Front and Turing patterns induced by Mexican-hat-like nonlocal feedback

We consider the effects of a Mexican-hat-shaped nonlocal spatial coupling, i.e., symmetric long-range inhibition superimposed with short-range excitation, upon front propagation in a model of a bistable reaction-diffusion system. We show that the velocity of front propagation can be controlled up to a certain coupling strength beyond which spatially periodic patterns, such as Turing patterns or coexistence of spatially homogeneous solutions and Turing patterns, may be induced. This behaviour is investigated through a linear stability analysis of the spatially homogeneous steady states and numerical investigations of the full nonlinear equations in dependence upon the nonlocal coupling strength and the ratio of the excitatory and inhibitory coupling ranges.Comment: Accepted in EP

Nonlinearity of local dynamics promotes multi-chimeras

Chimera states are complex spatio-temporal patterns in which domains of synchronous and asynchronous dynamics coexist in coupled systems of oscillators. We examine how the character of the individual elements influences chimera states by studying networks of nonlocally coupled Van der Pol oscillators. Varying the bifurcation parameter of the Van der Pol system, we can interpolate between regular sinusoidal and strongly nonlinear relaxation oscillations, and demonstrate that more pronounced nonlinearity induces multi-chimera states with multiple incoherent domains. We show that the stability regimes for multi-chimera states and the mean phase velocity profiles of the oscillators change significantly as the nonlinearity becomes stronger. Furthermore, we reveal the influence of time delay on chimera patterns

Evaluation of large language models for assessing code maintainability

Increased availability of open-source software repositories and recent advances in code analysis using large language models (LLMs) has triggered a wave of new work to automate software engineering tasks that were previously very difficult to automate. In this paper, we investigate a recent line of work that hypothesises that comparing the probability of code generated by LLMs with the probability the current code would have had can indicate potential quality problems. We investigate the association between the cross-entropy of code generated by ten different models (based on GPT2 and Llama2) and the following quality aspects: readability, understandability, complexity, modularisation, and overall maintainability assessed by experts and available in an benchmark dataset. Our results show that, controlling for the number of logical lines of codes (LLOC), cross-entropy computed by LLMs is indeed a predictor of maintainability on a class level (the higher the cross-entropy the lower the maintainability). However, this relation is reversed when one does not control for LLOC (e.g., comparing small classes with longer ones). Furthermore, while the complexity of LLMs affects the range of cross-entropy (smaller models tend to have a wider range of cross-entropy), this plays a significant role in predicting maintainability aspects. Our study limits itself on ten different pretrained models (based on GPT2 and Llama2) and on maintainability aspects collected by Schnappinger et al. When controlling for logical lines of code (LLOC), cross-entropy is a predictor of maintainability. However, while related work has shown the potential usefulness of cross-entropy at the level of tokens or short sequences, at the class level this criterion alone may prove insufficient to predict maintainability and further research is needed to make best use of this information in practice.Comment: 14 pages, 4 figures, 8 table

Impact du comportement des utilisateurs dans les réseaux pair-à pair, modélisation et simulation multi-agents

Network access and services are becoming ubiquitous, and the number of their users and usage is still growing rapidily. Controlling those networks is incresaingly complex. At the same time, the notion of infrastructure is also shaken by new technologies such as P2P or adhoc networks. Standard control and evaluation mechanism are not taking into account the complexity, diversity and dynamicity of the users' behavior, which are the subject of study of multi-agent simulation. This document explores the opportunity to bridge the usual networking modelling and simulation tools with the multi-agent approach

Statistical mechanics of the self-gravitating gases

The self-gravitating systems are formed by particles interacting through gravity. They describe structure formation in the universe. As a consequence of the long range interaction of gravity, they are inhomogeneous even at thermal equilibrium. We study the self-gravitating systems with several kinds of particles and the self-gravitating systems in the presence of the cosmological constant $Lambda$. We formulate the statistical mechanics and the mean field approach describing the gaseous phase. We explicitely compute the density of particles and thermodynamic quantities. The presence of $Lambda$ extends the domain of stability of the gaseous phase. Monte Carlo simulations show that the mean field describes the gaseous phase with an excellent accuracy. Scalling law of the self-gravitating systems with several kinds of particles is found. At the critical point the fractal dimension is independant of their composition and is $1.6...$~

Mod\'elisation multi-niveaux dans AA4MM

In this article, we propose to represent a multi-level phenomenon as a set of interacting models. This perspective makes the levels of representation and their relationships explicit. To deal with coherence, causality and coordination issues between models, we rely on AA4MM, a metamodel dedicated to such a representation. We illustrate our proposal and we show the interest of our approach on a flocking phenomenon

Dynamics of reaction-diffusion patterns controlled by asymmetric nonlocal coupling as limiting case of differential advection

A one-component bistable reaction-diffusion system with asymmetric nonlocal coup ling is derived as limiting case of a two-component activator-inhibitor reaction -diffusion model with differential advection. The effects of asymmetric nonlocal couplings in such a bistable reaction-diffusi on system are then compared to the previously studied case of a system with symm etric nonlocal coupling. We carry out a linear stability analysis of the spatially homogeneous steady sta tes of the model and numerical simulations of the model to show how the asymmetr ic nonlocal coupling controls and alters the steady states and the front dynamic s in the system. In a second step, a third fast reaction-diffusion equation is included which ind uces the formation of more complex patterns. A linear stability analysis predicts traveling waves for asymmetric nonlocal coupling in contrast to a stationary Turing patterns for a system with symmetric nonlocal coupling. These findings are verified by direct numerical integration of the full equations with nonlocal coupling.Comment: 9 pages, 10 figures, submitte

Badgers: generating data quality deficits with Python

Generating context specific data quality deficits is necessary to experimentally assess data quality of data-driven (artificial intelligence (AI) or machine learning (ML)) applications. In this paper we present badgers, an extensible open-source Python library to generate data quality deficits (outliers, imbalanced data, drift, etc.) for different modalities (tabular data, time-series, text, etc.). The documentation is accessible at https://fraunhofer-iese.github.io/badgers/ and the source code at https://github.com/Fraunhofer-IESE/badgersComment: 17 pages, 16 figure