Supersoft sources in M 31: Comparing the XMM-Newton Deep Survey, ROSAT and Chandra catalogues

To investigate the transient nature of supersoft sources (SSSs) in M 31, we compared SSS candidates of the XMM-Newton Deep Survey, ROSAT PSPC surveys and the Chandra catalogues in the same field. We found 40 SSSs in the XMM-Newton observations. While 12 of the XMM-Newton sources were brighter than the limiting flux of the ROSAT PSPC survey, only two were detected with ROSAT ~10 yr earlier. Five correlate with recent optical novae which explains why they were not detected by ROSAT. The remaining 28 XMM-Newton SSSs have fluxes below the ROSAT detection threshold. Nevertheless we found one correlation with a ROSAT source, which had significantly larger fluxes than during the XMM-Newton observations. Ten of the XMM-Newton SSSs were detected by Chandra with <1-~6 yr between the observations. Five were also classified as SSSs by Chandra. Of the 30 ROSAT SSSs three were confirmed with XMM-Newton, while for 11 sources other classifications are suggested. Of the remaining 16 sources one correlates with an optical nova. Of the 42 Chandra very-soft sources five are classified as XMM-Newton SSSs, while for 22 we suggest other classifications. Of the remaining 15 sources, nine are classified as transient by Chandra, one of them correlates with an optical nova. These findings underlined the high variability of the sources of this class and the connection between SSSs and optical novae. Only three sources, were detected by all three missions as SSSs. Thus they are visible for more than a decade, despite their variability.Comment: 6 pages, 1 figure, Proc. of workshop "SuperSoft X-ray Sources - New Developments", ESTEC/Villafranca, May 2009, accepted for publication in Aston.Nach

Urban Living – Smart & Sustainable!? – Tool für den Wohnungsvergleich

Das auf der Plattform www.wohnungsvergleich.at verfügbare interaktive online-Wohnungsvergleich-Tool bietet Wohnungssuchenden im urbanen Raum eine konkrete Entscheidungshilfe bei der Wohnungswahl und informiert umfassend über Qualitätsmerkmale, die hinter Zielkriterien aus gängigen Nachhaltigkeitsbewertungssystemen von Gebäuden und Siedlungen - wie etwa dem klima:aktiv Gebäudestandard oder TQB – Total Quality Building - stehen. Indem die technische Dimension, in der diese Kriterien formuliert sind, auf eine für UserInnen verständliche Ebene übersetzt wird, werden persönliche Vorteile im Kontext des smarten, nachhaltigen Wohnens in Städten deutlich. Das in einem partizipativen Prozess entwickelte Tool bietet damit eine wertvolle Hilfe bei der Strukturierung von Entscheidungsprozessen und erhöht die „Treffsicherheit“ von Wohnentscheidungen und in weiterer Folge die Wohnzufriedenheit wesentlich. Gleichzeitig kann der Zugewinn an Wissen und Bewusstsein zu Nachhaltigkeits- und Smart-City-relevanten Qualitätsmerkmalen auf Seiten der EndkundInnen auch stimulierend auf die Anbieterseite wirken und die Entwicklung der Immobilienwirtschaft in Richtung Nachhaltigkeit unterstützen. Kern des Wohnungsvergleich-Tools sind 33 individuell, je nach persönlicher Präferenz auswählbare Wohnwunsch-Kriterien in acht Themenbereichen. Im Rahmen des Wohnungsvergleichs beurteilen die UserInnen, wie sehr die in Frage kommenden Wohnungen diese Kriterien erfüllen. Um diese Beurteilung zu erleichtern, werden in den Kriterien-Kurzbeschreibungen in der Rubrik „Worauf soll ich achten?“ Aspekte und Fragen angeführt, auf die, etwa im Rahmen von Wohnungsbesichtigungen, geachtet werden sollte. Zusätzlich zum Wohnungsvergleich über das online-Tool stehen die Wohnwunsch-Kriterien in Form von ausdruckbaren PDF-Checklisten zur Verfügung, die direkt vor Ort bei Wohnungsbesichtigungen verwendet werden können. In den Wohnungsvergleich-Ergebnisdarstellungen sehen die UserInnen als zentrale Aussage den Grad der Wohnwunsch-Erfüllung der verglichenen Wohnungen. In den Detailauswertungen werden spezielle Effekte, wie der Smart-City-Effekt und der klima:aktiv-Effekt, angezeigt, die im Vorfeld allen Wohnwunsch-Kriterien auf Basis von ExpertInnen-Einschätzungen zugewiesen wurden und einen Indikator für die Smartness bzw. Klimafreundlichkeit der verglichenen Wohnungen sowie des persönlichen Wohnwunsches darstellen. Zudem ist der Backend-Auswertebereich des Tools eine für Immobilienanbieter und –makler, aber auch Förderstellen interessante Datenquelle, aus der Hinweise zu den am Markt nachgefragten und auf Basis von EndkundInnen-Beurteilungen vorhandenen Qualitätsmerkmalen von Wohnungen abgeleitet werden können. Das Wohnungsvergleich-Tool wurde von der ÖGUT in Kooperation mit dem auf multimediale Web-Applikationen spezialisierten Unternehmen akaryon in einem einjährigen, von der ZIT – Die Technologieagentur der Stadt Wien geförderten Kommunikationsprojekt entwickelt; einige weitere Aktivitäten auf Basis des Projekts wurden zudem seitens des Lebensministeriums über das Programm klima:atkiv Bauen und Sanieren sowie das BMVIT unterstützt

Liquidity commonality and risk management

We propose to model the joint distribution of bid-ask spreads and log returns of a stock portfolio by using Autoregressive Conditional Double Poisson and GARCH processes for the marginals and vine copulas for the dependence structure. By estimating the joint multivariate distribution of both returns and bid-ask spreads from intraday data, we incorporate the measurement of commonalities in liquidity and comovements of stocks and bid-ask spreads into the forecasting of three types of liquidity-adjusted Value-at-Risk (L-IVaR). In a preliminary analysis, we document strong extreme comovements in liquidity and strong tail dependence between bid-ask spreads and log returns across the firms in our sample thus motivating our use of a vine copula model. Furthermore, the backtesting results for the L-IVaR of a portfolio consisting of five stocks listed on the NASDAQ show that the proposed models perform well in forecasting liquidity-adjusted intraday portfolio profits and losses

On the Integrated Spectrum of the X-ray Binaries and the Origin of Soft X-ray Emission from the Bulge of M31

Using ROSAT PSPC data, we have performed several tests aimed at understanding the origin of the soft X-ray spectral component detected from the bulge of M31. We find that a significant soft component in the spectrum of the bulge is spatially correlated with the unresolved X-ray emission near the core of M31, which is probably a hot interstellar medium or perhaps a population of multiple faint sources. For the first time, we extracted the spectrum of this unresolved emission, by removing point sources dominating the integral spectrum of the bulge, and found it to be responsible for the most of soft excess. A soft spectral component is not at all needed to fit the point source spectrum that remains after subtracting the unresolved emission. The integral spectra of bright point sources, both inside and outside of the M31 bulge, can be fitted with a single power-law in the ROSAT band. Our analysis rules out the previous suggestion that all bulge emission in M31 may be generated by low mass X-ray binaries (Irwin & Bregman, 1999).Comment: 11 pages incl. 2 figures, 2 tables, accepted to ApJ

Is tail risk priced in credit default swap premia?

We show that the propensity of a bank to experience extreme comovements in its credit default swap premia together with the market is priced in the bank’s default swap spread during the financial crisis. We measure a bank’s CDS tail beta by estimating the upper tail dependence between its default swap spreads and a credit default swap market index. Our study shows that protection sellers receive a premium for bearing the risk of extreme upward comovements in default risk. The economic significance of this effect is large yet limited to the recent financial crisis. Banks in the upper quintile of CDS tail beta have spreads that are on average 140 basis points higher than those of banks in the lower CDS tail beta quintile

Populations of X-ray binaries and the dynamical history of their host galaxies

The observed luminosity distributions of X-ray sources indicate the presence of several populations of X-ray binaries in the nearby galaxies. Each population has its formation and evolutionary history, depending on the host environment. The features seen in the log N($>$S) -- log S curves for different types of galaxies and for different galactic components can be reproduced by a birth-death model, in which the lifespans of the binaries are inversely proportional to their X-ray brightness. Conversely, the dynamical history of a galaxy can be inferred from the luminosity distributions of its X-ray binary populations.Comment: accepted for publication in Publ. Astron Soc. Australia, text is revise

X-ray emission from optical novae in M 31

The first supersoft source (SSS) identification with an optical nova in M 31 was based on ROSAT observations. Twenty additional X-ray counterparts (mostly identified as SSS by their hardness ratios) were detected using archival ROSAT, XMM-Newton and Chandra observations obtained before July 2002. Based on these results optical novae seem to constitute the major class of SSS in M 31. An analysis of archival Chandra HRC-I and ACIS-I observations obtained from July 2004 to February 2005 demonstrated that M 31 nova SSS states lasted from months to about 10 years. Several novae showed short X-ray outbursts starting within 50 d after the optical outburst and lasting only two to three months. The fraction of novae detected in soft X-rays within a year after the optical outburst was more than 30%. Ongoing optical nova monitoring programs, optical spectral follow-up and an up-to-date nova catalogue are essential for the X-ray work. Re-analysis of archival nova data to improve positions and find additional nova candidates are urgently needed for secure recurrent nova identifications. Dedicated XMM-Newton/Chandra monitoring programs for X-ray emission from optical novae covering the center area of M 31 continue to provide interesting new results (e.g. coherent 1105s pulsations in the SSS counterpart of nova M31N 2007-12b). The SSS light curves of novae allow us - together with optical information - to estimate the mass of the white dwarf, of the ejecta and the burned mass in the outburst. Observations of the central area of M 31 allow us - in contrast to observations in the Galaxy - to monitor many novae simultaneously and proved to be prone to find many interesting SSS and nova types.Comment: 6 pages, 4 figures, accepted for publication in Aston.Nach

The X-ray Globular Cluster Population in NGC 1399

We report on the {\it Chandra} observations of the elliptical galaxy NGC 1399, concentrating on the X-ray sources identified with globular clusters (GCs). A large fraction of the 2-10 keV X-ray emission in the $8' \times 8'$ {\it Chandra} image is resolved into point sources with luminosities $\ge 5 \times 10^{37}$ \ergsec. These sources are most likely Low Mass X-ray Binaries (LMXBs). In a region imaged by {\it HST} about 70% of the X-ray sources are located within GCs. This association suggests that in giant elliptical galaxies luminous X-ray binaries preferentially form in GCs. Many of the GC sources have super-Eddington luminosities (for an accreting neutron star) and their average luminosity is higher than the non-GC sources. The X-ray spectral properties of both GC and non-GC sources are similar to those of LMXBs in our Galaxy. Two of the brightest sources, one of which is in a GC, have an ultra-soft spectrum, similar to that seen in the high state of black hole candidates. The ``apparent'' super-Eddington luminosity in many cases may be due to multiple LMXB systems within individual GCs, but with some of the most extremely luminous systems containing massive black holes.Comment: accepted in ApJ letter. 10 pages 5 figure

A complex geo-scientific strategy for landslide hazard mitigation ? from airborne mapping to ground monitoring

International audienceAfter a large landslide event in Sibratsgfäll/Austria several exploration methods were evaluated on their applicability to investigate and monitor landslide areas. The resulting optimised strategy consists of the combined application of airborne electromagnetics, ground geoelectrical measurements and geoelectrical monitoring combined with hydrological and geological mapping and geotechnical modelling. Interdisciplinary communication and discussion was the primary key to assess this complicated hazard situation