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Register a new userFirst Observations of Solar Disk Gamma Rays over a Full Solar Cycle
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The solar disk is among the brightest gamma-ray sources in the sky. It is also among the most mysterious. No existing model fully explains the luminosity, spectrum, time variability, and morphology of its emission. We perform the first analysis of solar-disk gamma rays over a full 11-year solar cycle, utilizing a powerful new method to differentiate solar signals from astrophysical backgrounds. We produce: (i) a robustly measured spectrum from 100 MeV to 100 GeV, reaching a precision of several percent in the 1-10 GeV range, (ii) new results on the anti-correlation between solar activity and gamma-ray emission, (iii) strong constraints on short-timescale variability, ranging from hours to years, and (iv) new detections of the equatorial and polar morphologies of high-energy gamma rays. Intriguingly, we find no significant energy dependence in the time variability of solar-disk emission, indicating that strong magnetic-field effects close to the solar surface, rather than modulation throughout the heliosphere, must primarily control the flux and morphology of solar-disk emission.
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The observed multi-GeV gamma-ray emission from the solar disk --- sourced by hadronic cosmic rays interacting with gas, and affected by complex magnetic fields --- is not understood. Utilizing an improved analysis of the Fermi-LAT data that includes the first resolved imaging of the disk, we find strong evidence that this emission is produced by two separate mechanisms. Between 2010-2017 (the rise to and fall from solar maximum), the gamma-ray emission is dominated by a polar component. Between 2008-2009 (solar minimum) this component remains present, but the total emission is instead dominated by a new equatorial component with a brighter flux and harder spectrum. Most strikingly, although 6 gamma rays above 100 GeV are observed during the 1.4 years of solar minimum, none are observed during the next 7.8 years. These features, along with a 30-50 GeV spectral dip which will be discussed in a companion paper, were not anticipated by theory. To understand the underlying physics, Fermi and HAWC observations of the imminent Cycle 25 solar minimum are crucial.
The solar disk is a bright source of multi-GeV gamma rays, due to the interactions of hadronic cosmic rays with the solar atmosphere. However, the underlying production mechanism is not understood, except that its efficiency must be greatly enhanced by magnetic fields that redirect some cosmic rays from ingoing to outgoing before they interact. To elucidate the nature of this emission, we perform a new analysis of solar atmospheric gamma rays with 9 years of Fermi-LAT data, which spans nearly the full 11-year solar cycle. We detect significant gamma-ray emission from the solar disk from 1 GeV up to $gtrsim200$ GeV. The overall gamma-ray spectrum is much harder ($sim E_{gamma}^{-2.2}$) than the cosmic-ray spectrum ($sim E_{rm CR}^{-2.7}$). We find a clear anticorrelation between the solar cycle phase and the gamma-ray flux between 1-10 GeV. Surprisingly, we observe a spectral dip between $sim$30-50 GeV in an otherwise power-law spectrum. This was not predicted, is not understood, and may provide crucial clues to the gamma-ray emission mechanism. The flux above 100 GeV, which is brightest during the solar minimum, poses exciting opportunities for HAWC, LHAASO, IceCube, and KM3NeT.
The photospheric spatial distribution of the main magnetic polarities of bipolar active regions (ARs) presents during their emergence deformations are known as magnetic tongues. They are attributed to the presence of twist in the toroidal magnetic flux-tubes that form the ARs. The aim of this article is to study the twist of newly emerged ARs from the evolution of magnetic tongues observed in photospheric line-of-sight magnetograms. We apply the procedure described by Poisson et al. (2015, Solar Phys. 290, 727) to ARs observed over the full Solar Cycle 23 and the beginning of Cycle 24. Our results show that the hemispherical rule obtained using the tongues as a proxy of the twist has a weak sign-dominance (53 % in the southern hemisphere and 58 % in the northern hemisphere). By defining the variation of the tongue angle, we characterize the strength of the magnetic tongues during different phases of the AR emergence. We find that there is a tendency of the tongues to be stronger during the beginning of the emergence and to become weaker as the AR reaches its maximum magnetic flux. We compare this evolution with the emergence of a toroidal flux-rope model with non-uniform twist. The variety of evolution of the tongues in the analyzed ARs can only be reproduced when using a broad range of twist profiles, in particular having a large variety of twist gradient in the direction vertical to the photosphere. Although the analytical model used is a special case, selected to minimize the complexity of the problem, the results obtained set new observational constraints to theoretical models of flux-rope emergence that form bipolar ARs.
We investigate the spatial correlation properties of the solar wind using simultaneous observations by the ACE and WIND spacecraft. We use mutual information as a nonlinear measure of correlation and compare this to linear correlation. We find that the correlation lengthscales of fluctuations in density and magnetic field magnitude vary strongly with the solar cycle, whereas correlation lengths of fluctuations in B field components do not. We find the correlation length of |B| ~ 120 Re at solar minimum and ~ 270 Re at maximum and the correlation length of density ~ 75 Re at minimum and ~ 170 Re at minimum. The components of the B field have correlation lengths ~ correlation length |B| at minimum.
In order to assure a stable series of recorded images of sufficient quality for further scientific analysis, an objective image quality measure is required. Especially when dealing with ground-based observations, which are subject to varying seeing conditions and clouds, the quality assessment has to take multiple effects into account and provide information about the affected regions. In this study, we develop a deep learning method that is suited to identify anomalies and provide an image quality assessment of solar full-disk H$alpha$ filtergrams. The approach is based on the structural appearance and the true image distribution of high-quality observations. We employ a neural network with an encoder-decoder architecture to perform an identity transformation of selected high-quality observations. The encoder network is used to achieve a compressed representation of the input data, which is reconstructed to the original by the decoder. We use adversarial training to recover truncated information based on the high-quality image distribution. When images with reduced quality are transformed, the reconstruction of unknown features (e.g., clouds, contrails, partial occultation) shows deviations from the original. This difference is used to quantify the quality of the observations and to identify the affected regions. We apply our method to full-disk H$alpha$ filtergrams from Kanzelhohe Observatory recorded during 2012-2019 and demonstrate its capability to perform a reliable image quality assessment for various atmospheric conditions and instrumental effects, without the requirement of reference observations. Our quality metric achieves an accuracy of 98.5% in distinguishing observations with quality-degrading effects from clear observations and provides a continuous quality measure which is in good agreement with the human perception.
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