275 research outputs found
RAM-Efficient External Memory Sorting
In recent years a large number of problems have been considered in external
memory models of computation, where the complexity measure is the number of
blocks of data that are moved between slow external memory and fast internal
memory (also called I/Os). In practice, however, internal memory time often
dominates the total running time once I/O-efficiency has been obtained. In this
paper we study algorithms for fundamental problems that are simultaneously
I/O-efficient and internal memory efficient in the RAM model of computation.Comment: To appear in Proceedings of ISAAC 2013, getting the Best Paper Awar
10091 Abstracts Collection -- Data Structures
From February 28th to March 5th 2010, the Dagstuhl Seminar 10091 "Data
Structures" was held in Schloss Dagstuhl~--~Leibniz Center for
Informatics. It brought together 45 international researchers to
discuss recent developments concerning data structures in terms of
research, but also in terms of new technologies that impact how data
can be stored, updated, and retrieved. During the seminar a fair
number of participants presented their current research and open
problems where discussed. This document first briefly describes the
seminar topics and then gives the abstracts of the presentations given
during the seminar
The radial evolution of solar wind speeds
The WSA-ENLIL model predicts significant evolution of the solar wind speed. Along a flux tube the solar wind speed at 1.0 AU and beyond is found to be significantly altered from the solar wind speed in the outer corona at 0.1 AU, with most of the change occurring within a few tenths of an AU from the Sun. The evolution of the solar wind speed is most pronounced during solar minimum for solar wind with observed speeds at 1.0 AU between 400 and 500 km/s, while the fastest and slowest solar wind experiences little acceleration or deceleration. Solar wind ionic charge state observations made near 1.0 AU during solar minimum are found to be consistent with a large fraction of the intermediate-speed solar wind having been accelerated or decelerated from slower or faster speeds. This paper sets the groundwork for understanding the evolution of wind speed with distance, which is critical for interpreting the solar wind composition observations near Earth and throughout the inner heliosphere. We show from composition observations that the intermediate-speed solar wind (400-500 km/s) represents a mix of what was originally fast and slow solar wind, which implies a more bimodal solar wind in the corona than observed at 1.0 AU
Querying Probabilistic Neighborhoods in Spatial Data Sets Efficiently
In this paper we define the notion
of a probabilistic neighborhood in spatial data: Let a set of points in
, a query point , a distance metric \dist,
and a monotonically decreasing function be
given. Then a point belongs to the probabilistic neighborhood of with respect to with probability f(\dist(p,q)). We envision
applications in facility location, sensor networks, and other scenarios where a
connection between two entities becomes less likely with increasing distance. A
straightforward query algorithm would determine a probabilistic neighborhood in
time by probing each point in .
To answer the query in sublinear time for the planar case, we augment a
quadtree suitably and design a corresponding query algorithm. Our theoretical
analysis shows that -- for certain distributions of planar -- our algorithm
answers a query in time with high probability
(whp). This matches up to a logarithmic factor the cost induced by
quadtree-based algorithms for deterministic queries and is asymptotically
faster than the straightforward approach whenever .
As practical proofs of concept we use two applications, one in the Euclidean
and one in the hyperbolic plane. In particular, our results yield the first
generator for random hyperbolic graphs with arbitrary temperatures in
subquadratic time. Moreover, our experimental data show the usefulness of our
algorithm even if the point distribution is unknown or not uniform: The running
time savings over the pairwise probing approach constitute at least one order
of magnitude already for a modest number of points and queries.Comment: The final publication is available at Springer via
http://dx.doi.org/10.1007/978-3-319-44543-4_3
Ensemble Forecasts of Solar Wind Connectivity to 1 Rs using ADAPT-WSA
The solar wind which arrives at any location in the solar system is, in
principle, relatable to the outflow of solar plasma from a single source
location. This source location, itself usually being part of a larger coronal
hole, is traceable to 1 Rs along the Sun's magnetic field, in which the entire
path from 1 Rs to a location in the heliosphere is referred to as the solar
wind connectivity. While not directly measurable, the connectivity between the
near-Earth solar wind is of particular importance to space weather. The solar
wind solar source region can be obtained by leveraging near-sun magnetic field
models and a model of the interplanetary solar wind. In this article we present
a method for making an ensemble forecast of the connectivity presented as a
probability distribution obtained from a weighted collection of individual
forecasts from the combined Air Force Data Assimilative Photospheric Flux
Transport - Wang Sheeley Arge (ADAPT-WSA) model. The ADAPT model derives the
photospheric magnetic field from synchronic magnetogram data, using flux
transport physics and ongoing data assimilation processes. The WSA model uses a
coupled set of potential field type models to derive the coronal magnetic
field, and an empirical relationship to derive the terminal solar wind speed
observed at Earth. Our method produces an arbitrary 2D probability distribution
capable of reflecting complex source configurations with minimal assumptions
about the distribution structure, prepared in a computationally efficient
manner.Comment: Accepted to the journal "Space Weather
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The distribution of solar wind speeds during solar minimum: calibration for numerical solar wind modeling constraints on the source of the slow solar wind
It took the solar polar passage of Ulysses in the early 1990s to establish the global structure of the solar wind speed during solar minimum. However, it remains unclear if the solar wind is composed of two distinct populations of solar wind from different sources (e.g., closed loops which open up to produce the slow solar wind) or if the fast and slow solar wind rely on the superradial expansion of the magnetic field to account for the observed solar wind speed variation. We investigate the solar wind in the inner corona using the Wang-Sheeley-Arge (WSA) coronal model incorporating a new empirical magnetic topology–velocity relationship calibrated for use at 0.1 AU. In this study the empirical solar wind speed relationship was determined by using Helios perihelion observations, along with results from Riley et al. (2003) and Schwadron et al. (2005) as constraints. The new relationship was tested by using it to drive the ENLIL 3-D MHD solar wind model and obtain solar wind parameters at Earth (1.0 AU) and Ulysses (1.4 AU). The improvements in speed, its variability, and the occurrence of high-speed enhancements provide confidence that the new velocity relationship better determines the solar wind speed in the outer corona (0.1 AU). An analysis of this improved velocity field within the WSA model suggests the existence of two distinct mechanisms of the solar wind generation, one for fast and one for slow solar wind, implying that a combination of present theories may be necessary to explain solar wind observations
A simple optimal randomized algorithm for sorting on the PDM
The Parallel Disks Model (PDM) has been proposed to alleviate the I/O bottleneck that arises in the processing of massive data sets. Sorting has been extensively studied on the PDM model due to the fundamental nature of the problem. Several randomized algorithms are known for sorting. Most of the prior algorithms suffer from undue complications in memory layouts, implementation, or lack of tight analysis. In this paper we present a simple randomized algorithm that sorts in optimal time with high probablity and has all the desirable features for practical implementation
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Metrics for solar wind prediction models: Comparison of empirical, hybrid, and physics-based schemes with 8 years of L1 observations
Space weather effects on technological systems originate with energy carried from the Sun to the terrestrial environment by the solar wind. In this study, we present results of modeling of solar corona-heliosphere processes to predict solar wind conditions at the L1 Lagrangian point upstream of Earth. In particular we calculate performance metrics for (1) empirical, (2) hybrid empirical/physics-based, and (3) full physics-based coupled corona-heliosphere models over an 8-year period (1995–2002). L1 measurements of the radial solar wind speed are the primary basis for validation of the coronal and heliosphere models studied, though other solar wind parameters are also considered. The models are from the Center for Integrated Space-Weather Modeling (CISM) which has developed a coupled model of the whole Sun-to-Earth system, from the solar photosphere to the terrestrial thermosphere. Simple point-by-point analysis techniques, such as mean-square-error and correlation coefficients, indicate that the empirical coronal-heliosphere model currently gives the best forecast of solar wind speed at 1 AU. A more detailed analysis shows that errors in the physics-based models are predominately the result of small timing offsets to solar wind structures and that the large-scale features of the solar wind are actually well modeled. We suggest that additional “tuning” of the coupling between the coronal and heliosphere models could lead to a significant improvement of their accuracy. Furthermore, we note that the physics-based models accurately capture dynamic effects at solar wind stream interaction regions, such as magnetic field compression, flow deflection, and density buildup, which the empirical scheme cannot
Compressed Data Structures for Dynamic Sequences
We consider the problem of storing a dynamic string over an alphabet
in compressed form. Our representation
supports insertions and deletions of symbols and answers three fundamental
queries: returns the -th symbol in ,
counts how many times a symbol occurs among the
first positions in , and finds the position
where a symbol occurs for the -th time. We present the first
fully-dynamic data structure for arbitrarily large alphabets that achieves
optimal query times for all three operations and supports updates with
worst-case time guarantees. Ours is also the first fully-dynamic data structure
that needs only bits, where is the -th order
entropy and is the string length. Moreover our representation supports
extraction of a substring in optimal time
- …