X-ray outbursts of low-mass X-ray binary transients observed in the RXTE era

We have performed a statistical study of the properties of 110 bright X-ray outbursts in 36 low-mass X-ray binary transients (LMXBTs) seen with the All-Sky Monitor (2--12 keV) on board the {\it Rossi X-ray Timing Explorer} ({\it RXTE}) in 1996--2011. We have measured a number of outburst properties, including peak X-ray luminosity, rate of change of luminosity on a daily timescale, $e$-folding rise and decay timescales, outburst duration, and total radiated energy. We found that the average properties such as peak X-ray luminosity, rise and decay timescales, outburst duration, and total radiated energy of black hole LMXBTs, are at least two times larger than those of neutron star LMXBTs, implying that the measurements of these properties may provide preliminary clues as to the nature of the compact object of a newly discovered LMXBT. We also found that the outburst peak X-ray luminosity is correlated with the rate of change of X-ray luminosity in both the rise and the decay phases, which is consistent with our previous studies. Positive correlations between total radiated energy and peak X-ray luminosity, and between total radiated energy and the $e$-folding rise or decay timescale, are also found in the outbursts. These correlations suggest that the mass stored in the disk before an outburst is the primary initial condition that sets up the outburst properties seen later. We also found that the outbursts of two transient stellar-mass ULXs in M31 also roughly follow the correlations, which indicate that the same outburst mechanism works for the brighter outbursts of these two sources in M31 that reached the Eddington luminosity.Comment: Accepted to Ap

Searching For a Lost Plane

Malaysia plane MH370 disappeared en route from Kuala Lumpur to Beijing on 8, March 2014. Besides considering the factors such as air piracy, weather, electromagnetic wave, and kinds of bugs of the airplane, in order to find the wreckage efficiently the growing concern is to confirm a limited area where the airplane probably fell, and then to find an optimum way to find the plane. It’s essential to build such a model involving both of the two layers mentioned above that can cover all the searching area by using the most efficient way. The first layer is to confirm the limited area. We use the Poisson Probability Distribution, the Drag equation, and the Proper Orthogonal Decomposition Theorem to assume the direction of the airplane and the sea area where it probably fell. All assumptions are based on the actual situation. The second model will basically rely on the Bayesian principles. In this case, the model would be advantageous as it will rely on contingency as an important role in the search for lost objects in the sea or on land. As matter of fact, any information that is provided to the search team would be put into good use as it will be used in developing the probabilities. It is also good in that it\u27s flexible and would be good enough to sustain the ongoing search even with new information or facts obtained regarding the flight of the plane and/or the initial findings of the debris. This helps in rounding down to a lesser geographical search region and, by extension, increases the probability of getting the plane