Exploring Variables and Simplifying Problems in 3 Dimensions

In summary, the conversation discusses simplifying a problem involving variables and the Kronecker delta, and ultimately trying to prove a specific equation. The expert explains that the Kronecker delta simply replaces one variable with another and provides a helpful tip for solving the problem.
  • #1
timscully
5
0
1. Variables

Given a generalized basis in three dimensions: [tex]e_{1},e_{2},e_{3}[/tex] and the standard Kronecker delta [tex]\delta_{ij}[/tex], and using Einstein summation.
With the vector [tex]\textbf{x},\textbf{y},\textbf{z}[/tex] I'm trying to simplify this problem:

2. Problem
[tex]\delta_{il} . \delta_{jm} . x_{j}[/tex]

3. My attempt
[tex]\delta_{il}.\delta_{jm} . \textbf{x} . e_{j}
= (e_{i}. e_{l}) . (e_{j} . e_{m}) . \textbf{x} . e_{j}
= (e_{j}. e_{j}) . (e_{l} . e_{m} . e_{j}) . \textbf{x}
= 1 . (e_{l} . e_{m} . e_{j}) . \textbf{x} [/tex]

Surely this leads to [tex]\delta_{il} . \delta_{jm} . x_{j} = 0[/tex] as [tex]e_{l} , e_{m} , e_{j}[/tex] are all orthagonal ?

Ultimately I'm trying to prove that
[tex](\delta_{il} . \delta_{jm} - \delta_{jl} . \delta_{im}).x_{j}.y_{l}.z_{m}
= y_{i}.x_{j}.z_{j} - z_{i}.x_{j}.y_{j}[/tex]
 
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  • #2
Welcome to PF!

timscully said:
I'm trying to simplify this problem:
[tex]\delta_{il} . \delta_{jm} . x_{j}[/tex]

Ultimately I'm trying to prove that
[tex](\delta_{il} . \delta_{jm} - \delta_{jl} . \delta_{im}).x_{j}.y_{l}.z_{m}
= y_{i}.x_{j}.z_{j} - z_{i}.x_{j}.y_{j}[/tex]

Hi timscully! Welcome to PF! :smile:

(have a delta: δ :wink:)

Forget about the basis vectors!

All δij does is replace i by j (or vice versa) in anything else.

So δijxj = xi, δijxi = xj.

So just plug 'n' play! :biggrin:
 
  • #3
Thanks for the welcome.

It looks like a great forum.

So, is [tex]\delta_{ij} . x_{m}[/tex] zero, because m is neither i nor j ?
 
  • #4
not a sum

timscully said:
Thanks for the welcome.

It looks like a great forum.

So, is [tex]\delta_{ij} . x_{m}[/tex] zero, because m is neither i nor j ?

Nooo:bugeye:

δijxj is a sum over all values of j, so it only depends on i: δijxj = xi.

But δijxm is not a sum; there is no "contraction"; it still depends on i j and m: δijxm = xm if i = j and = 0 if i≠j. :smile:
 
  • #5
Got it. Much appreciated.
 

FAQ: Exploring Variables and Simplifying Problems in 3 Dimensions

What are variables and how are they used in exploring problems in 3 dimensions?

Variables are quantities that can change or vary in a given situation. In exploring problems in 3 dimensions, variables are used to represent the dimensions or parameters of the problem. This allows for a systematic approach to analyzing and solving the problem.

How does simplifying problems in 3 dimensions help in understanding complex concepts?

Simplifying problems in 3 dimensions involves breaking down a complex problem into smaller, more manageable parts. This helps in understanding complex concepts by providing a clearer and more organized framework for analysis and problem-solving.

What are some common techniques for exploring variables in 3 dimensions?

Some common techniques for exploring variables in 3 dimensions include graphing, creating equations and models, using geometric shapes and figures, and using technology such as computer simulations or 3D modeling software.

How can exploring variables in 3 dimensions be applied in real-world situations?

Exploring variables in 3 dimensions can be applied in various fields such as engineering, physics, architecture, and even in everyday life. It can help in designing structures, predicting and analyzing the behavior of physical systems, and solving real-world problems involving multiple dimensions.

What are some challenges that may arise when exploring variables in 3 dimensions?

Some challenges that may arise when exploring variables in 3 dimensions include visualizing and representing 3D objects or systems, dealing with complex mathematical calculations, and identifying and controlling for all relevant variables in a given problem. Additionally, technology limitations or errors may also pose challenges in exploring variables in 3 dimensions.

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