The Chinese-French SVOM mission for Gamma-Ray Burst studies

We present the Space-based multi-band astronomical Variable Objects Monitor mission (SVOM) decided by the Chinese National Space Agency (CNSA) and the French Space Agency (CNES). The mission which is designed to detect about 80 Gamma-Ray Bursts (GRBs) of all known types per year, will carry a very innovative scientific payload combining a gamma-ray coded mask imagers sensitive in the range 4 keV to 250 keV, a soft X-ray telescope operating between 0.5 to 2 keV, a gamma-ray spectro-photometer sensitive in the range 50 keV to 5 MeV, and an optical telescope able to measure the GRB afterglow emission down to a magnitude limit M$_R=23$ with a 300 s exposure. A particular attention will be also paid to the follow-up in making easy the observation of the SVOM detected GRB by the largest ground based telescopes. Scheduled for a launch in 2013, it will provide fast and reliable GRB positions, will measure the broadband spectral energy distribution and temporal properties of the prompt emission, and will quickly identify the optical afterglows of detected GRBs, including those at very high redshift.Comment: Proceedings of the SF2A conference, Paris, 200

Phase Lag and Coherence Function of X-ray emission from Black Hole Candidate XTE J1550-564

We report the results from measuring the phase lag and coherence function of X-ray emission from black hole candidate (BHC) XTE J1550-564. These X-ray temporal properties have been recognized to be increasingly important in providing important diagnostics of the dynamics of accretion flows around black holes. For XTE J1550-564, we found significant hard lag --- the X-ray variability in high energy bands {\em lags} behind that in low energy bands --- associated both with broad-band variability and quasi-periodic oscillation (QPO). However, the situation is more complicated for the QPO: while hard lag was measured for the first harmonic of the signal, the fundamental component showed significant {\em soft} lag. Such behavior is remarkably similar to what was observed of microquasar GRS 1915+105. The phase lag evolved during the initial rising phase of the 1998 outburst. The magnitude of both the soft and hard lags of the QPO increases with X-ray flux, while the Fourier spectrum of the broad-band lag varies significantly in shape. The coherence function is relatively high and roughly constant at low frequencies, and begins to drop almost right after the first harmonic of the QPO. It is near unity at the beginning and decreases rapidly during the rising phase. Also observed is that the more widely separated the two energy bands are the less the coherence function between the two. It is interesting that the coherence function increases significantly at the frequencies of the QPO and its harmonics. We discuss the implications of the results on the models proposed for BHCs.Comment: To appear in ApJ Letter

Entity Synonym Discovery via Multipiece Bilateral Context Matching

Being able to automatically discover synonymous entities in an open-world setting benefits various tasks such as entity disambiguation or knowledge graph canonicalization. Existing works either only utilize entity features, or rely on structured annotations from a single piece of context where the entity is mentioned. To leverage diverse contexts where entities are mentioned, in this paper, we generalize the distributional hypothesis to a multi-context setting and propose a synonym discovery framework that detects entity synonyms from free-text corpora with considerations on effectiveness and robustness. As one of the key components in synonym discovery, we introduce a neural network model SYNONYMNET to determine whether or not two given entities are synonym with each other. Instead of using entities features, SYNONYMNET makes use of multiple pieces of contexts in which the entity is mentioned, and compares the context-level similarity via a bilateral matching schema. Experimental results demonstrate that the proposed model is able to detect synonym sets that are not observed during training on both generic and domain-specific datasets: Wiki+Freebase, PubMed+UMLS, and MedBook+MKG, with up to 4.16% improvement in terms of Area Under the Curve and 3.19% in terms of Mean Average Precision compared to the best baseline method.Comment: In IJCAI 2020 as a long paper. Code and data are available at https://github.com/czhang99/SynonymNe