@phdthesis{Winkler2015,
  author    = {Winkler, Marco},
  title     = {On the Role of Triadic Substructures in Complex Networks},
  publisher = {epubli GmbH},
  address   = {Berlin},
  isbn      = {978-3-7375-5654-5},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-116022},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2015},
  abstract  = {In the course of the growth of the Internet and due to increasing availability of data, over the last two decades, the field of network science has established itself as an own area of research. With quantitative scientists from computer science, mathematics, and physics working on datasets from biology, economics, sociology, political sciences, and many others, network science serves as a paradigm for interdisciplinary research. One of the major goals in network science is to unravel the relationship between topological graph structure and a network's function. As evidence suggests, systems from the same fields, i.e. with similar function, tend to exhibit similar structure. However, it is still vague whether a similar graph structure automatically implies likewise function. This dissertation aims at helping to bridge this gap, while particularly focusing on the role of triadic structures. After a general introduction to the main concepts of network science, existing work devoted to the relevance of triadic substructures is reviewed. A major challenge in modeling triadic structure is the fact that not all three-node subgraphs can be specified independently of each other, as pairs of nodes may participate in multiple of those triadic subgraphs. In order to overcome this obstacle, we suggest a novel class of generative network models based on so called Steiner triple systems. The latter are partitions of a graph's vertices into pair-disjoint triples (Steiner triples). Thus, the configurations on Steiner triples can be specified independently of each other without overdetermining the network's link structure. Subsequently, we investigate the most basic realization of this new class of models. We call it the triadic random graph model (TRGM). The TRGM is parametrized by a probability distribution over all possible triadic subgraph patterns. In order to generate a network instantiation of the model, for all Steiner triples in the system, a pattern is drawn from the distribution and adjusted randomly on the Steiner triple. We calculate the degree distribution of the TRGM analytically and find it to be similar to a Poissonian distribution. Furthermore, it is shown that TRGMs possess non-trivial triadic structure. We discover inevitable correlations in the abundance of certain triadic subgraph patterns which should be taken into account when attributing functional relevance to particular motifs - patterns which occur significantly more frequently than expected at random. Beyond, the strong impact of the probability distributions on the Steiner triples on the occurrence of triadic subgraphs over the whole network is demonstrated. This interdependence allows us to design ensembles of networks with predefined triadic substructure. Hence, TRGMs help to overcome the lack of generative models needed for assessing the relevance of triadic structure. We further investigate whether motifs occur homogeneously or heterogeneously distributed over a graph. Therefore, we study triadic subgraph structures in each node's neighborhood individually. In order to quantitatively measure structure from an individual node's perspective, we introduce an algorithm for node-specific pattern mining for both directed unsigned, and undirected signed networks. Analyzing real-world datasets, we find that there are networks in which motifs are distributed highly heterogeneously, bound to the proximity of only very few nodes. Moreover, we observe indication for the potential sensitivity of biological systems to a targeted removal of these critical vertices. In addition, we study whole graphs with respect to the homogeneity and homophily of their node-specific triadic structure. The former describes the similarity of subgraph distributions in the neighborhoods of individual vertices. The latter quantifies whether connected vertices are structurally more similar than non-connected ones. We discover these features to be characteristic for the networks' origins. Moreover, clustering the vertices of graphs regarding their triadic structure, we investigate structural groups in the neural network of C. elegans, the international airport-connection network, and the global network of diplomatic sentiments between countries. For the latter we find evidence for the instability of triangles considered socially unbalanced according to sociological theories. Finally, we utilize our TRGM to explore ensembles of networks with similar triadic substructure in terms of the evolution of dynamical processes acting on their nodes. Focusing on oscillators, coupled along the graphs' edges, we observe that certain triad motifs impose a clear signature on the systems' dynamics, even when embedded in a larger network structure.},
  subject      = {Netzwerk},
  language  = {en}
}
@phdthesis{CardosoBarato2010,
  author    = {Cardoso Barato, Andre},
  title     = {Nonequilibrium phase transitions and surface growth},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-50122},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2010},
  abstract  = {This thesis is concerned with the statistical physics of various systems far from thermal equilibrium, focusing on universal critical properties, scaling laws and the role of fluctuations. To this end we study several models which serve as paradigmatic examples, such as surface growth and non-equilibrium wetting as well as phase transitions into absorbing states. As a particular interesting example of a model with a non-conventional scaling behavior, we study a simplified model for pulsed laser deposition by rate equations and Monte Carlo simulations. We consider a set of equations, where islands are assumed to be point-like, as well as an improved one that takes the size of the islands into account. The first set of equations is solved exactly but its predictive power is restricted to the first few pulses. The improved set of equations is integrated numerically, is in excellent agreement with simulations, and fully accounts for the crossover from continuous to pulsed deposition. Moreover, we analyze the scaling of the nucleation density and show numerical results indicating that a previously observed logarithmic scaling does not apply. In order to understand the impact of boundaries on critical phenomena, we introduce particle models displaying a boundary-induced absorbing state phase transition. These are one-dimensional systems consisting of a single site (the boundary) where creation and annihilation of particles occur, while particles move diffusively in the bulk. We study different versions of these models and confirm that, except for one exactly solvable bosonic variant exhibiting a discontinuous transition with trivial exponents, all the others display a non-trivial behavior, with critical exponents differing from their mean-field values, representing a universality class. We show that these systems are related to a \$(0+1)\$-dimensional non-Markovian model, meaning that in nonequilibrium a phase transition can take place even in zero dimensions, if time long-range interactions are considered. We argue that these models constitute the simplest universality class of phase transition into an absorbing state, because the transition is induced by the dynamics of a single site. Moreover, this universality class has a simple field theory, corresponding to a zero dimensional limit of direct percolation with L{\'e}vy flights in time. Another boundary phenomena occurs if a nonequilibrium growing interface is exposed to a substrate, in this case a nonequilibrium wetting transition may take place. This transition can be studied through Langevin equations or discrete growth models. In the first case, the Kardar-Parisi-Zhang equation, which defines a very robust universality class for nonequilibrium moving interfaces, is combined with a soft-wall potential. While in the second, microscopic models, in the corresponding universality class, with evaporation and deposition of particles in the presence of hard-wall are studied. Equilibrium wetting is related to a particular case of the problem, corresponding to the Edwards-Wilkinson equation with a potential in the continuum approach or to the fulfillment of detailed balance in the microscopic models. In this thesis we present the analytical and numerical methods used to investigate the problem and the very rich behavior that is observed with them. The entropy production for a Markov process with a nonequilibrium stationary state is expected to give a quantitative measure of the distance form equilibrium. In the final chapter of this thesis, we consider a Kardar-Parisi-Zhang interface and investigate how entropy production varies with the interface velocity and its dependence on the interface slope, which are quantities that characterize how far the stationary state of the interface is away from equilibrium. We obtain results in agreement with the idea that the entropy production gives a measure of the distance from equilibrium. Moreover we use the same model to study fluctuation relations. The fluctuation relation is a symmetry in the large deviation function associated to the probability of the variation of entropy during a fixed time interval. We argue that the entropy and height are similar quantities within the model we consider and we calculate the Legendre transform of the large deviation function associated to the height for small systems. We observe that there is no fluctuation relation for the height, nevertheless its large deviation function is still symmetric.},
  subject      = {Nichtgleichgewichtsstatistik},
  language  = {en}
}