Searching for the 1 mHz variability in the flickering of V4743 Sgr: A cataclysmic variable accreting at a high rate

Dobrotka, A.; Orio, Marina; Benka, Denis; Vanderburg, Andrew

doi:10.1051/0004-6361/202039742

Cited by 5 publications

(3 citation statements)

References 44 publications

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“…With the result obtained with the XMM-Newton data we draw the conclusions that CAL 83 has a variable period, ruling out that the observed LS periodogram is modulated by a stable period with variable amplitude (even if also the amplitude varies). As mentioned above, Dobrotka et al (2021) were able to model the periodogram of Nova LMC 2009a in the SSS phase even only with variable amplitude, but a variable period appeared to yield better simulations. While in the LMC 2009a the scattering was around 0.4 s, in CAL 83 it is quite longer, namely 2.1 s, allowing a more definite conclusion.…”

Section: Simulating the Cal 83 Data For Better Understandingmentioning

confidence: 86%

NICER monitoring of supersoft X-ray sources

Orio,

Gendreau,

Giese

et al. 2022

Preprint

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We monitored four supersoft sources -two persistent ones, CAL 83 and MR Vel, and the recent novae YZ Ret (Nova Ret 2020) and V1674 Her (Nova Her 2021) -with NICER. The two persistent SSS were observed with unvaried X-ray flux level and spectrum, respectively, 13 and 20 years after the last observations. Short period modulations of the supersoft X-ray source (SSS) appear where the spectrum of the luminous central source was fully visible (in CAL 83 and V1674 Her) and were absent in YZ Ret and MR Vel, in which the flux originated in photoionized or shocked plasma, while the white dwarf (WD) was not observable. We thus suggest that the pulsations occur on, or very close to, the WD surface. The pulsations of CAL 83 were almost unvaried after 15 years, including an irregular drift of the 67 s period by 2.1 s. Simulations, including previous XMM-Newton data, indicate actual variations in period length within hours, rather than an artifact of the variable amplitude of the pulsations. Large amplitude pulsations with a period of 501.53±0.30 s were always detected in V1674 Her, as long as the SSS was observable. This period seems to be due to rotation of a highly magnetized WD. We cannot confirm the maximum effective temperature of ( 145,000 K) previously inferred for this nova, and discuss the difficulty in interpreting its spectrum. The WD appears to present two surface zones, one of which does not emit SSS flux.

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Section: Simulating the Cal 83 Data For Better Understandingmentioning

confidence: 86%

NICER monitoring of supersoft X-ray sources

Orio,

Gendreau,

Giese

et al. 2022

Preprint

Self Cite

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“…This QPO is exceedingly weak, appearing only in three bins of the PDS. Scientists already hypothesized that most binary star systems exhibit a similarly subtle QPO at the frequency mentioned earlier [16][17][18]. To accurately describe our data, we need to identify a model that fits our observations.…”

Section: Signal Processing Timing Analysismentioning

confidence: 97%

Detection of a Quasiperiodic Phenomenon of a Binary Star System Using Convolutional Neural Network

Benka,

Vašová,

Kebísek

et al. 2023

Intelligent Automation &Amp; Soft Computing

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Pattern recognition algorithms are commonly utilized to discover certain patterns, particularly in image-based data. Our study focuses on quasiperiodic oscillations (QPO) in celestial objects referred to as cataclysmic variables (CV). We are dealing with interestingly indistinct QPO signals, which we analyze using a power density spectrum (PDS). The confidence in detecting the latter using certain statistical approaches may come out with less significance than the truth. We work with real and simulated QPO data of a CV called MV Lyrae. Our primary statistical tool for determining confidence levels is sigma intervals. The aforementioned CV has scientifically proven QPO existence, but as indicated by our analysis, the QPO ended up falling below 1 − σ , and such QPOs are not noteworthy based on the former approach. We intend to propose and ultimately train a convolutional neural network (CNN) using two types of QPO data with varying amounts of training dataset lengths. We aim to demonstrate the accuracy and viability of the classification using a CNN in comparison to sigma intervals. The resulting detection rate of our algorithm is very plausible, thus proving the effectiveness of CNNs in this scientific area.

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“…For example, a handful of variable stars with periods < 90 minutes are found among ∼10 million variable candidates in the ZTF survey (Ofek et al 2020) and a few dozen M dwarf flares are found in four years of ASAS-SN transient alerts (Schmidt et al 2019). They miss classes such as double white dwarf binaries with periods down to ∼5 minutes (Kruckow et al 2021), transiting planets with periods down to ∼4 hr (Smith et al 2018), magnetic reconnection flares with durations from minutes to hours (Namekata et al 2017), and stochastic flickering in CV disks with characteristic timescales of around 1000 s (Dobrotka et al 2021).…”

Section: Introductionmentioning

confidence: 99%

An Evenly Spaced LSST Cadence for Rapidly Variable Stars

Feigelson,

Bianco,

Bonito

2023

ApJS

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Stars exhibit a bewildering variety of rapidly variable behaviors ranging from explosive magnetic flares to stochastically changing accretion to periodic pulsations or rotation. The principal Rubin Observatory Legacy Survey of Space and Time (LSST) surveys will have cadences too sparse and irregular to capture many of these phenomena. We propose here an LSST microsurvey to observe a single Galactic field, rich in unobscured stars, in a continuous sequence of 30 s exposures for one long winter night in a single photometric band. The result will be a unique data set of ∼1 million regularly spaced stellar light curves. The light curves will constitute a comprehensive collection of late-type stellar flaring, but also other classes like short-period binary systems and cataclysmic variables, young stellar objects, and ultrashort-period exoplanets. An unknown variety of anomalous solar system, Galactic, and extragalactic variables and transients may also be present. A powerful array of statistical procedures can be applied to individual light curves from the long-standing fields of time series analysis, signal processing, and econometrics. Dozens of “features” describing the variability can be extracted and the ensemble of light curves can be subject to advanced machine-learning clustering procedures. This will give a unique, authoritative, objective taxonomy of the rapidly variable sky derived from identically cadenced light curves. This microsurvey is best performed early in the Rubin Observatory program, and the results can inform the wider community on the best approaches to variable star identification and classification from the sparse, irregular cadences that dominate the planned surveys.

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Searching for the 1 mHz variability in the flickering of V4743 Sgr: A cataclysmic variable accreting at a high rate

Cited by 5 publications

References 44 publications

NICER monitoring of supersoft X-ray sources

NICER monitoring of supersoft X-ray sources

Detection of a Quasiperiodic Phenomenon of a Binary Star System Using Convolutional Neural Network

An Evenly Spaced LSST Cadence for Rapidly Variable Stars

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