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I have a somewhat weird question regarding some problems I have been encountering lately when dealing with transformations of the general covariant derivative to cartesian coordinates and back. In the following, I will use Latin indices for cartesian components and greek indices for the general curved case.

In general, I have two sets of independent variables $v^i$ and $x^i$ or in the curvilinear case $v^\sigma$, $\xi^\sigma$, where $v$ are components of a sample space velocity and $\xi$ and $x$ are a parameterization of a position. The dependant variable is a probability distribution $f$.

We now consider for simplicity a term in the form of

$\nabla_\nu (v^\nu f)$

where $\nabla$ denotes the covariant derivative. When transforming this expression to cartesian coordiantes and the covariant derivative reduces to a partial derivative. I the have, since $x^i$ and $v^i$ are independent variables $\partial_i v^j=0$ and thus

$\nabla_\nu (v^\nu f) = \nabla_i (v^i f) = v^i \nabla_if$.

However, I do not see what stops me from transforming this back to the curvilinear basis and I thus obtain

$\nabla_\nu (v^\nu f) = v^\nu \nabla_\nu f$

which can only be true if $\nabla_\nu v^\mu=0$, but we $\xi^\nu$ and $v^\nu$ should be independent variables, which I have always assumed to mean $\partial_\mu v^\nu=0$ not $\nabla_\nu v^\mu=0$. ( I know that $\nabla_i v^j=0$ leads naturally to $\nabla_\nu v^\mu=0$ since the tensor equation should hold in any coordinate frame. However, it still seems a bit weird since we are explicitly seeking a form where the sample space velocity components and the position are independent of one another )

Maybe my assumption / interpretation of coordinate independence is flawed. I would greatly appreciate any input.

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2 Answers 2

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Functional independence $\frac{\partial}{\partial y^\alpha} V^\beta =0$ and zero covariant derivative $\nabla_\alpha V^\beta=0$ are disjoint facts, generally speaking.

In orthonormal Cartesian coordinates they are however equivalent, but this is false when passing to other coordinate systems.

Take $\mathbb{R}^2$ equipped with the standard Levi-Civita connection and consider a vector field $V$ which has constant components in Cartesian coordinates. In other words the Cartesian components of $V$ are not functions of the Cartesian coordinates. This is equivalent to say that $\nabla_\alpha V^\beta=0$. This second requirement is intrinsic, it does not depend on the choice of coordinates. However it does not mean that, for instance, the components of $V$ in polar plane coordinates $\theta, r$ are independent from $\theta, r$. This is obvious without a computation just by thinking to the shape of curves $r=$ constant and $\theta=$ constant.

Analytically speaking the dependence arises form the transformation law of components. For instance, $$V^r = \frac{\partial r}{\partial x}V^x + \frac{\partial r}{\partial y}V^y = \frac{x}{\sqrt{x^2+y^2}} V^x + \frac{y}{\sqrt{x^2+y^2}} V^y\:.$$ You see that, even if $V^x$ and $V^y$ are constant -- and this is just the requirement $\nabla_\mu V^\mu=0$ -- the component $V^r$ is not constant and the reason is due to the appearance of the non-constant factors $\frac{\partial r}{\partial x}$ and $\frac{\partial r}{\partial y}$.

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  • $\begingroup$ Thank you very much! You are absolutely right. That these two facts are disjoint had slipped my mind. Maybe to elaborate a bit further on my question: we have a kinetic equation written in a cartesian basis and where $\partial_i v^j=0$ was assumed and we wanted to transform this equation to an arbitrary basis where $\partial_\mu v^\nu=0$. But due to the assumption taken during the cartesian derivation (And due to the disjoint nature you mentioned), this should not be possible as we have restricted ourself to the case where $\nabla_\mu v^\nu=0$. $\endgroup$
    – Johannes C
    Commented Nov 12, 2022 at 11:38
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If I got your question right, you're computing the gradient of a vector field $f \mathbf{v}$, and you want to find the components of the gradient, defined as the covariant derivatives, using:

  • 2 sets of coordinates $q^i$, $Q^i$, with $Q_i$ Cartesian, to describe the space $\mathbf{r} = \mathbf{r}^q(q^i) = \mathbf{r}^Q(Q^i)$, using this notation to explicitly write the position in space $\mathbf{r}$ as two functions $\mathbf{r}^q$, $\mathbf{r}^Q$ with different sets of coordinates; these two representations can be related, knowing the transformation rule $q^i(Q^k)$ as

    $\mathbf{r} = \mathbf{r}^q(q^i) = \mathbf{r}^q(q^i(Q^k)) = \mathbf{r}^Q(Q^k) $.

  • the vectors of the natural bases $\mathbf{b}_i = \frac{\partial \mathbf{r}}{\partial q^i}$, $\mathbf{B}_i = \frac{\partial \mathbf{r}}{\partial Q^i}$, induced by the coordinates, so that we can write the vector field

    $f \mathbf{v} = f v^i \ \mathbf{b}_i = f V^k \ \mathbf{B}_k$.

    These vectors are related using differentiation of composite functions

    $\mathbf{B}_k (Q^a) = \dfrac{\mathbf{\partial \mathbf{r}}}{\partial Q^k}(Q^a) = \dfrac{\mathbf{\partial \mathbf{r}}^Q}{\partial Q^k}(Q^a) = \dfrac{\mathbf{\partial \mathbf{r}}^q}{\partial Q^k}(q^i(Q^a)) = \dfrac{\mathbf{\partial \mathbf{r}}^q}{\partial q^i}(q^i(Q^a)) \dfrac{\partial q^i}{\partial Q^k}(Q^a) = \mathbf{b}_i (q^i(Q^a)) \dfrac{\partial q^i}{\partial Q^k}(Q^a)$,

    thus, hiding the functional dependence for brevity, we have found the law of transformation between the vectors of the two bases,

    $\mathbf{B}_k = \mathbf{b}_i \dfrac{\partial q^i}{\partial Q^k}$.

Now, the gradient of this vector field $\nabla ( f \mathbf{v} )$ can be written using the natural bases and their reciprocal bases $\{\mathbf{b}^i\}_i$, $\{\mathbf{B}^k\}_k$ as

$\nabla (f \mathbf{v}) = \mathbf{b}^i \otimes \dfrac{\partial}{\partial q^i} (f \mathbf{v}) = \mathbf{B}^a \otimes \dfrac{\partial}{\partial Q^a} (f \mathbf{v})$

Using coordinates $q^i$, we get

$\nabla (f \mathbf{v}) = \mathbf{b}^i \otimes \dfrac{\partial}{\partial q^i} (f \mathbf{v}) = \mathbf{b}^i \otimes \dfrac{\partial}{\partial q^i} (f v^k \mathbf{b}_k) = \\ \qquad \quad = \mathbf{b}^i \otimes \left[ \dfrac{\partial}{\partial q^i} (f v^k ) \mathbf{b}_k + f v^k \dfrac{\partial \mathbf{b}_k}{\partial q^i} \right] = \\ \qquad \quad = \mathbf{b}^i \otimes \left[ \dfrac{\partial}{\partial q^i} (f v^k ) \mathbf{b}_k + f v^k \dfrac{\partial \mathbf{b}_k}{\partial q^i} \right] = \\ \qquad \quad = \mathbf{b}^i \otimes \left[ \dfrac{\partial}{\partial q^i} (f v^k ) \mathbf{b}_k + f v^k \Gamma^{(q)\ell}_{ik} \mathbf{b}_{\ell} \right] = \mathbf{b}^i \otimes \mathbf{b}_k \left[ \dfrac{\partial}{\partial q^i} (f v^k ) + f v^{\ell} \Gamma^{(q)k}_{i \ell} \right] = \mathbf{b}^i \otimes \mathbf{b}_k \nabla^{(q)}_{/i} v^k$,

while using Cartesian coordinates $Q^a$, for which the vectors of the natural basis are uniform in space and thus their derivatives w.r.t. the coordinates $Q^a$, i.e. Christoffel symbols $\Gamma^{Q,a}_{bc}$ are identically zero, we get

$\nabla (f \mathbf{v}) = \mathbf{B}^a \otimes \mathbf{B}_b \dfrac{\partial V^b}{\partial Q^a} = \mathbf{B}^a \otimes \mathbf{B}_b \nabla^{(Q)}_{/a} V^b$.

It's possible to prove that the two expressions of the gradient are equivalent, being just the representation of the same tensor object using 2 different sets of coordinates and bases.

(writing, and checking symbols...)

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  • $\begingroup$ Thank you very much for your answer. Your calculations are correct. I think I just had a conceptual problem but Valters's answer cleared up my misunderstanding. $\endgroup$
    – Johannes C
    Commented Nov 12, 2022 at 11:44
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    $\begingroup$ Great. I won't go on with the computations, then $\endgroup$
    – basics
    Commented Nov 12, 2022 at 11:44

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