60 research outputs found
No Time for Dead Time: Use the Fourier Amplitude Differences to Normalize Dead-time-affected Periodograms
Dead time affects many of the instruments used in X-ray astronomy, by
producing a strong distortion in power density spectra. This can make it
difficult to model the aperiodic variability of the source or look for
quasi-periodic oscillations. Whereas in some instruments a simple a priori
correction for dead-time-affected power spectra is possible, this is not the
case for others such as NuSTAR, where the dead time is non-constant and long
(~2.5 ms). Bachetti et al. 2015 suggested the cospectrum obtained from light
curves of independent detectors within the same instrument as a possible way
out, but this solution has always only been a partial one: the measured rms was
still affected by dead time, because the width of the power distribution of the
cospectrum was modulated by dead time in a frequency-dependent way.
In this Letter we suggest a new, powerful method to normalize cospectra and,
with some caveats, even power density spectra. Our approach uses the difference
of the Fourier amplitudes from two independent detectors to characterize and
filter out the effect of dead time. This method is crucially important for the
accurate modelling of periodograms derived from instruments affected by dead
time on board current missions like NuSTAR and ASTROSAT, but also future
missions such as IXPEComment: 8 pages, 5 figures, Published on ApJL on 2018 January 3
Intermittency and Lifetime of the 625 Hz QPO in the 2004 Hyperflare from the Magnetar SGR 1806-20 as evidence for magnetic coupling between the crust and the core
Quasi-periodic oscillations (QPOs) detected in the 2004 giant flare from SGR
1806-20 are often interpreted as global magneto-elastic oscillations of the
neutron star. There is, however, a large discrepancy between theoretical
models, which predict that the highest frequency oscillations should die out
rapidly, and the observations, which suggested that the highest-frequency
signals persisted for ~100s in X-ray data from two different spacecraft. This
discrepancy is particularly important for the high-frequency QPO at ~625 Hz.
However, previous analyses did not systematically test whether the signal could
also be there in much shorter data segments, more consistent with the
theoretical predictions. Here, we test for the presence of the high-frequency
QPO at 625 Hz in data from both the Rossi X-ray Timing Explorer (RXTE) and the
Ramaty High Energy Solar Spectroscopic Imager (RHESSI) systematically both in
individual rotational cycles of the neutron star, as well as averaged over
multiple successive rotational cycles at the same phase. We find that the QPO
in the RXTE data is consistent with being only present in a single cycle, for a
short duration of ~0.5s, whereas the RHESSI data are as consistent with a
short-lived signal that appears and disappears as with a long-lived QPO. Taken
together, this data provides evidence for strong magnetic interaction between
the crust and the core.Comment: Accepted for publication in ApJ. The data and simulations are
available at
http://figshare.com/articles/SGR_1806_20_Giant_Flare_Data_and_Simulations/1126082
, the code can be downloaded from
https://github.com/dhuppenkothen/giantflare-paper , some documentation is
under
http://nbviewer.ipython.org/github/dhuppenkothen/giantflare-paper/blob/master/documents/giantflare-analysis.ipyn
Fourier Domain
The changes in brightness of an astronomical source as a function of time are
key probes into that source's physics. Periodic and quasi-periodic signals are
indicators of fundamental time (and length) scales in the system, while
stochastic processes help uncover the nature of turbulent accretion processes.
A key method of studying time variability is through Fourier methods, the
decomposition of the signal into sine waves, which yields a representation of
the data in frequency space. With the extension into \textit{spectral timing}
the methods built on the Fourier transform can not only help us characterize
(quasi-)periodicities and stochastic processes, but also uncover the complex
relationships between time, photon energy and flux in order to help build
better models of accretion processes and other high-energy dynamical physics.
In this Chapter, we provide a broad, but practical overview of the most
important relevant methods.Comment: 50 pages, 13 figures. This Chapter will appear in the Section "Timing
Analysis" of the "Handbook of X-ray and Gamma-ray Astrophysics" (Editors in
chief: C. Bambi and A. Santangelo
Hack Weeks as a model for Data Science Education and Collaboration
Across almost all scientific disciplines, the instruments that record our
experimental data and the methods required for storage and data analysis are
rapidly increasing in complexity. This gives rise to the need for scientific
communities to adapt on shorter time scales than traditional university
curricula allow for, and therefore requires new modes of knowledge transfer.
The universal applicability of data science tools to a broad range of problems
has generated new opportunities to foster exchange of ideas and computational
workflows across disciplines. In recent years, hack weeks have emerged as an
effective tool for fostering these exchanges by providing training in modern
data analysis workflows. While there are variations in hack week
implementation, all events consist of a common core of three components:
tutorials in state-of-the-art methodology, peer-learning and project work in a
collaborative environment. In this paper, we present the concept of a hack week
in the larger context of scientific meetings and point out similarities and
differences to traditional conferences. We motivate the need for such an event
and present in detail its strengths and challenges. We find that hack weeks are
successful at cultivating collaboration and the exchange of knowledge.
Participants self-report that these events help them both in their day-to-day
research as well as their careers. Based on our results, we conclude that hack
weeks present an effective, easy-to-implement, fairly low-cost tool to
positively impact data analysis literacy in academic disciplines, foster
collaboration and cultivate best practices.Comment: 15 pages, 2 figures, submitted to PNAS, all relevant code available
at https://github.com/uwescience/HackWeek-Writeu
NuSTAR Hard X-ray View of Low-luminosity Active Galactic Nuclei: High-energy Cutoff and Truncated Thin Disk
We report the analysis of simultaneous XMM-Newton+NuSTAR observations of two
low-luminosity Active Galactic Nuclei (LLAGN), NGC 3998 and NGC 4579. We do not
detect any significant variability in either source over the ~3 day length of
the NuSTAR observations. The broad-band 0.5-60 keV spectrum of NGC 3998 is best
fit with a cutoff power-law, while the one for NGC 4579 is best fit with a
combination of a hot thermal plasma model, a power-law, and a blend of
Gaussians to fit an Fe complex observed between 6 and 7 keV. Our main spectral
results are the following: (1) neither source shows any reflection hump with a
reflection fraction upper-limits and for NGC 3998
and NGC 4579, respectively; (2) the 6-7 keV line complex in NGC 4579 could
either be fit with a narrow Fe K line at 6.4 keV and a moderately broad Fe XXV
line, or 3 relatively narrow lines, which includes contribution from Fe XXVI;
(3) NGC 4579 flux is 60% brighter than previously detected with XMM-Newton,
accompanied by a hardening in the spectrum; (4) we measure a cutoff energy
keV in NGC 3998, which represents the lowest and
best constrained high-energy cutoff ever measured for an LLAGN; (5) NGC 3998
spectrum is consistent with a Comptonization model with either a sphere
() or slab () geometry, corresponding
to plasma temperatures between 20 and 150 keV. We discuss these results in the
context of hard X-ray emission from bright AGN, other LLAGN, and hot accretion
flow models.Comment: 14 pages, 11 figures, 4 tables, accepted for publication in Ap
Mapping the X-ray variability of GRS1915+105 with machine learning
Black hole X-ray binary systems (BHBs) contain a close companion star
accreting onto a stellar-mass black hole. A typical BHB undergoes transient
outbursts during which it exhibits a sequence of long-lived spectral states,
each of which is relatively stable. GRS 1915+105 is a unique BHB that exhibits
an unequaled number and variety of distinct variability patterns in X-rays.
Many of these patterns contain unusual behaviour not seen in other sources.
These variability patterns have been sorted into different classes based on
count rate and color characteristics by Belloni et al (2000). In order to
remove human decision-making from the pattern-recognition process, we employ an
unsupervised machine learning algorithm called an auto-encoder to learn what
classifications are naturally distinct by allowing the algorithm to cluster
observations. We focus on observations taken by the Rossi X-ray Timing
Explorer's Proportional Counter Array.
We find that the auto-encoder closely groups observations together that are
classified as similar under the Belloni et al (2000) system, but that there is
reasonable grounds for defining each class as made up of components from 3
groups of distinct behaviour.Comment: 17 pages, 27 figures. For associated projection code to view the
interactive 3D plot, see https://github.com/bjricketts/grs1915-auto-encode
Extending the and statistics to generic pulsed profiles
The search for astronomical pulsed signals within noisy data, in the radio
band, is usually performed through an initial Fourier analysis to find
"candidate" frequencies and then refined through the folding of the time series
using trial frequencies close to the candidate. In order to establish the
significance of the pulsed profiles found at these trial frequencies, pulsed
profiles are evaluated with a chi-squared test, to establish how much they
depart from a null hypothesis where the signal is consistent with a flat
distribution of noisy measurements. In high-energy astronomy, the chi-squared
statistic has widely been replaced by the statistic and the H-test as
they are more sensitive to extra information such as the harmonic content of
the pulsed profile. The statistic and H-test were originally developed
for the use with "event data", composed of arrival times of single photons,
leaving it unclear how these methods could be used in radio astronomy. In this
paper, we present a version of the statistic and H-test for pulse
profiles with Gaussian uncertainties, appropriate for radio or even optical
pulse profiles. We show how these statistical indicators provide better
sensitivity to low-significance pulsar candidates with respect to the usual
chi-squared method, and a straightforward way to discriminate between pulse
profile shapes. Moreover, they provide an additional tool for Radio Frequency
Interference (RFI) rejection.Comment: 15 pages, 5 figure
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