On the multi-orbital band structure and itinerant magnetism of iron-based superconductors

This paper explains the multi-orbital band structures and itinerant magnetism of the iron-pnictide and chalcogenides. We first describe the generic band structure of an isolated FeAs layer. Use of its Abelian glide-mirror group allows us to reduce the primitive cell to one FeAs unit. From density-functional theory, we generate the set of eight Fe $d$ and As $p$ localized Wannier functions for LaOFeAs and their tight-binding (TB) Hamiltonian, $h(k)$. We discuss the topology of the bands, i.e. allowed and avoided crossings, the origin of the d6 pseudogap, as well as the role of the As $p$ orbitals and the elongation of the FeAs$_{4}$ tetrahedron. We then couple the layers, mainly via interlayer hopping between As $p_{z}$ orbitals, and give the formalism for simple and body-centered tetragonal stackings. This allows us to explain the material-specific 3D band structures. Due to the high symmetry, several level inversions take place as functions of $k_{z}$ or pressure, resulting in linear band dispersions (Dirac cones). The underlying symmetry elements are, however, easily broken, so that the Dirac points are not protected, nor pinned to the Fermi level. From the paramagnetic TB Hamiltonian, we form the band structures for spin spirals with wavevector $q$ by coupling $h(k)$ and $h (k+q)$. The band structure for stripe order is studied as a function of the exchange potential, $\Delta$, using Stoner theory. Gapping of the Fermi surface (FS) for small $\Delta$ requires matching of FS dimensions (nesting) and $d$-orbital characters. The origin of the propeller-shaped FS is explained. Finally, we express the magnetic energy as the sum over band-structure energies, which enables us to understand to what extent the magnetic energies might be described by a Heisenberg Hamiltonian, and the interplay between the magnetic moment and the elongation of the FeAs4 tetrahedron

Magnetism and its microscopic origin in iron-based high-temperature superconductors

High-temperature superconductivity in the iron-based materials emerges from, or sometimes coexists with, their metallic or insulating parent compound states. This is surprising since these undoped states display dramatically different antiferromagnetic (AF) spin arrangements and N$\rm \acute{e}$el temperatures. Although there is general consensus that magnetic interactions are important for superconductivity, much is still unknown concerning the microscopic origin of the magnetic states. In this review, progress in this area is summarized, focusing on recent experimental and theoretical results and discussing their microscopic implications. It is concluded that the parent compounds are in a state that is more complex than implied by a simple Fermi surface nesting scenario, and a dual description including both itinerant and localized degrees of freedom is needed to properly describe these fascinating materials.Comment: 14 pages, 4 figures, Review article, accepted for publication in Nature Physic

Magnetic interactions in iron superconductors: A review

High temperature superconductivity in iron pnictides and chalcogenides emerges when a magnetic phase is suppressed. The multi-orbital character and the strength of correlations underlie this complex phenomenology, involving magnetic softness and anisotropies, with Hund's coupling playing an important role. We review here the different theoretical approaches used to describe the magnetic interactions in these systems. We show that taking into account the orbital degree of freedom allows us to unify in a single phase diagram the main mechanisms proposed to explain the (\pi,0) order in iron pnictides: the nesting-driven, the exchange between localized spins, and the Hund induced magnetic state with orbital differentiation. Comparison of theoretical estimates and experimental results helps locate the Fe superconductors in the phase diagram. In addition, orbital physics is crucial to address the magnetic softness, the doping dependent properties, and the anisotropies.Comment: Invited review article for a focus issue of Comptes Rendus Physique: 26 pages, 10 figures. Revised version, as accepted. Small changes throughout the text plus new subsection (Sec. IIIE

Review on Superconducting Materials

Short review of the topical comprehension of the superconductor materials classes Cuprate High-Temperature Superconductors, other oxide superconductors, Iron-based Superconductors, Heavy-Fermion Superconductors, Nitride Superconductors, Organic and other Carbon-based Superconductors and Boride and Borocarbide Superconductors, featuring their present theoretical understanding and their aspects with respect to technical applications.Comment: A previous version of this article has been published in \" Applied Superconductivity: Handbook on Devices and Applications \", Wiley-VCH ISBN: 978-3-527-41209-9. The new extended and updated version will be published in \" Encyclopedia of Applied Physics \", Wiley-VC

Towards Mobility Data Science (Vision Paper)

Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of GPS-equipped mobile devices and other inexpensive location-tracking technologies, mobility data is collected ubiquitously. In recent years, the use of mobility data has demonstrated significant impact in various domains including traffic management, urban planning, and health sciences. In this paper, we present the emerging domain of mobility data science. Towards a unified approach to mobility data science, we envision a pipeline having the following components: mobility data collection, cleaning, analysis, management, and privacy. For each of these components, we explain how mobility data science differs from general data science, we survey the current state of the art and describe open challenges for the research community in the coming years.Comment: Updated arXiv metadata to include two authors that were missing from the metadata. PDF has not been change

Mobility Data Science (Dagstuhl Seminar 22021)

This report documents the program and the outcomes of Dagstuhl Seminar 22021 "Mobility Data Science". This seminar was held January 9-14, 2022, including 47 participants from industry and academia. The goal of this Dagstuhl Seminar was to create a new research community of mobility data science in which the whole is greater than the sum of its parts by bringing together established leaders as well as promising young researchers from all fields related to mobility data science. Specifically, this report summarizes the main results of the seminar by (1) defining Mobility Data Science as a research domain, (2) by sketching its agenda in the coming years, and by (3) building a mobility data science community. (1) Mobility data science is defined as spatiotemporal data that additionally captures the behavior of moving entities (human, vehicle, animal, etc.). To understand, explain, and predict behavior, we note that a strong collaboration with research in behavioral and social sciences is needed. (2) Future research directions for mobility data science described in this report include a) mobility data acquisition and privacy, b) mobility data management and analysis, and c) applications of mobility data science. (3) We identify opportunities towards building a mobility data science community, towards collaborations between academic and industry, and towards a mobility data science curriculum

Psychometric properties of the German version of the fears of compassion scales

The cultivation of compassion is associated with beneficial effects on physical and psychological health, satisfaction with life and social relationships. However, some individuals, especially those high in psychopathological symptoms or those with particular disorders such as borderline personality disorder (BPD) may demonstrate pronounced fears of engagement in compassionate experiences or behaviours. Furthermore, fears of compassion have been found to impede progress in psychotherapy. The 38‐item fears of compassion scales (FCS) is a self‐report questionnaire for measuring trait levels of fears of compassion (a) one receives from others (FCFO), (b) one feels towards others (FCTO) and (c) one feels for oneself (self‐compassion; FSC). The FCS is an internationally used instrument of proven validity and reliability in both clinical and nonclinical samples. In the present study, a German translation of the FCS including its three subscales was provided, and the psychometric properties were examined in 430 participants from four different samples: (a) a sample from the general population; (b) a mixed sample of psychiatric residential and outpatients; (c) a clinical sample of residential and outpatients with a primary diagnosis of BPD and (d) a sample of healthy control participants. Internal consistencies were excellent for the German version of the FSC and acceptable to excellent for its subscales. Correlations with established measures of mental health demonstrate its validity. Additionally, the German FCS discriminates significantly between individuals from the general population and patients, thus supporting its specificity. The German FCS is suitable to detect potential obstacles in cultivating compassion in psychotherapeutic treatments and beyond.N/

Spin-Density-Wave Gap with Dirac Nodes and Two-Magnon Raman Scattering in BaFe2As2

Raman selection rules for electronic and magnetic excitations in BaFe2As2 were theoretically investigated and applied them to the separate detection of the nodal and anti-nodal gap excitations at the spin density wave (SDW) transition and the separate detection of the nearest and the next nearest neighbor exchange interaction energies. The SDW gap has Dirac nodes, because many orbitals participate in the electronic states near the Fermi energy. Using a two-orbital band model the electronic excitations near the Dirac node and the anti-node are found to have different symmetries. Applying the symmetry difference to Raman scattering the nodal and anti-nodal electronic excitations are separately obtained. The low-energy spectra from the anti-nodal region have critical fluctuation just above TSDW and change into the gap structure by the first order transition at TSDW, while those from the nodal region gradually change into the SDW state. The selection rule for two-magnon scattering from the stripe spin structure was obtained. Applying it to the two-magnon Raman spectra it is found that the magnetic exchange interaction energies are not presented by the short-range superexchange model, but the second derivative of the total energy of the stripe spin structure with respect to the moment directions. The selection rule and the peak energy are expressed by the two-magnon scattering process in an insulator, but the large spectral weight above twice the maximum spin wave energy is difficult to explain by the decayed spin wave. It may be explained by the electronic scattering of itinerant carriers with the magnetic self-energy in the localized spin picture or the particle-hole excitation model in the itinerant spin picture. The magnetic scattering spectra are compared to the insulating and metallic cuprate superconductors whose spins are believed to be localized.Comment: 38 pages, 11 figure

GIS and Transport Modeling – Strengthening the Spatial Perspective

The movement and transport of people and goods is spatial by its very nature. Thus, geospatial fundamentals of transport systems need to be adequately considered in transport models. Until recently this was not always the case. Instead, transport research and geography evolved widely independently in domain silos. However, driven by recent conceptual, methodological and technical developments the need for an integrated approach is obvious. This paper attempts to outline the potential of Geographical Information Systems (GIS) for transport modeling. We identify three fields of transport modeling where the spatial perspective can significantly contribute to a more efficient modeling process and more reliable model results, namely geospatial data, disaggregated transport models and the role of geo-visualization. For these three fields, available findings from various domains are compiled before open aspects are formulated as research questions. The overall aim of this paper is to strengthen the spatial perspective in transport modeling and to call for a further integration of GIS in the domain of transport modeling