Communication
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Dual-Quaternion Julia Fractals
Version 1
: Received: 11 April 2023 / Approved: 12 April 2023 / Online: 12 April 2023 (06:04:14 CEST)
How to cite: Kenwright, B. Dual-Quaternion Julia Fractals. Preprints 2023, 2023040246. https://doi.org/10.20944/preprints202304.0246.v1 Kenwright, B. Dual-Quaternion Julia Fractals. Preprints 2023, 2023040246. https://doi.org/10.20944/preprints202304.0246.v1
Abstract
Fractals offer the ability to generate fascinating geometric shapes with all sorts of unique characteristics (for instance, fractal geometry provides a basis for modelling infinite detail found in nature). While fractals are non-euclidean mathematical objects which possess an assortment of properties (e.g., attractivity and symmetry), they are also able to be scaled down, rotated, skewed and replicated in embedded contexts. Hence, many different types of fractals have come into limelight since their origin discovery. One particularly popular method for generating fractal geometry is using Julia sets. Julia sets provide a straightforward and innovative method for generating fractal geometry using an iterative computational modelling algorithm. In this paper, we present a method that combines Julia sets with dual-quaternion algebra. Dual-quaternions are an alluring principal with a whole range interesting mathematical possibilities. Extending fractal Julia sets to encompass dual-quaternions algebra provides us with a novel visualize solution. We explain the method of fractals using the dual-quaternions in combination with Julia sets. Our prototype implementation demonstrate an efficient methods for rendering fractal geometry using dual-quaternion Julia sets based upon an uncomplicated ray tracing algorithm. We show a number of different experimental isosurface examples to demonstrate the viability of our approach.
Keywords
graphics; dual-quaternion; visualization; fractals; geometry; graphical processing unit
Subject
Computer Science and Mathematics, Computer Vision and Graphics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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