 1) cognitive performance, 2) health-related quality of life (HRQoL), and 3) sleep duration and quality. Cognitive performance was measured through six "game-like" tests, assessing verbal and visuo-spatial performance repeatedly. HRQoL was assessed as fatigue, mood and stress on a Likert-scale (1-10). Sleep duration and efficiency was measured using activity trackers. We fitted mixed models with random intercepts per participant on cognitive, HRQoL and sleep scores. Possible time-varying confounders were assessed at daily intervals by questionnaire and used for model adjustment. RESULTS: A total of 121 participants ultimately took part in the SPUTNIC study, including 63 from Besancon and 58 from Basel. Self-reported wireless phone use and screen time were sporadically associated with visuo-spatial and verbal cognitive performance, compatible with chance findings. We found a small but robust significant increase in stress 0.03 (0.00-0.06; on a 1-10 Likert-scale) in relation to a 10-min increase in mobile phone screen time. Sleep duration and quality were not associated with either cordless or mobile phone calls, or with screen time. DISCUSSION: The study did not find associations between short-term RF-EMF markers and cognitive performance, HRQoL, or sleep duration and quality. The most consistent finding was increased stress in relation to more screen time, but no association with cordless or mobile phone call time

Pseudo-time Schroedinger equation with absorbing potential for quantum scattering calculations

The Schroedinger equation with an energy-dependent complex absorbing potential, associated with a scattering system, can be reduced for a special choice of the energy-dependence to a harmonic inversion problem of a discrete pseudo-time correlation function. An efficient formula for Green's function matrix elements is also derived. Since the exact propagation up to time 2t can be done with only t real matrix-vector products, this gives an unprecedently efficient scheme for accurate calculations of quantum spectra for possibly very large systems.Comment: 9 page

From spin liquid to magnetic ordering in the anisotropic kagome Y-Kapellasite Y3Cu9(OH)19Cl8: a single crystal study

Y3Cu9(OH)19Cl8 realizes an original anisotropic kagome model hosting a rich magnetic phase diagram [M. Hering et al, npj Computational Materials 8, 1 (2022)]. We present an improved synthesis of large phase-pure single crystals via an external gradient method. These crystals were investigated in details by susceptibility, specific heat, thermal expansion, neutron scattering and local muSR and NMR techniques. At variance with polycristalline samples, the study of single crystals gives evidence for subtle structural instabilities at 33K and 13K which preserve the global symmetry of the system and thus the magnetic model. At 2.1K the compound shows a magnetic transition to a coplanar (1/3,1/3) long range order as predicted theoretically. However our analysis of the spin wave excitations yields magnetic interactions which locate the compound closer to the phase boundary to a classical jammed spin liquid phase. Enhanced quantum fluctuations at this boundary may be responsible for the strongly reduced ordered moment of the Cu2+, estimated to be 0.075muB from muSR

Electrons imitating light: Frustrated supercritical collapse in charged arrays on graphene

The photon-like electronic dispersion of graphene bestows its charge carriers with unusual confinement properties that depend strongly on the geometry and strength of the surrounding potential. Here we report bottom-up synthesis of atomically-precise one-dimensional (1D) arrays of point charges aimed at exploring supercritical confinement of carriers in graphene for new geometries. The arrays were synthesized by arranging F4TCNQ molecules into a 1D lattice on back-gated graphene devices, allowing precise tuning of both the molecular charge state and the array periodicity. Dilute arrays of ionized F4TCNQ molecules are seen to behave like isolated subcritical charges but dense arrays show emergent supercriticality. In contrast to compact supercritical clusters, extended 1D charge arrays exhibit both supercritical and subcritical characteristics and belong to a new physical regime termed frustrated supercritical collapse. Here carriers in the far-field are attracted by a supercritical charge distribution, but have their fall to the center frustrated by subcritical potentials in the near-field, similar to the trapping of light by a dense cluster of stars in general relativity

Pauli's Principle in Probe Microscopy

Exceptionally clear images of intramolecular structure can be attained in dynamic force microscopy through the combination of a passivated tip apex and operation in what has become known as the "Pauli exclusion regime" of the tip-sample interaction. We discuss, from an experimentalist's perspective, a number of aspects of the exclusion principle which underpin this ability to achieve submolecular resolution. Our particular focus is on the origins, history, and interpretation of Pauli's principle in the context of interatomic and intermolecular interactions.Comment: This is a chapter from "Imaging and Manipulation of Adsorbates using Dynamic Force Microscopy", a book which is part of the "Advances in Atom and Single Molecule Machines" series published by Springer [http://www.springer.com/series/10425]. To be published late 201

Probing the Role of Interlayer Coupling and Coulomb Interactions on Electronic Structure in Few-Layer MoSe2 Nanostructures

Despite the weak nature of interlayer forces in transition metal dichalcogenide (TMD) materials, their properties are highly dependent on the number of layers in the few-layer two-dimensional (2D) limit. Here, we present a combined scanning tunneling microscopy/spectroscopy and GW theoretical study of the electronic structure of high quality single- and few-layer MoSe2 grown on bilayer graphene. We find that the electronic (quasiparticle) bandgap, a fundamental parameter for transport and optical phenomena, decreases by nearly one electronvolt when going from one layer to three due to interlayer coupling and screening effects. Our results paint a clear picture of the evolution of the electronic wave function hybridization in the valleys of both the valence and conduction bands as the number of layers is changed. This demonstrates the importance of layer number and electron-electron interactions on van der Waals heterostructures, and helps to clarify how their electronic properties might be tuned in future 2D nanodevices