Linear Algebra Flashcards

1
Q

What does Sylvestors criterion determine?

A

If a matrix is positive-definite

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2
Q

What 3 things are equivalent in terms of if A is diagonalisable?

A

A is similar to D
The eigen values of A are distinct
A is real, symmetric

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3
Q

A and B are similar if there exists an invertible matrix M such that…

A

A=M^-1BM
A and B will have the same eigenvalues

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4
Q

K vectors in Rn. If k>n, k=n, k<n

A

k>n = not linearly independent
k<n = don’t span
k=n then if basis then matrix non singular

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5
Q

Dim V =

A

The cardinality of any basis for V

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6
Q

If u1,u2,..,uk are in v, then the span(u1,…,uk) is

A

A subspace of v

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7
Q

Subspace criteria

A

Existence of origin
Closure under addition
Closure under scalar multiplication

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8
Q

Properties of groups

A

Closure under .
Associativity
Identity
Inverse

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9
Q

Two groups are isomorphic if

A

There exists a bijection between the groups preserving group operation

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10
Q

Lagrange for groups

A

If H is a subgroup of G then |H| divides |G|

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11
Q

Direct product

A

= every possible pair of elements, one from each group

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12
Q

Sign of a permutation

A

+1 if sigma is the product of an even number of transpositions
-1 if an odd number

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13
Q

If T is a linear map then the following are equivalent

A

ket(T)=0
T is injective
If v1,v2,..,vk are LI in v then T(v1),T(v2),…,T(vk) are LI in w

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14
Q

Symmetric group sn

A

Elements are all the permutations on n distinct symbols
|Sn|= n!

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15
Q

Transposition

A

A permutation that exchanges 2 elements and leaves the rest alone

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16
Q

Alternating group

A

Subset of Sn containing all even permutations
|An|= n!/2

17
Q

Permutation of a set

A

A bijection to itself

18
Q

If L is hermitean then <Lv,v> is real

A

If L is anti-hermitean then <Lv,v> is purely imaginary

19
Q

Basis

A

= LI and span

20
Q

rank and nullity = k

A

rk(A) = number of leading 1’s in RREF
nullity(A) = number of columns in RREF without a leading 1

21
Q

dimU+dimV=

A

dim(U+V)+dim(U intersect W)

22
Q

If V is the direct sum of U and W then

A

If u1,uk basis of U and w1,wp basis for w then u1,uk,w1,wp basis for v
dimV=dimU+dimW
each v can be written uniquely as v=u+w

23
Q

Area of a triangle with vertices a,b,c

A

1/2 |det(b-a,c-a)|

24
Q

Scalar triple

A

a dot bxc

25
Q

If u is the orthogonal projection of v onto U then

A

||u||^2<=||v||^2

26
Q

Bessel’s inequality

A

If u1,…,unis an orthonormal basis for u and v= k1u1+k2u2+…knun then
the sum of ki^2 <=||v||^2

27
Q

If u0 is the orthogonal projection of v0 onto U then for all u

A

||u-v0||>=||u0-v0||

28
Q

Projection operator P:V to V

A

im(P) = U ker(P) = U complement thing
P^2=P
P(u)=u
(I-P)P=P(I-P)=0
P(v)= (v,u1)u1 +..+(v,uk)uk where ui is an orthonormal basis of U

29
Q

V = direct sum of U and U orthogonal complement

A
30
Q

U orthogonal complement =

A

{v in V: (u,v)=0 for all u in U}

31
Q

Pythagoras

A

||u+v||^2 = ||u||^2+||v||^2

32
Q

Real cauchy-schwartz inequality

A

(u,v)^2<=(u,u)(v,v)

33
Q

Complex IP

A

<u,v>= conjugate of <v,u>

34
Q

Basis =

A

maximal LI set
minimal spanning set
any u in v can be written as a sum of the vectors

35
Q

Nullspace/kernel

A

Solution space to Ax=0

36
Q

Rowspace

A

A^ty= c has a solution

37
Q

Columnspace

A

Ax=b has a solution

38
Q

Solving differential equations

A

-write as a matrix
-diagonalise A=MDM
-x= Mw
-w dot = Dw
-solve e
-use x=Mw to get back to x