在5D色彩空间中说明几何代数和微分几何

W. Benger
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引用次数: 0

摘要

几何代数(GA)因其对代数对象和运算的直接几何解释而广受欢迎。它基于向量空间上的Clifford代数,并通过可逆积(即除以向量)等运算扩展了向量的线性代数。这种形式允许向量上的完全代数与标量或复数上的完全代数相同。它特别适用于任意维度的旋转。在欧几里得三维空间中,四元数在数值上优于旋转矩阵,并已广泛应用于计算机图形学。然而,它们在数字形式之外的意义往往仍然是神秘的。遗传算法允许根据旋转平面进行直观的解释,并通过将向量嵌入到更高维度,但仍然直观地可掌握的多向量空间,将此概念扩展到任意维度。然而,我们对超过三个空间维度的直觉是不足的。色彩空间也形成了一个矢量空间,虽然是非空间性质的,但由原色红、绿、蓝旋转而成。GA的形式也可以应用于此,令人惊讶的是,它与微分几何中已知的向量和协向量的概念相结合:流形上的切向量对应于加性的红色/绿色/蓝色,而共切空间中的协向量对应于减法的原色品红色、黄色、青色。遗传算法将向量、双向量和反向量作为其广义多向量代数对象群的一部分。在三维空间矢量中,反矢量、双矢量和共矢量都是可以相互识别的三维物体,因此它们之间的区别是隐藏的。混淆产生于诸如“法向量”和“轴向量”之类的概念。高维空间更清楚地显示出这种差异。使用颜色而不是空间维度,我们可以通过将“透明度”视为颜色向量的一个独立的四维属性来扩展我们的直觉。因此,我们可以在狭义/广义相对论中探索4D GA或时空。然而,即使在四维空间中,矢量、共矢量、双矢量和双共矢量之间也可能存在令人困惑的歧义:双矢量和双共矢量——都是六维物体——在视觉上是等同的。它们只有在五维或更高的维度上才变得明确。设想五维几何图形对人类的思维来说更具挑战性,但在色彩空间中,我们可以添加另一种属性“纹理”来构成五维向量空间。双矢量和双共矢量的特性在这里变得很明显:我们仍然可以在视觉上研究所有可能的颜色/透明度/纹理组合。这种高维但直观的方法证明了在特殊情况下识别不同类型的向量之前需要区分它们,这也澄清了三维欧几里得空间中代数对象的含义,并允许在三维中更好地制定算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Illustrating Geometric Algebra and Differential Geometry in 5D Color Space
Geometric Algebra (GA) is popular for its immediate geometric interpretations of algebraic objects and operations. It is based on Clifford Algebra on vector spaces and extends linear algebra of vectors by operations such as an invertible product, i.e. divisions by vectors. This formalism allows for a complete algebra on vectors same as for scalar or complex numbers. It is particularly suitable for rotations in arbitrary dimensions. In Euclidean 3D space quaternions are known to be numerically superior to rotation matrices and already widely used in computer graphics. However, their meaning beyond its numerical formalism often remains mysterious. GA allows for an intuitive interpretation in terms of planes of rotations and extends this concept to arbitrary dimensions by embedding vectors into a higher dimensional, but still intuitively graspable space of multi-vectors. However, out intuition of more than three spatial dimensions is deficient. The space of colors forms a vector space as well, though one of non-spatial nature, but spun by the primary colors red, green, blue. The GA formalism can be applied here as well, amalgamating surprisingly with the notion of vectors and co-vectors known from differential geometry: tangential vectors on a manifold correspond to additive colors red/green/blue, whereas co-vectors from the co-tangential space correspond to subtractive primary colors magenta, yellow, cyan. GA in turn considers vectors, bi-vectors and anti-vectors as part of its generalized multi-vector zoo of algebraic objects. In 3D space vectors, anti-vectors, bi-vectors and covectors are all three-dimensional objects that can be identified with each other, so their distinction is concealed. Confusions arise from notions such as “normal vectors” vs. “axial vectors”. Higher dimensional spaces exhibit the differences more clearly. Using colors instead of spatial dimensions we can expand our intuition by considering "transparency" as an independent, four-dimensional property of a color vector. We can thereby explore 4D GA alternatively to spacetime in special/general relativity. However, even in 4D possibly confusing ambiguities remain between vectors, co-vectors, bi-vectors and bi-co-vectors: bi-vectors and bi-co-vectors - both six-dimensional objects - are visually equivalent. They become unequivocal only in five or higher dimensions. Envisioning five-dimensional geometry is even more challenging to the human mind, but in color space we can add another property, "texture" to constitute a five-dimensional vector space. The properties of a bi-vector and a bi-co-vector becomes evident there: We can still study all possible combinations of colors/transparency/texture visually. This higher-dimensional yet intuitive approach demonstrates the need to distinguish among different kinds of vectors before identifying them in special situations, which also clarifies the meanings of algebraic objects in 3D Euclidean space and allows for better formulations of algorithms in 3D.
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