Compressed Distributed Gradient Descent: Communication-Efficient Consensus over Networks

Network consensus optimization has received increasing attention in recent years and has found important applications in many scientific and engineering fields. To solve network consensus optimization problems, one of the most well-known approaches is the distributed gradient descent method (DGD). However, in networks with slow communication rates, DGD's performance is unsatisfactory for solving high-dimensional network consensus problems due to the communication bottleneck. This motivates us to design a communication-efficient DGD-type algorithm based on compressed information exchanges. Our contributions in this paper are three-fold: i) We develop a communication-efficient algorithm called amplified-differential compression DGD (ADC-DGD) and show that it converges under {\em any} unbiased compression operator; ii) We rigorously prove the convergence performances of ADC-DGD and show that they match with those of DGD without compression; iii) We reveal an interesting phase transition phenomenon in the convergence speed of ADC-DGD. Collectively, our findings advance the state-of-the-art of network consensus optimization theory.Comment: 11 pages, 11 figures, IEEE INFOCOM 201

A hybrid model approach for strange and multi-strange hadrons in 2.76 A TeV Pb+Pb collisions

Using the VISHNU hybrid model, we calculate the multiplicity, spectra, and elliptic flow of $\Lambda$, $\Xi$ and $\Omega$ in 2.76 A TeV Pb+Pb collisions. Comparisons between our calculations and the ALICE measurements show that the model generally describes the soft hadron data of these strange and multi-strange hadrons at several centrality bins. Mass ordering of elliptic flow among $\pi$, K, p, $\Lambda$, $\Xi$ and $\Omega$ has also been studied and discussed. With a nice description of the particle yields, we explore chemical and thermal freeze-out of various hadrons species at the LHC within the framework of the VISHNU hybrid model.Comment: version 2: with several references added, published in PR

Suppression of nano-channel ion conductance by electro-osmotic flow in nano-channels with weakly overlapping electrical double layers

This theoretical study investigates the nonlinear ionic current-voltage characteristics of nano-channels that have weakly overlapping electrical double layers. Numerical simulations as well as a 1-D mathematical model are developed to reveal that the electro-osmotic flow (EOF) interplays with the concentration-polarization process and depletes the ion concentration inside the channels, thus significantly suppressing the channel conductance. The conductance may be restored at high electrical biases in the presence of recirculating vortices within the channels. As a result of the EOF-driven ion depletion, a limiting-conductance behavior is identified, which is intrinsically different from the classical limiting-current behavior