Exploring the Properties of Scalar Product & Law of Cosines

In summary, the conversation discusses the definition of the Scalar Product and the Law of Cosines, as well as the introduction of a new operation called ##\circ##. However, the derivation using this operation is incorrect due to assumptions of linearity and commutativity. It is important to prove the properties of any new operation before applying basic arithmetic rules.
  • #1
Devil Moo
44
1
Scalar Product is defined as ##\mathbf A \cdot \mathbf B = | \vec A | | \vec B | \cos \theta##.

With the construct of a triangle, the Law of Cosines is proved.
##\mathbf A## points to the tail of ##\mathbf B##.
Well, ##\mathbf C## starts from the tail of ##\mathbf A## and points to somewhere.
Finally, ##\mathbf B## points to the head of ##\mathbf C##.

Now someone defines a new operation such as ##\mathbf A \circ \mathbf B = | \vec A | | \vec B | \sin \theta##. Following the same steps of proving the Law of Cosines.

##\begin{align}
\mathbf C & = \mathbf A + \mathbf B \nonumber \\
\mathbf C \circ \mathbf C & = (\mathbf A + \mathbf B) \circ (\mathbf A + \mathbf B) \nonumber \\
| \vec C | | \vec C | \sin 0 & = | \vec A | | \vec A | \sin 0 + | \vec B | | \vec B | \sin 0 + 2 | \vec A | | \vec B | \sin \theta \nonumber \\
| \vec A | | \vec B | \sin \theta & = 0 \nonumber
\end{align}##

##\theta = 0##, ##\mathbf A = 0## or ##\mathbf B = 0##?

I am not quite understand what the result means. It seems the result is not consistent with the constructed triangle.
 
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  • #2
How is the angle defined? In the usual scalar product, this isn't important, because ##\cos (\theta)=\cos (-\theta).##
This changes with the sine. I have the feeling that this could be a problem when adding ##|A||B|\sin(\theta)## and ##|B||A|\sin(\theta)## and pretend it would be commutative. Also the distributive property has to be proven.
 
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  • #3
fresh_42 said:
Also the distribution law has to be proven.
Which is impossible, because the operation is not distributive.

The assumption of commutativity is the other mistake in post #1.
 
  • #4
This derivation is incorrect, because you assumed the operation you have defined ##\circ##, is linear, in order to go from the second step to the third. Instead we have the identity.
$$
\mathbf A \times \mathbf B=(\mathbf A \circ \mathbf B) \mathbf n
$$
where ##\mathbf n## is a unit vector perpendicular to both ##\mathbf A## and ##\mathbf B##, in the direction obtained from the right-hand rule (in the case ##\mathbf A=\mathbf B##, you may pick any ##\mathbf n##). Then, if ##\mathbf C = \mathbf A + \mathbf B##,
$$
\mathbf C \times \mathbf C = (\mathbf A + \mathbf B) \times (\mathbf A + \mathbf B)
$$
Now the cross product ##\times## is linear, but you also get terms ##\mathbf A \times \mathbf B## and ##\mathbf B \times \mathbf A##, which cancel by a property of the cross product. So in the end you get
$$
\mathbf C \times \mathbf C = \mathbf A \times \mathbf A + \mathbf B \times \mathbf B
$$
Which just says that ##0=0+0##.

Another way to see that your conclusion does not hold, is simply to see that ##\mathbf A \times \mathbf B## is non-zero in general, so by taking the magnitude, we find that ##|\mathbf A \circ \mathbf B|## is non-zero in general, and hence ##\mathbf A \circ \mathbf B## is non-zero in general.
 
  • #5
fresh_42 said:
How is the angle defined?
Now it is defined as the angle between ##\mathbf A## and ##\mathbf B## where ##\theta## is smaller than or equal to ##\pi## and it is commutative.

mfb said:
Which is impossible, because the operation is not distributive.
How do you find out that it is not distributive?

Lucas SV said:
Another way to see that your conclusion does not hold, is simply to see that ##\mathbf A \times \mathbf B## is non-zero in general, so by taking the magnitude, we find that ##|\mathbf A \circ \mathbf B|## is non-zero in general, and hence ##\mathbf A \circ \mathbf B## is non-zero in general.
Um... How are these two examples related to the derivation?
 
  • #6
Devil Moo said:
How do you find out that it is not distributive?
By looking at an example.
$$A = \begin{pmatrix} 1 \\ 0 \\ 0 \end{pmatrix}, B = \begin{pmatrix} -1 \\ 0 \\ 0 \end{pmatrix}, C = \begin{pmatrix} 0 \\ 1 \\ 0 \end{pmatrix}$$
$$(A+B) \circ C = 0 \neq A \circ C + B \circ C$$
 
  • #7
If you object, that you only need ##A \circ (A+B) = A \circ B## then compute it with ##A=(1,2)\, , \, B=(1,3)##.
 
  • #8
fresh_42 said:
If you object, that you only need ##A \circ (A+B) = A \circ B## then compute it with ##A=(1,2)\, , \, B=(1,3)##.
Huh?
That works, but this is not the only operation that was used in post 1.
 
  • #9
So if we have to define something, we have to calculate these laws before applying using the basic arithmetic rules.
 
  • #10
You may define whatever you want.

1.) As long as it is well-defined.
This wasn't the case in your first attempt, because you assigned two possible values ##|A||B| \sin(\theta)## and ##|A||B| \sin(-\theta)## to ##A \circ B##. A definition is not allowed to be ambiguous.

If this is given, it is absolutely legitimate to define, e.g. an operation ##\circ##. But the next steps should then be to try and find out, which properties such an operation has. This includes algebraic rules it obeys. There might be new formulas, known ones that are partially true or even totally true, ones which would be nice to have but don't hold and so on.

2.) Any "basic rule" has to be proven before it is allowed to be applied.
This means that rules you may be used to by arithmetic from real numbers are not automatically true in the context of your new operation. Therefore they have to be proven first. E.g. matrix multiplication isn't commutative, squares of complex numbers aren't positive and so on.
You gave an example yourself: ##A \circ A = 0## although ##A \neq 0##.

3) You might not need the entire basic rule.
E.g. you didn't need distribution in all cases for your argument. Only in some special cases. Therefore you didn't need to prove distribution, merely the ones you actually use. However, it doesn't hold even in these cases.

4.) You may summarize the above as follows: well-definition - toolbox - theorems.
 
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Likes Lucas SV

1. What is the scalar product and how is it calculated?

The scalar product, also known as the dot product, is a mathematical operation that takes two vectors and returns a scalar value. It is calculated by multiplying the corresponding components of the two vectors and then adding the products together.

2. What are the properties of scalar product?

The properties of scalar product include commutativity, distributivity, and associativity. Commutativity means that the order of the vectors does not matter in the calculation. Distributivity means that the scalar product of a vector with the sum of two other vectors is equal to the sum of the scalar products of the first vector with each of the other two vectors. Associativity means that the scalar product of a vector with the sum of two other vectors is equal to the sum of the scalar products of the first vector with each of the other two vectors.

3. What is the Law of Cosines and how is it used?

The Law of Cosines is a mathematical formula that relates the lengths of the sides of a triangle to the cosine of one of its angles. It is used to find the missing side or angle of a triangle when the other two sides and an angle are known. The formula is c² = a² + b² - 2ab cosC, where c is the length of the side opposite angle C, and a and b are the lengths of the other two sides.

4. Can the scalar product and Law of Cosines be used in any type of triangle?

Yes, the scalar product and Law of Cosines can be used in any type of triangle, including acute, right, and obtuse triangles. However, the calculations may vary slightly depending on the type of triangle.

5. How are the scalar product and Law of Cosines related?

The scalar product is used in the Law of Cosines to find the cosine of a triangle's angle. In turn, the Law of Cosines can also be used to find the scalar product of two vectors by using the formula c² = a² + b² - 2ab cosC and solving for the cosine term.

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