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Entropy
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Advanced Signal Processing in Heliospheric Physics
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Advanced Signal Processing in Heliospheric Physics

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Astrophysics, Cosmology, and Black Holes".

Deadline for manuscript submissions: closed (31 July 2013) | Viewed by 21334

Special Issue Editor

Dr. Jack Ireland

E-Mail
Guest Editor
L-3 Communications GSI, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Interests: coronal seismology; coronal and chromospheric structure and heating

Special Issue Information

Dear Colleagues,

Heliospheric physics is the study of the phenomena of the Earth-Sun system. We seek to understand how solar phenomena are created, how energy is transported from the solar surface through interplanetary space, and how that energy interacts with terrestrial systems, both natural, technological and societal. This requires the study of the many complex, and often interconnected nonlinear phenomena at many different time and length scales. Further, the amount of data available, as well as the variety of data sources (space-based, ground-based) are larger than ever before, making it possible to combine physical modelling with statistical signal processing in order to advance our understanding of heliospheric physics.

We seek papers that address the challenges of how to make best use of physical and statistical modelling in order to extract as much information as possible out of the heterogeneous data available. Topics of interest include, but are not limited to:

  • solar atmosphere plasma turbulence
  • intermittency, multifractality
  • segmentation of solar features, exploitation of catalogs
  • prediction of solar transients (flares, coronal mass ejections), and their propagation through the heliosphere
  • DEM analysis, study of thermal structure, source separation
  • long-term statistical analysis (solar cycle studies).
  • time-frequency and time-scale analysis (oscillations, feature extraction)
  • multidimensional image reconstruction
  • dimensionality reduction
  • content-based image retrieval

Dr. Jack Ireland
Guest editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


Keywords

  • information theory
  • entropy
  • machine learning
  • Bayesian
  • frequentist data analysis
  • computer vision
  • solar wind
  • solar atmosphere
  • magnetic field
  • solar transients

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Published Papers (3 papers)

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4517 KiB  
Article
Signal Processing for the Measurement of the Deuterium/Hydrogen Ratio in the Local Interstellar Medium
by Diego Francisco Rodríguez Moreno, Peter Wurz, Lukas Saul, Maciej Bzowski, Marzena Aleksanda Kubiak, Justyna Maria Sokół, Priscilla Frisch, Stephen Anthony Fuselier, David John McComas, Eberhard Möbius and Nathan Schwadron
Entropy 2014, 16(2), 1134-1168; https://doi.org/10.3390/e16021134 - 24 Feb 2014
Cited by 14 | Viewed by 7435
Abstract
We report on a comprehensive signal processing procedure for very low signal levels for the measurement of neutral deuterium in the local interstellar medium from a spacecraft in Earth orbit. The deuterium measurements were performed with the IBEX-Lo camera on NASA’s Interstellar Boundary [...] Read more.
We report on a comprehensive signal processing procedure for very low signal levels for the measurement of neutral deuterium in the local interstellar medium from a spacecraft in Earth orbit. The deuterium measurements were performed with the IBEX-Lo camera on NASA’s Interstellar Boundary Explorer (IBEX) satellite. Our analysis technique for these data consists of creating a mass relation in three-dimensional time of flight space to accurately determine the position of the predicted D events, to precisely model the tail of the H events in the region where the H tail events are near the expected D events, and then to separate the H tail from the observations to extract the very faint D signal. This interstellar D signal, which is expected to be a few counts per year, is extracted from a strong terrestrial background signal, consisting of sputter products from the sensor’s conversion surface. As reference we accurately measure the terrestrial D/H ratio in these sputtered products and then discriminate this terrestrial background source. During the three years of the mission time when the deuterium signal was visible to IBEX, the observation geometry and orbit allowed for a total observation time of 115.3 days. Because of the spinning of the spacecraft and the stepping through eight energy channels the actual observing time of the interstellar wind was only 1.44 days. With the optimised data analysis we found three counts that could be attributed to interstellar deuterium. These results update our earlier work. Full article
(This article belongs to the Special Issue Advanced Signal Processing in Heliospheric Physics)
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7780 KiB  
Article
3D Reconstruction of Coronal Loops by the Principal Component Analysis
by Giuseppe Nisticò, Erwin Verwichte and Valery M. Nakariakov
Entropy 2013, 15(10), 4520-4539; https://doi.org/10.3390/e15104520 - 22 Oct 2013
Cited by 9 | Viewed by 6687
Abstract
Knowing the three dimensional structure of plasma filaments in the uppermost part of the solar atmosphere, known as coronal loops, and especially their length, is an important parameter in the wave-based diagnostics of this part of the Sun. The combination of observations of [...] Read more.
Knowing the three dimensional structure of plasma filaments in the uppermost part of the solar atmosphere, known as coronal loops, and especially their length, is an important parameter in the wave-based diagnostics of this part of the Sun. The combination of observations of the Sun from different points of observations in space, thanks to the most recent missions, including the Solar Dynamics Observatory (SDO) and the Solar TErrestrial RElations Observatory (STEREO), allows us to infer information about the geometrical shape of coronal loops in 3D space. Here, we propose a new method to reconstruct the loop shape starting from stereoscopically determined 3D points, which sample the loop length, by principal component analysis. This method is shown to retrieve in an easy way the main parameters that define the loop, e.g., the minor and major axes, the loop plane, the azimuthal and inclination angles, for the special case of a coplanar loop. Full article
(This article belongs to the Special Issue Advanced Signal Processing in Heliospheric Physics)
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11053 KiB  
Article
Optimization of Curvilinear Tracing Applied to Solar Physics and Biophysics
by Markus J. Aschwanden, Bart De Pontieu and Eugene A. Katrukha
Entropy 2013, 15(8), 3007-3030; https://doi.org/10.3390/e15083007 - 26 Jul 2013
Cited by 28 | Viewed by 6656
Abstract
We developed an automated pattern recognition code that is particularly well suited to extract one-dimensional curvilinear features from two-dimensional digital images. A former version of this Oriented Coronal Curved Loop Tracing (OCCULT) code was applied to spacecraft images of magnetic loops in the [...] Read more.
We developed an automated pattern recognition code that is particularly well suited to extract one-dimensional curvilinear features from two-dimensional digital images. A former version of this Oriented Coronal Curved Loop Tracing (OCCULT) code was applied to spacecraft images of magnetic loops in the solar corona, recorded with the NASA spacecraft, Transition Region And Coronal Explorer (TRACE), in extreme ultra-violet wavelengths. Here, we apply an advanced version of this code (OCCULT-2), also, to similar images from the Solar Dynamics Observatory (SDO), to chromospheric H-α images obtained with the Swedish Solar Telescope (SST) and to microscopy images of microtubule filaments in live cells in biophysics. We provide a full analytical description of the code, optimize the control parameters and compare the automated tracing with visual/manual methods. The traced structures differ by up to 16 orders of magnitude in size, which demonstrates the universality of the tracing algorithm. Full article
(This article belongs to the Special Issue Advanced Signal Processing in Heliospheric Physics)
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