Understanding 3D Rotations & Linear Relationships in Physics

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SUMMARY

This discussion focuses on the mathematical representation of 3D rotations as presented in Arfken's "Mathematical Methods for Physicists." The key equations discussed include the transformation of vector components from one basis to another, specifically the equations A_i ' = ∑_j (e_j'·e_i)A_j and A_i ' = ∑_j (∂x_i '/∂x_j)A_j. The participant seeks clarification on the transition from using unit vectors to coordinate representation and the justification of using the dot product in this context. The discussion emphasizes the application of the chain rule in transforming vector components.

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  • Understanding of vector transformations in 3D space
  • Familiarity with the concepts of basis vectors and coordinate systems
  • Knowledge of the chain rule in calculus
  • Basic proficiency in linear algebra and tensor notation
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  • Study the derivation of the chain rule in the context of vector transformations
  • Explore the geometric interpretation of 3D rotations using unit vectors
  • Learn about tensor representation and its applications in physics
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Physicists, mathematicians, and students studying advanced physics or mathematical methods, particularly those interested in understanding 3D rotations and their applications in tensor analysis.

electricspit
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Hello, I'm trying to get a hang of the definition presented in Arfken - Mathematical Methods for Physicists for 3 dimensional rotations (a setup for an introduction to tensors). That being said I'm a Physicist and I'd like a component approach if possible to the explanation. They give:

<br /> A_i &#039; = \sum\limits_j (\hat{e}_j&#039;\cdot\hat{e}_i)A_j<br />

Which is just a rotation from \vec{A} to the primed basis:

<br /> \vec{A}=A_1 \hat{e}_1 + A_2 \hat{e}_2 + A_3 \hat{e}_3<br />

<br /> \vec{A}&#039;=A_1&#039;\hat{e}_1&#039;+A_2&#039;\hat{e}_2&#039;+A_3&#039;\hat{e}_3&#039;<br />

The first equation I'm not really confused about, it's just representing one vector in another basis. It shows that the coefficient in front of each component is just the projection of the primed unit vector onto the unprimed vector. They do a graphical derivation. What I have a problem with is their next step and the justification:

<br /> A_i &#039; = \sum\limits_j (\frac{\partial x_i &#039;}{\partial x_j})A_j<br />

So I can justify to myself why this should be true, in English the dot product above and the partial derivative is saying the same thing. The change in the i^{th} primed coordinate relative to the j^{th} unprimed coordinate.

I'm not sure why they are all of a sudden using x_i to represent the coordinates and also why it is okay to represent the dot product in this way. They give an explanation:

The formula of Eq. (4.2) corresponds to the application of the chain rule to convert the set Aj into the set Ai', and is valid for Aj and Ai' of arbitrary magnitude because both vectors depend linearly on their components.

Does anyone have a more clear justification?

Thank you so much!
 
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You should correct the first equation:

A_i &#039; = \sum\limits_j (\hat{e}_j\cdot\hat{e}_i&#039;)A_j

The result derives from this relation:

\hat{e}_i&#039; = \sum\limits_j (\frac{\partial x_i &#039;}{\partial x_j})\hat{e}_j
 
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Sorry it was fairly zoomed out on the PDF I had. Also thanks!
 

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