116 research outputs found

    Coronal shocks associated with CMEs and flares and their space weather consequences

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    We study the geoeffectiveness of a sample of complex events; each includes a coronal type II burst, accompanied by a GOES SXR flare and LASCO CME. The radio bursts were recorded by the ARTEMIS-IV radio spectrograph, in the 100-650 MHz range; the GOES SXR flares and SOHO/LASCO CMEs, were obtained from the Solar Geophysical Data (SGD) and the LASCO catalogue respectively. These are compared with changes of solar wind parameters and geomagnetic indices in order to establish a relationship between solar energetic events and their effects on geomagnetic activity.Comment: Universal Heliophysical Processes, Proceedings of the International Astronomical Union, IAU Symposium, Volume 257, p. 61-6

    Computing maximum cliques in B2B_2-EPG graphs

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    EPG graphs, introduced by Golumbic et al. in 2009, are edge-intersection graphs of paths on an orthogonal grid. The class BkB_k-EPG is the subclass of EPG graphs where the path on the grid associated to each vertex has at most kk bends. Epstein et al. showed in 2013 that computing a maximum clique in B1B_1-EPG graphs is polynomial. As remarked in [Heldt et al., 2014], when the number of bends is at least 44, the class contains 22-interval graphs for which computing a maximum clique is an NP-hard problem. The complexity status of the Maximum Clique problem remains open for B2B_2 and B3B_3-EPG graphs. In this paper, we show that we can compute a maximum clique in polynomial time in B2B_2-EPG graphs given a representation of the graph. Moreover, we show that a simple counting argument provides a 2(k+1){2(k+1)}-approximation for the coloring problem on BkB_k-EPG graphs without knowing the representation of the graph. It generalizes a result of [Epstein et al, 2013] on B1B_1-EPG graphs (where the representation was needed)

    Reconstructing the 3-D Trajectories of CMEs in the Inner Heliosphere

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    A method for the full three-dimensional (3-D) reconstruction of the trajectories of coronal mass ejections (CMEs) using Solar TErrestrial RElations Observatory (STEREO) data is presented. Four CMEs that were simultaneously observed by the inner and outer coronagraphs (COR1 and 2) of the Ahead and Behind STEREO satellites were analysed. These observations were used to derive CME trajectories in 3-D out to ~15Rsun. The reconstructions using COR1/2 data support a radial propagation model. Assuming pseudo-radial propagation at large distances from the Sun (15-240Rsun), the CME positions were extrapolated into the Heliospheric Imager (HI) field-of-view. We estimated the CME velocities in the different fields-of-view. It was found that CMEs slower than the solar wind were accelerated, while CMEs faster than the solar wind were decelerated, with both tending to the solar wind velocity.Comment: 17 pages, 10 figures, 1 appendi

    On the Parameterized Complexity of Clique Elimination Distance

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    A Backward/Forward Recovery Approach for the Preconditioned Conjugate Gradient Algorithm

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    Several recent papers have introduced a periodic verification mechanism to detect silent errors in iterative solvers. Chen [PPoPP'13, pp. 167--176] has shown how to combine such a verification mechanism (a stability test checking the orthogonality of two vectors and recomputing the residual) with checkpointing: the idea is to verify every dd iterations, and to checkpoint every cĂ—dc \times d iterations. When a silent error is detected by the verification mechanism, one can rollback to and re-execute from the last checkpoint. In this paper, we also propose to combine checkpointing and verification, but we use algorithm-based fault tolerance (ABFT) rather than stability tests. ABFT can be used for error detection, but also for error detection and correction, allowing a forward recovery (and no rollback nor re-execution) when a single error is detected. We introduce an abstract performance model to compute the performance of all schemes, and we instantiate it using the preconditioned conjugate gradient algorithm. Finally, we validate our new approach through a set of simulations
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