Related papers: Helioseismic finite-frequency sensitivity kernels …
Both muon tomography and gravimetry are geophysical methods that provide information on the density structure of the Earth's subsurface. Muon tomography measures the natural flux of cosmic muons and its attenuation produced by the screening…
Plasma turbulence involves complex, nonlinear interactions of electromagnetic fields and charged particles across multiple scales. Studying these phenomena in space plasmas, like the solar wind, is facilitated by the intrinsic scale…
We propose a spherical kernel for efficient graph convolution of 3D point clouds. Our metric-based kernels systematically quantize the local 3D space to identify distinctive geometric relationships in the data. Similar to the regular grid…
Context. The details of the spectral profiles of extreme UV emission lines from solar active regions contain key information to investigate the structure, dynamics, and energetics of the solar upper atmosphere. Aims. We characterize the…
Solar oscillations consist of a rich spectrum of internal acoustic waves and surface gravity waves, stochastically excited by turbulent convection. They have been monitored almost continuously over the last ten years with high-precision…
Modeling geophysical processes as low-dimensional dynamical systems and regressing their vector field from data is a promising approach for learning emulators of such systems. We show that when the kernel of these emulators is also learned…
We analyze a solar active region observed by the Hinode CaII H line using the time-distance helioseismology technique, and infer wave-speed perturbation structures and flow fields beneath the active region with a high spatial resolution.…
The solar corona and young solar wind may be characterized by critical surfaces -- the sonic, Alfv\'en, and first plasma-$\beta$ unity surfaces -- that demarcate regions where the solar wind flow undergoes certain crucial transformations.…
We derive formulae connecting the frequency variations in the spectrum of solar oscillations to the dynamical quantities that are expected to change over the solar activity cycle. This is done for both centroids and the asymmetric part of…
We introduce a new method for the investigation of low-amplitude transverse oscillations of solar plasma non-uniformities, such as coronal loops, individual strands in coronal arcades, jets, prominence fibrils, polar plumes, and other…
Recently, we have developed a method useful for mapping large-scale horizontal velocity fields in the solar photosphere. The method was developed, tuned and calibrated using the synthetic data. Now, we applied the method to the series of…
Precise numerical standard solar models (SSMs) now agree with one another and with helioseismological observations in the convective and outer radiative zones. Nevertheless these models obscure how luminosity, neutrino production and g-mode…
Density-based clustering methodology has been widely considered in the statistical literature for classifying Euclidean observations. However, this approach has not been contemplated for directional data yet. In this work, directional…
The release of density structures at the tip of the coronal helmet streamers, likely as a consequence of magnetic reconnection, contributes to the mass flux of the slow solar wind. In situ measurements in the vicinity of the heliospheric…
Physical processes that manifest as tangential vector fields on a sphere are common in geophysical and environmental sciences. These naturally occurring vector fields are often subject to physical constraints, such as being curl-free or…
Estimates of the photospheric magnetic, electric and plasma velocity fields are essential for studying the dynamics of the solar atmosphere, for example through the derivative quantities of Poynting and relative helicity flux and by using…
Aims. We show how the build-up of magnetic gradients in the Sun's corona may be inferred directly from photospheric velocity data. This enables computation of magnetic connectivity measures such as the squashing factor without recourse to…
The ability to measure differences in collected data is of fundamental importance for quantitative science and machine learning, motivating the establishment of metrics grounded in physical principles. In this study, we focus on the…
The subsurface structure of an "average" supergranule is derived from existing HMI pipeline time-distance data products and compared to the best helioseismic flow model detailed in Duvall and Hanasoge (2013). We find that significant…
The uncertainty of the energy generated by photovoltaic systems incurs an additional cost for a guaranteed, reliable supply of energy (i.e., energy storage). This investigation aims to decrease the additional cost by introducing…