Volume 616, August 2018
|Number of page(s)||8|
|Published online||27 August 2018|
Rotating network jets in the quiet Sun as observed by IRIS
Group of Astrophysics, University of Maria Curie-Skłodowska,
ul. Radziszewskiego 10,
2 Department of Physics, Indian Institute of Technology (Banaras Hindu University), Varanasi 22105, India
Accepted: 3 May 2018
Aims. We perform a detailed observational analysis of network jets to understand their kinematics, rotational motion, and underlying triggering mechanism(s). We analyzed the quiet-Sun (QS) data.
Methods. IRIS high-resolution imaging and spectral observations (slit-jaw images: Si IV 1400.0 Å; raster: Si IV 1393.75 Å) were used to analyze the omnipresent rotating network jets in the transition region (TR). In addition, we also used observations from the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamic Observation (SDO).
Results. The statistical analysis of 51 network jets is performed to understand their various mean properties, e.g., apparent speed (140.16 ± 39.41 km s−1), length (3.16 ± 1.18 Mm), and lifetimes (105.49 ± 51.75 s). The Si IV 1393.75 Å line has a secondary component along with its main Gaussian, which is formed due to the high-speed plasma flows (i.e., network jets). The variation in Doppler velocity across these jets (i.e., blueshift on one edge and redshift on the other) signify the presence of inherited rotational motion. The statistical analysis predicts that the mean rotational velocity (i.e., ΔV) is 49.56 km s−1. The network jets have high-angular velocity in comparison to the other class of solar jets.
Conclusions. The signature of network jets is inherited in TR spectral lines in terms of the secondary component of the Si IV 1393.75 Å line. The rotational motion of network jets is omnipresent, which is reported first for this class of jet-like features. The magnetic reconnection seems to be the most favorable mechanism for the formation of these network jets.
Key words: Sun: activity / Sun: corona / Sun: transition region / magnetohydrodynamics (MHD) / methods: numerical
© ESO 2018
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