Signatures of Type III Solar Radio Bursts from Nanoflares: Modeling

Chhabra, Sherry; Klimchuk, J. A.; Gary, Dale E.

doi:10.3847/1538-4357/ac2364

Cited by 3 publications

(2 citation statements)

References 41 publications

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“…Reporting their discovery, Mondal et al (2020), henceforth referred to as M20, hypothesised that the detected impulsive emissions are weaker cousins of the type III and/or type I radio bursts (Reid & Ratcliffe 2014;Chhabra et al 2021) and are likely related to the nanoflares (Parker 1988). Like earlier works, the hypothesis is that the nanoflares would accelerate electrons to energies higher than the thermal background, which would then emit plasma emission through various waveparticle and wave-wave interactions (Aschwanden 2005).…”

Section: Introductionmentioning

confidence: 93%

Understanding the morphology of Weak Impulsive Narrowband Quiet Sun Emissions (WINQSEs)

Bawaji¹,

Alam²,

Mondal

et al. 2022

Preprint

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<p>The solar coronal heating problem has been around for several decades. While it has been well established that magnetic fields are responsible for transporting the energy from the photosphere to the corona, it has been a challenge to understand the details of the energy dissipation processes. One such process was proposed by Parker, who hypothesized that this dissipation occurs through small scale magnetic reconnections happening throughout the corona. While there are several indications that this mechanism may be active, till date direct observation of these small reconnections have not been possible. Hence searching for indirect signatures of these events is very important. One such probable signature was discovered by Mondal et al. (2020), where they demonstrated the presence of ubiquitous impulsive radio emissions in the solar corona during a very quiet time. These emissions are now named Weak Impulsive Narrowband Quiet Sun Emissions (WINQSEs). Due to the potential importance of this discovery and its implications, it is crucial that the detection techniques are improved and that we search for these transients in more datasets to confirm/reject their ubiquitous nature. In this work, we have developed a machine learning (ML) algorithm suitable for identifying and characterising the spatial distribution and morphology&#160; of WINQSEs. For morphological characterisation we use 2D Gaussians which are found to&#160; describe the brightness distribution of the majority of these transients very well. Since WINQSEs are expected to be the radio counterparts of the weak reconnections, we expected them to&#160; be essentially unresolved at an angular resolution of 3.5 arcminutes. We find, however, that most of the WINQSEs are resolved by the instrument, though the distribution of their area is very steep. We hypothesise that while intrinsically unresolved, the area of WINQSEs becomes large due to coronal scattering effects. This then also presents the exciting possibility of using WINQSEs to regularly study the nature of scattering close to the Sun, which currently is only possible during solar radio bursts. Here we present a quick overview of our ML algorithm, along with a summary of our results about the morphological properties of WINQSEs, and explore the possibility of using them to study coronal scattering.&#160;</p>

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Section: Introductionmentioning

confidence: 93%

Understanding the morphology of Weak Impulsive Narrowband Quiet Sun Emissions (WINQSEs)

Bawaji¹,

Alam²,

Mondal

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Reporting their discovery, Mondal et al (2020), henceforth referred to as M20, hypothesized that the detected impulsive emissions are weaker cousins of the type III and/or type I radio bursts (Reid & Ratcliffe 2014;Chhabra et al 2021) and are likely related to the nanoflares (Parker 1988). Like earlier works, the hypothesis is that the nanoflares would accelerate electrons to energies higher than the thermal background, which would then emit plasma emission through various waveparticle and wave-wave interactions (Aschwanden 2005).…”

Section: Introductionmentioning

confidence: 94%

An Unsupervised Machine Learning-based Algorithm for Detecting Weak Impulsive Narrowband Quiet Sun Emissions and Characterizing Their Morphology

Bawaji,

Alam,

Mondal

et al. 2023

ApJ

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The solar corona is extremely dynamic. Every leap in observational capabilities has been accompanied by unexpected revelations of complex dynamic processes. The ever more sensitive instruments now allow us to probe events with increasingly weaker energetics. A recent leap in the low-frequency radio solar imaging ability has led to the discovery of a new class of emissions, namely weak impulsive narrowband quiet Sun emissions (WINQSEs). They are hypothesized to be the radio signatures of coronal nanoflares and could potentially have a bearing on the long standing coronal heating problem. In view of the significance of this discovery, this work has been followed up by multiple independent studies. These include detecting WINQSEs in multiple data sets, using independent detection techniques and software pipelines, and looking for their counterparts at other wavelengths. This work focuses on investigating morphological properties of WINQSEs and also improves upon the methodology used for detecting WINQSEs in earlier works. We present a machine learning-based algorithm to detect WINQSEs, classify them based on their morphology, and model the isolated ones using 2D Gaussians. We subject multiple data sets to this algorithm to test its veracity. Interestingly, despite the expectations of their arising from intrinsically compact sources, WINQSEs tend to be resolved in our observations. We propose that this angular broadening arises due to coronal scattering. Hence, WINQSEs can provide ubiquitous and ever-present diagnostic of coronal scattering (and, in turn, coronal turbulence) in the quiet Sun regions, which has not been possible until date.

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Coronal diagnostics of solar type III radio bursts using LOFAR and PSP observations

Nedal,

Kozarev,

Zhang

et al. 2023

A&A

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Context. Solar type III radio bursts are common phenomena, recognized as the result of accelerated electron beams propagating through the solar corona. These bursts are of particular interest as they provide valuable information about the magnetic field and plasma conditions in the corona, which are difficult to measure directly. Aims. This study aims to investigate the ambiguous source and the underlying physical processes of the type III radio bursts that occurred on April 3, 2019, through the utilization of multi-wavelength observations from the Low-Frequency Array (LOFAR) radio telescope and the Parker Solar Probe (PSP) space mission, as well as incorporating results from a Potential Field Source Surface (PFSS) and magnetohydrodynamic (MHD) models. The primary goal is to identify the spatial and temporal characteristics of the radio sources, as well as the plasma conditions along their trajectories. Methods. We applied data preprocessing techniques to combine high- and low-frequency observations from LOFAR and PSP between 2.6 kHz and 80 MHz. We then extracted information on the frequency drift and speed of the accelerated electron beams from the dynamic spectra. Additionally, we used LOFAR interferometric observations to image the sources of the radio emission at multiple frequencies and determine their locations and kinematics in the corona. Lastly, we analyzed the plasma parameters and magnetic field along the trajectories of the radio sources using PFSS and MHD model results. Results. We present several notable findings related to type III radio bursts. Firstly, through our automated implementation, we were able to effectively identify and characterize 9 type III radio bursts in the LOFAR-PSP combined dynamic spectrum and 16 type III bursts in the LOFAR dynamic spectrum. We found that the frequency drift for the detected type III bursts in the combined spectrum ranges between 0.24 and 4 MHz s−1, while the speeds of the electron beams range between 0.013 and 0.12 C. Secondly, our imaging observations show that the electrons responsible for these bursts originate from the same source and within a short time frame of fewer than 30 min. Finally, our analysis provides informative insights into the physical conditions along the path of the electron beams. For instance, we found that the plasma density obtained from the magnetohydrodynamic algorithm outside a sphere (MAS) model is significantly lower than the expected theoretical density.

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Signatures of Type III Solar Radio Bursts from Nanoflares: Modeling

Cited by 3 publications

References 41 publications

Understanding the morphology of Weak Impulsive Narrowband Quiet Sun Emissions (WINQSEs)

Understanding the morphology of Weak Impulsive Narrowband Quiet Sun Emissions (WINQSEs)

An Unsupervised Machine Learning-based Algorithm for Detecting Weak Impulsive Narrowband Quiet Sun Emissions and Characterizing Their Morphology

Coronal diagnostics of solar type III radio bursts using LOFAR and PSP observations

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