Basis Vectors & Inner Product: A No-Nonsense Introduction

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Discussion Overview

The discussion revolves around the nature of basis vectors and the inner product in different coordinate systems, particularly in the context of special and general relativity. Participants explore the implications of using canonical basis vectors versus other forms, the relationship between basis vectors and the metric tensor, and how these concepts apply to vector quantities in physics.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • Some participants argue that the claim that basis vectors are canonical in any coordinate system is incorrect, citing the example of spherical coordinates where the metric is not the identity matrix.
  • Others suggest that the properties of inner products are more consistent with the idea that a vector's norm can be expressed in any coordinate system.
  • A participant emphasizes the distinction between basis vectors and metrics, noting that any positive definite bilinear form can define an inner product.
  • There is a discussion about how to express vectors in polar coordinates and the relationship between these vectors and their Cartesian counterparts.
  • Some participants propose that vectors in theories of relativity can be constructed from curves in manifolds, raising questions about the association of vector quantities like four-momentum to paths in these manifolds.
  • It is noted that different curves can yield the same tangent vector, leading to the concept of equivalence classes of curves for defining tangent vectors at a point.

Areas of Agreement / Disagreement

Participants express differing views on the definition and implications of basis vectors and metrics, indicating that multiple competing perspectives remain without a clear consensus.

Contextual Notes

The discussion highlights the complexity of defining basis vectors and metrics in various coordinate systems, as well as the implications for vector quantities in physics. There are unresolved mathematical steps and assumptions regarding the nature of inner products and the role of the metric tensor.

Who May Find This Useful

This discussion may be of interest to those studying advanced topics in physics, particularly in relativity, vector calculus, and differential geometry.

kent davidge
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I read from this page https://properphysics.wordpress.com...se-introduction-to-special-relativity-part-6/

that the basis vectors are the canonical basis vectors in any coordinate system. This seems to be wrong, because if that was the case the metric would be the identity matrix in any coordinate system, and we know that, for example, in spherical coordinates the metric has components ##\{1, r^2, r^2 \sin^2 \varphi \}##. So should I conclude that what is said on that page is wrong?

On the other hand, what is said on there seems to be more consistent with the inner product properties, because then a vector ##V = Ae_1 + Be_2## would have norm ##\sqrt{A^2 + B^2}## in any coordinate system.

So I'm not sure what conclusion I should draw from that page.
 
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It seems this lecture deals with special relativity. You can take it like Cartesian coordinates. In general relativity curvilinear coordinates or no orthogonal coordinate are used. You will learn mathematics for such a complex geometry at that time.
 
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There should have been an additional adjective: Cartesian or orthonormal and eventually finite-dimensional, too. Given any basis ##v_1,v_2,\cdot ,v_n## the coordinates of these vectors according to this basis, i.e. according to themselves, are always ##(1,0,\ldots ,0)\; , \;(0,1,0,\ldots ,0)\; , \; etc. ##.

A metric is something else. You can have any positive definite, symmetric bilinear form to define a inner (scalar) product for a metric and a norm, or define a metric otherwise. The standard inner product is simply the one, that belongs to the identity matrix as bilinear form.
 
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kent davidge said:
I read from this page https://properphysics.wordpress.com...se-introduction-to-special-relativity-part-6/

that the basis vectors are the canonical basis vectors in any coordinate system. This seems to be wrong, because if that was the case the metric would be the identity matrix in any coordinate system, and we know that, for example, in spherical coordinates the metric has components ##\{1, r^2, r^2 \sin^2 \varphi \}##. So should I conclude that what is said on that page is wrong?

On the other hand, what is said on there seems to be more consistent with the inner product properties, because then a vector ##V = Ae_1 + Be_2## would have norm ##\sqrt{A^2 + B^2}## in any coordinate system.

So I'm not sure what conclusion I should draw from that page.

People mean different things by the basis vectors. If you have a path through space ##\mathcal{P}(s)## as a function of a path parameter, ##s##, then the corresponding tangent vector is just: ##V = \frac{d \mathcal{P}}{ds}##. If you have a coordinate system ##x^\mu##, then the most straight-forward way to define the "components" of ##V## are using the coordinates: ##V^\mu \equiv \frac{dx^\mu}{ds}##. That is, ##V^\mu## is just the rate of change in the coordinate ##x^\mu## as you move along the path ##\mathcal{P}(s)##.

So let's take the example of 2D polar coordinates ##r, \theta##. Then the components of velocity are given by: ##V^r = \frac{dr}{ds}## and ##V^\theta = \frac{d\theta}{ds}##. These are related to the rectangular coordinates ##(x,y)## through:

##V^x = \frac{\partial x}{\partial r} V^r + \frac{\partial x}{\partial \theta} V^\theta##
##V^y = \frac{\partial y}{\partial r} V^r + \frac{\partial y}{\partial \theta} V^\theta##

Using ##x = r\ cos(\theta)## and ##y = r\ sin(\theta)##, this means:

##V^x = cos(\theta) V^r - r sin(\theta) V^\theta##
##V^y = sin(\theta) V^r + r cos(\theta) V^\theta##

Now, we have: ##|V|^2 = (V^x)^2 + (V^y)^2 = cos^2(\theta) (V^r)^2 - 2 r sin(\theta) cos(\theta) V^r V^\theta + r^2 sin^2(\theta) (V^\theta)^2 + sin^2(\theta) (V^r)^2 + 2 r sin(\theta) cos(\theta) V^r V^\theta + r^2 cos^2(\theta) (V^\theta)^2 = (V^r)^2 + r^2 (V^\theta)^2##

So if you want ##|V|^2## to be independent of what coordinate system you are using, then you have to use the metric tensor:

##|V|^2 = \sum_{\alpha \beta} g_{\alpha \beta} V^\alpha V^\beta##

In cartesian coordinates: ##g_{xx} = g_{yy} = 1##. In polar coordinates, ##g_{rr} = 1## but ##g_{\theta \theta} = r^2##

In terms of basis vectors, this means choosing ##e_r = cos(\theta) e_x + sin(\theta) e_y## and ##e_\theta = - r sin(\theta) e_x + r cos(\theta) e_y##. In this basis, the magnitudes of the basis vectors are not 1. ##|e_\theta| = r##.

Now, in a lot of introductory books about vector calculus, they try to keep the metric tensor as the simple form ##g_{rr} = g_{\theta \theta} = 1##. To do this, they have to absorb the ##r^2## into the definition of ##V^\theta##: They use ##\tilde{V}^\theta \equiv r V^\theta##. This means choosing different basis vectors:

##\hat{r} \equiv e_r##
##\hat{\theta} \equiv \frac{1}{r} e_\theta##

This is a non-coordinate basis, in that ##\tilde{V}^\theta## is unequal to ##\frac{d\theta}{ds}##.
 
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stevendaryl said:
People mean different things by the basis vectors. If you have a path through space ##\mathcal{P}(s)## as a function of a path parameter, ##s##, [...]
Hmm, interesting. So we can build all the vectors of our theories (special and general relativity) in terms of curves through out appropriate manifolds? Does this mean we can associate, say, a four-momentum, or a four-velocity, to a path in some manifold? i.e. not just "position in space and time" but also any other vector quantity?
 
kent davidge said:
Hmm, interesting. So we can build all the vectors of our theories (special and general relativity) in terms of curves through out appropriate manifolds? Does that mean we can associate, say, the four-momentum, or a four-velocity, to a path in some manifold?

Given a parametrized path through the manifold, you have an associated vector, namely the "velocity" (but with position viewed as a function of the parameter, not time). But a vector doesn't uniquely define a path, though. If you have a vector field ##V(\mathcal{P})##, that is, a vector at every point in space, then a vector field plus a starting location ##\mathcal{P}_0## uniquely determines a path: There is only one path ##\mathcal{P}(s)## satisfying ##\mathcal{P}(0) = \mathcal{P}_0## and ##\frac{d\mathcal{P}}{ds} = V(\mathcal{P}(s))##
 
As stevendaryl says different curves can give rise to the same tangent vector, but you can define tangent vectors at a point as equivalent classes of curves.
 
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martinbn said:
As stevendaryl says different curves can give rise to the same tangent vector, but you can define tangent vectors at a point as equivalent classes of curves.
Oh yea, I have read about that
 

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