Mapping the Conditions for Hydrodynamic Instability on Steady State Accretion Models of Protoplanetary Disks

Hydrodynamical instabilities in disks around young stars depend on the thermodynamic stratification of the disk and on the local rate of thermal relaxation. Here, we map the spatial extent of unstable regions for the Vertical Shear Instability (VSI), the Convective OverStability (COS), and the amplification of vortices via the Subcritical Baroclinic Instability (SBI). We use steady state accretion disk models, including stellar irradiation, accretion heating and radiative transfer. We determine the local radial and vertical stratification and thermal relaxation rate in the disk, in dependence of the stellar mass, disk mass and mass accretion rate. We find that passive regions of disks - i.e. the midplane temperature dominated by irradiation - are COS unstable about one pressure scale height above the midplane and VSI unstable at radii $> 10 \, \text{au}$. Vortex amplification via SBI should operate in most parts of active and passive disks. For active parts of disks (midplane temperature determined by accretion power) COS can become active down to the midplane. Same is true for the VSI because of the vertically adiabatic stratification of an internally heated disk. If hydro instabilities or other non-ideal MHD processes are able to create $\alpha$-stresses ($> 10^{-5}$) and released accretion energy leads to internal heating of the disk, hydrodynamical instabilities are likely to operate in significant parts of the planet forming zones in disks around young stars, driving gas accretion and flow structure formation. Thus hydro-instabilities are viable candidates to explain the rings and vortices observed with ALMA and VLT.Comment: 24 pages, 13 figures, Accepted for publication in Ap

Neuromorphic Learning towards Nano Second Precision

Temporal coding is one approach to representing information in spiking neural networks. An example of its application is the location of sounds by barn owls that requires especially precise temporal coding. Dependent upon the azimuthal angle, the arrival times of sound signals are shifted between both ears. In order to deter- mine these interaural time differences, the phase difference of the signals is measured. We implemented this biologically inspired network on a neuromorphic hardware system and demonstrate spike-timing dependent plasticity on an analog, highly accelerated hardware substrate. Our neuromorphic implementation enables the resolution of time differences of less than 50 ns. On-chip Hebbian learning mechanisms select inputs from a pool of neurons which code for the same sound frequency. Hence, noise caused by different synaptic delays across these inputs is reduced. Furthermore, learning compensates for variations on neuronal and synaptic parameters caused by device mismatch intrinsic to the neuromorphic substrate.Comment: 7 pages, 7 figures, presented at IJCNN 2013 in Dallas, TX, USA. IJCNN 2013. Corrected version with updated STDP curves IJCNN 201

FAIR DO Cookbook – Recipes for FAIR Digital Objects

Working in the realm of FAIR Digital Objects can be very abstract and sometimes overwhelming. There are so many aspects which have to be addressed in order to create a first FAIR Digital Object. The FAIR DO Cookbook aims to guide researchers and explain all required knowledge, ingredients, and steps to execute. The target audience are people building, controlling or maintaining infrastructure or software that should work with FAIR DOs in come way, as well as people interested in types, profiles, and PIDs work and how they can be created

Regional dispersion of cooperation activities as success factor of innovation oriented SME

In this paper, we analyze the relationships between different types of innovation and collaboration, given the varying geographical distance of the latter. The study is based on the data of the research project 'KompNet 2011 - Factors determining the success of regional innovation networks', which examines the innovation activities of small and medium-sized enterprises (SME) in and closely around Jena (Thuringia). The aim of this paper is to explore to what extent spatial reach of collaboration linkages determines innovation orientation and innovative behavior. That means: Innovation performance could be positively related to (a) to a high intensity of local collaboration, (b) the intensity of international collaboration or (c) neither regional nor (inter)national collaborations. In a first step we summarize the relevant literature which comprises aspects of our central subject under investigation. We additionally discuss the necessity of keeping in mind several control variables for theoretical and empirical reasons. In the following we present descriptive analyses relating to the regional reach of collaboration in general, the impact of collaboration on innovation and the links between the regional reach of cooperation and different forms of innovation, i.e. product, process, marketing and organizational innovation. In a final step we discuss the results of several regression models. We observe that there is no significant influence of the geographical variables on the innovative performance of SME. Therefore our findings suggest that innovative firms rely on collaboration partners at a variety of spatial distances. The results also show a significant and positive influence of the intensity of competition on the innovativeness of firms in all models. Furthermore product- and process innovations are created by firms with intensive cooperative activities to scientific institutions, while a wide variety of cooperation partners and a strong focus on quality leadership turns out to be important for the development of marketing- and organizational innovations. --cooperation,geographical reach,innovation,intensity of competition,marketing innovation,organizational innovation,process innovation,product innovation,quality leadership,regional dispersion,SME,spatial distance

FAIR DO Lab – A FAIR Digital Object Lab for your research

The FAIR Digital Object Lab is an extendable and adjustable software stack for generic FAIR Digital Object (FAIR DO) tasks. It consists of a set of interacting components with services and tools for creation, validation, discovery, curation, and more. The creation and maintenance of FAIR DOs is not trivial, as their PIDs contain typed record information. They are meant to be machine-actionable, not human-readable. Easing the creation and maintenance of FAIR DOs, as well as making FAIR DOs searchable and human-accessible, are functions of the FAIR DO Lab. While it started as the “FAIR DO Testbed”, development now focuses on production-readiness and user interfaces

The effect of heterogeneity on decorrelation mechanisms in spiking neural networks: a neuromorphic-hardware study

High-level brain function such as memory, classification or reasoning can be realized by means of recurrent networks of simplified model neurons. Analog neuromorphic hardware constitutes a fast and energy efficient substrate for the implementation of such neural computing architectures in technical applications and neuroscientific research. The functional performance of neural networks is often critically dependent on the level of correlations in the neural activity. In finite networks, correlations are typically inevitable due to shared presynaptic input. Recent theoretical studies have shown that inhibitory feedback, abundant in biological neural networks, can actively suppress these shared-input correlations and thereby enable neurons to fire nearly independently. For networks of spiking neurons, the decorrelating effect of inhibitory feedback has so far been explicitly demonstrated only for homogeneous networks of neurons with linear sub-threshold dynamics. Theory, however, suggests that the effect is a general phenomenon, present in any system with sufficient inhibitory feedback, irrespective of the details of the network structure or the neuronal and synaptic properties. Here, we investigate the effect of network heterogeneity on correlations in sparse, random networks of inhibitory neurons with non-linear, conductance-based synapses. Emulations of these networks on the analog neuromorphic hardware system Spikey allow us to test the efficiency of decorrelation by inhibitory feedback in the presence of hardware-specific heterogeneities. The configurability of the hardware substrate enables us to modulate the extent of heterogeneity in a systematic manner. We selectively study the effects of shared input and recurrent connections on correlations in membrane potentials and spike trains. Our results confirm ...Comment: 20 pages, 10 figures, supplement

RDA Collection Registry Adoption

During her carreer, probably every scientist comes to the point where an aggregation of potentially diverse resources is required. May it be measurements of the same sample using different instruments, linking a publication to a certain dataset or providing data, source code and analysis results in a citable manner. The RDA Working Group on Research Data Collections (RDC) has identified the need for leveraging such aggregations in a unified, cross-community way as for sure, each research data management platform offers aggregations in a certain way, but without paying too much attention on interoperability and reusability aspects of such resource collections. In order to overcome this gap, the RDC WG formulated recommendations on how to build up cross-community Research Data Collection Registries taking into account other RDA recommendations like PID Information Types and Type Registries. The final recommendation was published in 2017 together with some first adoptions. At Karlsruhe Institute of Technology, the department „Data Exploitation Methods“ (DEM), which is part of the local computing center „Steinbuch Centre for Computing“, took up the recommendations and implemented a fully featured version of a Collection Registry that is in the meantime available in version 1.1. The poster describes the adoption and full implementation of the Collection Registry which is based on the output of the RDA Working Group on Research Data Collections. It introduces the current implementation of the recommendation and elaborate adaptions, e.g. ETag support and pagination, made compared to the final output of the WG. Furthermore, the poster will present possible usage scenarios and future plans involving the use of the Collection Registry. This work has been supported by the research program ‘Engineering Digital Futures’ of the Helmholtz Association of German Research Centers and the Helmholtz Metadata Collaboration Platform

Exploring the potential of brain-inspired computing

The gap between brains and computers regarding both their cognitive capability and power efficiency is remarkably huge. Brains process information massively in parallel and its constituents are intrinsically self-organizing, while in digital computers the execution of instructions is deterministic and rather serial. The recent progress in the development of dedicated hardware systems implementing physical models of neurons and synapses enables to efficiently emulate spiking neural networks. In this work, we verify the design and explore the potential for brain-inspired computing of such an analog neuromorphic system, called Spikey. We demonstrate the versatility of this highly configurable substrate by the implementation of a rich repertoire of network models, including models for signal propagation and enhancement, general purpose classifiers, cortical models and decorrelating feedback systems. Network emulations on Spikey are highly accelerated and consume less than 1 nJ per synaptic transmission. The Spikey system, hence, outperforms modern desktop computers in terms of fast and efficient network simulations closing the gap to brains. During this thesis the stability, performance and user-friendliness of the Spikey system was improved integrating it into the neuroscientific tool chain and making it available for the community. The implementation of networks suitable to solve everyday tasks, like object or speech recognition, qualifies this technology to be an alternative to conventional computers. Considering the compactness, computational capability and power efficiency, neuromorphic systems may qualify as a valuable complement to classical computation