Tracking the Temporal-Evolution of Supernova Bubbles in Numerical Simulations

Marco Canducci*, Albolfazl Taghribi, Michele Mastropietro, Sven De Rijcke, Reynier Peletier, Kerstin Bunte, Peter Tino

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)
262 Downloads (Pure)

Abstract

The study of low-dimensional, noisy manifolds embedded in a higher dimensional space has been extremely useful in many applications, from the chemical analysis of multi-phase flows to simulations of galactic mergers. Building a probabilistic model of the manifolds has helped in describing their essential properties and how they vary in space. However, when the manifold is evolving through time, a joint spatio-temporal modelling is needed, in order to fully comprehend its nature. We propose a first-order Markovian process that propagates the spatial probabilistic model of a manifold at fixed time, to its adjacent temporal stages. The proposed methodology is demonstrated using a particle simulation of an interacting dwarf galaxy to describe the evolution of a cavity generated by a Supernova
Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning - IDEAL
EditorsH. Yin
Place of PublicationCham
PublisherSpringer International Publishing
Pages493-501
Number of pages8
ISBN (Electronic)978-3-030-91608-4
ISBN (Print)978-3-030-91607-7
DOIs
Publication statusPublished - Nov-2021
EventInternational Conference on Intelligent Data Engineering and Automated Learning: IDEAL 2021 - Manchester, United Kingdom
Duration: 25-Nov-202127-Nov-2021

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume13113
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Intelligent Data Engineering and Automated Learning
Country/TerritoryUnited Kingdom
City Manchester
Period25/11/202127/11/2021

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