Small scale structure in diffuse molecular gas from repeated FUSE and visible spectra of HD 34078

We present preliminary results from an ongoing program devoted to a study of small scale structure in the spatial distribution of molecular gas. Our work is based on multi-epoch FUSE and visible observations of HD34078. A detailed comparison of H2, CH and CH+ absorption lines is performed. No short term variations are seen (except for highly excited H2) but long-term changes in N(CH) are clearly detected when comparing our data to spectra taken about 10 years ago.Comment: 4 pages, 2 figures, To appear in the Proceedings of the XVII IAP Colloquium "Gaseous Matter in Galaxies and Intergalactic Space

A pp-adic RanSaC algorithm for stereo vision using Hensel lifting

A $p$-adic variation of the Ran(dom) Sa(mple) C(onsensus) method for solving the relative pose problem in stereo vision is developped. From two 2-adically encoded images a random sample of five pairs of corresponding points is taken, and the equations for the essential matrix are solved by lifting solutions modulo 2 to the 2-adic integers. A recently devised $p$-adic hierarchical classification algorithm imitating the known LBG quantisation method classifies the solutions for all the samples after having determined the number of clusters using the known intra-inter validity of clusterings. In the successful case, a cluster ranking will determine the cluster containing a 2-adic approximation to the "true" solution of the problem.Comment: 15 pages; typos removed, abstract changed, computation error remove

Rushes summarization by IRIM consortium: redundancy removal and multi-feature fusion

International audienceIn this paper, we present the first participation of a consortium of French laboratories, IRIM, to the TRECVID 2008 BBC Rushes Summarization task. Our approach resorts to video skimming. We propose two methods to reduce redundancy, as rushes include several takes of scenes. We also take into account low and midlevel semantic features in an ad-hoc fusion method in order to retain only significant content

Warm H2_2 as a probe of massive accretion and feedback through shocks and turbulence across cosmic time

Galaxy formation depends on a complex interplay between gravitational collapse, gas accretion, merging, and feedback processes. Yet, after many decades of investigation, these concepts are poorly understood. This paper presents the argument that warm H$_2$ can be used as a tool to unlock some of these mysteries. Turbulence, shocks and outflows, driven by star formation, AGN activity or inflows, may prevent the rapid buildup of star formation in galaxies. Central to our understanding of how gas is converted into stars is the process by which gas can dissipate its mechanical energy through turbulence and shocks in order to cool. H$_2$ lines provide direct quantitative measurements of kinetic energy dissipation in molecular gas in galaxies throughout the Universe. Based on the detection of very powerful H$_2$ lines from z = 2 galaxies and proto-clusters at the detection limits of {\it Spitzer}, we are confident that future far-IR and UV H$_2$ observations will provide a wealth of new information and insight into galaxy evolution to high-z. Finally, at the very earliest epoch of star and galaxy formation, warm H$_2$ may also provide a unique glimpse of molecular gas collapse at 7 $<$ z $<$ 12 in massive dark matter (DM) halos on their way to forming the very first galaxies. Such measurements are beyond the reach of existing and planned observatories.Comment: Submitted as a science White Paper to the Astronomy and Astrophysics Astro 2020 Decadal Survey call issued by the National Academies of Sciences, Engineering and Medicine (March 11 2019

The X-ray source content of the XMM-Newton Galactic plane survey

We report the results of an optical campaign carried out by the XMM-Newton Survey Science Centre with the specific goal of identifying the brightest X-ray sources in the XMM-Newton Galactic plane survey. In addition to photometric and spectroscopic observations obtained at the ESO-VLT and ESO-3.6 m, we used cross-correlations with the 2XMMi, USNO-B1.0, MASS, and GLIMPSE catalogues to advance the identification process. Active coronae account for 16 of the 30 positively or tentatively identified X-ray sources and exhibit the softest X-ray spectra. Many of the identified hard X-ray sources are associated with massive stars, possible members of binary systems and emitting at intermediate X-ray luminosities of 1032−34 erg s−1. Among these are (i) a very absorbed, likely hyper-luminous star with X-ray/optical spectra and luminosities comparable to those of η Carina; (ii) a new X-rayselected WN8 Wolf-Rayet star in which most of the X-ray emission probably arises from wind collision in a binary; (iii) a new Be/X-ray star belonging to the growing class of γ-Cas analogues; and (iv) a possible supergiant X-ray binary of the kind discovered recently by INTEGRAL. One of the sources, XGPS-25, has a counterpart of moderate optical luminosity that exhibits HeII λ4686 and Bowen CIII-NIII emission lines, suggesting that this may be a quiescent or X-ray shielded low mass X-ray binary, although its X-ray properties might also be consistent with a rare kind of cataclysmic variable (CV). We also report the discovery of three new CVs, one of which is a likely magnetic system displaying strong X-ray variability. The soft (0.4–2.0 keV) band log N(>S )−log S curve is completely dominated by active stars in the flux range of 1 × 10−13 to 1 × 10−14 erg cm−2 s−1. Several active coronae are also detected above 2 keV suggesting that the population of RS CVn binaries contributes significantly to the hard X-ray source population. In total, we are able to identify a large fraction of the hard (2–10 keV) X-ray sources in the flux range of 1 × 10−12 to 1 × 10−13 erg cm−2 s−1 with Galactic objects at a rate consistent with what is expected for the Galactic contribution alone.We thank an anonymous referee for useful comments which helped to improve the quality of this paper. We are grateful to O. Herent for carrying out some of the observations presented in this work. This work has been supported in part by the DLR (Deutsches Zentrum für Luftund Raumfahrt) under grants 50 OX 0201 and 50 OX 0801. I.N. is supported by the Spanish Ministerio de Ciencia e Innovación under grants AYA2008-06166-C03-03 and CSD2006-70. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. The DENIS project has been partly funded by the SCIENCE and the HCM plans of the European Commission under grants CT920791 and CT940627. It is supported by INSU, MEN and CNRS in France, by the State of Baden-Württemberg in Germany, by DGICYT in Spain, by CNR in Italy, by FFwFBWF in Austria, by FAPESP in Brazil, by OTKA grants F-4239 and F-013990 in Hungary, and by the ESO C&EE grant A-04-046. Jean Claude Renault from IAP was the Project manager. Observations were carried out thanks to the contribution of numerous students and young scientists from all involved institutes, under the supervision of P. Fouqué, survey astronomer resident in Chile. The WHT is operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias. The observation presented here was taken as part of the ING service programme (proposal SW2005A06). This research has made use of Aladin, of the VizieR catalogue access tool and of Simbad at CDS, Strasbourg, France

IRIM at TRECVID 2011: Semantic Indexing and Instance Search

12 pages - TRECVID workshop notebook papers/slides available at http://www-nlpir.nist.gov/projects/tvpubs/tv.pubs.org.htmlInternational audienceThe IRIM group is a consortium of French teams work- ing on Multimedia Indexing and Retrieval. This paper describes its participation to the TRECVID 2011 se- mantic indexing and instance search tasks. For the semantic indexing task, our approach uses a six-stages processing pipelines for computing scores for the likeli- hood of a video shot to contain a target concept. These scores are then used for producing a ranked list of im- ages or shots that are the most likely to contain the tar- get concept. The pipeline is composed of the following steps: descriptor extraction, descriptor optimization, classification, fusion of descriptor variants, higher-level fusion, and re-ranking. We evaluated a number of dif- ferent descriptors and tried different fusion strategies. The best IRIM run has a Mean Inferred Average Pre- cision of 0.1387, which ranked us 5th out of 19 partic- ipants. For the instance search task, we we used both object based query and frame based query. We formu- lated the query in standard way as comparison of visual signatures either of object with parts of DB frames or as a comparison of visual signatures of query and DB frames. To produce visual signatures we also used two apporaches: the first one is the baseline Bag-Of-Visual- Words (BOVW) model based on SURF interest point descriptor; the second approach is a Bag-Of-Regions (BOR) model that extends the traditional notion of BOVW vocabulary not only to keypoint-based descrip- tors but to region based descriptors

IRIM at TRECVID 2013: Semantic Indexing and Instance Search

International audienceThe IRIM group is a consortium of French teams working on Multimedia Indexing and Retrieval. This paper describes its participation to the TRECVID 2013 semantic indexing and instance search tasks. For the semantic indexing task, our approach uses a six-stages processing pipelines for computing scores for the likelihood of a video shot to contain a target concept. These scores are then used for producing a ranked list of images or shots that are the most likely to contain the target concept. The pipeline is composed of the following steps: descriptor extraction, descriptor optimization, classiffication, fusion of descriptor variants, higher-level fusion, and re-ranking. We evaluated a number of different descriptors and tried different fusion strategies. The best IRIM run has a Mean Inferred Average Precision of 0.2796, which ranked us 4th out of 26 participants