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Topological methods can provide a way of proposing new metrics and methods of scrutinising data, that otherwise may be overlooked. In this work, a method of quantifying the shape of data, via a topic called topological data analysis will be…

Machine Learning · Statistics 2022-09-25 Tristan Gowdridge , Nikolaos Dervilis , Keith Worden

While sunspots are easily observed at the solar surface, determining their subsurface structure is not trivial. There are two main hypotheses for the subsurface structure of sunspots: the monolithic model and the cluster model. Local…

The machine learning technique of persistent homology classifies complex systems or datasets by computing their topological features over a range of characteristic scales. There is growing interest in applying persistent homology to…

Optics · Physics 2021-03-03 Daniel Leykam , Dimitris G Angelakis

Topological data analysis (TDA) is a rapidly developing collection of methods for studying the shape of point cloud and other data types. One popular approach, designed to be robust to noise and outliers, is to first use a smoothing…

Methodology · Statistics 2017-12-27 Chul Moon , Noah Giansiracusa , Nicole A. Lazar

We studied the solar surface flows (differential rotation and meridional circulation) using a magnetic element feature tracking technique by which the surface velocity is obtained using magnetic field data. We used the line-of-sight…

Solar and Stellar Astrophysics · Physics 2018-09-05 Shinsuke Imada , Masashi Fujiyama

In topological data analysis, persistent homology is used to study the "shape of data". Persistent homology computations are completely characterized by a set of intervals called a bar code. It is often said that the long intervals…

Computational Geometry · Computer Science 2025-02-19 Peter Bubenik , Michael Hull , Dhruv Patel , Benjamin Whittle

The aim of this article is to describe a new perspective on functoriality of persistent homology and explain its intrinsic symmetry that is often overlooked. A data set for us is a finite collection of functions, called measurements, with a…

Algebraic Topology · Mathematics 2020-05-26 Wojciech Chacholski , Alessandro De Gregorio , Nicola Quercioli , Francesca Tombari

Persistent homology is a widely used tool in Topological Data Analysis that encodes multiscale topological information as a multi-set of points in the plane called a persistence diagram. It is difficult to apply statistical theory directly…

Statistics Theory · Mathematics 2013-12-03 Frédéric Chazal , Brittany Terese Fasy , Fabrizio Lecci , Alessandro Rinaldo , Larry Wasserman

The use of acoustic holography in the high-frequency $p$-mode spectrum can resolve the source distributions of enhanced acoustic emissions within halo structures surrounding active regions. In doing so, statistical methods can then be…

Solar and Stellar Astrophysics · Physics 2015-08-06 Chris S. Hanson , Alina C. Donea , K. D. Leka

Persistent homology is a method for probing topological properties of point clouds and functions. The method involves tracking the birth and death of topological features (2000) as one varies a tuning parameter. Features with short…

Long-lived rotational and meridional flows are important ingredients of the solar cycle. Magnetic field images have typically been used to measure these flows on the solar surface by cross-correlating thin longitudinal strips or square…

Solar and Stellar Astrophysics · Physics 2017-02-15 Derek A. Lamb

Helioseismology, the study of global solar oscillations, has proved to be an extremely powerful tool for the investigation of the internal structure and dynamics of the Sun. Studies of time changes in frequency observations of solar…

Solar and Stellar Astrophysics · Physics 2023-03-15 M. P. Di Mauro

Recent observations from Parker Solar Probe have revealed that the solar wind has a highly variable structure. How this complex behaviour is formed in the solar corona is not yet known, since it requires omnipresent fluctuations, which…

Supergranules in the quiet Sun are outlined by a web-like structure of enhanced magnetic field strength, the so-called magnetic network. We aim to map the magnetic network field around the average supergranule near disk center. We use…

Solar and Stellar Astrophysics · Physics 2015-07-08 J. Langfellner , L. Gizon , A. C. Birch

Aims: The interactions of velocity scales on the Sun's surface, from granulation to supergranulation are still not understood, nor are their interaction with magnetic fields. We thus aim at giving a better description of dynamics in the…

Solar and Stellar Astrophysics · Physics 2009-02-16 T. Roudier , M. Rieutord , D. Brito , F. Rincon , J. M. Malherbe , N. Meunier , T. Berger , Z. Frank

We use the magnetic butterfly diagram to determine the speed of the magnetic flux transport on the solar surface towards the poles. The manifestation of the flux transport is clearly visible as elongated structures extended from the sunspot…

Astrophysics · Physics 2009-11-13 M. Svanda , A. G. Kosovichev , J. Zhao

Small bipolar magnetic features are observed to appear in the interior of individual granules in the quiet Sun, signaling the emergence of tiny magnetic loops from the solar interior. We study the origin of those features as part of the…

Solar and Stellar Astrophysics · Physics 2018-06-05 F. Moreno-Insertis , J. Martinez-Sykora , V. H. Hansteen , D. Muñoz

A key question in understanding the observed magnetic field topologies of cool stars is the link between the small- and the large-scale magnetic field and the influence of the stellar parameters on the magnetic field topology. We examine…

Solar and Stellar Astrophysics · Physics 2018-05-23 L. T. Lehmann , M. M. Jardine , D. H. Mackay , A. A. Vidotto

The solar cycle is a complex phenomenon, a comprehensive understanding of which requires the study of various tracers. Here, we consider the solar cycle as manifested in the harmonics of the solar large-scale surface magnetic field,…

Solar and Stellar Astrophysics · Physics 2024-03-12 V. N. Obridko , A. S. Shibalova , D. D. Sokoloff

Persistent homology is a topological feature used in a variety of applications such as generating features for data analysis and penalizing optimization problems. We develop an approach to accelerate persistent homology computations…

Algebraic Topology · Mathematics 2023-01-19 Yuan Luo , Bradley J. Nelson