Related papers: Preprocess the Photospheric Vector Magnetograms fo…
The finite-element analysis of three-dimensional magnetostatic problems in terms of magnetic vector potential has proven to be one of the most efficient tools capable of providing the excellent quality results but becoming computationally…
Nonnegative matrix factorization (NMF) has become a very popular technique in machine learning because it automatically extracts meaningful features through a sparse and part-based representation. However, NMF has the drawback of being…
We investigate the recently quantified misalignment of $\alpha_{mis} \approx 20^\circ-40^\circ$ between the 3-D geometry of stereoscopically triangulated coronal loops observed with STEREO/EUVI (in four active regions) and theoretical…
Nonnegative Matrix Factorization (NMF) is an important unsupervised learning method to extract meaningful features from data. To address the NMF problem within a polynomial time framework, researchers have introduced a separability…
The multislice method, which simulates the propagation of the incident electron wavefunction through a crystal, is a well-established method for analyzing the multiple scattering effects that an electron beam may undergo. The inclusion of…
Photon loss rates set an effective upper limit on the size of computations that can be run on current linear optical quantum devices. We present a family of techniques designed to mitigate the effects of photon loss on both output…
We consider a set of M images, whose pixel intensities at a common point can be treated as the components of a M-dimensional vector. We are interested in the estimation of the modulus of such a vector associated to a compact source. For…
In this paper, a potential field extrapolation and three nonlinear force-free (NLFF) field extrapolations (optimization, direct boundary integral (DBIE) and approximate vertical integration (AVI) methods) are used to study the spatial…
We introduce NPEFF (Non-Negative Per-Example Fisher Factorization), an interpretability method that aims to uncover strategies used by a model to generate its predictions. NPEFF decomposes per-example Fisher matrices using a novel…
The realization of optical non-reciprocity is crucial for many device applications, and also of fundamental importance for manipulating and protecting the photons with desired time-reversal symmetry. Recently, various new mechanisms of…
Preconditioning is a key component of MCMC algorithms that improves sampling efficiency by facilitating exploration of geometrically complex target distributions through an invertible map. While linear preconditioners are often sufficient…
The solar active region (AR) 12192 was one of the most flare productive region of solar cycle 24, which produced many X-class flares; the most energetic being an X3.1 flare on October 24, 2014 at 21:10 UT. Customarily, such events are…
The coronal magnetic field plays a fundamental role in governing coronal activities, driving space-weather events, and shaping the heliosphere. Due to a lack of direct observations, extrapolation models such as the Potential Field Source…
We present a Python code for calculating and displaying magnetic field extrapolations from given two-dimensional boundary conditions, specifically from solar surface magnetograms. The code implements analytical magnetohydrostatic models…
Photospheric magnetic vector maps from two different instruments are used to model the nonlinear force-free coronal magnetic field above an active region. We use vector maps inferred from polarization measurements of the Solar Dynamics…
Force-free extrapolations are widely used to study the magnetic field in the solar corona based on surface measurements. The extrapolations assume that the ratio of internal energy of the plasma to magnetic energy, the plasma-beta is…
Photospheric electric fields, estimated from sequences of vector magnetic field and Doppler measurements, can be used to estimate the flux of magnetic energy (the Poynting flux) into the corona and as time-dependent boundary conditions for…
The signal resulting from magnetic resonance spectroscopy is occupied by noises and irregularities so in the further analysis preprocessing techniques have to be introduced. The main idea of the paper is to develop a model of a signal as a…
Nonnegative matrix factorization (NMF) is a linear dimensionality reduction technique for nonnegative data, with applications such as hyperspectral unmixing and topic modeling. NMF is a difficult problem in general (NP-hard), and its…
In micromagnetic simulations, the demagnetization field is by far the computationally most expensive field component and often a limiting factor in large multilayer systems. We present an exact method to calculate the demagnetization field…