Second derivative composite function

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Discussion Overview

The discussion revolves around finding the second time derivative of a composite function f(g(t)), where f is a function of g, which is itself a function of time t. Participants explore the application of the chain rule and the implications of vector calculus in this context, including the use of the Laplacian operator.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant presents a solution involving the first and second derivatives of f with respect to g, using notation that includes the Laplacian operator.
  • Another participant agrees with the initial approach but suggests testing it with simple examples.
  • A different participant critiques the notation and claims that the application of the chain rule for vector-valued functions has been misapplied, providing a detailed derivation of the second derivative.
  • Concerns are raised about dimensional consistency in the calculations, particularly regarding the treatment of the Hessian matrix and its interaction with vectors.
  • Further clarification is provided about the nature of the Hessian as a rank 3 tensor and its implications for the dimensionality of the resulting expressions.
  • A later post reiterates the original question and introduces a generalized product notation for the chain rule, suggesting a different perspective on the derivatives involved.

Areas of Agreement / Disagreement

Participants express differing views on the correctness of the initial solution and the application of the chain rule. There is no consensus on the validity of the original approach, and multiple competing interpretations of the mathematical expressions remain unresolved.

Contextual Notes

Participants highlight potential issues with dimensional analysis and the treatment of tensor ranks, indicating that assumptions about the nature of the functions and their derivatives may not be fully addressed.

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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