Understanding Scalar and Vector Products in Geometric Algebra

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Discussion Overview

The discussion revolves around the operations involving scalar and vector products within the framework of geometric algebra. Participants explore the definitions and implications of these operations, including scalar multiplication, vector scaling, and the distinctions between dot and cross products, while also considering their applicability in various dimensions.

Discussion Character

  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant lists operations involving scalars and vectors, questioning the validity of certain products.
  • Another participant clarifies that the "x" symbol likely refers to the vector cross-product and the "." symbol to the scalar product, emphasizing that these operations apply only to vectors.
  • Some participants challenge the characterization of scalar cross scalar as "not valid," suggesting it could denote a pair rather than being outright invalid.
  • There is a discussion about interpreting the cross product in the context of set theory, with some arguing that the terminology used may be misleading.
  • One participant notes that the operations discussed also apply to higher-dimensional vectors, such as 7D vectors, while expressing dissatisfaction with the properties of the 7D cross product.

Areas of Agreement / Disagreement

Participants express differing views on the validity of certain operations and the interpretation of notation, indicating that multiple competing views remain. There is no consensus on the characterization of scalar products or the implications of the operations discussed.

Contextual Notes

Some participants highlight limitations in the definitions and interpretations of operations, particularly regarding the context in which the symbols are used. The discussion reflects a range of assumptions and interpretations that are not universally accepted.

smims
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(Scalar)·(Scalar) = Scalar
(Scalar)·(Vector) = Scalar
(Vector)·(Vector) = Scalar
(Scalar)x(Scalar) = Not valid
(Scalar)x(Vector) = Vector
(Vector)x(Vector) = VectorDid I get them right, if not why?

Thanks
 
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By "x" do you mean the vector cross-product? And by "." do you mean the vector scalar product? If the answer is yes, then those operations are only applicable to a pair of vectors. I would say there are four common types of "multiplication" involving scalars and 3D vectors:
  1. Scalar times scalar to produce a scalar (ordinary multiplication)
  2. Scalar times vector to produce a vector (scaling a vector)
  3. Vector times vector to produce a scalar (scalar or "dot" product)
  4. Vector times vector to produce a vector ("cross" product)
 
5. Scalar cross scalar to denote the pair (scalar,scalar). "Not valid" is misleading here.
6. Scalar cross vector also denotes a pair and no vector. If it is supposed to be a vector, the cross has to be explicitly defined, e.g as scaling.
 
fresh_42 said:
5. Scalar cross scalar to denote the pair (scalar,scalar). "Not valid" is misleading here.
You are interpreting AxB for scalars A and B in the sense of the Cartesian product of a pair of sets? [the set of ordered pairs (a,b) where a is an element of A and b is an element of B]. That is rather a stretch since A and B are not sets and their cross product would not be an ordered pair but would, rather, be a [possibly singleton] set of ordered pairs.
 
jbriggs444 said:
You are interpreting AxB for scalars A and B in the sense of the Cartesian product of a pair of sets? [the set of ordered pairs (a,b) where a is an element of A and b is an element of B]. That is rather a stretch since A and B are not sets and their cross product would not be an ordered pair but would, rather, be a [possibly singleton] set of ordered pairs.
Agreed. I simply found "not valid" a bit harsh, esp. because the word scalar has been put into brackets. Sometimes I've also read lines like ##2 \times 2 = 4##.
 
fresh_42 said:
Agreed. I simply found "not valid" a bit harsh, esp. because the word scalar has been put into brackets. Sometimes I've also read lines like ##2 \times 2 = 4##.
If one insists on intepreting ##\times## in the sense of the Cartesian product and interpreting 2 in the sense of set theory and the Von Neumann construction then it would be more correct to say that ##|2 \times 2| = 4## and that ##2 \times 2## = { (0,0), (0,1), (1,0), (1,1) }

This follows since, in the Von Neumann construction, 2 = {0,1}.

Bringing us back on topic for this thread... One should interpret the ##\times## notation according to context. In the context of ##2 \times 2## and a discussion of scalars and vectors, it cannot reasonably denote either a cross product of vectors or a Cartesian product of sets. The most reasonable interpretation would as an ordinary product of integers.
 
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Thank you all for your feedback.
The comments certainly help a lot.
 
stevendaryl said:
By "x" do you mean the vector cross-product? And by "." do you mean the vector scalar product? If the answer is yes, then those operations are only applicable to a pair of vectors. I would say there are four common types of "multiplication" involving scalars and 3D vectors:
  1. Scalar times scalar to produce a scalar (ordinary multiplication)
  2. Scalar times vector to produce a vector (scaling a vector)
  3. Vector times vector to produce a scalar (scalar or "dot" product)
  4. Vector times vector to produce a vector ("cross" product)
It works for 7D vectors as well.
 
Zafa Pi said:
It works for 7D vectors as well.

It works in any dimension with geometric algebra as well. Also, the 7D cross product is unsatisfactory: no Jacobi identify and it's not unique.
 

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