Separation and fractionation of order and disorder in highly polydisperse systems

We study a polydisperse soft-spheres model for colloids by means of microcanonical Monte Carlo simulations. We consider a polydispersity as high as 24%. Although solidification occurs, neither a crystal nor an amorphous state are thermodynamically stable. A finite size scaling analysis reveals that in the thermodynamic limit: a the fluid-solid transition is rather a crystal-amorphous phase-separation, b such phase-separation is preceded by the dynamic glass transition, and c small and big particles arrange themselves in the two phases according to a complex pattern not predicted by any fractionation scenario.

Erratum: Suppression of localization in kronig-penney models with correlated disorder (Vol. 49, PG 147, 1994)

We consider the electron dynamics and transport properties of one-dimensional continuous models with random, short-range correlated impurities. We develop a generalized Poincare map formalism to cast the Schrodinger equation for any potential into a discrete set of equations, illustrating its application by means of a specific example. We then concentrate on the case of a Kronig-Penney model with dimer impurities. The previous technique allows us to show that this model presents infinitely many resonances (zeroes of the reflection coefficient at a single dimer) that give rise to a band of extended states, in contradiction with the general viewpoint that all one-dimensional models with random potentials support only localized states. We report on exact transfer-matrix numerical calculations of the transmission coefFicient, density of states, and localization length for various strengths of disorder. The most important conclusion so obtained is that this kind of system has a very large number of extended states. Multifractal analysis of very long systems clearly demonstrates the extended character of such states in the thermodynamic limit. In closing, we brieBy discuss the relevance of these results in several physical contexts.

Brownian Carnot engine

The Carnot cycle imposes a fundamental upper limit to the efficiency of a macroscopic motor operating between two thermal baths. However, this bound needs to be reinterpreted at microscopic scales, where molecular bio-motors and some artificial micro-engines operate. As described by stochastic thermodynamics, energy transfers in microscopic systems are random and thermal fluctuations induce transient decreases of entropy, allowing for possible violations of the Carnot limit. Here we report an experimental realization of a Carnot engine with a single optically trapped Brownian particle as the working substance. We present an exhaustive study of the energetics of the engine and analyse the fluctuations of the finite-time efficiency, showing that the Carnot bound can be surpassed for a small number of non-equilibrium cycles. As its macroscopic counterpart, the energetics of our Carnot device exhibits basic properties that one would expect to observe in any microscopic energy transducer operating with baths at different temperatures. Our results characterize the sources of irreversibility in the engine and the statistical properties of the efficiency-an insight that could inspire new strategies in the design of efficient nano-motors.

A Hardware Implementation of a Run-Time Scheduler for Reconfigurable Systems

New generation embedded systems demand high performance, efficiency and flexibility. Reconfigurable hardware can provide all these features. However the costly reconfiguration process and the lack of management support have prevented a broader use of these resources. To solve these issues we have developed a scheduler that deals with task-graphs at run-time, steering its execution in the reconfigurable resources while carrying out both prefetch and replacement techniques that cooperate to hide most of the reconfiguration delays. In our scheduling environment task-graphs are analyzed at design-time to extract useful information. This information is used at run-time to obtain near-optimal schedules, escaping from local-optimum decisions, while only carrying out simple computations. Moreover, we have developed a hardware implementation of the scheduler that applies all the optimization techniques while introducing a delay of only a few clock cycles. In the experiments our scheduler clearly outperforms conventional run-time schedulers based on As-Soon-As-Possible techniques. In addition, our replacement policy, specially designed for reconfigurable systems, achieves almost optimal results both regarding reuse and performance.

A Hardware Task-Graph Scheduler for Reconfigurable Multi-tasking Systems

Reconfigurable hardware can be used to build a multitasking system where tasks are assigned to HW resources at run-time according to the requirements of the running applications. These tasks are frequently represented as direct acyclic graphs and their execution is typically controlled by an embedded processor that schedules the graph execution. In order to improve the efficiency of the system, the scheduler can apply prefetch and reuse techniques that can greatly reduce the reconfiguration latencies. For an embedded processor all these computations represent a heavy computational load that can significantly reduce the system performance. To overcome this problem we have implemented a HW scheduler using reconfigurable resources. In addition we have implemented both prefetch and replacement techniques that obtain as good results as previous complex SW approaches, while demanding just a few clock cycles to carry out the computations. We consider that the HW cost of the system (in our experiments 3% of a Virtex-II PRO xc2vp30 FPGA) is affordable taking into account the great efficiency of the techniques applied to hide the reconfiguration latency and the negligible run-time penalty introduced by the scheduler computations.