Second derivative composite function

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The discussion centers on finding the second time derivative of a composite function f(g(t)). The initial solution provided is critiqued for incorrect notation and dimensional inconsistencies, particularly regarding the treatment of the Laplacian and tensor dimensions. The correct application of the chain rule for vector-valued functions is emphasized, highlighting the need to properly account for tensor ranks in calculations. The conversation concludes with clarifications on the dimensional aspects of the derivatives involved. Understanding these nuances is crucial for accurately deriving the second derivative in this context.
aliekor
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Hi guys, I have this function


f(g(t)) and I have to find the second time derivative of f, is it correct the following solution?:

f''=∂f/∂g*g'=∇f*g'
f ''=∇^2f*|g'|^2+∇f*g''

where ∇^2 is the laplacian function
 
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Looks ok to me. Try it with some simple examples.
 
Your (standard) notational abuse has confused you.

The chain rule for a vector-valued function (f) of a vector-valued function (g) of a scalar (t) is:
<br /> \frac{d\mathbf{f}(\mathbf{g})}{dt} = (\nabla \mathbf{f}) \cdot <br /> \frac{d\mathbf{g}}{dt}<br />
ie
<br /> \frac{df_i(\mathbf{g})}{dt}(t) = \sum_j \frac{\partial f_i}{\partial x_j}(\mathbf{g}(t)) \frac{dg_j}{dt}(t).<br />

Differentiating with respect to t and using the product rule gives:
<br /> \frac{d^2\mathbf{f}(\mathbf{g})}{dt^2} = \left(\frac{d}{dt}(\nabla \mathbf{f})\right) \cdot \frac{d\mathbf{g}}{dt} + (\nabla \mathbf{f}) \cdot <br /> \frac{d^2\mathbf{g}}{dt^2}<br />
Using the chain rule on the first term gives
<br /> \frac{d}{dt}(\nabla \mathbf{f}) = (\nabla \nabla \mathbf{f})\cdot \frac{d\mathbf{g}}{dt} <br />
and so
<br /> \frac{d^2\mathbf{f}(\mathbf{g})}{dt^2} = <br /> \left(\left((\nabla \nabla \mathbf{f}) \cdot \frac{d\mathbf{g}}{dt}\right) \cdot <br /> \frac{d\mathbf{g}}{dt}\right) + (\nabla \mathbf{f}) \cdot <br /> \frac{d^2\mathbf{g}}{dt^2}<br />
ie
<br /> \frac{d^2f_i(\mathbf{g})}{dt^2} = <br /> \sum_j \sum_k \frac{dg_j}{dt} \frac {dg_k}{dt} \frac{\partial^2 f_i}{\partial x_j \partial x_k} + \sum_j \frac{d^2g_j}{dt^2} \frac{\partial f_i}{\partial x_j}.<br />

You appear to have the first term as
<br /> \sum_j \sum_k \left(\frac {dg_j}{dt}\right)^2 \frac{\partial^2 f_i}{\partial x_k^2}<br />
which is incorrect.
 
Thank you pasmith, actually I didn't get comething with the dimensions:
if I have g as a vector 2x1
<br /> \nabla \nabla \mathbf{f}<br />
will be a 2x2 matrix. In the calculus of :
<br /> \left(\left((\nabla \nabla \mathbf{f}) \cdot \frac{d\mathbf{g}}{dt}\right) \cdot <br /> \frac{d\mathbf{g}}{dt}\right) <br />
I have a matrix 2x2 times a vector 2X1 which gives a vector 2x1 and this vector is multiplied by a vector 2x1 but the dimension are wrong.
 
aliekor said:
Thank you pasmith, actually I didn't get comething with the dimensions:
if I have g as a vector 2x1
<br /> \nabla \nabla \mathbf{f}<br />
will be a 2x2 matrix.

Actually it's a 2x2x2 (ie, rank 3) tensor:
<br /> (\nabla\nabla \mathbf{f})_{ijk} = \frac{\partial^2 f_i}{\partial x_j \partial x_k}<br />

In the calculus of :
<br /> \left(\left((\nabla \nabla \mathbf{f}) \cdot \frac{d\mathbf{g}}{dt}\right) \cdot <br /> \frac{d\mathbf{g}}{dt}\right) <br />
I have a matrix 2x2 times a vector 2X1 which gives a vector 2x1 and this vector is multiplied by a vector 2x1 but the dimension are wrong.

This is a rank 3 tensor dotted with two vectors (rank 1 tensors), which is equivalent to a
rank 5 tensor contracted over two pairs of indices, yielding a rank 1 tensor (ie a vector).
In cartesian components, it is

<br /> \sum_{j}\sum_{k} \frac{\partial^2 f_i}{\partial x_j \partial x_k} \frac{dg_j}{dt} \frac{dg_k}{dt}<br />
 
aliekor said:
Hi guys, I have this function


f(g(t)) and I have to find the second time derivative of f, is it correct the following solution?:

f''=∂f/∂g*g'=∇f*g'
f ''=∇^2f*|g'|^2+∇f*g''

where ∇^2 is the laplacian function

$$(a * \nabla_t) f = [(\{a * \nabla_t \} g) * \nabla_g] f(g)$$
This is the chain rule. The stars just mean a generalized product. This form of the chain rule is valid for ##t## vector or scalar. Here, ##a## must be a scalar, so we'll just cancel it out.

$$\nabla_t f = [(\nabla_t g) \cdot \nabla_g] f(g)$$

Clearly, then,
$$\nabla_t^2 f = [(\nabla_t g) \cdot \nabla_g]^2 f(g)$$
 

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