Laplacian growth as one-dimensional turbulence

A new model of Laplacian stochastic growth is formulated using conformal mappings. The model describes two growth regimes, stable and turbulent, separated by a sharp phase transition. The first few Fourier components of the mapping define the web, an envelope of the cluster. The web is used to study the transition and the dynamics of large-scale features of the cluster characterized by evolution from macro- to micro-scales. Also, we derive scaling laws for the cluster size.Comment: 4 pages, RevTex, 4 figure

Topology and Evolution of Technology Innovation Networks

The web of relations linking technological innovation can be fairly described in terms of patent citations. The resulting patent citation network provides a picture of the large-scale organization of innovations and its time evolution. Here we study the patterns of change of patents registered by the US Patent and Trademark Office (USPTO). We show that the scaling behavior exhibited by this network is consistent with a preferential attachment mechanism together with a Weibull-shaped aging term. Such attachment kernel is shared by scientific citation networks, thus indicating an universal type of mechanism linking ideas and designs and their evolution. The implications for evolutionary theory of innovation are discussed.Comment: 6 pages, 5 figures, submitted to Physical Review

Opinion formation driven by PageRank node influence on directed networks

We study a two states opinion formation model driven by PageRank node influence and report an extensive numerical study on how PageRank affects collective opinion formations in large-scale empirical directed networks. In our model the opinion of a node can be updated by the sum of its neighbor nodes' opinions weighted by the node influence of the neighbor nodes at each step. We consider PageRank probability and its sublinear power as node influence measures and investigate evolution of opinion under various conditions. First, we observe that all networks reach steady state opinion after a certain relaxation time. This time scale is decreasing with the heterogeneity of node influence in the networks. Second, we find that our model shows consensus and non-consensus behavior in steady state depending on types of networks: Web graph, citation network of physics articles, and LiveJournal social network show non-consensus behavior while Wikipedia article network shows consensus behavior. Third, we find that a more heterogeneous influence distribution leads to a more uniform opinion state in the cases of Web graph, Wikipedia, and Livejournal. However, the opposite behavior is observed in the citation network. Finally we identify that a small number of influential nodes can impose their own opinion on significant fraction of other nodes in all considered networks. Our study shows that the effects of heterogeneity of node influence on opinion formation can be significant and suggests further investigations on the interplay between node influence and collective opinion in networks.Comment: 10 pages, 6 figures. Published in Physica A 436, 707-715 (2015

Using the Topology of Large Scale Structure to constrain Dark Energy

The use of standard rulers, such as the scale of the Baryonic Acoustic oscillations (BAO), has become one of the more powerful techniques employed in cosmology to probe the entity driving the accelerating expansion of the Universe. In this paper, the topology of large scale structure (LSS) is used as one such standard ruler to study this mysterious `dark energy'. By following the redshift evolution of the clustering of luminous red galaxies (LRGs) as measured by their 3D topology (counting structures in the cosmic web), we can chart the expansion rate and extract information about the equation of state of dark energy. Using the technique first introduced in (Park & Kim, 2009), we evaluate the constraints that can be achieved using 3D topology measurements from next-generation LSS surveys such as the Baryonic Oscillation Spectroscopic Survey (BOSS). In conjunction with the information that will be available from the Planck satellite, we find a single topology measurement on 3 different scales is capable of constraining a single dark energy parameter to within 5% and 10% when dynamics are permitted. This offers an alternative use of the data available from redshift surveys and serves as a cross-check for BAO studies.Comment: 8 pages, 5 figures, 2 tables, Submitted to MNRAS, updated acknowledgement

Quenching in Cosmic Sheets: Tracing the Impact of Large Scale Structure Collapse on the Evolution of Dwarf Galaxies

Dwarf galaxies are thought to quench primarily due to environmental processes most typically occurring in galaxy groups and clusters or around single, massive galaxies. However, at earlier epochs, ($5 < z < 2$), the collapse of large scale structure (forming Zel'dovich sheets and subsequently filaments of the cosmic web) can produce volume-filling accretion shocks which elevate large swaths of the intergalactic medium (IGM) in these structures to a hot ($T>10^6$ K) phase. We study the impact of such an event on the evolution of central dwarf galaxies ($5.5 < \log M_* < 8.5$) in the field using a spatially large, high resolution cosmological zoom simulation which covers the cosmic web environment between two protoclusters. We find that the shock-heated sheet acts as an environmental quencher much like clusters and filaments at lower redshift, creating a population of quenched, central dwarf galaxies. Even massive dwarfs which do not quench are affected by the shock, with reductions to their sSFR and gas accretion. This process can potentially explain the presence of isolated quenched dwarf galaxies, and represents an avenue of pre-processing, via which quenched satellites of bound systems quench before infall.Comment: 15 pages, 10 figures. Submitted to MNRA

Evolution of cosmic filaments in the MTNG simulation

We present a study of the evolution of cosmic filaments across redshift with emphasis on some important properties: filament lengths, growth rates, and radial profiles of galaxy densities. Following an observation-driven approach, we build cosmic filament catalogues at z=0,1,2,3 and 4 from the galaxy distributions of the large hydro-dynamical run of the MilleniumTNG project. We employ the extensively used DisPerSE cosmic web finder code, for which we provide a user-friendly guide, including the details of a physics-driven calibration procedure, with the hope of helping future users. We perform the first statistical measurements of the evolution of connectivity in a large-scale simulation, finding that the connectivity of cosmic nodes (defined as the number of filaments attached) globally decreases from early to late times. The study of cosmic filaments in proper coordinates reveals that filaments grow in length and radial extent, as expected from large-scale structures in an expanding Universe. But the most interesting results arise once the Hubble flow is factored out. We find remarkably stable comoving filament length functions and over-density profiles, showing only little evolution of the total population of filaments in the past ~12.25 Gyrs. However, by tracking the spatial evolution of individual structures, we demonstrate that filaments of different lengths actually follow different evolutionary paths. While short filaments preferentially contract, long filaments expand along their longitudinal direction with growth rates that are the highest in the early, matter dominated Universe. Filament diversity at fixed redshift is also shown by the different (~$5 \sigma$) density values between the shortest and longest filaments. Our results hint that cosmic filaments can be used as additional probes for dark energy, but further theoretical work is still needed.Comment: 17 pages, submitted to Astronomy & Astrophysics, comments welcome