Resumption of mass accretion in RS Oph

The latest outburst of the recurrent nova RS Oph occurred in 2006 February. Photometric data presented here show evidence of the resumption of optical flickering, indicating re-establishment of accretion by day 241 of the outburst. Magnitude variations of up to 0.32 mag in V band and 0.14 mag in B band on time-scales of 600–7000 s are detected. Over the two-week observational period, we also detect a 0.5 mag decline in the mean brightness, from V≈ 11.4 to 11.9, and record B≈ 12.9 mag. Limits on the mass accretion rate of [inline image] are calculated, which span the range of accretion rates modelled for direct wind accretion and Roche lobe overflow mechanisms. The current accretion rates make it difficult for thermonuclear runaway models to explain the observed recurrence interval, and this implies average accretion rates are typically higher than seen immediately post-outburst

The Computer Science Ontology: A Large-Scale Taxonomy of Research Areas

Ontologies of research areas are important tools for characterising, exploring, and analysing the research landscape. Some fields of research are comprehensively described by large-scale taxonomies, e.g., MeSH in Biology and PhySH in Physics. Conversely, current Computer Science taxonomies are coarse-grained and tend to evolve slowly. For instance, the ACM classification scheme contains only about 2K research topics and the last version dates back to 2012. In this paper, we introduce the Computer Science Ontology (CSO), a large-scale, automatically generated ontology of research areas, which includes about 26K topics and 226K semantic relationships. It was created by applying the Klink-2 algorithm on a very large dataset of 16M scientific articles. CSO presents two main advantages over the alternatives: i) it includes a very large number of topics that do not appear in other classifications, and ii) it can be updated automatically by running Klink-2 on recent corpora of publications. CSO powers several tools adopted by the editorial team at Springer Nature and has been used to enable a variety of solutions, such as classifying research publications, detecting research communities, and predicting research trends. To facilitate the uptake of CSO we have developed the CSO Portal, a web application that enables users to download, explore, and provide granular feedback on CSO at different levels. Users can use the portal to rate topics and relationships, suggest missing relationships, and visualise sections of the ontology. The portal will support the publication of and access to regular new releases of CSO, with the aim of providing a comprehensive resource to the various communities engaged with scholarly data

High Energy Phenomena in Clusters of Galaxies

Several phenomena in high energy astrophysics have been recently related to clusters of galaxies and to cosmic ray interactions occurring inside these structures. In many of these phenomena the observable effects depend on the energy density of cosmic rays confined in the Intra Cluster (IC) medium, which is a poorly known quantity. We propose here that useful indications about this quantity can be obtained from present and future observations of galaxy clusters in the radio and hard X-ray frequency ranges.Comment: 5 pages, 3 Figures, Latex (using espcrc2,epsfig), to appear in the Proceedings of the TAUP97, Eds. A. DiCredico et al., in press. Send comments to S.Colafrancesco: [email protected]

A Gaussian process framework for modelling instrumental systematics: application to transmission spectroscopy

Transmission spectroscopy, which consists of measuring the wavelength-dependent absorption of starlight by a planet's atmosphere during a transit, is a powerful probe of atmospheric composition. However, the expected signal is typically orders of magnitude smaller than instrumental systematics, and the results are crucially dependent on the treatment of the latter. In this paper, we propose a new method to infer transit parameters in the presence of systematic noise using Gaussian processes, a technique widely used in the machine learning community for Bayesian regression and classification problems. Our method makes use of auxiliary information about the state of the instrument, but does so in a non-parametric manner, without imposing a specific dependence of the systematics on the instrumental parameters, and naturally allows for the correlated nature of the noise. We give an example application of the method to archival NICMOS transmission spectroscopy of the hot Jupiter HD 189733, which goes some way towards reconciling the controversy surrounding this dataset in the literature. Finally, we provide an appendix giving a general introduction to Gaussian processes for regression, in order to encourage their application to a wider range of problems.Comment: 6 figures, 1 table, accepted for publication in MNRA

Klink-2: integrating multiple web sources to generate semantic topic networks

The amount of scholarly data available on the web is steadily increasing, enabling different types of analytics which can provide important insights into the research activity. In order to make sense of and explore this large-scale body of knowledge we need an accurate, comprehensive and up-to-date ontology of research topics. Unfortunately, human crafted classifications do not satisfy these criteria, as they evolve too slowly and tend to be too coarse-grained. Current automated methods for generating ontologies of research areas also present a number of limitations, such as: i) they do not consider the rich amount of indirect statistical and semantic relationships, which can help to understand the relation between two topics – e.g., the fact that two research areas are associated with a similar set of venues or technologies; ii) they do not distinguish between different kinds of hierarchical relationships; and iii) they are not able to handle effectively ambiguous topics characterized by a noisy set of relationships. In this paper we present Klink-2, a novel approach which improves on our earlier work on automatic generation of semantic topic networks and addresses the aforementioned limitations by taking advantage of a variety of knowledge sources available on the web. In particular, Klink-2 analyses networks of research entities (including papers, authors, venues, and technologies) to infer three kinds of semantic relationships between topics. It also identifies ambiguous keywords (e.g., “ontology”) and separates them into the appropriate distinct topics – e.g., “ontology/philosophy” vs. “ontology/semantic web”. Our experimental evaluation shows that the ability of Klink-2 to integrate a high number of data sources and to generate topics with accurate contextual meaning yields significant improvements over other algorithms in terms of both precision and recall

X-ray and UV observations of V751 Cyg in an optical high state

Aims: The VY Scl system (anti-dwarf nova) V751 Cyg is examined following a claim of a super-soft spectrum in the optical low state. Methods: A serendipitous XMM-Newton X-ray observation and, 21 months later, Swift X-ray and UV observations, have provided the best such data on this source so far. These optical high-state datasets are used to study the flux and spectral variability of V751 Cyg. Results: Both the XMM-Newton and Swift data show evidence for modulation of the X-rays for the first time at the known 3.467 hr orbital period of V751 Cyg. In two Swift observations, taken ten days apart, the mean X-ray flux remained unchanged, while the UV source brightened by half a magnitude. The X-ray spectrum was not super-soft during the optical high state, but rather due to multi-temperature optically thin emission, with significant (10^{21-22} cm^-2) absorption, which was higher in the observation by Swift than that of XMM-Newton. The X-ray flux is harder at orbital minimum, suggesting that the modulation is related to absorption, perhaps linked to the azimuthally asymmetric wind absorption seen previously in H-alpha.Comment: 6 pages, 9 figures, accepted for publication in A&

Antiphase dynamics in a multimode semiconductor laser with optical injection

A detailed experimental study of antiphase dynamics in a two-mode semiconductor laser with optical injection is presented. The device is a specially designed Fabry-Perot laser that supports two primary modes with a THz frequency spacing. Injection in one of the primary modes of the device leads to a rich variety of single and two-mode dynamical scenarios, which are reproduced with remarkable accuracy by a four dimensional rate equation model. Numerical bifurcation analysis reveals the importance of torus bifurcations in mediating transitions to antiphase dynamics and of saddle-node of limit cycle bifurcations in switching of the dynamics between single and two-mode regimes.Comment: 7 pages, 9 figure

A-STAR: The All-Sky Transient Astrophysics Reporter

The small mission A-STAR (All-Sky Transient Astrophysics Reporter) aims to locate the X-ray counterparts to ALIGO and other gravitational wave detector sources, to study the poorly-understood low luminosity gamma-ray bursts, and to find a wide variety of transient high-energy source types, A-STAR will survey the entire available sky twice per 24 hours. The payload consists of a coded mask instrument, Owl, operating in the novel low energy band 4-150 keV, and a sensitive wide-field focussing soft X-ray instrument, Lobster, working over 0.15-5 keV. A-STAR will trigger on ~100 GRBs/yr, rapidly distributing their locations.Comment: Accepted for the European Astronomical Society Publications Series: Proceedings of the Fall 2012 Gamma-Ray Burst Symposium held in Marbella, Spain, 8-12 Oct 201

TechMiner: Extracting Technologies from Academic Publications

In recent years we have seen the emergence of a variety of scholarly datasets. Typically these capture ‘standard’ scholarly entities and their connections, such as authors, affiliations, venues, publications, citations, and others. However, as the repositories grow and the technology improves, researchers are adding new entities to these repositories to develop a richer model of the scholarly domain. In this paper, we introduce TechMiner, a new approach, which combines NLP, machine learning and semantic technologies, for mining technologies from research publications and generating an OWL ontology describing their relationships with other research entities. The resulting knowledge base can support a number of tasks, such as: richer semantic search, which can exploit the technology dimension to support better retrieval of publications; richer expert search; monitoring the emergence and impact of new technologies, both within and across scientific fields; studying the scholarly dynamics associated with the emergence of new technologies; and others. TechMiner was evaluated on a manually annotated gold standard and the results indicate that it significantly outperforms alternative NLP approaches and that its semantic features improve performance significantly with respect to both recall and precision