Mohammad Reza Ejtehadi — Page 2

arXiv2009

Simulation of Droplet Trains in Microfluidic Networks

In this work we show that in a microfluidic network and in low Reynolds numbers a system can be irreversible because of hysteresis effects.The network, which is employed in our simulations, is taken from recent experiments. The network consists of one loop connected to input and output pipes. A train of droplets enter the system at a uniform rate, but they may leave it in different patterns, e.g. periodic or even chaotic. The out put pattern depends on the time interval among the incoming droplets as well as the network geometry and for some parameters the system is not reversible.

physics.flu-dyn↗

arXiv2008

The energy landscape networks of spin-glasses

We have studied the topology of the energy landscape of a spin-glass model and the effect of frustration on it by looking at the connectivity and disconnectivity graphs of the inherent structure. The connectivity network shows the adjacency of energy minima whereas the disconnectivity network tells us about the heights of the energy barriers. Both graphs are constructed by the exact enumeration of a two-dimensional square lattice of a frustrated spin glass with nearest-neighbor interactions up to the size of 27 spins. The enumeration of the energy-landscape minima as well as the analytical mean-field approximation show that these minima have a Gaussian distribution, and the connectivity graph has a log-Weibull degree distribution of shape $κ=8.22$ and scale $λ=4.84$. To study the effect of frustration on these results, we introduce an unfrustrated spin-glass model and demonstrate that the degree distribution of its connectivity graph shows a power-law behavior with the -3.46 exponent, which is similar to the behavior of proteins and Lennard-Jones clusters in its power-law form.

cond-mat.stat-mech↗