ﻻ يوجد ملخص باللغة العربية
Timing of high-count rate sources with the NuSTAR Small Explorer Mission requires specialized analysis techniques. NuSTAR was primarily designed for spectroscopic observations of sources with relatively low count-rates rather than for timing analysis of bright objects. The instrumental dead time per event is relatively long (~2.5 msec), and varies by a few percent event-to-event. The most obvious effect is a distortion of the white noise level in the power density spectrum (PDS) that cannot be modeled easily with the standard techniques due to the variable nature of the dead time. In this paper, we show that it is possible to exploit the presence of two completely independent focal planes and use the cross power density spectrum to obtain a good proxy of the white noise-subtracted PDS. Thereafter, one can use a Monte Carlo approach to estimate the remaining effects of dead time, namely a frequency-dependent modulation of the variance and a frequency-independent drop of the sensitivity to variability. In this way, most of the standard timing analysis can be performed, albeit with a sacrifice in signal to noise relative to what would be achieved using more standard techniques. We apply this technique to NuSTAR observations of the black hole binaries GX 339-4, Cyg X-1 and GRS 1915+105.
We present a Bayesian parameter-estimation pipeline to measure the properties of inspiralling stellar-mass black hole binaries with LISA. Our strategy (i) is based on the coherent analysis of the three noise-orthogonal LISA data streams, (ii) employs
The spectra of black hole binaries in the low/hard state are complex, with evidence for multiple different Comptonisation regions contributing to the hard X-rays in addition to a cool disc component. We show this explicitly for some of the best RXTE
Pulsar Timing Arrays are a prime tool to study unexplored astrophysical regimes with gravitational waves. Here we show that the detection of gravitational radiation from individually resolvable super-massive black hole binary systems can yield direct
We introduce a technique for gravitational-wave analysis, where Gaussian process regression is used to emulate the strain spectrum of a stochastic background using population-synthesis simulations. This leads to direct Bayesian inference on astrophys
We present the results obtained from detailed spectral and timing studies of extra-galactic black hole X-ray binaries LMC~X--1 and LMC~X--3, using simultaneous observations with {it Nuclear Spectroscopic Telescope Array (NuSTAR)} and {it Neil Gehrels