What are the possible values of the determinant of an orthogonal matrix?

In summary, the conversation discusses finding all possible values of the determinant of an orthogonal matrix. It is mentioned that the transpose of an orthogonal matrix is its inverse, and the determinant of a matrix is related to the determinant of its transpose. The conversation also mentions the theorem that det(AB) = det(A)det(B).
  • #1
salman213
302
1
Hi I had a final today and one of the questions was

find all the possible values of det Q if Q is a orthogonal matrix

I m still wondering how would I do this? Any ideas?
 
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  • #2
What is the definition of an orthogonal matrix?
 
  • #3
well i guess the vectors which make up the matrix are orthogonal and so have a dot product of 0?

and the transpose of an orthogonal matrix is its inverse


but I am not sure how to use this to find out all values of the determinant
 
  • #4
Ok, so you know the transpose of an orthogonal matrix is its inverse. So, we have [itex]M^TM=I[/itex]. Now, let's take the determinant of this; [itex]det(M^TM)=det(I)[/itex]. I presume you know what the right hand side is equal to. Now, what can one say about the relationship between the determinant of a matrix, and the determinant of its transpose?
 
  • #5
but how is the determinant of(M^TM) = det(M)

if M is a orthogonal matrix




by the way since you said det (i) its 1..right?

and I do know the det(M^t) = det (M)

but det (M^tM) = 1 and I am not understanding how that is = det (M)
 
  • #6
salman213 said:
and I do know the det(M^t) = det (M)

but det (M^tM) = 1 and I am not understanding how that is = det (M)

Right, so putting these two facts together we have det(M2)=1. Can you find det(M) from this expression?
 
  • #7
hmmm...salman213 perhaps this is the theorem you want

det(AB) = det(A)det(B)
 
  • #8
oh okk..cool..thanks
 

1. What is the concept of "Determinant of Orthogonal"?

The determinant of orthogonal is a mathematical concept that measures the scaling factor of a linear transformation in a vector space. It is used to determine how much a vector or set of vectors change in size or orientation after being transformed. In simpler terms, it is a way to quantify the distortion or stretching that occurs in a vector space.

2. How is the determinant of orthogonal calculated?

The determinant of orthogonal is calculated by taking the product of all the eigenvalues of the orthogonal matrix. An orthogonal matrix is a square matrix whose columns and rows are orthogonal unit vectors, meaning they are mutually perpendicular and have a length of 1. This product of eigenvalues is also equal to the volume of the parallelepiped defined by the transformed vectors.

3. What is the significance of the determinant of orthogonal?

The determinant of orthogonal has several important uses in mathematics and science. It is used in linear algebra to solve systems of linear equations, and it is also used in calculus to calculate the volume of an arbitrary region in space. In physics, it is used to determine the moment of inertia of a rigid body and in computer graphics, it is used to transform 3D objects.

4. How does the determinant of orthogonal relate to the concept of orthogonality?

The determinant of orthogonal and the concept of orthogonality are closely related. An orthogonal matrix is one in which all the columns and rows are orthogonal to each other. This means that the dot product of any two columns or rows will be zero. The determinant of orthogonal, as mentioned earlier, is calculated using the eigenvalues of an orthogonal matrix. So, the determinant of orthogonal is a way to quantify the orthogonality of a matrix.

5. Can the determinant of orthogonal be negative?

No, the determinant of orthogonal cannot be negative. Since an orthogonal matrix is made up of orthogonal unit vectors, the determinant is always positive or zero. This is because the product of all the eigenvalues will either be positive or zero, and the determinant is equal to this product. If the determinant is zero, it means that the transformation has no effect on the vectors, and if it is positive, it means that the vectors are stretched or rotated without being flipped.

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