Reaching the boundary between stellar kinematic groups and very wide binaries. III. Sixteen new stars and eight new wide systems in the beta Pictoris moving group

Aims. We look for common proper motion companions to stars of the nearby young beta Pictoris moving group. Methods. First, we compiled a list of 185 beta Pictoris members and candidate members from 35 representative works. Next, we used the Aladin and STILTS virtual observatory tools, and the PPMXL proper motion and Washington Double Star catalogues to look for companion candidates. The resulting potential companions were subjects of a dedicated astro-photometric follow-up using public data from all-sky surveys. After discarding 67 sources by proper motion and 31 by colour-magnitude diagrams, we obtained a final list of 36 common proper motion systems. The binding energy of two of them is perhaps too small to be considered physically bound. Results. Of the 36 pairs and multiple systems, eight are new, 16 have only one stellar component previously classified as a beta Pictoris member, and three have secondaries at or below the hydrogen-burning limit. Sixteen stars are reported here for the first time as moving group members. The unexpected large number of high-order multiple systems, 12 triples and two quadruples among 36 systems, may suggest a biased list of members towards close binaries or an increment of the high-order-multiple fraction for very wide systems.Comment: A&A in pres

Some properties of local weighted second-order statistics for spatio-temporal point processes

Diagnostics of goodness-of-fit in the theory of point processes are often considered through the transformation of data into residuals as a result of a thinning or a rescaling procedure. We alternatively consider here second-order statistics coming from weighted measures. Motivated by Adelfio and Schoenberg (2009) for the temporal and spatial cases, we consider an extension to the spatio-temporal context in addition to focussing on local characteristics. In particular, our proposed method assesses goodness-of-fit of spatio-temporal models by using local weighted secondorder statistics, computed after weighting the contribution of each observed point by the inverse of the conditional intensity function that identifies the process. Weighted second-order statistics directly apply to data without assuming homogeneity nor transforming the data into residuals, eliminating thus the sampling variability due to the use of a transforming procedure. We provide some characterisations and show a number of simulation studies