On the Statistical Properties of Cospectra

In recent years, the cross-spectrum has received considerable attention as a means of characterizing the variability of astronomical sources as a function of wavelength. The cospectrum has only recently been understood as a means of mitigating instrumental effects dependent on temporal frequency in astronomical detectors, as well as a method of characterizing the coherent variability in two wavelength ranges on different timescales. In this paper, we lay out the statistical foundations of the cospectrum, starting with the simplest case of detecting a periodic signal in the presence of white noise, under the assumption that the same source is observed simultaneously in independent detectors in the same energy range. This case is especially relevant for detecting faint X-ray pulsars in detectors heavily affected by instrumental effects, including NuSTAR, Astrosat, and IXPE, which allow for even sampling and where the cospectrum can act as an effective way to mitigate dead time. We show that the statistical distributions of both single and averaged cospectra differ considerably from those for standard periodograms. While a single cospectrum follows a Laplace distribution exactly, averaged cospectra are approximated by a Gaussian distribution only for more than ~30 averaged segments, dependent on the number of trials. We provide an instructive example of a quasi-periodic oscillation in NuSTAR and show that applying standard periodogram statistics leads to underestimated tail probabilities for period detection. We also demonstrate the application of these distributions to a NuSTAR observation of the X-ray pulsar Hercules X-1

Quasi-Periodic Oscillations in Short Recurring Bursts of the magnetars SGR 1806-20 and SGR 1900+14 Observed With RXTE

Quasi-periodic oscillations (QPOs) observed in the giant flares of magnetars are of particular interest due to their potential to open up a window into the neutron star interior via neutron star asteroseismology. However, only three giant flares have been observed. We therefore make use of the much larger data set of shorter, less energetic recurrent bursts. Here, we report on a search for QPOs in a large data set of bursts from the two most burst-active magnetars, SGR 1806-20 and SGR 1900+14, observed with the Rossi X-ray Timing Explorer (RXTE). We find a single detection in an averaged periodogram comprising 30 bursts from SGR 1806-20, with a frequency of 57 Hz and a width of 5 Hz, remarkably similar to a giant flare QPO observed from SGR 1900+14. This QPO fits naturally within the framework of global magneto-elastic torsional oscillations employed to explain the giant flare QPOs. Additionally, we uncover a limit on the applicability of Fourier analysis for light curves with low background count rates and strong variability on short timescales. In this regime, standard Fourier methodology and more sophisticated Fourier analyses fail in equal parts by yielding an unacceptably large number of false positive detections. This problem is not straightforward to solve in the Fourier domain. Instead, we show how simulations of light curves can offer a viable solution for QPO searches in these light curves.Comment: accepted for publication in ApJ; 12 pages, 7 figures; code + instructions at https://github.com/dhuppenkothen/MagnetarQPOSearchPaper ; associated data products at http://figshare.com/articles/SGR_1900_14_RXTE_Data/1184101 (SGR 1900+14) and http://figshare.com/articles/SGR_1806_20_Bursts_RXTE_data_set/1184427 (SGR 1806-20

Magnetar giant flare high-energy emission

High energy ($> 250$ keV) emission has been detected persisting for several tens of seconds after the initial spike of magnetar giant flares. It has been conjectured that this emission might arise via inverse Compton scattering in a highly extended corona generated by super-Eddington outflows high up in the magnetosphere. In this paper we undertake a detailed examination of this model. We investigate the properties of the required scatterers, and whether the mechanism is consistent with the degree of pulsed emission observed in the tail of the giant flare. We conclude that the mechanism is consistent with current data, although the origin of the scattering population remains an open question. We propose an alternative picture in which the emission is closer to that star and is dominated by synchrotron radiation. The $RHESSI$ observations of the December 2004 flare modestly favor this latter picture. We assess the prospects for the Fermi Gamma-Ray Space Telescope to detect and characterize a similar high energy component in a future giant flare. Such a detection should help to resolve some of the outstanding issues.Comment: 20 pages, 14 figure

Rotational phase dependence of magnetar bursts

The trigger for the short bursts observed in $\gamma$-rays from many magnetar sources remains unknown. One particular open question in this context is the localization of burst emission to a singular active region or a larger area across the neutron star. While several observational studies have attempted to investigate this question by looking at the phase dependence of burst properties, results have been mixed. At the same time, it is not obvious a priori that bursts from a localized active region would actually give rise to a detectable phase-dependence, taking into account issues such as geometry, relativistic effects, and intrinsic burst properties such brightness and duration. In this paper, we build a simple theoretical model to investigate the circumstances under which the latter effects could affect detectability of a dependence of burst emission on rotational phase. We find that even for strongly phase-dependent emission, inferred burst properties may not show a rotational phase dependence depending on the geometry of the system and the observer. Furthermore, the observed properties of bursts with durations short as 10-20% of the spin period can vary strongly depending on the rotational phase at which the burst was emitted. We also show that detectability of a rotational phase dependence depends strongly on the minimum number of bursts observed, and find that existing burst samples may simply be too small to rule out a phase dependence.Comment: 15 pages, 17 figure

Constraining the limiting brightness temperature and Doppler factors for the largest sample of radio bright blazars

Relativistic effects dominate the emission of blazar jets complicating our understanding of their intrinsic properties. Although many methods have been proposed to account for them, the variability Doppler factor method has been shown to describe the blazar populations best. We use a Bayesian hierarchical code called {\it Magnetron} to model the light curves of 1029 sources observed by the Owens Valley Radio Observatory's 40-m telescope as a series of flares with an exponential rise and decay, and estimate their variability brightness temperature. Our analysis allows us to place the most stringent constraints on the equipartition brightness temperature i.e., the maximum achieved intrinsic brightness temperature in beamed sources which we found to be $\rm \langle T_{eq}\rangle=2.78\times10^{11}K\pm26\%$. Using our findings we estimated the variability Doppler factor for the largest sample of blazars increasing the number of available estimates in the literature by almost an order of magnitude. Our results clearly show that $\gamma$-ray loud sources have faster and higher amplitude flares than $\gamma$-ray quiet sources. As a consequence they show higher variability brightness temperatures and thus are more relativistically beamed, with all of the above suggesting a strong connection between the radio flaring properties of the jet and $\gamma$-ray emission.Comment: 14 pages, 8 figures, accepted for publication in AP

Accurate X-ray Timing in the Presence of Systematic Biases With Simulation-Based Inference

Because many of our X-ray telescopes are optimized towards observing faint sources, observations of bright sources like X-ray binaries in outburst are often affected by instrumental biases. These effects include dead time and photon pile-up, which can dramatically change the statistical inference of physical parameters from these observations. While dead time is difficult to take into account in a statistically consistent manner, simulating dead time-affected data is often straightforward. This structure makes the issue of inferring physical properties from dead time-affected observations fall into a class of problems common across many scientific disciplines. There is a growing number of methods to address them under the name of Simulation-Based Inference (SBI), aided by new developments in density estimation and statistical machine learning. In this paper, we introduce SBI as a principled way to infer variability properties from dead time-affected light curves. We use Sequential Neural Posterior Estimation to estimate the posterior probability for variability properties. We show that this method can recover variability parameters on simulated data even when dead time is variable, and present results of an application of this approach to NuSTAR observations of the galactic black hole X-ray binary GRS 1915+105