189 research outputs found
Dynamical Hierarchies
<Guest Editor's Introduction>
N=1 Sigma Models in AdS_4
We study sigma models in AdS_4 with global N=1 supersymmetry and find that
they differ significantly from their flat-space cousins -- the target space is
constrained to be a Kahler manifold with an exact Kahler form, the
superpotential transforms under Kahler transformations, the space of
supersymmetric vacua is generically a set of isolated points even when the
superpotential vanishes, and the R-symmetry is classically broken by the
cosmological constant. Remarkably, the exactness of the Kahler class is also
required for the sigma model to arise as a decoupling limit of N=1
supergravity, and ensures the vanishing of gravitational anomalies. As simple
applications of these results, we argue that fields with AdS_4 scale masses are
ubiquitous in, for example, type IIB N=1 AdS_4 vacua stabilized near large
volume; we also show that the Affleck-Dine-Seiberg runaway of N_f < N_c SQCD is
regulated by considering the theory in AdS_4.Comment: 32 pages; v2: minor changes and references added; v3: discussion in
sect. 5 extended, version published in JHE
Critical phenomena in complex networks
The combination of the compactness of networks, featuring small diameters,
and their complex architectures results in a variety of critical effects
dramatically different from those in cooperative systems on lattices. In the
last few years, researchers have made important steps toward understanding the
qualitatively new critical phenomena in complex networks. We review the
results, concepts, and methods of this rapidly developing field. Here we mostly
consider two closely related classes of these critical phenomena, namely
structural phase transitions in the network architectures and transitions in
cooperative models on networks as substrates. We also discuss systems where a
network and interacting agents on it influence each other. We overview a wide
range of critical phenomena in equilibrium and growing networks including the
birth of the giant connected component, percolation, k-core percolation,
phenomena near epidemic thresholds, condensation transitions, critical
phenomena in spin models placed on networks, synchronization, and
self-organized criticality effects in interacting systems on networks. We also
discuss strong finite size effects in these systems and highlight open problems
and perspectives.Comment: Review article, 79 pages, 43 figures, 1 table, 508 references,
extende
CUDA simulations of active dumbbell suspensions
We describe and analyze CUDA simulations of hydrodynamic interactions in
active dumbbell suspensions. GPU-based parallel computing enables us not only
to study the time-resolved collective dynamics of up to a several hundred
active dumbbell swimmers but also to test the accuracy of effective
time-averaged models. Our numerical results suggest that the stroke-averaged
model yields a relatively accurate description down to distances of only a few
times the dumbbell's length. This is remarkable in view of the fact that the
stroke-averaged model is based on a far-field expansion. Thus, our analysis
confirms that stroke-averaged far-field equations of motion may provide a
useful starting point for the derivation of hydrodynamic field equations.Comment: 16 pages, 4 figure
Evolutionary fundamentals of social inequality, dominance and cooperation
Die vorliegende Studie behandelt anhand spieltheoretischer Modelle das Thema der evolutionƤren Grundlagen der sozialen Ungleichheit, Hierarchie und Demokratie in der menschlichen Gesellschaft. Der gedankliche Aufbau erfolgt in drei Stufen. ZunƤchst wird mit Hilfe eines logistischen Wachstumsmodells die Frage der sozialen Ungleichheit als Problem der ungleichen Verteilung seltener Ressourcen dargestellt, woran sich eine Betrachtung der sozialen Ungleichheit unter dem Aspekt der sozialen Macht anschlieĆt. Im abschlieĆenden Teil werden die KrƤfte in der menschlichen Gemeinschaft beschrieben, die gegen die extreme Ungleichheit wirken, d. h. im besonderen auf die Mechanismen hingewiesen, die Ć¼ber die Arbeitsteilung und Entwicklung spezialisierter technischer Fertigkeiten zur Bildung von Koalitionen gegenĆ¼ber den MƤchtigen und Reichen fĆ¼hren. (ML
Computing multi-scale organizations built through assembly
The ability to generate and control assembling structures built over many orders of magnitude is an unsolved challenge of engineering and science. Many of the presumed transformational benefits of nanotechnology and robotics are based directly on this capability. There are still significant theoretical difficulties associated with building such systems, though technology is rapidly ensuring that the tools needed are becoming available in chemical, electronic, and robotic domains. In this thesis a simulated, general-purpose computational prototype is developed which is capable of unlimited assembly and controlled by external input, as well as an additional prototype which, in structures, can emulate any other computing device. These devices are entirely finite-state and distributed in operation. Because of these properties and the unique ability to form unlimited size structures of unlimited computational power, the prototypes represent a novel and useful blueprint on which to base scalable assembly in other domains.
A new assembling model of Computational Organization and Regulation over Assembly Levels (CORAL) is also introduced, providing the necessary framework for this investigation. The strict constraints of the CORAL model allow only an assembling unit of a single type, distributed control, and ensure that units cannot be reprogrammed - all reprogramming is done via assembly. Multiple units are instead structured into aggregate computational devices using a procedural or developmental approach. Well-defined comparison of computational power between levels of organization is ensured by the structure of the model. By eliminating ambiguity, the CORAL model provides a pragmatic answer to open questions regarding a framework for hierarchical organization.
Finally, a comparison between the designed prototypes and units evolved using evolutionary algorithms is presented as a platform for further research into novel scalable assembly. Evolved units are capable of recursive pairing ability under the control of a signal, a primitive form of unlimited assembly, and do so via symmetry-breaking operations at each step. Heuristic evidence for a required minimal threshold of complexity is provided by the results, and challenges and limitations of the approach are identified for future evolutionary studies
The free energy principle for action and perception: A mathematical review
The āfree energy principleā (FEP) has been suggested to provide a unified theory of the brain, integrating data and theory relating to action, perception, and learning. The theory and implementation of the FEP combines insights from Helmholtzian āperception as inferenceā, machine learning theory, and statistical thermodynamics. Here, we provide a detailed mathematical evaluation of a suggested biologically plausible implementation of the FEP that has been widely used to develop the theory. Our objectives are (i) to describe within a single article the mathematical structure of this implementation of the FEP; (ii) provide a simple but complete agent-based model utilising the FEP and (iii) to disclose the assumption structure of this implementation of the FEP to help elucidate its significance for the brain sciences
A Macro-Level Order Metric for Self-Organizing Adaptive Systems
Analyzing how agent interactions affect macro-level self-organized behaviors can yield a deeper understanding of how complex adaptive systems work. The dynamic nature of complex systems makes it difficult to determine if, or when, a system has reached a state of equilibrium or is about to undergo a major transition reflecting the appearance of self-organized states. Using the notion of local neighborhood entropy, this paper presents a metric for evaluating the macro-level order of a system. The metric is tested in two dissimilar complex adaptive systems with self-organizing properties: An autonomous swarm searching for multiple dynamic targets and Conway\u27s Game of Life. In both domains, the proposed metric is able to graphically capture periods of increasing and decreasing self-organization (i.e. changes in macro-level order), equilibrium and points of criticality; displaying its general applicability in identifying these behaviors in complex adaptive systems. Abstract Ā© 2018 IEEE
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