Coordinates, vector spaces and linear transformations Flashcards

1
Q

Describe orthogonal vectors

A

2 vectors are orthogonal to each other if they are perpendicular, ie if their dot product = 0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Define orthonormal

A

A set of vectors are orthonormal/form an orthonormal basis if all vectors have a magnitude of 1 and if they are all orthogonal to one another

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Give the 2x2 matrix that rotates a vector α degrees anti-clockwise

A
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Describe the determinant of a matrix product

A

For any square matrix, det(AB) = det(A) x det(B)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Give the equation for the cofactor, cij of an element aij

A

Where Mij (or minor) is the matrix left over when the elements in row i and column j have been removed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Define the Jacobian

A

|J| (the determinant of the transformation matrix J) is the Jacobian, which gives the factor by which the volume element changes in a transformation.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Describe 6 properties of determinants

A

1) Swapping rows and columns does not change the determinant
2) A determinant vanishes if one of the rows or columns contains only zeroes
3) If a row or column is multiplied by a constant, the determinant will also be multiplied by that constant.
4) A determinant vanishes if two rows or columns are multiples of each other
5) If we interchange a pair of rows or columns the determinant changes sign
6) Adding a multiple of one row or column to another doesn’t change the value of the determinant

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Describe the transpose of a matrix, A

A

AT is obtained by switching the rows for columns. Starting with an m x n matrix, an n x m will be obtained.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Describe the transposition of matrix products

A

Transposing a product of matrices reverses the order of multiplication, despite how many elements are involved. (ABC)T = CTBTAT

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Describe symmetrical matrices

A

If AT = A, A is symmetric.

If AT = -1, A is antisymmetric.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Describe the product of orthogonal matrices

A

If A and B are orthogonal matrices, their product, C = AB will also be an orthogonal matrix

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Describe how to take the complex conjugate of a matrix

A

Take the complex conjugate of each element. (A*)ij = a*ij

Note: if A = A*, the matrix is real

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Describe hermitian conjugation

A

Also known as the Hermitian adjoint and represented by a superscript dagger (), it is a combination of complex conjugation and transposition, in either order: A = (AT)* = (A*)T

If A = A, A is Hermitian

If A = -A, A is anti-Hermitian

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Describe how to work out the Hermitian conjugate of a matrix product

A

(AB) = BA

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Describe the trace of a matrix

A

The trace of a matrix is the sum of all diagonal elements.

Tr(A) = a11 + a22 + a33 + ….

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Describe how to work out the determinant of a matrix A

A

Multiply each element of one row or column by its cofactor and add the results. Eg for a 3x3 matrix, the determinant can be calculated by working out a11c11 + a12c12 + a13c13

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Describe the inverse of a matrix A

A

The inverse of a matrix, defined as A-1 is given such that AA-1 = I

C is the matrix made up of the cofactors of A. CT is known as the adjoint matrix to A, denoted by Aadj

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Describe the Kronecker delta, δij

A
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Describe a unitary matrix

A

A square matrix U is unitary if UU = UU = I

20
Q

Describe linearly dependent vectors

A

A set of vectors X1, X2,…, Xn are linearly dependent if constants ci cant be found (not all zeroes) such that c1X1 + c2X2 + … + cnXn = 0. If no such constants exist, then Xi are linearly independent.

21
Q

Give the equation of a diagonalised matrix

A

D = L-1ML

M is the diagonalisable matrix

L is the matrix whose columns are the eigenvectors of M

22
Q

Give the equation for the diagonalisable matrix M to any power

A

Mn = LDnL-1

23
Q

Describe a normal matrix

A

A matrix is described as normal if MM = MM

24
Q

Give the equation for the inverse of a matrix

A

Where C is the matrix made up of the cofactors of A. C is knowns as the adjoint matrix to A, Aadj

25
Q

State a property of all normal matrices

A

All normal matrices are all diagonalisable. Unitary, orthogonal, hermitian, and real symmetric matrices are all normal and hence diagonalisable

26
Q

Describe a hermitian matrix

A

A square matrix H is said to be hermitian if H= H

27
Q

Describe a real and symmetric matrix

A

A matrix is real and symmetric if its entries are real and ST = S

28
Q

Describe an orthogonal matrix

A

A square matrix O is orthogonal if it has real entries and OTO = OOT = I

29
Q

Give the compact equation for finding the factor by which the volume element changes when we make a transformation.

A

dr’ = Jdr

30
Q

Describe how to test for linear dependence using determinants

A

The column vectors in question can be written as a matrix - columns forming columns. The determinant of this matrix M is taken.

If det(M) = 0, the vectors are linearly depedent

If det(M) ≠ 0, the vectors are linearly independent

31
Q

Give the equation needed to work out eigenvectors

A

Mv = λv

32
Q

Give the determinant of a 2x2 matrix A

A

DetA = a11a22-a12a21

33
Q

Give the characteristic equation used to find eigenvalues

A
34
Q

Define a diagonal matrix

A

A square matrix with elements only along the diagonal

35
Q

Describe Cramer’s rule

A
36
Q
A
37
Q
A
38
Q
A
39
Q
A
40
Q
A
41
Q
A
42
Q
A
43
Q
A
44
Q
A
45
Q
A