Discovery of Periodic Dips in the Brightest Hard X-Ray Source of M31 with EXTraS

Marelli, M.; Tiengo, A.; Luca, A. De; Salvetti, D.; Saronni, Luca; Sidoli, L.; Paizis, A.; Salvaterra, R.; Belfiore, A.; Israel, G. L.; Haberl, F.; D’Agostino, Daniele

doi:10.3847/2041-8213/aa9b2e

Cited by 11 publications

(11 citation statements)

References 18 publications

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“…Moreover, we have reported the presence of periodic dips in the Chandra X-ray light curve of M51 ULX-7. Although X-ray dips are also seen in bright X-ray binaries (Marelli et al 2017) and ULXs (Wang et al 2018), this is the first evidence of such a property in ULXPs. The physical origin of the dips remains unclear, but they could be related to a plethora of mechanisms that have been proposed to explain similar features in HMXBs.…”

Section: Discussionmentioning

confidence: 64%

Chandra Probes the X-Ray Variability of M51 ULX-7: Evidence of Propeller Transition and X-Ray Dips on Orbital Periods

Vasilopoulos

Koliopanos

Haberl

et al. 2021

ApJ

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We report on the temporal properties of the ultraluminous X-ray (ULX) pulsar M51 ULX-7 inferred from the analysis of the 2018-2020 Swift/X-ray Telescope monitoring data and archival Chandra data obtained over a period of 33 days in 2012. We find an extended low flux state, which might be indicative of propeller transition, lending further support to the interpretation that the neutron star is rotating near equilibrium. Alternatively, this offstate could be related to a variable superorbital period. Moreover, we report the discovery of periodic dips in the X-ray light curve that are associated with the binary orbital period. The presence of the dips implies a configuration where the orbital plane of the binary is closer to an edge-on orientation, and thus demonstrates that favorable geometries are not necessary in order to observe ULX pulsars. These characteristics are similar to those seen in prototypical X-ray pulsars such as Her X-1 and SMC X-1 or other ULX pulsars such as NGC 5907 ULX1.

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Section: Discussionmentioning

confidence: 64%

Chandra Probes the X-Ray Variability of M51 ULX-7: Evidence of Propeller Transition and X-Ray Dips on Orbital Periods

Vasilopoulos

Koliopanos

Haberl

et al. 2021

ApJ

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“…Most of them (97% in the core, 80% in the corona, and 83% in the tail) are dips. While some of the dips are instrumental errors occurring at the beginning or the end of the observation, we find many well-known dipping sources, for example: 2XMM J125048.6+410743 (Lin et al 2013) and 3XMM J004232.1+411314 (Marelli et al 2017).…”

Section: Dips and Eclipsesmentioning

confidence: 71%

“…With the introduction of this new tool, we were able to explore the EXTraS data set, focusing on variable sources, quickly selecting a number of objects that have interesting properties that warrant further investigation, including different kinds of binary systems (from binary stars to ULXs) as well as more peculiar sources. While some of these objects were already investigated and described in the literature, for example the most luminous dipper known 3XMM J004232.2+411314 (Marelli et al 2017), the peculiar transient 3XMM J063045.4-603113 (Mainetti et al 2016), and the poorly understood, low-mass AGN XMMU J134736.6+173403 (Carpano et al 2008), we also extracted some new interesting sources (Sect. 4.4).…”

Section: Discussionmentioning

confidence: 99%

Exploring X-ray variability with unsupervised machine learning

Pasquato

Marelli

Luca

et al. 2022

A&A

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Context. XMM-Newton provides unprecedented insight into the X-ray Universe, recording variability information for hundreds of thousands of sources. Manually searching for interesting patterns in light curves is impractical, requiring an automated data-mining approach for the characterization of sources. Aims. Straightforward fitting of temporal models to light curves is not a sure way to identify them, especially with noisy data. We used unsupervised machine learning to distill a large data set of light-curve parameters, revealing its clustering structure in preparation for anomaly detection and subsequent searches for specific source behaviors (e.g., flares, eclipses). Methods. Self-organizing maps (SOMs) achieve dimensionality reduction and clustering within a single framework. They are a type of artificial neural network trained to approximate the data with a two-dimensional grid of discrete interconnected units, which can later be visualized on the plane. We trained our SOM on temporal-only parameters computed from 10 5 detections from the EXTraS (Exploring the X-ray Transient and variable Sky) catalog. Results. The resulting map reveals that the ≈ 2500 most variable sources are clustered based on temporal characteristics. We find distinctive regions of the SOM map associated with flares, eclipses, dips, linear light curves, and others. Each group contains sources that appear similar by eye. We single out a handful of interesting sources for further study. Conclusions. The condensed view of our dataset provided by SOMs allowed us to identify groups of similar sources, speeding up manual characterization by orders of magnitude. Our method also highlights problems with fitting simple temporal models to light curves and can be used to mitigate them to an extent. This will be crucial for fully exploiting the high data volume expected from upcoming X-ray surveys, and may also help with interpreting supervised classification models.

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“…Although this result is not included in the EXTraS catalogue, we briefly comment on it because it is a natural evolution of the project. 3XMM J004232.1+411314: Pulsations at about 3 s have been detected from this bright hard X-ray source located at 3.7' from the bulge of M31, and it is known to show dips with a likely orbital period of about 4.01 hr (Rodríguez Castillo et al 2018;Marelli et al 2017). By correcting the archival data for the unknown orbital parameters, we detected the 3 s signals from nine datasets over a baseline of 16 years (see also Fig.…”

Section: The Case Of M31mentioning

confidence: 99%

The EXTraS project: Exploring the X-ray transient and variable sky

Luca

Salvaterra

Belfiore

et al. 2021

A&A

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Temporal variability in flux and spectral shape is ubiquitous in the X-ray sky and carries crucial information about the nature and emission physics of the sources. The EPIC instrument on board the XMM-Newton observatory is the most powerful tool for studying variability even in faint sources. Each day, it collects a large amount of information about hundreds of new serendipitous sources, but the resulting huge (and growing) dataset is largely unexplored in the time domain. The project called Exploring the X-ray transient and variable sky (EXTraS) systematically extracted all temporal domain information in the XMM-Newton archive. This included a search and characterisation of variability, both periodic and aperiodic, in hundreds of thousands of sources spanning more than eight orders of magnitude in timescale and six orders of magnitude in flux, and a search for fast transients that were missed by standard image analysis. All results, products, and software tools have been released to the community in a public archive. A science gateway has also been implemented to allow users to run the EXTraS analysis remotely on recent XMM datasets. We give details on the new algorithms that were designed and implemented to perform all steps of EPIC data analysis, including data preparation, source and background modelling, generation of time series and power spectra, and search for and characterisation of different types of variabilities. We describe our results and products and give information about their basic statistical properties and advice on their usage. We also describe available online resources. The EXTraS database of results and its ancillary products is a rich resource for any kind of investigation in almost all fields of astrophysics. Algorithms and lessons learnt from our project are also a very useful reference for any current and future experiment in the time domain.

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Discovery of Periodic Dips in the Brightest Hard X-Ray Source of M31 with EXTraS

Cited by 11 publications

References 18 publications

Chandra Probes the X-Ray Variability of M51 ULX-7: Evidence of Propeller Transition and X-Ray Dips on Orbital Periods

Chandra Probes the X-Ray Variability of M51 ULX-7: Evidence of Propeller Transition and X-Ray Dips on Orbital Periods

Exploring X-ray variability with unsupervised machine learning

The EXTraS project: Exploring the X-ray transient and variable sky

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