SearcharxivSearch

arXiv subjects

K. Harrison

Publications and source records attributed to K. Harrison.

5 recordsLinked to original sources

Detection and characterisation of binary asteroid candidates through stellar occultations

Binary asteroids provide key access to fundamental parameters of Solar System remnants and planetary formations. However, the current knowledge of binary asteroids remains strongly biased by observational limitations, and main belt binary systems are still poorly characterised since current techniques preferentially detect either widely separated binaries close and bright systems. In this context, the high-precision astrometry of the Gaia mission has revealed a new population of candidate binaries exhibiting dynamical signatures consistent with unresolved companions. This work is part of the GaiaMoons program, and our aim with it was to characterise a sample of 357 potential binary asteroid targets and confirm or refute their binary nature. The properties of these candidates were derived from the high-precision photometric and astrometric observations provided by Gaia. We adopted stellar occultation as the observational method to study these targets. Between October 2023 and February 2026, we successfully carried out 165 observations for 101 targets. We subsequently analysed these events in the context of the available literature and previously reported observations. Thirty three observation led at least two positives for 24 objects that have undergone unprecedented occultation observation campaigns, with four objects showing indications of binary or contact binary features, namely 1127 Mimi, 35420 1998 AG6, 206 Hersilia, and 36882 2000 SW155. For the vast majority of these objects, the resulting dataset from all reduced observations provides unique physical and astrometric constraints, as they had never been observed through stellar occultations before. GaiaMoons illustrates how stellar occultation campaigns associated with Gaia observations generate a self-improving cycle to find new binary, thereby probing size and shape to constrain future observations.

astro-ph.EP

The long-term spectral changes of eta Carinae: are they caused by a dissipating occulter as indicated by CMFGEN models?

Eta Carinae ($\eta$\,Car) exhibits a unique set of P Cygni profiles with both broad and narrow components. Over many decades, the spectrum has changed -- there has been an increase in observed continuum fluxes and a decrease in FeII and HI emission line equivalent widths. The spectrum is evolving towards that of a P Cygni star such as P~Cygni itself and HDE~316285. The spectral evolution has been attributed to intrinsic variations such as a decrease in the mass-loss rate of the primary star or differential evolution in a latitudinal-dependent stellar wind. However intrinsic wind changes conflict with three observational results: the steady long-term bolometric luminosity; the repeating X-ray light curve over the binary period; and the constancy of the dust-scattered spectrum from the Homunculus. We extend previous work that showed a secular strengthening of P~Cygni absorptions by adding more orbital cycles to overcome temporary instabilities and by examining more atomic transitions. {\sc cmfgen} modeling of the primary wind shows that a time-decreasing mass-loss rate is not the best explanation for the observations. However, models with a `small' dissipating absorber in our line-of-site can explain both the increase in brightness and changes in the emission and P Cygni absorption profiles. If the spectral evolution is caused by the dissipating circumstellar medium, and not by intrinsic changes in the binary, the dynamical timescale to recover from the Great Eruption is much less than a century, different from previous suggestions.

astro-ph.SR

Ganga: a tool for computational-task management and easy access to Grid resources

In this paper, we present the computational task-management tool Ganga, which allows for the specification, submission, bookkeeping and post-processing of computational tasks on a wide set of distributed resources. Ganga has been developed to solve a problem increasingly common in scientific projects, which is that researchers must regularly switch between different processing systems, each with its own command set, to complete their computational tasks. Ganga provides a homogeneous environment for processing data on heterogeneous resources. We give examples from High Energy Physics, demonstrating how an analysis can be developed on a local system and then transparently moved to a Grid system for processing of all available data. Ganga has an API that can be used via an interactive interface, in scripts, or through a GUI. Specific knowledge about types of tasks or computational resources is provided at run-time through a plugin system, making new developments easy to integrate. We give an overview of the Ganga architecture, give examples of current use, and demonstrate how Ganga can be used in many different areas of science.

cs.DC

GANGA: a user-Grid interface for Atlas and LHCb

The Gaudi/Athena and Grid Alliance (GANGA) is a front-end for the configuration, submission, monitoring, bookkeeping, output collection, and reporting of computing jobs run on a local batch system or on the grid. In particular, GANGA handles jobs that use applications written for the Gaudi software framework shared by the Atlas and LHCb experiments. GANGA exploits the commonality of Gaudi-based computing jobs, while insulating against grid-, batch- and framework-specific technicalities, to maximize end-user productivity in defining, configuring, and executing jobs. Designed for a python-based component architecture, GANGA has a modular underpinning and is therefore well placed for contributing to, and benefiting from, work in related projects. Its functionality is accessible both from a scriptable command-line interface, for expert users and automated tasks, and through a graphical interface, which simplifies the interaction with GANGA for beginning and c1asual users. This paper presents the GANGA design and implementation, the development of the underlying software bus architecture, and the functionality of the first public GANGA release.

cs.SE

DIRAC - Distributed Infrastructure with Remote Agent Control

This paper describes DIRAC, the LHCb Monte Carlo production system. DIRAC has a client/server architecture based on: Compute elements distributed among the collaborating institutes; Databases for production management, bookkeeping (the metadata catalogue) and software configuration; Monitoring and cataloguing services for updating and accessing the databases. Locally installed software agents implemented in Python monitor the local batch queue, interrogate the production database for any outstanding production requests using the XML-RPC protocol and initiate the job submission. The agent checks and, if necessary, installs any required software automatically. After the job has processed the events, the agent transfers the output data and updates the metadata catalogue. DIRAC has been successfully installed at 18 collaborating institutes, including the DataGRID, and has been used in recent Physics Data Challenges. In the near to medium term future we must use a mixed environment with different types of grid middleware or no middleware. We describe how this flexibility has been achieved and how ubiquitously available grid middleware would improve DIRAC.

cs.DC