To understand the mechanism of coronal heating, it is crucial to derive the contribution of small-scale flares, the so-called nanoflares, to the heating up of the solar corona. To date, several studies have tried to derive the occurrence frequency distribution of flares as a function of energy to reveal the contribution of small-scale flares. However, there are no studies that derive the distribution with considering the following conditions: (1) evolution of the coronal loop plasma heated by small-scale flares, (2) loops smaller than the spatial resolution of the observed image, and (3) multiwavelength observation. To take into account these conditions, we introduce a new method to analyze small-scale flares statistically based on a one-dimensional loop simulation and a machine learning technique, that is, genetic algorithm. First, we obtain six channels of SDO/AIA light curves of the active-region coronal loops. Second, we carry out many coronal loop simulations and obtain the SDO/AIA light curves for each simulation in a pseudo-manner. Third, using the genetic algorithm, we estimate the best combination of simulated light curves that reproduce the observation. Consequently, the observed coronal loops are heated by small-scale flares with energy flux larger than that typically required to heat up an active region intermittently. Moreover, we derive the occurrence frequency distribution which have various power-law indices in the range from 1 to 3, which partially supports the nanoflare heating model. In contrast, we find that $90\%$ of the coronal heating is done by flares that have energy larger than $10^{25}~\mathrm{erg}$.
In solar flares, energy is released impulsively and is partly converted into thermal energy of hot plasmas and kinetic energy of accelerated nonthermal particles. Despite numerous efforts, no consensus on quantifying this energy balance has yet been reached. We aim to understand the reasons for the contradicting results on energy partition obtained by various recent studies. We considered five recent studies that address the thermal-nonthermal energy partition in solar flares. Their results are reviewed, and their methods are compared and discussed in detail. The main uncertainties in deriving…
A Convolutional Neural Network-Derived Catalog of Solar Flares from Soft X-Ray Observations
Sydney Institute for Astronomy, University of Sydney（悉尼大学天体物理研究所）；School of Physics, University of Melbourne（墨尔本大学物理学院）；OzGrav-Melbourne, Australian Research Council Centre of Excellence for Gravitational Wave Discovery（澳大利亚研究委员会引力波发现卓越中心）
We analyze here variations of the position and the vertical extent of the energy deposition layer (EDL) inthe C1.6 GOES-class solar flare observed at 10:20 UT on 2012 September 10. The variations of the EDL arecontrasted with the variations of the spectra and emission intensities recorded in the H-alpha line with the very high time resolution using the MSDP spectrograph at Bialkow Observatory. The flare radiated hard X-rays (HXR) detectable up to a energy of 70 keV. A numerical model of the flare used in the analysis assumes that the non-thermal electrons (NTEs) carried the external energy to …
In this study, we investigated the energy partition of four confined circular-ribbon flares (CRFs) near the solar disk center, which are observed simultaneously by SDO, GOES, and RHESSI. We calculated different energy components, including the radiative outputs in 1$-$8, 1$-$70, and 70$-$370 Å, total radiative loss, peak thermal energy derived from GOES and RHESSI, nonthermal energy in flare-accelerated electrons, and magnetic free energy before flares. It is found that the energy components increase systematically with the flare class, indicating that more energies are involved in larger flar…
Although late-type dwarfs and giant stars are substantially different, their flares are thought to originate in similar physical processes and differ only by a scale factor in the energy levels. We study the validity of this approach. We search for characteristics of flares on active giants, which might be statistically different from those on main-sequence stars. We used nearly 4000 flares of 61 giants and 20 stars of other types that were observed with Kepler in long-cadence mode, which is the only suitable database for this comparative study. For every flare, we derived the duration and ene…
We often find spectral signatures of chromospheric cold plasma ejections accompanied by flares in a wide range of spatial scales in the solar and stellar atmospheres. However, the relationship between physical quantities (such as mass, kinetic energy, and velocity) of cold ejecta and flare energy has not been investigated in a unified manner for the entire range of flare energies to date. This study analyzed the spectra of cold plasma ejections associated with small-scale flares and solar flares (energy $10^{25}-10^{29}\,\mathrm{erg}$) to supply smaller energy samples. We performed H$α$ imagin…
Optical Continuum Light Curves and Bolometric Energy Estimates of Solar White-light Flares
State Key Laboratory of Solar Activity and Space Weather, National Astronomical Observatories, Chinese Academy of Science（中国科学院国家天文台太阳活动与空间天气国家重点实验室）；School of Astronomy and Space Science, University of Chinese Academy of Sciences（中国科学院大学天文与空间科学学院）；Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences（中国科学院国家天文台光学天文重点实验室）；Purple Mountain Observatory, Chinese Academy of Sciences（中国科学院紫金山天文台）；School of Astronomy and Space Sciences, University of Science and Technology of China（中国科学技术大学天文与空间科学学院）；Institute for Frontiers in Astronomy and Astrophysics, Beijing Normal University（北京师范大学天文与天体物理前沿研究院）；New Cornerstone Science Laboratory, National Astronomical Observatories, Chinese Academy of Sciences（中国科学院国家天文台新基石科学实验室）
Observations of solar and stellar flares have revealed the presence of power law dependences between the flare energy and the time interval between flares. Various models have been proposed to explain these dependences, and to explain the numerical value of the power law indices. Here, we propose a model in which convective flows in granules force the foot-points of coronal magnetic loops, which are frozen-in to photospheric gas, to undergo a random walk. In certain conditions, this can lead to a twist in the loop, which drives the loop unstable if the twist exceeds a critical value. The possi…
We present a study of multi-wavelength observations, of a C 2.3 solar flare in Active Region NOAA 12353, observed on 2015 May 23, which reveal new properties of acoustic waves in the flaring region. The space-, and ground-based data measured by the HELioseismological Large Regions Interferometric Device, operating at the Vacuum Tower Telescope, the Atmospheric Imaging Assembly, and Helioseismic and Magnetic Imager on board the Solar Dynamic Observatory, were used in this paper. First, using power spectra of solar oscillations, we identified the dominant frequencies and their location at seven …
Recently, many superflares on solar-type stars were discovered as white-light flares (WLFs). A correlation between the energies (E) and durations (t) of superflares is derived as $t\propto E^{0.39}$, and this can be theoretically explained by magnetic reconnection ($t\propto E^{1/3}$). In this study, we carried out a statistical research on 50 solar WLFs with SDO/HMI to examine the t-E relation. As a result, the t-E relation on solar WLFs ($t\propto E^{0.38}$) is quite similar stellar superflares, but the durations of stellar superflares are much shorter than those extrapolated from solar WLFs…
Small-Scale and Transient EUV Kernels in Solar Flare Ribbons
University of Applied Sciences and Arts Northwestern Switzerland (FHNW)（西北瑞士应用科学与艺术大学）；ETH Zürich（苏黎世联邦理工学院）；Space Sciences Laboratory, University of California（加州大学空间科学实验室）；Astronomy & Astrophysics Section, School of Cosmic Physics, Dublin Institute for Advanced Studies, DIAS Dunsink Observatory（都柏林高等研究院宇宙物理学校天文学与天体物理学系邓辛克天文台）；Solar-Terrestrial Centre of Excellence (SIDC), Royal Observatory of Belgium（比利时皇家观测站太阳-地球卓越中心）；University College London, Mullard Space Science Laboratory（伦敦大学学院穆拉德空间科学实验室）
