An investigation of particle mixing in a gas-fluidized bed

Mechanism for particle movement in gas-fluidized beds was studied both from the theoretical and experimental points of view. In a two-dimensional fluidized bed particle trajectories were photographed when a bubble passed through

Adiabatic Quantum Computation and Deutsch's Algorithm

We show that by a suitable choice of a time dependent Hamiltonian, Deutsch's algorithm can be implemented by an adiabatic quantum computer. We extend our analysis to the Deutsch-Jozsa problem and estimate the required running time for both global and local adiabatic evolutions.Comment: 6 Pages, Revtex. Typos corrected, references added. Published versio

Thermodynamic Properties of Generalized Exclusion Statistics

We analytically calculate some thermodynamic quantities of an ideal $g$-on gas obeying generalized exclusion statistics. We show that the specific heat of a $g$-on gas ($g \neq 0$) vanishes linearly in any dimension as $T \to 0$ when the particle number is conserved and exhibits an interesting dual symmetry that relates the particle-statistics at $g$ to the hole-statistics at $1/g$ at low temperatures. We derive the complete solution for the cluster coefficients $b_l(g)$ as a function of Haldane's statistical interaction $g$ in $D$ dimensions. We also find that the cluster coefficients $b_l(g)$ and the virial coefficients $a_l(g)$ are exactly mirror symmetric ($l$=odd) or antisymmetric ($l$=even) about $g=1/2$. In two dimensions, we completely determine the closed forms about the cluster and the virial coefficients of the generalized exclusion statistics, which exactly agree with the virial coefficients of an anyon gas of linear energies. We show that the $g$-on gas with zero chemical potential shows thermodynamic properties similar to the photon statistics. We discuss some physical implications of our results.Comment: 24 pages, Revtex, Corrected typo

Benchmarking Practical RRM Algorithms for D2D Communications in LTE Advanced

Device-to-device (D2D) communication integrated into cellular networks is a means to take advantage of the proximity of devices and allow for reusing cellular resources and thereby to increase the user bitrates and the system capacity. However, when D2D (in the 3rd Generation Partnership Project also called Long Term Evolution (LTE) Direct) communication in cellular spectrum is supported, there is a need to revisit and modify the existing radio resource management (RRM) and power control (PC) techniques to realize the potential of the proximity and reuse gains and to limit the interference at the cellular layer. In this paper, we examine the performance of the flexible LTE PC tool box and benchmark it against a utility optimal iterative scheme. We find that the open loop PC scheme of LTE performs well for cellular users both in terms of the used transmit power levels and the achieved signal-to-interference-and-noise-ratio (SINR) distribution. However, the performance of the D2D users as well as the overall system throughput can be boosted by the utility optimal scheme, because the utility maximizing scheme takes better advantage of both the proximity and the reuse gains. Therefore, in this paper we propose a hybrid PC scheme, in which cellular users employ the open loop path compensation method of LTE, while D2D users use the utility optimizing distributed PC scheme. In order to protect the cellular layer, the hybrid scheme allows for limiting the interference caused by the D2D layer at the cost of having a small impact on the performance of the D2D layer. To ensure feasibility, we limit the number of iterations to a practically feasible level. We make the point that the hybrid scheme is not only near optimal, but it also allows for a distributed implementation for the D2D users, while preserving the LTE PC scheme for the cellular users.Comment: 30 pages, submitted for review April-2013. See also: G. Fodor, M. Johansson, D. P. Demia, B. Marco, and A. Abrardo, A joint power control and resource allocation algorithm for D2D communications, KTH, Automatic Control, Tech. Rep., 2012, qC 20120910, http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-10205

A large annotated corpus for learning natural language inference

Understanding entailment and contradiction is fundamental to understanding natural language, and inference about entailment and contradiction is a valuable testing ground for the development of semantic representations. However, machine learning research in this area has been dramatically limited by the lack of large-scale resources. To address this, we introduce the Stanford Natural Language Inference corpus, a new, freely available collection of labeled sentence pairs, written by humans doing a novel grounded task based on image captioning. At 570K pairs, it is two orders of magnitude larger than all other resources of its type. This increase in scale allows lexicalized classifiers to outperform some sophisticated existing entailment models, and it allows a neural network-based model to perform competitively on natural language inference benchmarks for the first time.Comment: To appear at EMNLP 2015. The data will be posted shortly before the conference (the week of 14 Sep) at http://nlp.stanford.edu/projects/snli

Major loop reconstruction from switching of individual particles

Major hysteresis loops of groups of isolated 60 mm square garnet particles of a regular two-dimensional array, have been measured magnetooptically. Individual loops for each particle were measured, and the statistics of the distribution of coercivities and interaction fields was determined. It is shown that from the measured coercivity distribution and calculated magnetostatic interaction fields the major hysteresis loop can be reconstructed. The switching sequence, and the major loop of an assembly of 535 particles were calculated numerically for two cases: first, when calculating the magnetostatic interaction, the 25 particles were assumed to be isolated; second, the major loop of the same 25 particles, embedded into a 939 square, was reconstructed taking into account the interactions among all 81 particles. The numerically simulated major hysteresis loops agree very well with the measured loops, demonstrating the reliability of numerical modeling