Related papers: Image patch analysis of sunspots and active region…

Classical approaches in cluster analysis are typically based on a feature space analysis. However, many applications lead to datasets with additional spatial information and a ground truth with spatially coherent classes, which will not…

The sunspots and other solar activity indicators tend to cluster on the surface of the Sun.These clusters very often occur at certain longitudes that persist in time.It is of general interest to find new and simple ways to characterize the…

We present an automated system for detecting, tracking, and cataloging emerging active regions throughout their evolution and decay using SOHO Michelson Doppler Interferometer (MDI) magnetograms. The SolarMonitor Active Region Tracking…

In several environmental applications data are functions of time, essentially con- tinuous, observed and recorded discretely, and spatially correlated. Most of the methods for analyzing such data are extensions of spatial statistical tools…

Magneto-static models may overcome some of the issues facing force-free magnetic field extrapolations. So far they have seen limited use and have faced problems when applied to quiet-Sun data. Here we present a first application to an…

Mapping of spatial hotspots, i.e., regions with significantly higher rates of generating cases of certain events (e.g., disease or crime cases), is an important task in diverse societal domains, including public health, public safety,…

The clustering of a data set is one of the core tasks in data analytics. Many clustering algorithms exhibit a strong contrast between a favorable performance in practice and bad theoretical worst-cases. Prime examples are least-squares…

Recently, there has been growing interest in the use of machine-learning methods for predicting solar flares. Initial efforts along these lines employed comparatively simple models, correlating features extracted from observations of…

One of the main goals of solar physics is the timely identification of eruptive active regions. Space missions such as Solar Orbiter or future Space Weather forecasting missions would largely benefit from this achievement. Our aim is to…

Using an efficient magnetic complexity index in the active-region solar photosphere, we quantify the preflare strength of the photospheric magnetic polarity inversion lines in 23 eruptive active regions with flare/CME/ICME events tracked…

Bayesian model-based clustering is a widely applied procedure for discovering groups of related observations in a dataset. These approaches use Bayesian mixture models, estimated with MCMC, which provide posterior samples of the model…

Nonnegative matrix factorization (NMF) is widely used for clustering with strong interpretability. Among general NMF problems, symmetric NMF is a special one that plays an important role in graph clustering where each element measures the…

We present an explanation for the well-known observation that complexity of the solar magnetic field is a necessary ingredient for strong activity such as large eruptive flares. Our model starts with the standard picture for the energy…

To create early warning capabilities for upcoming Space Weather disturbances, we have selected a dataset of 61 emerging active regions, which allows us to identify characteristic features in the evolution of acoustic power density to…

The purpose of this letter is to address a blind-spot in our knowledge of solar active region statistics. To the best of our knowledge there are no published results showing the variation of the Mount Wilson magnetic classifications as a…

After a brief introduction to the problem of subtraction of infrared divergences for high-order collider observables, we present a preliminary study of strongly-ordered soft and collinear multiple radiation from the point of view of…

In cluster analysis, a common first step is to scale the data aiming to better partition them into clusters. Even though many different techniques have throughout many years been introduced to this end, it is probably fair to say that the…

The topic of wind-clumping has been the subject of much activity in recent years, due to the impact that it can have on derived mass-loss rates. Here we present an alternative method of investigating wind-clumping, that of polarimetry. We…

Manifold regularization methods for matrix factorization rely on the cluster assumption, whereby the neighborhood structure of data in the input space is preserved in the factorization space. We argue that using the k-neighborhoods of all…

Since the Solar Dynamics Observatory (SDO) began recording ~ 1 TB of data per day, there has been an increased need to automatically extract features and events for further analysis. Here we compare the overall detection performance,…