Difficulties with derivative of a vector [Landau Textbook]

In summary, the conversation discusses the process of computing a pass from 1 to 106.15, involving the derivative of a function with respect to time and coordinates. The equation 106.15 is found by rearranging the terms and using certain conditions. The conversation also delves into the calculus behind the process and provides a final equation for the spatial and time dependence of the function. The conversation ends with a thank you and a clarification on the use of the notation ##n_{a \alpha}##.
  • #1
GrimGuy
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Hi guys, I'm having trouble computing a pass 1 to 106.15. It's in the pictures.

1618494074718.png


So, what a have to do is the derivative of ##f## with respect to time and coordinates. Then I need to rearrange the terms to find the equation 106.15. I am using the following conditions. ##r## vector varies in space and the vector ##r_a## varies in time.

I did that:
1618494870010.png


This calculus is from. (Section 106)
1618494426971.png
 

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  • #2
The spatial dependence of ##f## is in the argument ##\mathbf{r}##, whilst the time dependence is in the source positions ##\mathbf{r}_a##\begin{align*}
\partial_{\alpha} |\mathbf{r} - \mathbf{r}_a| &= \frac{x_{\alpha} - x_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} = n_{a \alpha}

\end{align*}Then taking the time derivative\begin{align*}
\partial_t \partial_{\alpha} |\mathbf{r} - \mathbf{r}_a| = \partial_t \left( \frac{x_{\alpha} - x_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} \right) &= \frac{-v_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} + (x_{\alpha} - x_{a \alpha}) \partial_t \left( \frac{1}{|\mathbf{r} - \mathbf{r}_a|} \right) \\

&= \frac{-v_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} + \frac{-(x_{\alpha} - x_{a \alpha})}{|\mathbf{r} - \mathbf{r}_a|^2} \left( \frac{(\mathbf{r} - \mathbf{r}_a) \cdot (-\mathbf{v}_a )}{|\mathbf{r} - \mathbf{r}_a|} \right) \\

&= \frac{-v_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} + \frac{n_{a \alpha} (\mathbf{n}_a \cdot \mathbf{v}_a)}{|\mathbf{r} - \mathbf{r}_a|}

\end{align*}Hence if ##f = -(k/2) \sum_a m_a |\mathbf{r} - \mathbf{r}_a |##, then\begin{align*}

\frac{\partial^2 f}{\partial t \partial x^a} &= \frac{k}{2} \sum_a m_a \left[ \frac{v_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} - \frac{n_{a \alpha} (\mathbf{n}_a \cdot \mathbf{v}_a)}{|\mathbf{r} - \mathbf{r}_a|} \right]\end{align*}and consequently\begin{align*}
h_{0 \alpha} &= \frac{8k}{2c^3} \sum_a \frac{m_a v_{a\alpha}}{|\mathbf{r} - \mathbf{r}_a|} - \frac{k}{2c^3} \sum_a \left[ \frac{m_av_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} - \frac{m_a n_{a \alpha} (\mathbf{n}_a \cdot \mathbf{v}_a)}{|\mathbf{r} - \mathbf{r}_a|} \right] \\

&= \frac{k}{2c^3} \sum_a \frac{m_a}{|\mathbf{r} - \mathbf{r}_a|} \left[ 7v_{a \alpha} + n_{a \alpha} (\mathbf{n}_a \cdot \mathbf{v}_a ) \right]\end{align*}
 
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  • #3
etotheipi said:
The spatial dependence of ##f## is in the argument ##\mathbf{r}##, whilst the time dependence is in the source positions ##\mathbf{r}_a##\begin{align*}
\partial_{\alpha} |\mathbf{r} - \mathbf{r}_a| &= \frac{x_{\alpha} - x_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} = n_{a \alpha}

\end{align*}Then taking the time derivative\begin{align*}
\partial_t \partial_{\alpha} |\mathbf{r} - \mathbf{r}_a| = \partial_t \left( \frac{x_{\alpha} - x_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} \right) &= \frac{-v_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} + (x_{\alpha} - x_{a \alpha}) \partial_t \left( \frac{1}{|\mathbf{r} - \mathbf{r}_a|} \right) \\

&= \frac{-v_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} + \frac{-(x_{\alpha} - x_{a \alpha})}{|\mathbf{r} - \mathbf{r}_a|^2} \left( \frac{(\mathbf{r} - \mathbf{r}_a) \cdot (-\mathbf{v}_a )}{|\mathbf{r} - \mathbf{r}_a|} \right) \\

&= \frac{-v_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} + \frac{n_{a \alpha} (\mathbf{n}_a \cdot \mathbf{v}_a)}{|\mathbf{r} - \mathbf{r}_a|}

\end{align*}Hence if ##f = -(k/2) \sum_a m_a |\mathbf{r} - \mathbf{r}_a |##, then\begin{align*}

\frac{\partial^2 f}{\partial t \partial x^a} &= \frac{k}{2} \sum_a m_a \left[ \frac{v_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} - \frac{n_{a \alpha} (\mathbf{n}_a \cdot \mathbf{v}_a)}{|\mathbf{r} - \mathbf{r}_a|} \right]\end{align*}and consequently\begin{align*}
h_{0 \alpha} &= \frac{8k}{2c^3} \sum_a \frac{m_a v_{a\alpha}}{|\mathbf{r} - \mathbf{r}_a|} - \frac{k}{2c^3} \sum_a \left[ \frac{m_av_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|} - \frac{m_a n_{a \alpha} (\mathbf{n}_a \cdot \mathbf{v}_a)}{|\mathbf{r} - \mathbf{r}_a|} \right] \\

&= \frac{k}{2c^3} \sum_a \frac{m_a}{|\mathbf{r} - \mathbf{r}_a|} \left[ 7v_{a \alpha} + n_{a \alpha} (\mathbf{n}_a \cdot \mathbf{v}_a ) \right]\end{align*}
Thx man, I'll take a time to understand and check it. Thank you a lot.

EDIT: I checked it and everything is fine and i could undestand the whole explanation, except for one little thing. What u were considering to write it '##n_{a \alpha}##'. It is the modul of the unit vector, or it is just a simplifyed notation to write ##\frac{x_{\alpha} - x_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|}## ?
 
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  • #4
GrimGuy said:
EDIT: I checked it and everything is fine and i could undestand the whole explanation, except for one little thing. What u were considering to write it '##n_{a \alpha}##'. It is the modul of the unit vector, or it is just a simplifyed notation to write ##\frac{x_{\alpha} - x_{a \alpha}}{|\mathbf{r} - \mathbf{r}_a|}## ?
Not the modulus, it's the second option: the ##\alpha## component of the vector ##\mathbf{n}_a := (\mathbf{r} - \mathbf{r}_a)/|\mathbf{r} - \mathbf{r}_a|##, as L&L define below the bit you posted. So ##n_{a \alpha} := (\mathbf{r} - \mathbf{r}_a)_{\alpha}/|\mathbf{r} - \mathbf{r}_a| = (x_{\alpha} - x_{a \alpha})/|\mathbf{r} - \mathbf{r}_a|##

I'll admit it's a slightly confusing notation on the authors' part, using ##a## to enumerate the different sources and ##\alpha## to denote vector components 😜
 
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FAQ: Difficulties with derivative of a vector [Landau Textbook]

What is a derivative of a vector?

A derivative of a vector is a mathematical concept that represents the rate of change of a vector quantity with respect to another variable. It is a measure of how much a vector changes in magnitude and direction as the independent variable changes.

Why is it difficult to calculate the derivative of a vector?

Calculating the derivative of a vector can be difficult because it involves finding the rate of change in multiple dimensions. This requires a thorough understanding of vector calculus and advanced mathematical techniques, making it a challenging task for many individuals.

What are some common difficulties encountered when working with derivatives of vectors?

Some common difficulties encountered when working with derivatives of vectors include understanding the concept of a vector derivative, applying the appropriate mathematical formulas, and visualizing the changes in magnitude and direction of the vector.

How can I improve my understanding of derivatives of vectors?

To improve your understanding of derivatives of vectors, it is important to have a strong foundation in vector calculus and practice solving problems involving vector derivatives. You can also seek help from a tutor or consult online resources for additional guidance.

How are derivatives of vectors used in real-world applications?

Derivatives of vectors have many real-world applications, such as in physics, engineering, and economics. They are used to analyze and model the changes in physical quantities, such as velocity and acceleration, and to optimize systems and processes. For example, derivatives of vectors are used in designing efficient routes for transportation and predicting the movement of objects in space.

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