Gradient as vector vs differential one-form

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Discussion Overview

The discussion revolves around the definition of the gradient of a function on a differentiable manifold, specifically whether it should be considered as a vector (##\nabla f##) or as a differential one-form (##df##). Participants explore the implications of having a metric tensor on the manifold and the different contexts in which these definitions apply.

Discussion Character

  • Debate/contested
  • Conceptual clarification
  • Technical explanation

Main Points Raised

  • Some participants assert that the gradient can be viewed as the vector ##\nabla f## at each point, while others argue it is the differential one-form ##df##.
  • It is noted that the inner product ##\nabla f \cdot v## requires a metric tensor, whereas the action of the one-form ##df## on a vector is defined without such a structure.
  • One participant claims that ##\nabla f## is actually a 1-form, suggesting that its index notation aligns with that of the partial derivative operator.
  • Another viewpoint is that the gradient can be defined via the level surfaces of a scalar function, independent of coordinates.
  • Some participants express uncertainty about the implications of defining the gradient without a coordinate chart, suggesting that the term "gradient" may carry different meanings.
  • There is a distinction made between the ##\nabla## operator and the exterior derivative ##d##, with the former requiring additional structure (a connection) that the latter does not.
  • It is mentioned that when applied to scalar functions, both ##\nabla f## and ##df## yield the same result, but this equivalence may not hold for higher-rank objects.

Areas of Agreement / Disagreement

Participants do not reach a consensus on whether the gradient should be defined as a vector or a differential one-form. Multiple competing views remain regarding the definitions and implications of these concepts.

Contextual Notes

Participants highlight that the definitions of gradient and differential one-form depend on the presence of additional structures, such as a metric tensor or a connection on the manifold. The discussion also reflects varying levels of rigor in mathematical definitions.

  • #31
vanhees71 said:
This is highly misleading, because it only works out using Cartesian coordinates for the vector space of an Euclidean affine space.

The natural general definition of a bare differentiable manifold is to define (alternating) differential forms as derivative operators on alternating tensor fields. Then the gradient of a scalar field naturally occurs as a one-form, i.e., a co-vector field,
$$\mathrm{d} \Phi=\mathrm{d}q^j \partial_j \Phi.$$
That's the exact same thing I wrote.

$$df = \frac{\partial f}{\partial x^i} dx^i$$

is a covector field.
 
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  • #32
vanhees71 said:
This is highly misleading
I'm as confused by this statement as @jbergman since what you wrote is the same as what he wrote (in the latter, coordinate independent part of his post). The only difference is that he also wrote an additional step where you use the metric to raise the index of the gradient covector field, which works if you have a metric on the manifold; you've already agreed that that's possible.
 
  • #33
What is misleading is the first equation reading
$$\text{grad} f= \frac{\partial f}{\partial x^i} \vec{e}_i=(\partial_i f) \vec{e}_i,$$
which obviously is not an invariant vector, because you shouldn't sum over two lower indices. What's correct is
$$\text{grad} f= (\partial_i f)\vec{e}^i,$$
which clearly shows that it is a co-vector (1-form) not a vector.

Only for a Cartesian basis you can identify ##\vec{e}_i## with ##\vec{e}^i##, because lowering and raising indices in this and only this case goes with the Kronecker ##\delta_{ij}=\delta^{ij}##.
 
  • #34
vanhees71 said:
What is misleading is the first equation reading
$$\text{grad} f= \frac{\partial f}{\partial x^i} \vec{e}_i=(\partial_i f) \vec{e}_i,$$
which obviously is not an invariant vector
And @jbergman explicitly said that this only works in ##\mathbb{R}^n## and does not work in the absence of coordinates.

vanhees71 said:
Only for a Cartesian basis you can identify ##\vec{e}_i## with ##\vec{e}^i##
And that part of @jbergman's post, as he explicitly said, was restricted to this case. He then went on, in the latter part of his post, to give a better formulation that is not dependent on any particular choice of coordinates. So he already gave the clarification that you are trying to give here. You're just repeating what he said in different words.
 
  • #35
vanhees71 said:
What is misleading is the first equation reading
$$\text{grad} f= \frac{\partial f}{\partial x^i} \vec{e}_i=(\partial_i f) \vec{e}_i,$$
which obviously is not an invariant vector, because you shouldn't sum over two lower indices. What's correct is
$$\text{grad} f= (\partial_i f)\vec{e}^i,$$
which clearly shows that it is a co-vector (1-form) not a vector.

Only for a Cartesian basis you can identify ##\vec{e}_i## with ##\vec{e}^i##, because lowering and raising indices in this and only this case goes with the Kronecker ##\delta_{ij}=\delta^{ij}##.
That was the whole point of the post, that the definition that is often presented to students in multivariable calculus is not coordinate free.
 
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  • #36
jbergman said:
That was the whole point of the post, that the definition that is often presented to students in multivariable calculus is not coordinate free.
Just to emphasize the obvious, it is not coordinate free, but it is a perfectly valid and correct definition.
 
  • #37
PeterDonis said:
And @jbergman explicitly said that this only works in ##\mathbb{R}^n## and does not work in the absence of coordinates.And that part of @jbergman's post, as he explicitly said, was restricted to this case. He then went on, in the latter part of his post, to give a better formulation that is not dependent on any particular choice of coordinates. So he already gave the clarification that you are trying to give here. You're just repeating what he said in different words.
It works only with Cartesian bases, not for general bases, even not in ##\mathbb{R}^n##.
 
  • #38
vanhees71 said:
It works only with Cartesian bases
Yes, in other words, with a particular choice of coordinates. @jbergman even gave an example of how it does not work in polar coordinates. Did you actually read what he wrote?
 
  • #39
Maybe I misunderstood the notation. I think we all agree finally.
 

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