The origin of RXJ1856.5-3754 and RXJ0720.4-3125 -- updated using new parallax measurements

RXJ1856 and RXJ0720 are the only young isolated radio-quiet neutron stars (NSs) for which trigonometric parallaxes were measured. Due to detection of their thermal emission in X-rays they are important to study NS cooling and to probe theoretical cooling models. Hence, a precise determination of their age is essential. Recently, new parallax measurements of RXJ1856 and RXJ0720 were obtained. Considering that NSs may originate from binary systems that got disrupted due to an asymmetric supernova, we attempt to identify runaway stars which may have been former companions to the NS progenitors. Such an identification would strongly support a particular birth scenario with time and place. We trace back each NS, runaway star and the centres of possible birth associations to find close encounters. The kinematic age is then given by the time since the encounter. We use Monte Carlo simulations to account for observational uncertainties. Using the most recent parallax measurement of 8.16+/-0.80 mas for RXJ1856, we find that it originated in the U Sco association 0.46+/-0.05 Myr ago. This is slightly larger than the value we reported earlier (0.3 Myr). Our result is strongly supported by its current radial velocity that we predict to be 6+19-20 km/s. This implies an inclination angle of 88+/-6 deg consistent with the bow shock. No suitable runaway star was found to be a potential former companion of RXJ1856. Making use of a recent parallax measurement for RXJ0720 of 3.6+/-1.6 mas, we find that this NS was possibly born in Tr 10 0.85+/-0.15 Myr ago. This is somewhat larger than the one obtained using the old parallax value (0.5 Myr). We suggest the B0 runaway supergiant HIP 43158 as a candidate for a former companion. Then, the current distance of RXJ0720 to the Sun should be 286+27-23 pc, in agreement with recent measurements. We then expect the radial velocity of RXJ0720 to be -76+34-17 km/s.Comment: accepted for publication in MNRAS additional supporting material can be found at http://www.astro.uni-jena.de/~nina/supporting_info.pdf the abstract has been adjusted to fit the length requirement (RXJ1856 = RXJ1856.5-3754, RXJ0720 = RXJ0720.4-3125, U Sco = Upper Scorpius, Tr 10 = Trumpler 10

A Search for wide visual companions of exoplanet host stars - The Calar Alto Survey

We have carried out a search for co-moving stellar and substellar companions around 18 exoplanet host stars with the infrared camera MAGIC at the 2.2m Calar Alto telescope, by comparing our images with images from the all sky surveys 2MASS, POSS I and II. Four stars of the sample namely HD80606, 55Cnc, HD46375 and BD-103166, are listed as binaries in the Washington Visual Double Star Catalogue (WDS). The binary nature of HD80606, 55Cnc, and HD46375 is confirmed with both astrometry as well as photometry, thereby the proper motion of the companion of HD46375 was determined here for the first time. We derived the companion masses as well as the longterm stability regions for additional companions in these three binary systems. We can rule out further stellar companions around all stars in the sample with projected separations between 270AU and 2500AU, being sensitive to substellar companions with masses down to \~60MJup (S/N=3). Furthermore we present evidence that the two components of the WDS binary BD-103166 are unrelated stars, i.e this system is a visual pair. The spectrophotometric distance of the primary (a K0 dwarf) is ~67pc, whereas the presumable secondary BD-103166B (a M4 to M5 dwarf) is located at a distance of 13pc in the foreground.Comment: accepted for publication in AN, 7 pages, 4 figure

New resampling method for evaluating stability of clusters

<p>Abstract</p> <p>Background</p> <p>Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in clustering procedures. Statistical methods are required to distinguish between real and random clusters. Several methods for assessing cluster stability have been published, including resampling methods such as the bootstrap.</p> <p>We propose a new resampling method based on continuous weights to assess the stability of clusters in hierarchical clustering. While in bootstrapping approximately one third of the original items is lost, continuous weights avoid zero elements and instead allow non integer diagonal elements, which leads to retention of the full dimensionality of space, i.e. each variable of the original data set is represented in the resampling sample.</p> <p>Results</p> <p>Comparison of continuous weights and bootstrapping using real datasets and simulation studies reveals the advantage of continuous weights especially when the dataset has only few observations, few differentially expressed genes and the fold change of differentially expressed genes is low.</p> <p>Conclusion</p> <p>We recommend the use of continuous weights in small as well as in large datasets, because according to our results they produce at least the same results as conventional bootstrapping and in some cases they surpass it.</p

Statistical tests for the comparison of two samples:the general alternative

It is common to test the null hypothesis that two samples were drawn from identical distributions; and the Smirnov (sometimes called Kolmogorov-Smirnov) test is conventionally applied. We present simulation results to compare the performance of this test with three recently introduced alternatives. We consider both continuous and discrete data. We show that the alternative methods preserve type I error at the nominal level as well as the Smirnov test but offer superior power. We argue for the routine replacement of the Smirnov test with the modified Baumgartner test according to Murakami (2006), or with the test proposed by Zhang (2006).</p

Statistical tests for the comparison of two samples:the general alternative

It is common to test the null hypothesis that two samples were drawn from identical distributions; and the Smirnov (sometimes called Kolmogorov-Smirnov) test is conventionally applied. We present simulation results to compare the performance of this test with three recently introduced alternatives. We consider both continuous and discrete data. We show that the alternative methods preserve type I error at the nominal level as well as the Smirnov test but offer superior power. We argue for the routine replacement of the Smirnov test with the modified Baumgartner test according to Murakami (2006), or with the test proposed by Zhang (2006).</p