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Register a new userStatistical Signatures of Nanoflare Activity. II. A Nanoflare Explanation for Periodic Brightenings in Flare Stars observed by NGTS
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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.
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Small-scale magnetic reconnection processes, in the form of nanoflares, have become increasingly hypothesized as important mechanisms for the heating of the solar atmosphere, for driving propagating disturbances along magnetic field lines in the Suns corona, and for instigating rapid jet-like bursts in the chromosphere. Unfortunately, the relatively weak signatures associated with nanoflares places them below the sensitivities of current observational instrumentation. Here, we employ Monte Carlo techniques to synthesize realistic nanoflare intensity time series from a dense grid of power-law indices and decay timescales. Employing statistical techniques, which examine the modeled intensity fluctuations with more than 10^7 discrete measurements, we show how it is possible to extract and quantify nanoflare characteristics throughout the solar atmosphere, even in the presence of significant photon noise. A comparison between the statistical parameters (derived through examination of the associated intensity fluctuation histograms) extracted from the Monte Carlo simulations and SDO/AIA 171{AA} and 94{AA} observations of active region NOAA 11366 reveals evidence for a flaring power-law index within the range of 1.82 - 1.90, combined with e-folding timescales of 385 +/- 26 s and 262 +/- 17 s for the SDO/AIA 171{AA} and 94{AA} channels, respectively. These results suggest that nanoflare activity is not the dominant heating source for the active region under investigation. This opens the door for future dedicated observational campaigns to not only unequivocally search for the presence of small-scale reconnection in solar and stellar environments, but also quantify key characteristics related to such nanoflare activity.
The properties of the acoustic modes are sensitive to magnetic activity. The unprecedented long-term Kepler photometry, thus, allows stellar magnetic cycles to be studied through asteroseismology. We search for signatures of magnetic cycles in the seismic data of Kepler solar-type stars. We find evidence for periodic variations in the acoustic properties of about half of the 87 analysed stars. In these proceedings, we highlight the results obtained for two such stars, namely KIC 8006161 and KIC 5184732.
The nanoflare paradigm of coronal heating has proven extremely promising for explaining the presence of hot, multi-million degree loops in the solar corona. In this paradigm, localized heating events supply enough energy to heat the solar atmosphere to its observed temperatures. Rigorously modeling this process, however, has proven difficult, since it requires an accurate treatment of both the magnetic field dynamics and reconnection as well as the plasmas response to magnetic perturbations. In this paper, we combine fully 3D magnetohydrodynamic (MHD) simulations of coronal active region plasma driven by photospheric motions with spatially-averaged, time-dependent hydrodynamic (HD) modeling of coronal loops to obtain physically motivated observables that can be quantitatively compared with observational measurements of active region cores. We take the behavior of reconnected field lines from the MHD simulation and use them to populate the HD model to obtain the thermodynamic evolution of the plasma and subsequently the emission measure distribution. We find the that the photospheric driving of the MHD model produces only very low-frequency nanoflare heating which cannot account for the full range of active region core observations as measured by the low-temperature emission measure slope. Additionally, we calculate the spatial and temporal distributions of field lines exhibiting collective behavior, and argue that loops occur due to random energization occurring on clusters of adjacent field lines.
In the Sun, the frequencies of the acoustic modes are observed to vary in phase with the magnetic activity level. These frequency variations are expected to be common in solar-type stars and contain information about the activity-related changes that take place in their interiors. The unprecedented duration of Kepler photometric time-series provides a unique opportunity to detect and characterize stellar magnetic cycles through asteroseismology. In this work, we analyze a sample of 87 solar-type stars, measuring their temporal frequency shifts over segments of length 90 days. For each segment, the individual frequencies are obtained through a Bayesian peak-bagging tool. The mean frequency shifts are then computed and compared with: 1) those obtained from a cross-correlation method; 2) the variation in the mode heights; 3) a photometric activity proxy; and 4) the characteristic timescale of the granulation. For each star and 90-d sub-series, we provide mean frequency shifts, mode heights, and characteristic timescales of the granulation. Interestingly, more than 60% of the stars show evidence for (quasi-)periodic variations in the frequency shifts. In the majority of the cases, these variations are accompanied by variations in other activity proxies. About 20% of the stars show mode frequencies and heights varying approximately in phase, in opposition to what is observed for the Sun.
Despite its prediction over two decades ago, the detection of faint, high-temperature (hot) emission due to nanoflare heating in non-flaring active region cores has proved challenging. Using an efficient two-fluid hydrodynamic model, this paper investigates the properties of the emission expected from repeating nanoflares (a nanoflare train) of varying frequency as well as the separate heating of electrons and ions. If the emission measure distribution ($mathrm{EM}(T)$) peaks at $T = T_m$, we find that $mathrm{EM}(T_m)$ is independent of details of the nanoflare train, and $mathrm{EM}(T)$ above and below $T_m$ reflects different aspects of the heating. Below $T_m$ the main influence is the relationship of the waiting time between successive nanoflares to the nanoflare energy. Above $T_m$ power-law nanoflare distributions lead to an extensive plasma population not present in a monoenergetic train. Furthermore, in some cases characteristic features are present in $mathrm{EM}(T)$. Such details may be detectable given adequate spectral resolution and a good knowledge of the relevant atomic physics. In the absence of such resolution we propose some metrics that can be used to infer the presence of hot plasma.
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