4,421 research outputs found
Effects of Contact Network Models on Stochastic Epidemic Simulations
The importance of modeling the spread of epidemics through a population has
led to the development of mathematical models for infectious disease
propagation. A number of empirical studies have collected and analyzed data on
contacts between individuals using a variety of sensors. Typically one uses
such data to fit a probabilistic model of network contacts over which a disease
may propagate. In this paper, we investigate the effects of different contact
network models with varying levels of complexity on the outcomes of simulated
epidemics using a stochastic Susceptible-Infectious-Recovered (SIR) model. We
evaluate these network models on six datasets of contacts between people in a
variety of settings. Our results demonstrate that the choice of network model
can have a significant effect on how closely the outcomes of an epidemic
simulation on a simulated network match the outcomes on the actual network
constructed from the sensor data. In particular, preserving degrees of nodes
appears to be much more important than preserving cluster structure for
accurate epidemic simulations.Comment: To appear at International Conference on Social Informatics (SocInfo)
201
Local antiferromagnetic exchange and collaborative Fermi surface as key ingredients of high temperature superconductors
Cuprates, ferropnictides and ferrochalcogenides are three classes of
unconventional high-temperature superconductors, who share similar phase
diagrams in which superconductivity develops after a magnetic order is
suppressed, suggesting a strong interplay between superconductivity and
magnetism, although the exact picture of this interplay remains elusive. Here
we show that there is a direct bridge connecting antiferromagnetic exchange
interactions determined in the parent compounds of these materials to the
superconducting gap functions observed in the corresponding superconducting
materials. High superconducting transition temperature is achieved when the
Fermi surface topology matches the form factor of the pairing symmetry favored
by local magnetic exchange interactions. Our result offers a principle guide to
search for new high temperature superconductors.Comment: 12 pages, 5 figures, 1 table, 1 supplementary materia
Pseudogap temperature as a Widom line in doped Mott insulators
The pseudogap refers to an enigmatic state of matter with unusual physical
properties found below a characteristic temperature in hole-doped
high-temperature superconductors. Determining is critical for
understanding this state. Here we study the simplest model of correlated
electron systems, the Hubbard model, with cluster dynamical mean-field theory
to find out whether the pseudogap can occur solely because of strong coupling
physics and short nonlocal correlations. We find that the pseudogap
characteristic temperature is a sharp crossover between different
dynamical regimes along a line of thermodynamic anomalies that appears above a
first-order phase transition, the Widom line. The Widom line emanating from the
critical endpoint of a first-order transition is thus the organizing principle
for the pseudogap phase diagram of the cuprates. No additional broken symmetry
is necessary to explain the phenomenon. Broken symmetry states appear in the
pseudogap and not the other way around.Comment: 6 pages, 4 figures and supplementary information; published versio
The Meissner effect in a strongly underdoped cuprate above its critical temperature
The Meissner effect and the associated perfect "bulk" diamagnetism together
with zero resistance and gap opening are characteristic features of the
superconducting state. In the pseudogap state of cuprates unusual diamagnetic
signals as well as anomalous proximity effects have been detected but a
Meissner effect has never been observed. Here we have probed the local
diamagnetic response in the normal state of an underdoped La1.94Sr0.06CuO4
layer (up to 46 nm thick, critical temperature Tc' < 5 K) which was brought
into close contact with two nearly optimally doped La1.84Sr0.16CuO4 layers (Tc
\approx 32 K). We show that the entire 'barrier' layer of thickness much larger
than the typical c axis coherence lengths of cuprates exhibits a Meissner
effect at temperatures well above Tc' but below Tc. The temperature dependence
of the effective penetration depth and superfluid density in different layers
indicates that superfluidity with long-range phase coherence is induced in the
underdoped layer by the proximity to optimally doped layers; however, this
induced order is very sensitive to thermal excitation.Comment: 7 pages, 7 figures + Erratu
Folate cycle enzyme MTHFD1L confers metabolic advantages in hepatocellular carcinoma
published_or_final_versio
A Regularized Graph Layout Framework for Dynamic Network Visualization
Many real-world networks, including social and information networks, are
dynamic structures that evolve over time. Such dynamic networks are typically
visualized using a sequence of static graph layouts. In addition to providing a
visual representation of the network structure at each time step, the sequence
should preserve the mental map between layouts of consecutive time steps to
allow a human to interpret the temporal evolution of the network. In this
paper, we propose a framework for dynamic network visualization in the on-line
setting where only present and past graph snapshots are available to create the
present layout. The proposed framework creates regularized graph layouts by
augmenting the cost function of a static graph layout algorithm with a grouping
penalty, which discourages nodes from deviating too far from other nodes
belonging to the same group, and a temporal penalty, which discourages large
node movements between consecutive time steps. The penalties increase the
stability of the layout sequence, thus preserving the mental map. We introduce
two dynamic layout algorithms within the proposed framework, namely dynamic
multidimensional scaling (DMDS) and dynamic graph Laplacian layout (DGLL). We
apply these algorithms on several data sets to illustrate the importance of
both grouping and temporal regularization for producing interpretable
visualizations of dynamic networks.Comment: To appear in Data Mining and Knowledge Discovery, supporting material
(animations and MATLAB toolbox) available at
http://tbayes.eecs.umich.edu/xukevin/visualization_dmkd_201
Superconductivity at the Border of Electron Localization and Itinerancy
The superconducting state of iron pnictides and chalcogenides exists at the
border of antiferromagnetic order. Consequently, these materials could provide
clues about the relationship between magnetism and unconventional
superconductivity. One explanation, motivated by the so-called bad-metal
behaviour of these materials, proposes that magnetism and superconductivity
develop out of quasi-localized magnetic moments which are generated by strong
electron-electron correlations. Another suggests that these phenomena are the
result of weakly interacting electron states that lie on nested Fermi surfaces.
Here we address the issue by comparing the newly discovered alkaline iron
selenide superconductors, which exhibit no Fermi-surface nesting, to their iron
pnictide counterparts. We show that the strong-coupling approach leads to
similar pairing amplitudes in these materials, despite their different Fermi
surfaces. We also find that the pairing amplitudes are largest at the boundary
between electronic localization and itinerancy, suggesting that new
superconductors might be found in materials with similar characteristics.Comment: Version of the published manuscript prior to final journal-editting.
Main text (23 pages, 4 figures) + Supplementary Information (14 pages, 7
figures, 3 tables). Calculation on the single-layer FeSe is added.
Enhancement of the pairing amplitude in the vicinity of the Mott transition
is highlighted. Published version is at
http://www.nature.com/ncomms/2013/131115/ncomms3783/full/ncomms3783.htm
Experimental and theoretical investigation of ligand effects on the synthesis of ZnO nanoparticles
ZnO nanoparticles with highly controllable particle sizes(less than 10 nm) were synthesized using organic capping ligands in Zn(Ac)2 ethanolic solution. The molecular structure of the ligands was found to have significant influence on the particle size. The multi-functional molecule tris(hydroxymethyl)-aminomethane (THMA) favoured smaller particle distributions compared with ligands possessing long hydrocarbon chains that are more frequently employed. The adsorption of capping ligands on ZnnOn crystal nuclei (where n = 4 or 18 molecular clusters of(0001) ZnO surfaces) was modelled by ab initio methods at the density functional theory (DFT) level. For the molecules examined, chemisorption proceeded via the formation of Zn...O, Zn...N, or Zn...S chemical bonds between the ligands and active Zn2+ sites on ZnO surfaces. The DFT results indicated that THMA binds more strongly to the ZnO surface than other ligands, suggesting that this molecule is very effective at stabilizing ZnO nanoparticle surfaces. This study, therefore, provides new insight into the correlation between the molecular structure of capping ligands and the morphology of metal oxide nanostructures formed in their presence
Neutron Scattering and Its Application to Strongly Correlated Systems
Neutron scattering is a powerful probe of strongly correlated systems. It can
directly detect common phenomena such as magnetic order, and can be used to
determine the coupling between magnetic moments through measurements of the
spin-wave dispersions. In the absence of magnetic order, one can detect diffuse
scattering and dynamic correlations. Neutrons are also sensitive to the
arrangement of atoms in a solid (crystal structure) and lattice dynamics
(phonons). In this chapter, we provide an introduction to neutrons and neutron
sources. The neutron scattering cross section is described and formulas are
given for nuclear diffraction, phonon scattering, magnetic diffraction, and
magnon scattering. As an experimental example, we describe measurements of
antiferromagnetic order, spin dynamics, and their evolution in the
La(2-x)Ba(x)CuO(4) family of high-temperature superconductors.Comment: 31 pages, chapter for "Strongly Correlated Systems: Experimental
Techniques", edited by A. Avella and F. Mancin
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