In this paper we report on the fourth soft gamma-ray source catalog obtained with the IBIS gamma-ray imager on board the INTEGRAL satellite. The scientific dataset is based on more than 70Ms of high quality observations performed during the first fiv
e and a half years of Core Program and public observations. Compared to previous IBIS surveys, this catalog includes a substantially increased coverage of extragalactic fields, and comprises more than 700 high-energy sources detected in the energy range 17--100 keV, including both transients and faint persistent objects which can only be revealed with longer exposure times. A comparison is provided with the latest Swift/BAT survey results.
Hard X-ray surveys have proven remarkably efficient in detecting intermediate polars and asynchronous polars, two of the rarest type of cataclysmic variable (CV). Here we present a global study of hard X-ray selected intermediate polars and asynchron
ous polars, focusing particularly on the link between hard X-ray properties and spin/orbital periods. To this end, we first construct a new sample of these objects by cross-correlating candidate sources detected in INTEGRAL/IBIS observations against catalogues of known CVs. We find 23 cataclysmic variable matches, and also present an additional 9 (of which 3 are definite) likely magnetic cataclysmic variables (mCVs) identified by others through optical follow-ups of IBIS detections. We also include in our analysis hard X-ray observations from Swift/BAT and SUZAKU/HXD in order to make our study more complete. We find that most hard X-ray detected mCVs have P_{spin}/P_{orb}<0.1 above the period gap. In this respect we also point out the very low number of detected systems in any band between P_{spin}/P_{orb}=0.3 and P_{spin}/P_{orb}=1 and the apparent peak of the P_{spin}/P_{orb} distribution at about 0.1. The observational features of the P_{spin} - P_{orb} plane are discussed in the context of mCV evolution scenarios. We also present for the first time evidence for correlations between hard X-ray spectral hardness and P_{spin}, P_{orb} and P_{spin}/P_{orb}. An attempt to explain the observed correlations is made in the context of mCV evolution and accretion footprint geometries on the white dwarf surface.
We give an overview of ISINA: INTEGRAL Source Identification Network Algorithm. This machine learning algorithm, using Random Forests, is applied to the IBIS/ISGRI dataset in order to ease the production of unbiased future soft gamma-ray source catal
ogues. First we introduce the dataset and the problems encountered when dealing with images obtained using the coded mask technique. The initial step of source candidate searching is introduced and an initial candidate list is created. A description of the feature extraction on the initial candidate list is then performed together with feature merging for these candidates. Three training and testing sets are created in order to deal with the diverse timescales encountered when dealing with the gamma-ray sky. Three independent Random Forest are built: one dealing with faint persistent source recognition, one dealing with strong persistent sources and a final one dealing with transients. For the latter, a new transient detection technique is introduced and described: the Transient Matrix. Finally the performance of the network is assessed and discussed using the testing set and some illustrative source examples.
