Incoherence of Bose-Einstein condensates at supersonic speeds due to quantum noise

We calculate the effect of quantum noise in supersonic transport of Bose-Einstein condensates. When an obstacle obstructs the flow of atoms, quantum fluctuations cause atoms to be scattered incoherently into random directions. This suppresses the propagation of Cherenkov radiation, creating quantum turbulence and a crescent of incoherent atoms around the obstacle. We observe similar dynamics if the BEC is stirred by a laser beam: crescents of incoherent atoms are emitted from the laser's turning-points. Finally, we investigate supersonic flow through a disordered potential, and find that the quantum fluctuations generate an accumulation of incoherent atoms as the condensate enters the disorder.Comment: 6 pages, 5 figure

Quantifying Finite Temperature Effects in Atom Chip Interferometry of Bose-Einstein Condensates

We quantify the effect of phase fluctuations on atom chip interferometry of Bose-Einstein condensates. At very low temperatures, we observe small phase fluctuations, created by mean-field depletion, and a resonant production of vortices when the two clouds are initially in anti-phase. At higher temperatures, we show that the thermal occupation of Bogoliubov modes makes vortex production vary smoothly with the initial relative phase difference between the two atom clouds. We also propose a technique to observe vortex formation directly by creating a weak link between the two clouds. The position and direction of circulation of the vortices is subsequently revealed by kinks in the interference fringes produced when the two clouds expand into one another. This procedure may be exploited for precise force measurement or motion detection.Comment: 7 pages, 5 figure

Duality Between Prefetching and Queued Writing with Parallel Disks

This is the published version, made available with the permission of the publisher. Copyright © 2005 Society for Industrial and Applied Mathematics.Parallel disks promise to be a cost effective means for achieving high bandwidth in applications involving massive data sets, but algorithms for parallel disks can be difficult to devise. To combat this problem, we define a useful and natural duality between writing to parallel disks and the seemingly more difficult problem of prefetching. We first explore this duality for applications involving read-once accesses using parallel disks. We get a simple linear time algorithm for computing optimal prefetch schedules and analyze the efficiency of the resulting schedules for randomly placed data and for arbitrary interleaved accesses to striped sequences. Duality also provides an optimal schedule for prefetching plus caching, where blocks can be accessed multiple times. Another application of this duality gives us the first parallel disk sorting algorithms that are provably optimal up to lower-order terms. One of these algorithms is a simple and practical variant of multiway mergesort, addressing a question that had been open for some time

Duality Between Prefetching and Queued Writing with Parallel Disks

AMS subject classifications. 68W10, 68W20, 68W40, 68M20, 68P10, 68P20, 68Q17 DOI. 10.1137/S0097539703431573Parallel disks promise to be a cost effective means for achieving high bandwidth in applications involving massive data sets, but algorithms for parallel disks can be difficult to devise. To combat this problem, we define a useful and natural duality between writing to parallel disks and the seemingly more difficult problem of prefetching. We first explore this duality for applications involving read-once accesses using parallel disks. We get a simple linear time algorithm for computing optimal prefetch schedules and analyze the efficiency of the resulting schedules for randomly placed data and for arbitrary interleaved accesses to striped sequences. Duality also provides an optimal schedule for prefetching plus caching, where blocks can be accessed multiple times. Another application of this duality gives us the first parallel disk sorting algorithms that are provably optimal up to lower-order terms. One of these algorithms is a simple and practical variant of multiway mergesort, addressing a question that had been open for some time

Disruption of reflecting Bose-Einstein condensates due to inter-atomic interactions and quantum noise

We perform fully three-dimensional simulations, using the truncated Wigner method, to investigate the reflection of Bose-Einstein condensates from abrupt potential barriers. We show that the inter-atomic interactions can disrupt the internal structure of a cigar-shaped cloud with a high atom density at low approach velocities, damping the center-of-mass motion and generating vortices. Furthermore, by incorporating quantum noise we show that scattering halos form at high approach velocities, causing an associated condensate depletion. We compare our results to recent experimental observations.Comment: 5 figure

The extinct, giant giraffid Sivatherium giganteum: skeletal reconstruction and body mass estimation

Sivatherium giganteum is an extinct giraffid from the Plio–Pleistocene boundary of the Himalayan foothills. To date, there has been no rigorous skeletal reconstruction of this unusual mammal. Historical and contemporary accounts anecdotally state that Sivatherium rivalled the African elephant in terms of its body mass, but this statement has never been tested. Here, we present a three-dimensional composite skeletal reconstruction and calculate a representative body mass estimate for this species using a volumetric method. We find that the estimated adult body mass of 1246 kg (857—1812 kg range) does not approach that of an African elephant, but confirms that Sivatherium was certainly a large giraffid, and may have been the largest ruminant mammal that has ever existed. We contrast this volumetric estimate with a bivariate scaling estimate derived from Sivatherium's humeral circumference and find that there is a discrepancy between the two. The difference implies that the humeral circumference of Sivatherium is greater than expected for an animal of this size, and we speculate this may be linked to a cranial shift in centre of mass

Identifying Highly Connected Counties Compensates for Resource Limitations when Evaluating National Spread of an Invasive Pathogen

Surveying invasive species can be highly resource intensive, yet near-real-time evaluations of invasion progress are important resources for management planning. In the case of the soybean rust invasion of the United States, a linked monitoring, prediction, and communication network saved U.S. soybean growers approximately $200 M/yr. Modeling of future movement of the pathogen (Phakopsora pachyrhizi) was based on data about current disease locations from an extensive network of sentinel plots. We developed a dynamic network model for U.S. soybean rust epidemics, with counties as nodes and link weights a function of host hectarage and wind speed and direction. We used the network model to compare four strategies for selecting an optimal subset of sentinel plots, listed here in order of increasing performance: random selection, zonal selection (based on more heavily weighting regions nearer the south, where the pathogen overwinters), frequency-based selection (based on how frequently the county had been infected in the past), and frequency-based selection weighted by the node strength of the sentinel plot in the network model. When dynamic network properties such as node strength are characterized for invasive species, this information can be used to reduce the resources necessary to survey and predict invasion progress

Remote sensing and modeling of mosquito abundance and habitats in Coastal Virginia, USA

The increase in mosquito populations following extreme weather events poses a major threat to humans because of mosquitoes’ ability to carry disease-causing pathogens, particularly in low-lying, poorly drained coastal plains vulnerable to tropical cyclones. In areas with reservoirs of disease, mosquito abundance information can help to identify the areas at higher risk of disease transmission. Using a Geographic Information System (GIS), mosquito abundance is predicted across the City of Chesapeake, Virginia. The mosquito abundance model uses mosquito light trap counts, a habitat suitability model, and dynamic environmental variables (temperature and precipitation) to predict the abundance of the species Culiseta melanura, as well as the combined abundance of the ephemeral species, Aedes vexans and Psorophora columbiae, for the year 2003. Remote sensing techniques were used to quantify environmental variables for a potential habitat suitability index for the mosquito species. The goal of this study was to produce an abundance model that could guide risk assessment, surveillance, and potential disease transmission. Results highlight the utility of integrating field surveillance, remote sensing for synoptic landscape habitat distributions, and dynamic environmental data for predicting mosquito vector abundance across low-lying coastal plains. Limitations of mosquito trapping and multi-source geospatial environmental data are highlighted for future spatial modeling of disease transmission risk