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Register a new userHow Swift is Redefining Time Domain Astronomy
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NASAs Swift satellite has completed ten years of amazing discoveries in time domain astronomy. Its primary mission is to chase gamma-ray bursts (GRBs), but due to its scheduling flexibility it has subsequently become a prime discovery machine for new types of behavior. The list of major discoveries in GRBs and other transients includes the long-lived X-ray afterglows and flares from GRBs, the first accurate localization of short GRBs, the discovery of GRBs at high redshift (z>8), supernova shock break-out from SN Ib, a jetted tidal disruption event, an ultra-long class of GRBs, high energy emission from flare stars, novae and supernovae with unusual characteristics, magnetars with glitches in their spin periods, and a short GRB with evidence of an accompanying kilonova. Swift has developed a dynamic synergism with ground based observatories. In a few years gravitational wave observatories will come on-line and provide exciting new transient sources for Swift to study.
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We aimed to detect a supernova (SN) shock breakout (SBO) with observations in time domain. The SBO marks the first escape of radiation from the blast wave that breaks through the photosphere of the star and launches the SN ejecta, and peaks in the ultraviolet and soft X-ray bands. The detection of a SBO allows determining the onset of the explosion with an accuracy from a few hours to a few seconds. Using the XRT and UVOT instruments onboard the Swift satellite we carried out a weekly cadenced, six months lasting monitoring of seven nearby (distance <50 Mpc) galaxies, namely NGC1084, NGC2207/IC2163, NGC2770, NGC4303/M61, NGC3147, NGC3690, NGC6754. We searched for variable/transient sources in the collected data. We found no evidence for a SN SBO event, but we discovered five objects located within the light of the sample galaxies that are variable in the X-ray and/or in the UV. Our sample galaxies are within the Universe volume that will be reached by the forthcoming advanced gravitational waves (GW) detectors (a-LIGO/a-Virgo), thus this work provides an example on how to carry out Swift surveys useful to detect the GW signal from SNe, and to detect counterparts to GW triggers.
THESEUS is a medium size space mission of the European Space Agency, currently under evaluation for a possible launch in 2032. Its main objectives are to investigate the early Universe through the observation of gamma-ray bursts and to study the gravitational waves electromagnetic counterparts and neutrino events. On the other hand, its instruments, which include a wide field of view X-ray (0.3-5 keV) telescope based on lobster-eye focusing optics and a gamma-ray spectrometer with imaging capabilities in the 2-150 keV range, are also ideal for carrying out unprecedented studies in time domain astrophysics. In addition, the presence onboard of a 70 cm near infrared telescope will allow simultaneous multi-wavelegth studies. Here we present the THESEUS capabilities for studying the time variability of different classes of sources in parallel to, and without affecting, the gamma-ray bursts hunt.
In time domain astronomy, recurrent transients present a special problem: how to infer total populations from limited observations. Monitoring observations may give a biassed view of the underlying population due to limitations on observing time, visibility and instrumental sensitivity. A similar problem exists in the life sciences, where animal populations (such as migratory birds) or disease prevalence, must be estimated from sparse and incomplete data. The class of methods termed Capture-Recapture is used to reconstruct population estimates from time-series records of encounters with the study population. This paper investigates the performance of Capture-Recapture methods in astronomy via a series of numerical simulations. The Blackbirds code simulates monitoring of populations of transients, in this case accreting binary stars (neutron star or black hole accreting from a stellar companion) under a range of observing strategies. We first generate realistic light-curves for populations of binaries with contrasting orbital period distributions. These models are then randomly sampled at observing cadences typical of existing and planned monitoring surveys. The classical capture-recapture methods, Lincoln-Peterson, Schnabel estimators, related techniques, and newer methods implemented in the Rcapture package are compared. A general exponential model based on the radioactive decay law is introduced, and demonstrated to recover (at 95% confidence) the underlying population abundance and duty cycle, in a fraction of the observing visits (10-50%) required to discover all the sources in the simulation. Capture-Recapture is a promising addition to the toolbox of time domain astronomy, and methods implemented in R by the biostats community can be readily called from within Python.
We show how new and upcoming advances in the age of time-domain and multi-wavelength astronomy will open up a new venue to probe the diversity of SN~Ia. We discuss this in the context of the ELT (ESO), as well as space based instrument such as James Webb Space Telescope (JWST). As examples we demonstrate how the power of very early observations, within hours to days after the explosion, and very late-time observations, such as light curves and mid-infrared spectra beyond 3 years, can be used to probe the link to progenitors and explosion scenarios. We identify the electron-capture cross sections of Cr, Mn, and Ni/Co as one of the limiting factors we will face in the future.
Celestial objects exhibit a wide range of variability in brightness at different wavebands. Surprisingly, the most common methods for characterizing time series in statistics -- parametric autoregressive modeling -- is rarely used to interpret astronomical light curves. We review standard ARMA, ARIMA and ARFIMA (autoregressive moving average fractionally integrated) models that treat short-memory autocorrelation, long-memory $1/f^alpha$ `red noise, and nonstationary trends. Though designed for evenly spaced time series, moderately irregular cadences can be treated as evenly-spaced time series with missing data. Fitting algorithms are efficient and software implementations are widely available. We apply ARIMA models to light curves of four variable stars, discussing their effectiveness for different temporal characteristics. A variety of extensions to ARIMA are outlined, with emphasis on recently developed continuous-time models like CARMA and CARFIMA designed for irregularly spaced time series. Strengths and weakness of ARIMA-type modeling for astronomical data analysis and astrophysical insights are reviewed.
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