Landau-Zener problem with waiting at the minimum gap and related quench dynamics of a many-body system

We discuss a technique for solving the Landau-Zener (LZ) problem of finding the probability of excitation in a two-level system. The idea of time reversal for the Schrodinger equation is employed to obtain the state reached at the final time and hence the excitation probability. Using this method, which can reproduce the well-known expression for the LZ transition probability, we solve a variant of the LZ problem, which involves waiting at the minimum gap for a time t(w); we find an exact expression for the excitation probability as a function of t(w). We provide numerical results to support our analytical expressions. We then discuss the problem of waiting at the quantum critical point of a many-body system and calculate the residual energy generated by the time-dependent Hamiltonian. Finally, we discuss possible experimental realizations of this work.

Waiting for Gajah: an elephant mutualist's contingency plan for an endangered megafaunal disperser

Large animals are disproportionately likely to go extinct, and the effects of this on ecosystem processes are unclear. Megaherbivores (weighing over 1000kg) are thought to be particularly effective seed dispersers, yet only a few plant species solely or predominantly adapted for dispersal by megaherbivores have been identified. The reasons for this paradox may be elucidated by examining the ecology of so-called megafaunal fruiting species in Asia, where large-fruited species have been only sparsely researched. We conducted focal tree watches, camera trapping, fruit ageing trials, dung seed counts and germination trials to understand the ecology of Dillenia indica, a large-fruited species thought to be elephant-dispersed, in a tropical moist forest (Buxa Tiger Reserve, India). We find that the initial hardness of the fruit of D.indica ensures that its small (6mm) seeds will primarily be consumed and dispersed by elephants and perhaps other megaherbivores. Elephants removed 63.3% of camera trap-monitored fruits taken by frugivores. If the fruit of D.indica is not removed by a large animal, the seeds of D.indica become available to successively smaller frugivores as its fruits soften. Seeds from both hard and soft fruits are able to germinate, meaning these smaller frugivores may provide a mechanism for dispersal without megaherbivores.Synthesis. Dillenia indica's strategy for dispersal allows it to realize the benefits of dispersal by megaherbivores without becoming fully reliant on these less abundant species. This risk-spreading dispersal behaviour suggests D.indica will be able to persist even if its megafaunal disperser becomes extinct.

Prediction of Queue Waiting Times for Metascheduling on Parallel Batch Systems

Prediction of queue waiting times of jobs submitted to production parallel batch systems is important to provide overall estimates to users and can also help meta-schedulers make scheduling decisions. In this work, we have developed a framework for predicting ranges of queue waiting times for jobs by employing multi-class classification of similar jobs in history. Our hierarchical prediction strategy first predicts the point wait time of a job using dynamic k-Nearest Neighbor (kNN) method. It then performs a multi-class classification using Support Vector Machines (SVMs) among all the classes of the jobs. The probabilities given by the SVM for the class predicted using k-NN and its neighboring classes are used to provide a set of ranges of predicted wait times with probabilities. We have used these predictions and probabilities in a meta-scheduling strategy that distributes jobs to different queues/sites in a multi-queue/grid environment for minimizing wait times of the jobs. Experiments with different production supercomputer job traces show that our prediction strategies can give correct predictions for about 77-87% of the jobs, and also result in about 12% improved accuracy when compared to the next best existing method. Experiments with our meta-scheduling strategy using different production and synthetic job traces for various system sizes, partitioning schemes and different workloads, show that the meta-scheduling strategy gives much improved performance when compared to existing scheduling policies by reducing the overall average queue waiting times of the jobs by about 47%.

Reliable estimation via simulation

Let a and s denote the inter arrival times and service times in a GI/GI/1 queue. Let a (n), s (n) be the r.v.s, with distributions as the estimated distributions of a and s from iid samples of a and s of sizes n. Let w be a r.v. with the stationary distribution lr of the waiting times of the queue with input (a, s). We consider the problem of estimating E [w~], tx > 0 and 7r via simulations when (a (n), s (n)) are used as input. Conditions for the accuracy of the asymptotic estimate, continuity of the asymptotic variance and uniformity in the rate of convergence to the estimate are obtained. We also obtain rates of convergence for sample moments, the empirical process and the quantile process for the regenerative processes. Robust estimates are also obtained when an outlier contaminated sample of a and s is provided. In the process we obtain consistency, continuity and asymptotic normality of M-estimators for stationary sequences. Some robustness results for Markov processes are included.

Performance modelling of a fault-tolerant real-time multiprocessor using stochastic Petri nets

The fault-tolerant multiprocessor (ftmp) is a bus-based multiprocessor architecture with real-time and fault- tolerance features and is used in critical aerospace applications. A preliminary performance evaluation is of crucial importance in the design of such systems. In this paper, we review stochastic Petri nets (spn) and developspn-based performance models forftmp. These performance models enable efficient computation of important performance measures such as processing power, bus contention, bus utilization, and waiting times.

Timing the Emergence of Resistance to Anti-HIV Drugs with Large Genetic Barriers

New antiretroviral drugs that offer large genetic barriers to resistance, such as the recently approved inhibitors of HIV-1 protease, tipranavir and darunavir, present promising weapons to avert the failure of current therapies for HIV infection. Optimal treatment strategies with the new drugs, however, are yet to be established. A key limitation is the poor understanding of the process by which HIV surmounts large genetic barriers to resistance. Extant models of HIV dynamics are predicated on the predominance of deterministic forces underlying the emergence of resistant genomes. In contrast, stochastic forces may dominate, especially when the genetic barrier is large, and delay the emergence of resistant genomes. We develop a mathematical model of HIV dynamics under the influence of an antiretroviral drug to predict the waiting time for the emergence of genomes that carry the requisite mutations to overcome the genetic barrier of the drug. We apply our model to describe the development of resistance to tipranavir in in vitro serial passage experiments. Model predictions of the times of emergence of different mutant genomes with increasing resistance to tipranavir are in quantitative agreement with experiments, indicating that our model captures the dynamics of the development of resistance to antiretroviral drugs accurately. Further, model predictions provide insights into the influence of underlying evolutionary processes such as recombination on the development of resistance, and suggest guidelines for drug design: drugs that offer large genetic barriers to resistance with resistance sites tightly localized on the viral genome and exhibiting positive epistatic interactions maximally inhibit the emergence of resistant genomes.

Focused Prefetching: Performance Oriented Prefetching Based On Commit Stalls

Loads that miss in L1 or L2 caches and waiting for their data at the head of the ROB cause significant slow down in the form of commit stalls. We identify that most of these commit stalls are caused by a small set of loads, referred to as LIMCOS (Loads Incurring Majority of COmmit Stalls). We propose simple history-based classifiers that track commit stalls suffered by loads to help us identify this small set of loads. We study an application of these classifiers to prefetching. The classifiers are used to train the prefetcher to focus on the misses suffered by LIMCOS. This, referred to as focused prefetching, results in a 9.8% gain in IPC over naive GHB based delta correlation prefetcher along with a 20.3% reduction in memory traffic for a set of 17 memory-intensive SPEC2000 benchmarks. Another important impact of focused prefetching is a 61% improvement in the accuracy of prefetches. We demonstrate that the proposed classification criterion performs better than other existing criteria like criticality and delinquent loads. Also we show that the criterion of focusing on commit stalls is robust enough across cache levels and can be applied to any prefetcher without any modifications to the prefetcher.

Heat-Transfer During Dropwise Condensation

A comprehensive model is developed for previous termheat transfernext term during previous termdropwise condensationnext term based on the assumption that previous termheat transfernext term takes place through the bare surface in between drops to form nuclei at nucleation sites during the waiting period required for nucleation. The dynamics of drop formation and surface renewal, and the presence of non-condensable gases in the vapour have been considered. The resulting equation expresses the dependence of the vapour-side previous termheat transfernext term coefficient on the previous termheatnext term flux, properties of the vapour, previous termcondensationnext term coefficient, mole fraction of non-condensable gases in the vapour, free area available for previous termcondensation,next term surface roughness and surface thermal properties. The equation is tested with the available data and the agreement is found to be satisfactory.

Improving the optimum generalised stop-and-wait ARQ scheme

Instead of waiting for the acknowledgments from all the copies of a single data block sent, as in the optimum generalised stop-and-wait ARQ scheme, the transmitter in the proposed scheme starts sending an optimum number of copies of the next block in the queue, soon after receiving the positive acknowledgment from the receiver, thereby further improving the throughput efficiency.

Reorientation of Water Inside Carbon Nanorings by Large Angular Jumps

Molecular dynamics simulations of the orientational dynamics of water molecules confined inside narrow carbon nanorings reveal that reorientational relaxation is mediated by large amplitude angular jumps. The distribution of waiting time between jumps peaks at about 60 fs, and has a slowly decaying exponential tail with a timescale of about 440 fs. These time scales are much faster than the mean waiting time between jumps of the water molecules in bulk.

Grids with multiple batch systems for performance enhancement of multi-component and parameter sweep parallel applications

In this work, we evaluate the benefits of using Grids with multiple batch systems to improve the performance of multi-component and parameter sweep parallel applications by reduction in queue waiting times. Using different job traces of different loads, job distributions and queue waiting times corresponding to three different queuing policies(FCFS, conservative and EASY backfilling), we conducted a large number of experiments using simulators of two important classes of applications. The first simulator models Community Climate System Model (CCSM), a prominent multi-component application and the second simulator models parameter sweep applications. We compare the performance of the applications when executed on multiple batch systems and on a single batch system for different system and application configurations. We show that there are a large number of configurations for which application execution using multiple batch systems can give improved performance over execution on a single system.

Analysis of the MAP/G(a,b)/1/N queue with multiple vacations

This paper deals with a batch service queue and multiple vacations. The system consists of a single server and a waiting room of finite capacity. Arrival of customers follows a Markovian arrival process (MAP). The server is unavailable for occasional intervals of time called vacations, and when it is available, customers are served in batches of maximum size ‘b’ with a minimum threshold value ‘a’. We obtain the queue length distributions at various epochs along with some key performance measures. Finally, some numerical results have been presented.

Performance analysis of a slotted-ALOHA protocol on a capture channel with fading

We consider the slotted ALOHA protocol on a channel with a capture effect. There are M waiting times which can be tight under realistic conditions. Finally, we obtain several results on the transient performance of the system, e.g., first time to overflow and the limits of the overflow process. We also extend the above results to the case of a capture channel exhibiting Markov modulated fading. Most of our results and proofs will be shown to hold also for the slotted ALOHA protocol without capture.

Memory effect in Dy0.5Sr0.5MnO3 single crystals

We have performed a series of magnetic aging experiments on single crystals of Dy0.5Sr0.5MnO3. The results demonstrate striking memory and chaos-like effects in this insulating half-doped perovskite manganite and suggest the existence of strong magnetic relaxation mechanisms of a clustered magnetic state. The spin-glass-like state established below a temperature T-sg approximate to 34 K originates from quenched disorder arising due to the ionic-radii mismatch at the rare earth site. However, deviations from the typical behavior seen in canonical spin glass materials are observed which indicate that the glassy magnetic properties are due to cooperative and frustrated dynamics in a heterogeneous or clustered magnetic state. In particular, the microscopic spin flip time obtained from dynamical scaling near the spin glass freezing temperature is four orders of magnitude larger than microscopic times found in atomic spin glasses. The magnetic viscosity deduced from the time dependence of the zero-field-cooled magnetization exhibits a peak at a temperature T < T-sg and displays a marked dependence on waiting time in zero field.

Performance analysis of the random early detection algorithm

In this article we consider a finite queue with its arrivals controlled by the random early detection algorithm. This is one of the most prominent congestion avoidance schemes in the Internet routers. The aggregate arrival stream from the population of transmission control protocol sources is locally considered stationary renewal or Markov modulated Poisson process with general packet length distribution. We study the exact dynamics of this queue and provide the stability and the rates of convergence to the stationary distribution and obtain the packet loss probability and the waiting time distribution. Then we extend these results to a two traffic class case with each arrival stream renewal. However, computing the performance indices for this system becomes computationally prohibitive. Thus, in the latter half of the article, we approximate the dynamics of the average queue length process asymptotically via an ordinary differential equation. We estimate the error term via a diffusion approximation. We use these results to obtain approximate transient and stationary performance of the system. Finally, we provide some computational examples to show the accuracy of these approximations.