Why are dimensions always at right angles?

  • Context: High School 
  • Thread starter Thread starter Sangam Swadik
  • Start date Start date
  • Tags Tags
    Angles Dimensions
Click For Summary

Discussion Overview

The discussion centers around the question of why dimensions are often represented at right angles, exploring the implications of this choice in various contexts, including mathematics and physics. Participants examine the nature of dimensions, coordinate systems, and the relevance of orthogonality in different frameworks.

Discussion Character

  • Debate/contested
  • Conceptual clarification
  • Mathematical reasoning

Main Points Raised

  • Some participants argue that dimensions are not inherently at right angles and can be represented in various ways, including skew and curvilinear coordinates.
  • Others suggest that right angles are chosen for convenience, simplifying calculations and avoiding complex trigonometric terms.
  • There is a contention regarding the terminology used, with some stating that "dimension" refers to a numerical measure rather than the coordinate axes themselves.
  • Some participants assert that in the context of the physical universe, dimensions are often treated as orthogonal, particularly in Euclidean spaces.
  • Others challenge the notion of dimensions being at right angles, emphasizing that measurements are human constructs and not inherent to the physical world.
  • In discussions about relativity, some participants mention that time is treated as a dimension that is orthogonal to spatial dimensions, referencing the Minkowski metric.
  • There are questions raised about the interpretation of angles in general relativity and the implications of the metric used.

Areas of Agreement / Disagreement

Participants express multiple competing views on the nature of dimensions and their representation. There is no consensus on whether dimensions must be at right angles, with some asserting that it is a convention while others maintain that it reflects a characteristic of the physical universe.

Contextual Notes

Some discussions highlight limitations in definitions and assumptions regarding dimensions and coordinate systems, particularly in the context of physics versus mathematics.

  • #31
WWGD said:
Yes, you can see it that way; this is the Riemannian metric tensor, a quadratic form , often represented as a matrix ##g(X_i, X_j)## where the {## X_i ##} is a basis for the tangent space. The Riemannian metric tensor associated with the standard Euclidean metric is, like you said, the identity. The Riemannian metric is an inner product, defined on tangent vectors at each point in a manifold.

I occurred to me after I wrote that post that by dx2, you meant the the square of the differential of x, not multiplication by the scalar, d. Is that correct? And so, as you imply, the vector of differentials, (dx,dy,dz) is a basis for the tangent space at (x,y,z)? Thanks for your help. I only know enough differential geometry to be dangerous, as they say...
 
Mathematics news on Phys.org
  • #32
Mark Harder said:
I occurred to me after I wrote that post that by dx2, you meant the the square of the differential of x, not multiplication by the scalar, d. Is that correct? And so, as you imply, the vector of differentials, (dx,dy,dz) is a basis for the tangent space at (x,y,z)? Thanks for your help. I only know enough differential geometry to be dangerous, as they say...

No problem, feel free to ask, I will do my best, and ask for clarification if needed.
Formally, ## dx^2 ## is ## dx\otimes dx ##, the tensor product of dx with itself. And dx,dy,dz are usually define as covectors, as a basis dual to the basis ## \partial/\partial x, \partial / \partial y, \partial /\partial z ## of basis tangent vector fields meaning ##dx( \partial /\partial x) =1 , dx (\partial /\partial y)=0 , i.e., dx_i (\partial / \partial_j):= \delta^i_j## , etc. This means that linear operators on tangent vectors are written as ## a(x,y,z)dx+b(x,y,z)dy+c(x,y,z)dz ## (notice that in the expression for your metric , you can have "mixed terms" ##dx \otimes dy ## , etc., but this is a somewhat-simplified version) , i.e., as linear combinations of these covector basis elements. dx, dy, dz are differential forms, i.e., linear maps defined on tangent vectors. This allows you to compute the length of curves.
Maybe more precisely, this metric or second fundamental form, and it allows you to find the length
of a parametrized curve under a given choice of metric. Here ## dx \otimes dx (v_1,v_2):=dx(v_1)dx(v_2) ## , meaning scalar multiplication, for vectors ## v_1, v_2 ##. This allows you to define forms on n-ples of vectors ( in this case, on pairs of vectors ), i.e., given linear maps ##dx, dy## defined on vectors ##v_1, v_2## , you can form a bilinear map ## dx \otimes dy ## defined on the ordered pair of vectors ## (v_1, v_2) ##, and so on, i.e., you can define k-linear maps on ordered k-ples of vectors. The collection of linear, bilinear,..k-linear maps defined on the exterior product of a vector space is called the exterior algebra of the exterior product. This can be defined on (the exterior product of) any vector space, not just the tangent space , exterior powers of the tangent space.

EDIT: the idea is that the fundamental form gives you a "local" version of length, so that, when integrated gives you the length of a curve, in the same sense that you define , when you do Riemann integration, a length element which you integrate to find the overall length of a curve.

EDIT 2: As you said, the metric is a quadratic form, defined on pairs of vector fields. In the differential
geometry version, a quadratic form is usually called a 2-form, which is a bilinear form ( meaning linear
separately in each variable ) defined on a pair of vector fields.

EDIT3: The post may have sprawled out of control, feel free to ask for clarifications.
 
Last edited:

Similar threads

  • · Replies 10 ·
Replies
10
Views
2K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 11 ·
Replies
11
Views
2K
  • · Replies 17 ·
Replies
17
Views
3K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K