arXiv subjects

Sungmin Lee

Publications and source records attributed to Sungmin Lee.

53 records · Page 3Linked to original sources

arXiv2017

Charge-spin correlation in van der Waals antiferromagenet NiPS3

Strong charge-spin coupling is found in a layered transition-metal trichalcogenide NiPS3, a van derWaals antiferromagnet, from our study of the electronic structure using several experimental and theoretical tools: spectroscopic ellipsometry, x-ray absorption and photoemission spectroscopy, and density-functional calculations. NiPS3 displays an anomalous shift in the optical spectral weight at the magnetic ordering temperature, reflecting a strong coupling between the electronic and magnetic structures. X-ray absorption, photoemission and optical spectra support a self-doped ground state in NiPS3. Our work demonstrates that layered transition-metal trichalcogenide magnets are a useful candidate for the study of correlated-electron physics in two-dimensional magnetic material.

cond-mat.str-el↗

arXiv2017

Ranking influential spreaders is an ill-defined problem

Finding influential spreaders of information and disease in networks is an important theoretical problem, and one of considerable recent interest. It has been almost exclusively formulated as a node-ranking problem -- methods for identifying influential spreaders rank nodes according to how influential they are. In this work, we show that the ranking approach does not necessarily work: the set of most influential nodes depends on the number of nodes in the set. Therefore, the set of $n$ most important nodes to vaccinate does not need to have any node in common with the set of $n+1$ most important nodes. We propose a method for quantifying the extent and impact of this phenomenon, and show that it is common in both empirical and model networks.

q-bio.PE↗

arXiv2016

Ising-Type Magnetic Ordering in Atomically Thin FePS3

Magnetism in two-dimensional materials is not only of fundamental scientific interest but also a promising candidate for numerous applications. However, studies so far, especially the experimental ones, have been mostly limited to the magnetism arising from defects, vacancies, edges or chemical dopants which are all extrinsic effects. Here, we report on the observation of intrinsic antiferromagnetic ordering in the two-dimensional limit. By monitoring the Raman peaks that arise from zone folding due to antiferromagnetic ordering at the transition temperature, we demonstrate that FePS3 exhibits an Ising-type antiferromagnetic ordering down to the monolayer limit, in good agreement with the Onsager solution for two-dimensional order-disorder transition. The transition temperature remains almost independent of the thickness from bulk to the monolayer limit with TN ~118 K, indicating that the weak interlayer interaction has little effect on the antiferromagnetic ordering.

cond-mat.mes-hall↗

arXiv2016

Tunneling transport of mono- and few-layers magnetic van der Waals MnPS$_3$

We have investigated the tunneling transport of mono- and few-layers of MnPS3 by using conductive atomic force microscopy. Due to the band alignment of indium tin oxide/MnPS3/Pt-Ir tip junction, the key features of both Schottky junction and Fowler-Nordheim tunneling (FNT) were observed for all the samples with varying thickness. Using the FNT model and assuming the effective electron mass (0.5 me) of MnPS3, we estimate the tunneling barrier height to be 1.31 eV and the dielectric breakdown strength as 5.41 MV/cm.

cond-mat.mes-hall↗

arXiv2015

Will solid-state drives accelerate your bioinformatics? In-depth profiling, performance analysis, and beyond

A wide variety of large-scale data has been produced in bioinformatics. In response, the need for efficient handling of biomedical big data has been partly met by parallel computing. However, the time demand of many bioinformatics programs still remains high for large-scale practical uses due to factors that hinder acceleration by parallelization. Recently, new generations of storage devices have emerged, such as NAND flash-based solid-state drives (SSDs), and with the renewed interest in near-data processing, they are increasingly becoming acceleration methods that can accompany parallel processing. In certain cases, a simple drop-in replacement of hard disk drives (HDDs) by SSDs results in dramatic speedup. Despite the various advantages and continuous cost reduction of SSDs, there has been little review of SSD-based profiling and performance exploration of important but time-consuming bioinformatics programs. For an informative review, we perform in-depth profiling and analysis of 23 key bioinformatics programs using multiple types of devices. Based on the insight we obtain from this research, we further discuss issues related to design and optimize bioinformatics algorithms and pipelines to fully exploit SSDs. The programs we profile cover traditional and emerging areas of importance, such as alignment, assembly, mapping, expression analysis, variant calling, and metagenomics. We explain how acceleration by parallelization can be combined with SSDs for improved performance and also how using SSDs can expedite important bioinformatics pipelines, such as variant calling by the Genome Analysis Toolkit (GATK) and transcriptome analysis using RNA sequencing (RNA-seq). We hope that this review can provide useful directions and tips to accompany future bioinformatics algorithm design procedures that properly consider new generations of powerful storage devices.

q-bio.GN↗

arXiv2014

Correlation and Network Topologies in Global and Local Stock Indices

This study examined how the correlation and network structure of 30 global indices and 145 local Korean indices belonging to the KOSPI 200 have changed during the 13-year period, 2000-2012. The correlations among the indices were calculated. The results showed that although the average correlations of the global indices increased with time, the local indices showed a decreasing trend except for drastic changes during crises. The average correlation of the local indices exceeded the global indices during the crises from 2000-2002, implying a strong correlation structure among the local indices during this period due to the detrimental effect of the dot-com bubble. The threshold networks (TN) were constructed in the observation time window by assigning a threshold value and determining the network topologies. A significant change in the network topologies was observed due to the financial crises in both markets. The Jaccard similarities were also determined using the common links of TNs. The TNs of the financial network were not consistent with the evolution of the time, and the successive TNs of the global indices were more similar than those of the successive local indices. Finally, the Jaccard similarities identified the change in the market state due to a crisis in both markets.

q-fin.ST↗

arXiv2012

Phase-shift inversion in oscillator systems with periodically switching couplings

A system's response to external periodic changes can provide crucial information about its dynamical properties. We investigate the synchronization transition, an archetypical example of a dynamic phase transition, in the framework of such a temporal response. The Kuramoto model under periodically switching interactions has the same type of phase transition as the original mean-field model. Furthermore, we see that the signature of the synchronization transition appears in the relative delay of the order parameter with respect to the phase of oscillating interactions as well. Specifically, the phase shift becomes significantly larger as the system gets closer to the phase transition so that the order parameter at the minimum interaction density can even be larger than that at the maximum interaction density, counterintuitively. We argue that this phase-shift inversion is caused by the diverging relaxation time, in a similar way to the resonance near the critical point in the kinetic Ising model. Our result, based on exhaustive simulations on globally coupled systems as well as scale-free networks, shows that an oscillator system's phase transition can be manifested in the temporal response to the topological dynamics of the underlying connection structure.

cond-mat.stat-mech↗

arXiv2011

Cooperation, structure and hierarchy in multiadaptive games

Game-theoretical models where the rules of the game and the interaction structure both coevolves with the game dynamics -- multiadaptive games -- capture very flexible situations where cooperation among selfish agents can emerge. In this work, we will discuss a multiadaptive model presented in a recent Letter [Phys. Rev. Lett. 106, 028702 (2011)], and generalizations of it. The model captures a non-equilibrium situation where social unrest increases the incentive to cooperate and, simultaneously, agents are partly free to influence with whom they interact. First, we investigate the details of how the feedback from the behavior of agents determines the emergence of cooperation and hierarchical contact structures. We also study the stability of the system to different types of noise, and find that different regions of parameter space show very different response. Some types of noise can destroy an all-cooperator state. If, on the other hand, hubs are stable, then so is the all-C state. Finally, we investigate the dependence of the ratio between the timescales of strategy updates and the evolution of the interaction structure. We find that a comparatively fast strategy dynamics is a prerequisite for the emergence of cooperation.

q-bio.PE↗

arXiv2011

Emergent Hierarchical Structures in Multiadaptive Games

We investigate a game-theoretic model of a social system where both the rules of the game and the interaction structure are shaped by the behavior of the agents. We call this type of model, with several types of feedback couplings from the behavior of the agents to their environment, a multiadaptive game. Our model has a complex behavior with several regimes of different dynamic behavior accompanied by different network topological properties. Some of these regimes are characterized by heterogeneous, hierarchical interaction networks, where cooperation and network topology coemerge from the dynamics.

q-bio.PE↗

arXiv2010

Exploiting temporal network structures of human interaction to effectively immunize populations

If we can lower the number of people needed to vaccinate for a community to be immune against contagious diseases, we can save resources and life. A key to reach such a lower threshold of immunization is to find and vaccinate people who, through their behavior, are more likely to become infected and effective to spread the disease than the average. Fortunately, the very behavior that makes these people important to vaccinate can help us finding them. People you have met recently are more likely to be socially active and thus central in the contact pattern, and important to vaccinate. We propose two immunization schemes exploiting temporal contact patterns. Both of these rely only on obtainable, local information and could implemented in practice. We show that these schemes outperform benchmark protocols in four real data sets under various epidemic scenarios. The data sets are dynamic, which enables us to make more realistic evaluations than other studies - we use information only about the past to perform the vaccination and the future to simulate disease outbreaks. We also use models to elucidate the mechanisms behind how the temporal structures make our immunization protocols efficient.

q-bio.PE↗

arXiv2010

Emergence of collective memories

We understand the dynamics of the world around us as by associating pairs of events, where one event has some influence on the other. These pairs of events can be aggregated into a web of memories representing our understanding of an episode of history. The events and the associations between them need not be directly experienced-they can also be acquired by communication. In this paper we take a network approach to study the dynamics of memories of history. First we investigate the network structure of a data set consisting of reported events by several individuals and how associations connect them. We focus our measurement on degree distributions, degree correlations, cycles (which represent inconsistencies as they would break the time ordering) and community structure. We proceed to model effects of communication using an agent-based model. We investigate the conditions for the memory webs of different individuals to converge to collective memories, how groups where the individuals have similar memories (but different from other groups) can form. Our work outlines how the cognitive representation of memories and social structure can co-evolve as a contagious process. We generate some testable hypotheses including that the number of groups is limited as a function of the total population size.

physics.soc-ph↗

arXiv2007

Diffusive capture processes for information search

We show how effectively the diffusive capture processes (DCP) on complex networks can be applied to information search in the networks. Numerical simulations show that our method generates only 2% of traffic compared with the most popular flooding-based query-packet-forwarding (FB) algorithm. We find that the average searching time, $ $, of the our model is more scalable than another well known $n$-random walker model and comparable to the FB algorithm both on real Gnutella network and scale-free networks with $γ=2.4$. We also discuss the possible relationship between $ $ and $ $, the second moment of the degree distribution of the networks.

physics.soc-ph↗

arXiv2007

Random walks and diameter of finite scale-free networks

Dynamical scalings for the end-to-end distance $R_{ee}$ and the number of distinct visited nodes $N_v$ of random walks (RWs) on finite scale-free networks (SFNs) are studied numerically. $\left< R_{ee} \right>$ shows the dynamical scaling behavior $\left = \bar{\ell}^α(γ, N) g(t/\bar{\ell}^z)$, where $\bar{\ell}$ is the average minimum distance between all possible pairs of nodes in the network, $N$ is the number of nodes, $γ$ is the degree exponent of the SFN and $t$ is the step number of RWs. Especially, $\left $ in the limit $t \to \infty$ satisfies the relation $\left< R_{ee} \right> \sim \bar{\ell}^α\sim d^α$, where $d$ is the diameter of network with $d ({\bar \ell}) \simeq \ln N$ for $γ\ge 3$ or $d ({\bar \ell}) \simeq \ln \ln N$ for $γ< 3$. Based on the scaling relation $\left< R_{ee} \right>$, we also find that the scaling behavior of the diameter of networks can be measured very efficiently by using RWs.

cond-mat.stat-mech↗

arXiv2006

Statistical properties of sampled networks by random walks

We study the statistical properties of the sampled networks by a random walker. We compare topological properties of the sampled networks such as degree distribution, degree-degree correlation, and clustering coefficient with those of the original networks. From the numerical results, we find that most of topological properties of the sampled networks are almost the same as those of the original networks for $γ\lesssim 3$. In contrast, we find that the degree distribution exponent of the sampled networks for $γ>3$ somewhat deviates from that of the original networks when the ratio of the sampled network size to the original network size becomes smaller. We also apply the sampling method to various real networks such as collaboration of movie actor, world wide web, and peer-to-peer networks. All topological properties of the sampled networks show the essentially same as the original real networks.

physics.soc-ph↗

arXiv2006

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 $γ>3$. However, $S(N,t)$ for $γ<3$ 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 $n(k)\sim k^{-σ}$. When $γ<3$, $n(k)$ 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 $γ$ dependent behavior of $S(N,t)$ and $.

cond-mat.dis-nn↗

arXiv2005

Condensation phase transitions of symmetric conserved-mass aggregation model on complex networks

We investigate condensation phase transitions of symmetric conserved-mass aggregation (SCA) model on random networks (RNs) and scale-free networks (SFNs) with degree distribution $P(k) \sim k^{-γ}$. In SCA model, masses diffuse with unite rate, and unit mass chips off from mass with rate $ω$. The dynamics conserves total mass density $ρ$. In the steady state, on RNs and SFNs with $γ>3$ for $ω\neq \infty$, we numerically show that SCA model undergoes the same type condensation transitions as those on regular lattices. However the critical line $ρ_c (ω)$ depends on network structures. On SFNs with $γ\leq 3$, the fluid phase of exponential mass distribution completely disappears and no phase transitions occurs. Instead, the condensation with exponentially decaying background mass distribution always takes place for any non-zero density. For the existence of the condensed phase for $γ\leq 3$ at the zero density limit, we investigate one lamb-lion problem on RNs and SFNs. We numerically show that a lamb survives indefinitely with finite survival probability on RNs and SFNs with $γ>3$, and dies out exponentially on SFNs with $γ\leq 3$. The finite life time of a lamb on SFNs with $γ\leq 3$ ensures the existence of the condensation at the zero density limit on SFNs with $γ\leq 3$ at which direct numerical simulations are practically impossible. At $ω= \infty$, we numerically confirm that complete condensation takes place for any $ρ> 0$ on RNs. Together with the recent study on SFNs, the complete condensation always occurs on both RNs and SFNs in zero range process with constant hopping rate.

cond-mat.stat-mech↗

arXiv2005

Coevolutionary dynamics on scale-free networks

We investigate Bak-Sneppen coevolution models on scale-free networks with various degree exponents $γ$ including random networks. For $γ>3$, the critical fitness value $f_c$ approaches to a nonzero finite value in the limit $N \to \infty$, whereas $f_c$ approaches to zero as $2<γ\le 3$. These results are explained by showing analytically $f_c(N) \simeq A/<(k+1)^2>_N$ on the networks with size $N$. The avalanche size distribution $P(s)$ shows the normal power-law behavior for $γ>3$. In contrast, $P(s)$ for $2 <γ\le 3$ has two power-law regimes. One is a short regime for small $s$ with a large exponent $τ_1$ and the other is a long regime for large $s$ with a small exponent $τ_2$ ($τ_1 > τ_2$). The origin of the two power-regimes is explained by the dynamics on an artificially-made star-linked network.

cond-mat.stat-mech↗