Is Associativity Key in Simplifying Multivector Products in Geometric Algebra?

  • Context: Graduate 
  • Thread starter Thread starter JonnyMaddox
  • Start date Start date
  • Tags Tags
    Geometric Product
Click For Summary

Discussion Overview

The discussion revolves around the properties of the geometric product in geometric algebra, particularly focusing on the associativity of the geometric product and its implications for simplifying multivector products. Participants explore specific examples of multivectors and their products, examining the calculations and relationships between the components.

Discussion Character

  • Exploratory
  • Mathematical reasoning
  • Technical explanation

Main Points Raised

  • Some participants assert that the geometric product is associative, allowing for the expression of multivector products in a simplified form.
  • One participant presents a specific example involving multivectors A and B, detailing their components and the resulting product M, while questioning the process of multiplying multivectors symbolically.
  • Another participant suggests that when simplifying products, it may be beneficial to omit the wedge product for clarity, proposing a relationship between the geometric product and the wedge product for orthogonal vectors.
  • There is a discussion about the implications of multiplying a specific result by a vector, with one participant questioning the treatment of a factor of 2 in the calculations and suggesting a geometric interpretation involving rotation and dilation.
  • Participants engage in clarifying the relationships between basis vectors and their products, with references to orthonormality and simplifications that can be made under certain conditions.

Areas of Agreement / Disagreement

Participants express varying interpretations of the geometric product and its simplifications. While some agree on the utility of associativity and specific relationships between products, others raise questions about the treatment of factors and the geometric implications of the operations, indicating that the discussion remains unresolved.

Contextual Notes

Some assumptions about the orthonormality of basis vectors and the treatment of the wedge product are present but not universally accepted. The discussion includes unresolved mathematical steps and varying interpretations of the results.

JonnyMaddox
Messages
74
Reaction score
1
Hi, I just want to see if I understood this. Since the geometric product is associative and so on we can write for two multivectors A and B given by

A= \alpha_{0}+\alpha_{1}e_{1}+\alpha_{2}e_{2}+\alpha_{3}e_{1}\wedge e_{2}
B= \beta_{0}+ \beta_{1}e_{1}+\beta_{2}e_{2}+\beta_{3}e_{1}\wedge e_{2}

the geometric product multiplication as

AB=M=\mu_{0}+\mu_{1}e_{1}+\mu_{2}e_{2}+\mu_{3}e_{1}e_{2}

Where for example \mu_{0}=\alpha_{0}\beta_{0}+\alpha_{1}\beta_{1}+\alpha_{2}\beta_{2}-\alpha_{3}\beta_{3} and so on.

Now let's take an example with beautiful vectors with numbers like a = (e_{1}+2e_{2}), a_{1}=(2e_{1}+3e_{3}), a_{2}=(2e_{1}+0e_{2})

So aa_{1}= 8- e_1\wedge e_{2} Now what if I multiply this with a_{2}?

(8-e_{1}\wedge e_{2})(2e_{1})? Is it just 16e_{1}-(e_{1}\wedge e_{2})(2e_{1}) ? My logic behind this is that one can symbolically (GP) multiply multivectors and then opens up his list with like 300 different products or something and then evaluates each of the products? Is this right?
 
Last edited:
Physics news on Phys.org
JonnyMaddox said:
Hi, I just want to see if I understood this. Since the geometric product is associative and so on we can write for two multivectors A and B given by

A= \alpha_{0}+\alpha_{1}e_{1}+\alpha_{2}e_{2}+\alpha_{3}e_{1}\wedge e_{2}
B= \beta_{0}+ \beta_{1}e_{1}+\beta_{2}e_{2}+\beta_{3}e_{1}\wedge e_{2}

the geometric product multiplication as

AB=M=\mu_{0}+\mu_{1}e_{1}+\mu_{2}e_{2}+\mu_{3}e_{1}e_{2}

Where for example \mu_{0}=\alpha_{0}\beta_{0}+\alpha_{1}\beta_{1}+\alpha_{2}\beta_{2}-\alpha_{3}\beta_{3} and so on.

Now let's take an example with beautiful vectors with numbers like a = (e_{1}+2e_{2}), a_{1}=(2e_{1}+3e_{3}), a_{2}=(2e_{1}+0e_{2})

So aa_{1}= 8- e_1\wedge e_{2} Now what if I multiply this with a_{2}?

(8-e_{1}\wedge e_{2})(2e_{1})? Is it just 16e_{1}-(e_{1}\wedge e_{2})(2e_{1}) ? My logic behind this is that one can symbolically (GP) multiply multivectors and then opens up his list with like 300 different products or something and then evaluates each of the products? Is this right?

To me, if you're dealing with geometric algebra, it's better to leave out the \wedge. For vectors, A \wedge B = \frac{1}{2}(AB - BA). If A and B are orthogonal, then A \wedge B = AB

So aa_{1}= 8- e_1 e_{2}.
Then when we multiply by 2 e_1 you just get:

8 e_1 - e_1 e_2 e_1

You can simplify using e_2 e_1 = -e_1 e_2 to get:
8 e_1 + e_1 e_1 e_2

Then you can use the fact that e_1 e_1 = 1 to get:
8 e_1 + e_2

(Note: this is assuming that your basis vectors are orthonormal:
e_i e_j + e_j e_i = 2 \delta_{ij})
 
  • Like
Likes   Reactions: 1 person
Hi stevendaryl,
I think I got it. If we can reformulate everything as GP then we can always use this simple relations between the orthogonal basis vectors, hm that was more then obvious...ok thank you.

When you multiply 8-e_{1}e_{2} by 2e_{1} where did you leave the factor of 2 in the result? I think it should be a rotation by 90 degrees anti-clockwise and dilation by factor 2?

Thx for your reply !
 
JonnyMaddox said:
Hi stevendaryl,
I think I got it. If we can reformulate everything as GP then we can always use this simple relations between the orthogonal basis vectors, hm that was more then obvious...ok thank you.

When you multiply 8-e_{1}e_{2} by 2e_{1} where did you leave the factor of 2 in the result? I think it should be a rotation by 90 degrees anti-clockwise and dilation by factor 2?

Thx for your reply !

That was a typo, sorry.
 

Similar threads

  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 32 ·
2
Replies
32
Views
5K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 4 ·
Replies
4
Views
3K
Replies
3
Views
3K