High-energy characteristics of the accretion-powered millisecond pulsar IGR J17591-2342 during its 2018 outburst: XMM-Newton, NICER, NuSTAR, and INTEGRAL view of the 0.3-300 keV X-ray band

IGR J17591−2342 is an accreting millisecond X-ray pulsar, discovered with INTEGRAL, which went into outburst around July 21, 2018. To better understand the physics acting in these systems during the outburst episode, we performed detailed temporal-, timing-, and spectral analyses across the 0.3–300 keV band using data from NICER, XMM-Newton, NuSTAR, and INTEGRAL. The hard X-ray 20–60 keV outburst profile covering ∼85 days is composed of four flares. Over the course of the maximum of the last flare, we discovered a type-I thermonuclear burst in INTEGRAL JEM-X data, posing constraints on the source distance. We derived a distance of 7.6±0.7 kpc, adopting Eddington-limited photospheric radius expansion and assuming anisotropic emission. In the timing analysis, using all NICER 1–10 keV monitoring data, we observed a rather complex set of behaviours starting with a spin-up period (MJD 58345–58364), followed by a frequency drop (MJD 58364–58370), an episode of constant frequency (MJD 58370–58383), concluded by irregular behaviour till the end of the outburst. The 1–50 keV phase distributions of the pulsed emission, detected up to ∼120 keV using INTEGRAL ISGRI data, was decomposed in three Fourier harmonics showing that the pulsed fraction of the fundamental increases from ∼10% to ∼17% going from ∼1.5 to ∼4 keV, while the harder photons arrive earlier than the soft photons for energies .10 keV. The total emission spectrum of IGR J17591−2342 across the 0.3–150 keV band could adequately be fitted in terms of an absorbed compPS model yielding as best fit parameters a column density of NH = (2.09 ± 0.05) × 1022 cm−2 , a blackbody seed photon temperature kTbb,seed of 0.64±0.02 keV, electron temperature kTe = 38.8±1.2 keV and Thomson optical depth τT = 1.59 ± 0.04. The fit normalisation results in an emission area radius of 11.3 ± 0.5 km adopting a distance of 7.6 kpc. Finally, the results are discussed within the framework of accretion physics- and X-ray thermonuclear burst theor

Neutron star cooling and the rp process in thermonuclear X-ray bursts

When the upper layer of an accreting neutron star experiences a thermonuclear runaway of helium and hydrogen, it exhibits an X-ray burst of a few keV with a cool-down phase of typically 1~minute. When there is a surplus of hydrogen, hydrogen fusion is expected to simmer during that same minute due to the rp process, which consists of rapid proton captures and slow beta-decays of proton-rich isotopes. We have analyzed the high-quality light curves of 1254 X-ray bursts, obtained with the Proportional Counter Array on the Rossi X-ray Timing Explorer between 1996 and 2012, to systematically study the cooling and rp process. This is a follow-up of a study on a selection of 37 bursts from systems that lack hydrogen and show only cooling during the bursts. We find that the bolometric light curves are well described by the combination of a power law and a one-sided Gaussian. The power-law decay index is between 1.3 and 2.1 and similar to that for the 37-bursts sample. There are individual bursters with a narrower range. The Gaussian is detected in half of all bursts, with a typical standard deviation of 50~s and a fluence ranging up to 60% of the total fluence. The Gaussian appears consistent with being due to the rp process. The Gaussian fluence fraction suggests that the layer where the rp process is active is underabundant in H by a factor of at least five with respect to cosmic abundances. Ninety-four percent of all bursts from ultracompact X-ray binaries lack the Gaussian component, and the remaining 6% are marginal detections. This is consistent with a hydrogen deficiency in these binaries. We find no clear correlation between the power law and Gaussian light-curve components.Comment: Accepted for publication in Astronomy & Astrophysics, 17 page

The Gravitational-wave Optical Transient Observer (GOTO)

The Gravitational-wave Optical Transient Observer (GOTO) is a wide-field telescope project focused on detecting optical counterparts to gravitational-wave sources. GOTO uses arrays of 40 cm unit telescopes (UTs) on a shared robotic mount, which scales to provide large fields of view in a cost-effective manner. A complete GOTO mount uses 8 unit telescopes to give an overall field of view of 40 square degrees, and can reach a depth of 20th magnitude in three minutes. The GOTO-4 prototype was inaugurated with 4 unit telescopes in 2017 on La Palma, and was upgraded to a full 8-telescope array in 2020. A second 8-UT mount will be installed on La Palma in early 2021, and another GOTO node with two more mount systems is planned for a southern site in Australia. When complete, each mount will be networked to form a robotic, dual-hemisphere observatory, which will survey the entire visible sky every few nights and enable rapid follow-up detections of transient sources

Processing GOTO data with the Rubin Observatory LSST Science Pipelines I: Production of coadded frames

The past few decades have seen the burgeoning of wide field, high cadence surveys, the most formidable of which will be the Legacy Survey of Space and Time (LSST) to be conducted by the Vera C. Rubin Observatory. So new is the field of systematic time-domain survey astronomy, however, that major scientific insights will continue to be obtained using smaller, more flexible systems than the LSST. One such example is the Gravitational-wave Optical Transient Observer (GOTO), whose primary science objective is the optical follow-up of Gravitational Wave events. The amount and rate of data production by GOTO and other wide-area, high-cadence surveys presents a significant challenge to data processing pipelines which need to operate in near real-time to fully exploit the time-domain. In this study, we adapt the Rubin Observatory LSST Science Pipelines to process GOTO data, thereby exploring the feasibility of using this "off-the-shelf" pipeline to process data from other wide-area, high-cadence surveys. In this paper, we describe how we use the LSST Science Pipelines to process raw GOTO frames to ultimately produce calibrated coadded images and photometric source catalogues. After comparing the measured astrometry and photometry to those of matched sources from PanSTARRS DR1, we find that measured source positions are typically accurate to sub-pixel levels, and that measured L-band photometries are accurate to ∼50 mmag at mL∼16 and ∼200 mmag at mL∼18. These values compare favourably to those obtained using GOTO's primary, in-house pipeline, GOTOPHOTO, in spite of both pipelines having undergone further development and improvement beyond the implementations used in this study. Finally, we release a generic "obs package" that others can build-upon should they wish to use the LSST Science Pipelines to process data from other facilities

Light curve classification with recurrent neural networks for GOTO: dealing with imbalanced data

The advent of wide-field sky surveys has led to the growth of transient and variable source discoveries. The data deluge produced by these surveys has necessitated the use of machine learning (ML) and deep learning (DL) algorithms to sift through the vast incoming data stream. A problem that arises in real-world applications of learning algorithms for classification is imbalanced data, where a class of objects within the data is underrepresented, leading to a bias for over-represented classes in the ML and DL classifiers. We present a recurrent neural network (RNN) classifier that takes in photometric time-series data and additional contextual information (such as distance to nearby galaxies and on-sky position) to produce real-time classification of objects observed by the Gravitational-wave Optical Transient Observer (GOTO), and use an algorithm-level approach for handling imbalance with a focal loss function. The classifier is able to achieve an Area Under the Curve (AUC) score of 0.972 when using all available photometric observations to classify variable stars, supernovae, and active galactic nuclei. The RNN architecture allows us to classify incomplete light curves, and measure how performance improves as more observations are included. We also investigate the role that contextual information plays in producing reliable object classification

Searching for Fermi GRB optical counterparts with the prototype gravitational-wave optical transient observer (GOTO)

The typical detection rate of ∼1 gamma-ray burst (GRB) per day by the Fermi Gamma-ray Burst Monitor (GBM) provides a valuable opportunity to further our understanding of GRB physics. However, the large uncertainty of the Fermi localization typically prevents rapid identification of multi-wavelength counterparts. We report the follow-up of 93 Fermi GRBs with the Gravitational-wave Optical Transient Observer (GOTO) prototype on La Palma. We selected 53 events (based on favourable observing conditions) for detailed analysis, and to demonstrate our strategy of searching for optical counterparts. We apply a filtering process consisting of both automated and manual steps to 60 085 candidates initially, rejecting all but 29, arising from 15 events. With ≈3 GRB afterglows expected to be detectable with GOTO from our sample, most of the candidates are unlikely to be related to the GRBs. Since we did not have multiple observations for those candidates, we cannot confidently confirm the association between the transients and the GRBs. Our results show that GOTO can effectively search for GRB optical counterparts thanks to its large field of view of ≈40 square degrees and its depth of ≈20 mag. We also detail several methods to improve our overall performance for future follow-up programs of Fermi GRBs

Searching for Fermi GRB optical counterparts with the prototype Gravitational-wave Optical Transient Observer (GOTO)

The typical detection rate of ∼1 gamma-ray burst (GRB) per day by the Fermi Gamma-ray Burst Monitor (GBM) provides a valuable opportunity to further our understanding of GRB physics. However, the large uncertainty of the Fermi localization typically prevents rapid identification of multiwavelength counterparts. We report the follow-up of 93 Fermi GRBs with the Gravitational-wave Optical Transient Observer (GOTO) prototype on La Palma. We selected 53 events (based on favourable observing conditions) for detailed analysis, and to demonstrate our strategy of searching for optical counterparts. We apply a filtering process consisting of both automated and manual steps to 60 085 candidates initially, rejecting all but 29, arising from 15 events. With ≈3 GRB afterglows expected to be detectable with GOTO from our sample, most of the candidates are unlikely to be related to the GRBs. Since we did not have multiple observations for those candidates, we cannot confidently confirm the association between the transients and the GRBs. Our results show that GOTO can effectively search for GRB optical counterparts thanks to its large field of view of ≈40 deg2 and its depth of ≈20 mag. We also detail several methods to improve our overall performance for future follow-up programmes of Fermi GRBs.</p