Statistical Signatures of Nanoflare Activity. II. A Nanoflare Explanation for Periodic Brightenings in Flare Stars observed by NGTS

Abstract

Several studies have documented periodic and quasi-periodic signals from the time series of dMe flare stars and other stellar sources. Such periodic signals, observed within quiescent phases (i.e., devoid of larger-scale microflare or flare activity), range in period from $1-1000$ seconds and hence have been tentatively linked to ubiquitous $p$-mode oscillations generated in the convective layers of the star. As such, most interpretations for the observed periodicities have been framed in terms of magneto-hydrodynamic wave behavior. However, we propose that a series of continuous nanoflares, based upon a power-law distribution, can provide a similar periodic signal in the associated time series. Adapting previous statistical analyses of solar nanoflare signals, we find the first statistical evidence for stellar nanoflare signals embedded within the noise envelope of M-type stellar lightcurves. Employing data collected by the Next Generation Transit Survey (NGTS), we find evidence for stellar nanoflare activity demonstrating a flaring power-law index of $3.25\pm 0.20$, alongside a decay timescale of $200\pm 100$ s. We also find that synthetic time series, consistent with the observations of dMe flare star lightcurves, are capable of producing quasi-periodic signals in the same frequency range as $p$-mode signals, despite being purely comprised of impulsive signatures. Phenomena traditionally considered a consequence of wave behaviour may be described by a number of high frequency but discrete nanoflare energy events. This new physical interpretation presents a novel diagnostic capability, by linking observed periodic signals to given nanoflare model conditions.

22 Pages, 8 figures, accepted for publication by ApJ

References in corpus (23)

• The XMM-Newton serendipitous survey IX. The fourth XMM-Newton serendipitous source catalogue
• Simulations of dynamo action in fully convective stars
• Statistical properties of superflares on solar-type stars based on 1-min cadence data
• Solar-type dynamo behaviour in fully convective stars without a tachocline
• The common patterns of nature
• Automated Solar Flare Statistics in Soft X-rays over 37 Years of GOES Observations - The Invariance of Self-Organized Criticality during Three Solar Cycles
• On the Existence of the Kolmogorov Inertial Range in the Terrestrial Magnetosheath Turbulence
• Global Energetics of Solar Flares: I. Magnetic Energies
• GALEX high time-resolution ultraviolet observations of dMe flare events
• Do A-type stars flare?
• Short Duration Stellar Flares in GALEX Data
• Plasma sloshing in pulse-heated solar and stellar coronal loops
• The Frequency-dependent Damping of Slow Magnetoacoustic Waves in a Sunspot Umbral Atmosphere
• First radio evidence for impulsive heating contribution to the quiet solar corona
• Signatures of Steady Heating in Time Lag Analysis of Coronal Emission
• Detection of a giant white-light flare on an L2.5 dwarf with the Next Generation Transit Survey
• Nanoflare Activity in the Solar Chromosphere
• Stellar dynamos with $\vec{\Omega }\times \vec{J}$ effect
• HiPERCAM: A high-speed, quintuple-beam CCD camera for the study of rapid variability in the Universe
• NGTS clusters survey -- II. White-light flares from the youngest stars in Orion
• Hydrodynamic Simulation of a nano-flare heated multi-strand solar atmospheric loop
• A transition of dynamo modes in M dwarfs: narrowing down the spectral range where the transition occurs*
• EUV Observational consequences of the spatial localisation of nanoflare heating within a multi-stranded atmospheric loop

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