Kirsten Bergmann

Electrical detection of magnetic skyrmions by tunnelling non-collinear magnetoresistance

Magnetic skyrmions are localized non-collinear spin textures with a high potential for future spintronic applications. Skyrmion phases have been discovered in a number of materials and a focus of current research is to prepare, detect and manipulate individual skyrmions for implementation in devices. The local experimental characterization of skyrmions has been performed by, for example, Lorentz microscopy or atomic-scale tunnel magnetoresistance measurements using spin-polarized scanning tunnelling microscopy. Here we report a drastic change of the differential tunnel conductance for magnetic skyrmions that arises from their non-collinearity: mixing between the spin channels locally alters the electronic structure, which makes a skyrmion electronically distinct from its ferromagnetic environment. We propose this tunnelling non-collinear magnetoresistance as a reliable all-electrical detection scheme for skyrmions with an easy implementation into device architectures.

Electric-field-driven switching of individual magnetic skyrmions

Controlling magnetism with electric fields is a key challenge to develop future energy-efficient devices. The present magnetic information technology is mainly based on writing processes requiring either local magnetic fields or spin torques, but it has also been demonstrated that magnetic properties can be altered on the application of electric fields. This has been ascribed to changes in magnetocrystalline anisotropy caused by spin-dependent screening and modifications of the band structure, changes in atom positions or differences in hybridization with an adjacent oxide layer. However, the switching between states related by time reversal, for example magnetization up and down as used in the present technology, is not straightforward because the electric field does not break time-reversal symmetry. Several workarounds have been applied to toggle between bistable magnetic states with electric fields, including changes of material composition as a result of electric fields. Here we demonstrate that local electric fields can be used to switch reversibly between a magnetic skyrmion and the ferromagnetic state. These two states are topologically inequivalent, and we find that the direction of the electric field directly determines the final state. This observation establishes the possibility to combine electric-field writing with the recently envisaged skyrmion racetrack-type memories.

Information Transfer by Vector Spin Chirality in Finite Magnetic Chains

Vector spin chirality is one of the fundamental characteristics of complex magnets. For a one-dimensional spin-spiral state it can be interpreted as the handedness, or rotational sense of the spiral. Here, using spin-polarized scanning tunneling microscopy, we demonstrate the occurrence of an atomic-scale spin spiral in finite individual bi-atomic Fe chains on the (5×1)-Ir(001) surface. We show that the broken inversion symmetry at the surface promotes one direction of the vector spin chirality, leading to a unique rotational sense of the spiral in all chains. Correspondingly, changes in the spin direction of one chain end can be probed tens of nanometers away, suggesting a new way of transmitting information about the state of magnetic objects on the nanoscale.

MULTIMODAL COMMUNICATION FROM MULTIMODAL THINKING|TOWARDS AN INTEGRATED MODEL OF SPEECH AND GESTURE PRODUCTION

A computational model for the automatic production of combined speech and iconic gesture is presented. The generation of multimodal behavior is grounded in processes of multimodal thinking, in which a propositional representation interacts and interfaces with an imagistic representation of visuo-spatial imagery. An integrated architecture for this is described, in which the planning of content and the planning of form across both modalities proceed in an interactive manner. Results from an empirical study are reported that inform the on-the-spot formation of gestures.

GNetIc --- Using Bayesian Decision Networks for Iconic Gesture Generation

Expressing spatial information with iconic gestures is abundant in human communication and requires to transform a referent representation into resembling gestural form. This task is challenging as the mapping is determined by the visuo-spatial features of the referent, the overall discourse context as well as concomitant speech, and its outcome varies considerably across different speakers. We present a framework, GNetIc, that combines data-driven with model-based techniques to model the generation of iconic gestures with Bayesian decision networks. Drawing on extensive empirical data, we discuss how this method allows for simulating speaker-specific vs. speaker-independent gesture production. Modeling results from a prototype implementation are presented and evaluated.

Individualized gesturing outperforms average gesturing: evaluating gesture production in virtual humans

How does a virtual agents gesturing behavior influence the users perception of communication quality and the agents personality? This question was investigated in an evaluation study of co-verbal iconic gestures produced with the Bayesian network-based production model GNetIc. A network learned from a corpus of several speakers was compared with networks learned from individual speaker data, as well as two control conditions. Results showed that automatically GNetIc-generated gestures increased the perceived quality of an object description given by a virtual human. Moreover, gesturing behavior generated with individual speaker networks was rated more positively in terms of likeability, competence and human-likeness.

Interface-induced chiral domain walls, spin spirals and skyrmions revealed by spin-polarized scanning tunneling microscopy

The spin textures of ultra-thin magnetic layers exhibit surprising variety. The loss of inversion symmetry at the interface of the magnetic layer and substrate gives rise to the so-called Dzyaloshinskii-Moriya interaction which favors non-collinear spin arrangements with unique rotational sense. Here we review the application of spin-polarized scanning tunneling microscopy to such systems, which has led to the discovery of interface-induced chiral domain walls and spin spirals. Recently, different interface-driven skyrmion lattices have been found, and the writing as well as the deleting of individual skyrmions based on local spin-polarized current injection has been demonstrated. These interface-induced non-collinear magnetic states offer new exciting possibilities to study fundamental magnetic interactions and to tailor material properties for spintronic applications.

A second chance to make a first impression? how appearance and nonverbal behavior affect perceived warmth and competence of virtual agents over time

First impressions of others are fundamental for the further development of a relationship and are thus of major importance for the design of virtual agents, too. We addressed the question whether there is a second chance for first impressions with regard to the major dimensions of social cognition–warmth and competence. We employed a novel experimental set-up that combined agent appearance (robot-like vs. human-like) and agent behavior (gestures present vs. absent) of virtual agents as between-subject factors with a repeated measures design. Results indicate that ratings of warmth depend on interaction effects of time and agent appearance, while evaluations of competence seem to depend on the interaction of time and nonverbal behavior. Implications of these results for basic and applied research on intelligent virtual agents will be discussed .

An Alignment-Capable Microplanner for Natural Language Generation

Alignment of interlocutors is a well known psycholinguistic phenomenon of great relevance for dialogue systems in general and natural language generation in particular. In this paper, we present the alignment-capable microplanner SPUD prime. Using a priming-based model of interactive alignment, it is flexible enough to model the alignment behaviour of human speakers to a high degree. This will allow for further investigation of which parameters are important to model alignment and how the human--computer interaction changes when the computer aligns to its users.

Modeling the semantic coordination of speech and gesture under cognitive and linguistic constraints

This paper addresses the semantic coordination of speech and gesture, a major prerequisite when endowing virtual agents with convincing multimodal behavior. Previous research has focused on building rule- or data-based models specific for a particular language, culture or individual speaker, but without considering the underlying cognitive processes. We present a flexible cognitive model in which both linguistic as well as cognitive constraints are considered in order to simulate natural semantic coordination across speech and gesture. An implementation of this model is presented and first simulation results, compatible with empirical data from the literature are reported.