Astrometry of H2_{2}O Masers in Nearby Star-Forming Regions with VERA --- IV. L1448C

We have carried out multi-epoch VLBI observations with VERA (VLBI Exploration of Radio Astrometry) of the 22~GHz H$_{2}$O masers associated with a Class 0 protostar L1448C in the Perseus molecular cloud. The maser features trace the base of collimated bipolar jet driven by one of the infrared counter parts of L1448C named as L1448C(N) or L1448-mm A. We detected possible evidences for apparent acceleration and precession of the jet according to the three-dimensional velocity structure. Based on the phase-referencing VLBI astrometry, we have successfully detected an annual parallax of the H$_{2}$O maser in L1448C to be 4.31$\pm$0.33~milliarcseconds (mas) which corresponds to a distance of 232$\pm$18~pc from the Sun. The present result is in good agreement with that of another H$_{2}$O maser source NGC~1333 SVS13A in the Perseus molecular cloud, 235~pc. It is also consistent with the photometric distance, 220~pc. Thus, the distance to the western part of the Perseus molecular cloud complex would be constrained to be about 235~pc rather than the larger value, 300~pc, previously reported.Comment: 15 pages, 5 figures, accepted for publication in PAS

Dynamic Trace-Based Data Dependency Analysis for Parallelization of C Programs

Writing parallel code is traditionally considered a difficult task, even when it is tackled from the beginning of a project. In this paper, we demonstrate an innovative toolset that faces this challenge directly. It provides the software developers with profile data and directs them to possible top-level, pipeline-style parallelization opportunities for an arbitrary sequential C program. This approach is complementary to the methods based on static code analysis and automatic code rewriting and does not impose restrictions on the structure of the sequential code or the parallelization style, even though it is mostly aimed at coarse-grained task-level parallelization. The proposed toolset has been utilized to define parallel code organizations for a number of real-world representative applications and is based on and is provided as free source

Darwin Meets Einstein: LISA Data Analysis Using Genetic Algorithms

This work presents the first application of the method of Genetic Algorithms (GAs) to data analysis for the Laser Interferometer Space Antenna (LISA). In the low frequency regime of the LISA band there are expected to be tens of thousands galactic binary systems that will be emitting gravitational waves detectable by LISA. The challenge of parameter extraction of such a large number of sources in the LISA data stream requires a search method that can efficiently explore the large parameter spaces involved. As signals of many of these sources will overlap, a global search method is desired. GAs represent such a global search method for parameter extraction of multiple overlapping sources in the LISA data stream. We find that GAs are able to correctly extract source parameters for overlapping sources. Several optimizations of a basic GA are presented with results derived from applications of the GA searches to simulated LISA data.Comment: 8 pages, 12 figure

Selenium and molybdenum enrichment in uranium roll-front deposits of Wyoming and Colorado, USA

Acknowledgements The authors wish to thank Cal VanHolland, Jim Bonner and John Cooper of Ur-Energy (Casper, Wyoming) for their assistance with sampling, data provision and feedback. We are grateful to Adrian Boyce and Alison McDonald of the Isotope Community Support Facility at SUERC for technical support with isotope sample preparation and analyses. Critical comments that greatly improved the manuscript from Samuel Spinks and Marat Abzalov are gratefully acknowledged. Funding This research was supported by a grant from the Natural Environment Research Council (NERC) (NE/M010953/1).Peer reviewedPublisher PD