BoRa Jeong, Violin

Sonata for Piano and Violin No. 2 in G, Op. 13 / Edvard Grieg; String Duo for Violin and Viola in G major, K. 423 / W.A. Mozart; Liebesleid / Fritz Kreisler; Liebesfreud / Fritz Kreisle

Annie Hyojeong Jeong, Violin

Sonata for Piano and Violin in G Major, K. 301 / Wolfgang Amadeus Mozart; Solo Violin Partita No. 3 in E Major, BWV 1006 / Johann Sebastian Bach; Violin Concerto in D Major, Op 35 / Pyotr Ilyich Tchaikovsk

Direct observation of the formation of polar nanoregions in Pb(Mg1/3_{1/3}Nb2/3_{2/3})O3_3 using neutron pair distribution function analysis

Using neutron pair distribution function (PDF) analysis over the temperature range from 1000 K to 15 K, we demonstrate the existence of local polarization and the formation of medium-range, polar nanoregions (PNRs) with local rhombohedral order in a prototypical relaxor ferroelectric Pb(Mg$_{1/3}$Nb$_{2/3}$)O$_3$. We estimate the volume fraction of the PNRs as a function of temperature and show that this fraction steadily increases from 0 % to a maximum of $\sim$ 30% as the temperature decreases from 650 K to 15 K. Below T$\sim$200 K the PNRs start to overlap as their volume fraction reaches the percolation threshold. We propose that percolating PNRs and their concomitant overlap play a significant role in the relaxor behavior of Pb(Mg$_{1/3}$Nb$_{2/3}$)O$_3$.Comment: 4 pages, 3 figure

Diffusive Capture Process on Complex Networks

We study the dynamical properties of a diffusing lamb captured by a diffusing lion on the complex networks with various sizes of $N$. We find that the life time $of a lamb scales as \sim N$ and the survival probability $S(N\to \infty,t)$ becomes finite on scale-free networks with degree exponent $\gamma>3$. However, $S(N,t)$ for $\gamma<3$ has a long-living tail on tree-structured scale-free networks and decays exponentially on looped scale-free networks. It suggests that the second moment of degree distribution $is the relevant factor for the dynamical properties in diffusive capture process. We numerically find that the normalized number of capture events at a node with degree$k$,$n(k)$, decreases as$n(k)\sim k^{-\sigma}$. When$\gamma<3$,$n(k)$still increases anomalously for$k\approx k_{max}$. We analytically show that$n(k)$satisfies the relation$n(k)\sim k^2P(k)$and the total number of capture events$N_{tot}$is proportional to$, which causes the $\gamma$ dependent behavior of $S(N,t)$ and $.Comment: 9 pages, 6 figure

Scale-free networks with tunable degree distribution exponents

We propose and study a model of scale-free growing networks that gives a degree distribution dominated by a power-law behavior with a model-dependent, hence tunable, exponent. The model represents a hybrid of the growing networks based on popularity-driven and fitness-driven preferential attachments. As the network grows, a newly added node establishes $m$ new links to existing nodes with a probability $p$ based on popularity of the existing nodes and a probability $1-p$ based on fitness of the existing nodes. An explicit form of the degree distribution $P(p,k)$ is derived within a mean field approach. For reasonably large $k$, $P(p,k) \sim k^{-\gamma(p)}{\cal F}(k,p)$, where the function ${\cal F}$ is dominated by the behavior of $1/\ln(k/m)$ for small values of $p$ and becomes $k$-independent as $p \to 1$, and $\gamma(p)$ is a model-dependent exponent. The degree distribution and the exponent $\gamma(p)$ are found to be in good agreement with results obtained by extensive numerical simulations.Comment: 12 pages, 2 figures, submitted to PR

Reverse engineering of linking preferences from network restructuring

We provide a method to deduce the preferences governing the restructuring dynamics of a network from the observed rewiring of the edges. Our approach is applicable for systems in which the preferences can be formulated in terms of a single-vertex energy function with f(k) being the contribution of a node of degree k to the total energy, and the dynamics obeys the detailed balance. The method is first tested by Monte-Carlo simulations of restructuring graphs with known energies, then it is used to study variations of real network systems ranging from the co-authorship network of scientific publications to the asset graphs of the New York Stock Exchange. The empirical energies obtained from the restructuring can be described by a universal function f(k) -k ln(k), which is consistent with and justifies the validity of the preferential attachment rule proposed for growing networks.Comment: 7 pages, 6 figures, submitted to PR