Search results for "Complex system"
showing 10 items of 226 documents
Analytic vectors, anomalies and star representations
1989
It is hinted that anomalies are not really anomalous since (at least in characteristic examples) they can be related to a lack of common analytic vectors for the Hamiltonian and the observables. We reanalyze the notions of analytic vectors and of local representations of Lie algebras in this light, and show how the notion of preferred observables introduced in the deformation (star product) approach to quantization may help give an anomaly-free formulation to physical problems. Finally, some remarks are made concerning the applicability of these considerations to field theory, especially in two dimensions.
High magnetic fields for fundamental physics
2018
Various fundamental-physics experiments such as measurement of the birefringence of the vacuum, searches for ultralight dark matter (e.g., axions), and precision spectroscopy of complex systems (including exotic atoms containing antimatter constituents) are enabled by high-field magnets. We give an overview of current and future experiments and discuss the state-of-the-art DC- and pulsed-magnet technologies and prospects for future developments.
Implementation of pressure reduction valves in a dynamic water distribution numerical model to control the inequality in water supply
2013
The analysis of water distribution networks has to take into account the variability of users' water demand and the variability of network boundary conditions. In complex systems, e.g. those characterized by the presence of local private tanks and intermittent distribution, this variability suggests the use of dynamic models that are able to evaluate the rapid variability of pressures and flows in the network. The dynamic behavior of the network also affects the performance of valves that are used for controlling the network. Pressure reduction valves (PRVs) are used for controlling pressure and reducing leakages. Highly variable demands can produce significant fluctuation of the PRV set po…
Development of multivariate and network models for the analysis of Big Data: applications in economics, insurance, and social sciences
2020
In questa tesi sviluppo metodi statistici multivariati e di rete per lo studio di sistemi complessi. In particolare, focalizzo la mia analisi sullo studio di reti complesse bipartite e le loro applicazioni a (i) l'economia, per capire l'effetto di contagio tra istituti finanziari e stati sovrani, (ii) la sorveglianza nelle assicurazioni, per individuare comportamenti fraudolenti, e (iii) le scienze sociali, per studiare l'effetto delle politiche del REF sulle eccellenze nella ricerca delle università in UK. In this thesis I develop multivariate statistical and network methods for the study of complex systems. In particular, I focus my analysis on the study of bipartite complex networks and …
COVARIANCE AND CORRELATION ESTIMATORS IN BIPARTITE SYSTEMS
2017
We present a weighted estimator of the covariance and correlation in bipartite complex systems with a double layer of heterogeneity. The advantage provided by the weighted estimators lies in the fact that the unweighted sample covariance and correlation can be shown to possess a bias. Indeed, such a bias affects real bipartite systems, and, for example, we report its effects on two empirical systems, one social and the other biological. On the contrary, our newly proposed weighted estimators remove the bias and are better suited to describe such systems.
The Complex System Theory for the Analysis of Inter-Firm Networks: A Literature Overview and Theoretic Framework
2011
In this paper we discuss the body of knowledge known as complex system theory and its relevance to the analysis of inter-firm networks. We start by addressing the development of systems thinking. Through a literature overview, we point out the main elements for the development of systemic thought from its beginning, through its application in business sciences, to the birth of Complex Systems Theory (CST). With these initial annotations we provide an introduction to the concepts of the complex systems theory. We will underscore those aspects of CST that can be useful to analyze inter-firm networks, in order to highlight the evolutionary dynamics of the networks and to clarify the logical li…
Measuring High-Order Interactions in Rhythmic Processes Through Multivariate Spectral Information Decomposition
2021
Many complex systems in physics, biology and engineering are modeled as dynamical networks and described using multivariate time series analysis. Recent developments have shown that the emergent dynamics of a network system are significantly affected by interactions involving multiple network nodes which cannot be described using pairwise links. While these higher-order interactions can be probed using information-theoretic measures, a rigorous framework to describe them in the frequency domain is still lacking. This work presents an approach for the spectral decomposition of multivariate information measures, capable of identifying higher-order synergistic and redundant interactions betwee…
Case-Sensitivity of Classifiers for WSD: Complex Systems Disambiguate Tough Words Better
2007
We present a novel method for improving disambiguation accuracy by building an optimal ensemble (OE) of systems where we predict the best available system for target word using a priori case factors (e.g. amount of training per sense). We report promising results of a series of best-system prediction tests (best prediction accuracy is 0.92) and show that complex/simple systems disambiguate tough/easy words better. The method provides the following benefits: (1) higher disambiguation accuracy for virtually any base systems (current best OE yields close to 2% accuracy gain over Senseval-3 state of the art) and (2) economical way of building more effective ensembles of all types (e.g. optimal,…
Analysis of neuronal networks in the visual system of the cat using statistical signals--simple and complex cells. Part II.
1978
Superimposing additively a two-dimensional noise process to deterministic input signals (bars) the neurons of area 17 show a class-specific reaction for the task of signal extraction. Moving both parts of the signals simultaneously and varying the signal to noise ratio (S/N) the simple cells achieve the same performance as resulted from the psychophysical experiment. Type I complex cells extract moving deterministic signals (i.e. bars) from the stationary noise, whereas in the answers of Type II complex cells the statistical parts of the signals predominate. Considering the different cell types each as a series of a linear and a nonlinear system one obtains the cell specific space-time freq…
Analysis of neuronal networks in the visual system of the cat using statistical signals
1976
If the input signals of the visual system in the cat are statistical patterns in space and time, a complete system analysis can be carried out. What counts here as a system are the neuronal networks between retina and recording site. In the case of linearity, one obtains the temporal impulse response functions at every point in the receptive field with the aid of correlation methods. The measuring time is about one minute. Some aspects of the procedure are explained in terms of examples. The method of measurement also makes it possible to determine the characteristic function of the system in time and space between different recording sites within the cortex. It is possible to specialize th…