Gouy phase shift of single-cycle picosecond acoustic pulses

Ultrafast laser pulses are used to generate single-cycle picosecond acoustic pulses in thin metal films on silicon. For small initial excitation spot sizes, propagation of the acoustic pulses across a 485-μm Si crystal leads to significant diffraction effects. The temporal reshaping of the acoustic wave form due to diffraction is investigated, and we demonstrate that the acoustic far field can be reached. © 2003 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71324/2/APPLAB-83-2-392-1.pd

Dynamic scaling regimes of collective decision making

We investigate a social system of agents faced with a binary choice. We assume there is a correct, or beneficial, outcome of this choice. Furthermore, we assume agents are influenced by others in making their decision, and that the agents can obtain information that may guide them towards making a correct decision. The dynamic model we propose is of nonequilibrium type, converging to a final decision. We run it on random graphs and scale-free networks. On random graphs, we find two distinct regions in terms of the "finalizing time" -- the time until all agents have finalized their decisions. On scale-free networks on the other hand, there does not seem to be any such distinct scaling regions

Imaging nanostructures with coherent phonon pulses

We demonstrate submicron resolution imaging using picosecond acoustic phonon pulses. High-frequency acoustic pulses are generated by impulsive thermoelastic excitation of a patterned 15-nm15-nm-thick metal film on a crystalline substrate using ultrafast optical pulses. The spatiotemporal diffracted acoustic strain field is measured on the opposite side of the substrate, and this field is used in a time-reversal algorithm to reconstruct the object. The image resolution is characterized using lithographically defined 1-micron1-micron-period Al structures on Si. Straightforward technical improvements should lead to resolution approaching 45 nm45nm, extending the resolution of acoustic microscopy into the nanoscale regime.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71146/2/APPLAB-84-25-5180-1.pd

Robust modeling of human contact networks across different scales and proximity-sensing techniques

The problem of mapping human close-range proximity networks has been tackled using a variety of technical approaches. Wearable electronic devices, in particular, have proven to be particularly successful in a variety of settings relevant for research in social science, complex networks and infectious diseases dynamics. Each device and technology used for proximity sensing (e.g., RFIDs, Bluetooth, low-power radio or infrared communication, etc.) comes with specific biases on the close-range relations it records. Hence it is important to assess which statistical features of the empirical proximity networks are robust across different measurement techniques, and which modeling frameworks generalize well across empirical data. Here we compare time-resolved proximity networks recorded in different experimental settings and show that some important statistical features are robust across all settings considered. The observed universality calls for a simplified modeling approach. We show that one such simple model is indeed able to reproduce the main statistical distributions characterizing the empirical temporal networks

Zonal shear and super-rotation in a magnetized spherical Couette flow experiment

We present measurements performed in a spherical shell filled with liquid sodium, where a 74 mm-radius inner sphere is rotated while a 210 mm-radius outer sphere is at rest. The inner sphere holds a dipolar magnetic field and acts as a magnetic propeller when rotated. In this experimental set-up called DTS, direct measurements of the velocity are performed by ultrasonic Doppler velocimetry. Differences in electric potential and the induced magnetic field are also measured to characterize the magnetohydrodynamic flow. Rotation frequencies of the inner sphere are varied between -30 Hz and +30 Hz, the magnetic Reynolds number based on measured sodium velocities and on the shell radius reaching to about 33. We have investigated the mean axisymmetric part of the flow, which consists of differential rotation. Strong super-rotation of the fluid with respect to the rotating inner sphere is directly measured. It is found that the organization of the mean flow does not change much throughout the entire range of parameters covered by our experiment. The direct measurements of zonal velocity give a nice illustration of Ferraro's law of isorotation in the vicinity of the inner sphere where magnetic forces dominate inertial ones. The transition from a Ferraro regime in the interior to a geostrophic regime, where inertial forces predominate, in the outer regions has been well documented. It takes place where the local Elsasser number is about 1. A quantitative agreement with non-linear numerical simulations is obtained when keeping the same Elsasser number. The experiments also reveal a region that violates Ferraro's law just above the inner sphere.Comment: Phys Rev E, in pres

Growing Scale-Free Networks with Tunable Clustering

We extend the standard scale-free network model to include a ``triad formation step''. We analyze the geometric properties of networks generated by this algorithm both analytically and by numerical calculations, and find that our model possesses the same characteristics as the standard scale-free networks like the power-law degree distribution and the small average geodesic length, but with the high-clustering at the same time. In our model, the clustering coefficient is also shown to be tunable simply by changing a control parameter - the average number of triad formation trials per time step.Comment: Accepted for publication in Phys. Rev.

Dynamic Community Detection into Analyzing of Wildfires Events

The study and comprehension of complex systems are crucial intellectual and scientific challenges of the 21st century. In this scenario, network science has emerged as a mathematical tool to support the study of such systems. Examples include environmental processes such as wildfires, which are known for their considerable impact on human life. However, there is a considerable lack of studies of wildfire from a network science perspective. Here, employing the chronological network concept -- a temporal network where nodes are linked if two consecutive events occur between them -- we investigate the information that dynamic community structures reveal about the wildfires' dynamics. Particularly, we explore a two-phase dynamic community detection approach, i.e., we applied the Louvain algorithm on a series of snapshots. Then we used the Jaccard similarity coefficient to match communities across adjacent snapshots. Experiments with the MODIS dataset of fire events in the Amazon basing were conducted. Our results show that the dynamic communities can reveal wildfire patterns observed throughout the year.Comment: 16 pages, 8 figure

Observing Quark-Gluon Plasma with Strange Hadrons

We review the methods and results obtained in an analysis of the experimental heavy ion collision research program at nuclear beam energy of 160-200A GeV. We study strange, and more generally, hadronic particle production experimental data. We discuss present expectations concerning how these observables will perform at other collision energies. We also present the dynamical theory of strangeness production and apply it to show that it agrees with available experimental results. We describe strange hadron production from the baryon-poor quark-gluon phase formed at much higher reaction energies, where the abundance of strange baryons and antibaryons exceeds that of nonstrange baryons and antibaryons.Comment: 39 journal pages (155kb text), 8 postscript figures, 8 table

Complex networks theory for analyzing metabolic networks

One of the main tasks of post-genomic informatics is to systematically investigate all molecules and their interactions within a living cell so as to understand how these molecules and the interactions between them relate to the function of the organism, while networks are appropriate abstract description of all kinds of interactions. In the past few years, great achievement has been made in developing theory of complex networks for revealing the organizing principles that govern the formation and evolution of various complex biological, technological and social networks. This paper reviews the accomplishments in constructing genome-based metabolic networks and describes how the theory of complex networks is applied to analyze metabolic networks.Comment: 13 pages, 2 figure