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IAS PYQs 3

We will cover following topics

1988

1) Show that a linear transformation of a vector space Vm of dimension m into a vector space Vn of dimension n over the same field can be represented by a matrix. T is linear transformation of v2 into v4 such that T(3,1)=(4,1,2,1), T(1,2)=(3,0,2,1) find the matrix of T.


2) Determine a basis of the subspace spanned by the vectors v1=(1,2,3), v2=(2,1,1), v3=(1,1,4), v4=(4,2,2).


3) Show that it is impossible for any 2×2 real symmetric matrix of the form [a1bba2](b0) to have identical eigen values.


4) Prove that the eigen values of a Hermitian matrix are all real and that an eigen value of a skew Hermitian matrix is either zero or a pure imaginary number.


5) By converting A to an echelon matrix, determine the rank of

A=[001289004653023147030937005731]

6) Given AB=AC does it follow that B=C? Can you provide a counter example?


7) Find a non- singular transformation of three variables which simultaneously diagonalizes.

A=[010111010]
B=[212122223]

Give the diagonal form of A.

1987

1.(i) Find all matrices which commute with the matrix [7352]

1.(ii) Prove that the product of two n×n symmetric matrices is a symmetric matrix, if and only if the matrices commute.


2) Show that the rank of the product of two square matrices A,B each of order n, satisfies the inequality rA+rnnrABmin(rA,rB), where r0 stands for the rank of a square matrix C.


3) If 1"a5, find the rank of the matrix (1111132a22a2a23a13a+232a+1)

TBC


4) If the eigen values of a matrix A are λj,j=1,2..n and if f(x) is a polynomial in x, show that the eigen values of the matrix, f(A) are f(λj),j=1,2n.


5) If A is a skew symmetric matrix and I, the corresponding unit matrix, show that (IA)(I+A)1 is orthogonal. Hence construct an orthogonal matrix, if A=(0a/ba/b0)


6) (i) If A,B are two arbitrary square matrices of which A is non-singular, show that AB and BA have the same characteristic polynomial.

(ii) Show that a real matrix A is orthogonal, if and only if |Ax|=|x| for all real vectors x.


7) Show that a necessary and sufficient condition for a system of Linear equations to be consistent is that the rank of the coefficient matrix is equal to the rank of the augmented matrix. Hence show that the system x+2y+5z+9=0, xy+3z2=0, 3x6yz25=0 is consistent and has a unique solution. Determine this solution.


8) In an n-dimensional vector space the system of vectors aj,j=1,2r are linearly independent and can be linearly expressed to terms of the vectors βk,k=1,2,,s. show that rs.

Find a maximal linearly independent subsystem of the system of linear forms f1=x+2y+z+3t, f2=4xy5z6t, f3=x3y4z7t, f4=2x+yz.


9) Let T: VW be a linear transformation. If V is finite dimensional then, show that rank (T) + nullity (T)=dimV.


10) Prove that two finite dimensional vector spaces V and W over the same field F are isomorphic if they are of the same dimension n.


11.(a) Prove that every square matrix is a root of its characteristic polynomial.

11.(b) Determine the eigen values and the corresponding eigen vectors of A=[221131122]


12) Let A and B be n - square matrices over F. show that AB and BA have the same eigen values.

1986

1) If A, B, C are three n×n matrices, show that A(BC)=(AB)C. Show by an example that the matrix multiplication is non-commutative.


2) Examine the correctness or otherwise of the statements:

(i) The division law is not valid in matrix algebra.

(ii) If A, B are square matrices each of order n and I is the corresonding unit matrix, the equation ABBA=I can never hold.


3) Find a 3×3 matrix X such that

[122130021]X=[101010011] may hold.


4) Find a maximal linearly independent subsystem in the system of vectors:

V1=(2,2,4), V2=(1,9,3), V3=(2,4,1) and V4=(3,7,1).


5) Show that the system of equations
4x+y2z+w=3 x2yz+2w=2 2x+5yw=1 3x+3yz3w=1 although consistent, is not uniquely solvable. Determine the general solution by choosing x as a parameter.


6) Show that
(i) a square matrix is singular, iff, atleast one of its characteristic roots (i.e., eigen values) is zero.
(ii) the rank of an n×n matrix A remains unchanged, if A is pre-multiplied or post-multiplied by a non-singular n×n matrix X and that rank (X1AX)=rank A. Prove that V is a vector space over K.


7) Find all the eigenvalues and a basis for each eigen space for the matrix [133353664].


8) Prove that every square matrix satisfies its own characteristic equation.


9) Prove that the rank of the product of two matrices cannot exceed the rank of either of them.


10) If M, N are two subspaces of a vector space S, show that their dimensions satisfy.

dim(M)+dim(N)=dim(MN)+dim(M+N)

11) Let V and W be vector spaces over the same field F and dimV=n, let {e1,e2,,en} be a basis of V. Show that a map f: {e1,e2,,e0}W can be uniquely extended to a linear transformation T: VW, whose restriction to the given basis {e} is f, that is T(ej)=f(e); j=1,2,,n.


12.(i) If A and B are two linear transformations on the space, and if A1 and B1 exist, then show that (AB)1 exists and (AB)1=B1A1.

12.(ii) Prove that similar matrices have the same characteristic polynomial and hence the same eigen values.

12.(iii) Prove that the eigen values of a Hermitian matrix are real.


13) Reduce 2x2+4xy+5y2+4x+13y1/2=0 to canonical form

(i) Find reciprocal of the matrix T=[011101110]

, show that the transform of the matrix A=12[b+ccabacbc+aabbcaca+b] by T, i.e. TAT is the diagonal matrix. Determine the eigen values of the matrix A.

1985

1) Let M1=(1000),M2=(0100),M3=(0010), M4=(0001) prove that the set {M1,M2,M3,M4} form the basis of the vector space of 2×2 matrices.


2) Find the inverse of the matrix (133143134).


3) Consider the basis S={V1,V2,V3} of R3, where V1=(1,1,1), V2=(1,1,0), V3=(1,0,0). Express (2,3,5) in terms of the basis V1, V2, V3. Let T:R3R2 be defined as T(V1)=(1,0), T(V2)=(2,1), T(V3)=(4,3). Find T(2,3,5).


4) Reduce the matrix to echelon form [634416125].


5) Show that if λ is an eigen value of matrix A then λn is an eigen value of An if n is a positive integer.


6) Determine the vectors (1,2,1), (2,1,1), (7,4,1) in R3 are linearly independent.


7) Solve

2x1+3x2+x3=9
x1+2x2+3x3=6
3x1+x22x3=8


8) Let V be the vector space of all functions from R in to R; let ve be the subset of even functions f, f(x)=f(x), and v0 be the subset of odd functions f f(x)=f(x). Prove that
(i) ve and v0 are subspaces of v
(ii) ve+v0=v
(iii) vev0={0}


9) Find the dimension and a basis of the solution space S of the system

x1+2x2+2x3x4+3x5=0
x1+2x2+3x3+x4+x5=0
3x1+6x2+8x3+x4+5x5=0


10) Let w1 and w2 be subspaces of a finite dimensional vector space V. Prove that (w1+w2)0=w10w20.


11) Prove that every matrix is a zero of its characteristic polynomial.


12) If A is an orthogonal matrix and if B=AP, where P is non-singular, then prove that PB1 is orthogonal.

1984

1) If w1 and w2 are finite-dimensional subspaces of a vector space v then show that w1+w2 is finite dimensional and

dimw1+dimw2=dim(w1w2)+dim(w1+w2)

2) Show that row equivalent matrices have the same rank.


3) A linear transformation T of a vector space V with finite basis {α1,α2,αn} is non-singular iff the vectors α1T,..αnT are linearly independent in V. When this is the case, show that T has a linear inverse, T1, with TT1=T1 T=I.


4) Solve the following system of equations:

3x1+2x2+2x35x4=8
2x1+5x2+5x318x4=9
4x1x2x3+8x4=7


5) Let A be a square matrix and T be non-singular. Let A~=T1AT. Show that
(i) A and A~ have the same eigen values
(ii) Trace A=T trace A~
(iii) If X be an eigen vector of A corresponding to an eigen value then T1X is a eigen vector of A~ corresponding to the same eigen value.


6) A 3×3 matrix has the eigen values λ1=6, λ2=2, and λ3=1 and the corresponding eigen vectors are (232), (954), (441). Find the matrix.


7) Let V be the set of all functions from a non-empty set X into a field K, for any functions f,gv and any scalar kK, let (f+g) and kf be the functions in v defined as follows:

(f+g)(x)=f(x)+g(x),(kf)(x)=kf(x) for every xX.


8) Find all the eigenvalues and a basis for each eigen space for the matrix (133353664).


9) Prove that every square matrix satisfies its own characteristic equation.


10) Prove that the rank of the product of two matrices cannot exceed the rank of either of them.

1983

1) Let V be a finitely generated vector space. Show that V has a finite basis and any two bases of V have the same number of vectors.


2) Let V be the vector space of polynomials of degree 3. Determine whether the following vectors of V are linearly dependent or independent: u=t33t2+5t+1, v=t3t2+8t+2, w=2t34t2+9t+5.


3) For any linear transformation T:V1V2, prove that rank(T)= min(dimV1,dimV2).


4) Show that every non-singular matrix can be expressed as a product of elementary matrices.


5) Reduce the matrix [012112323113] to its normal form and hence or otherwise determine its rank.


6) Show that the equations
x+y+z=3
3x5y+2z=8
5x3y+4z=14 are consistent and solve them.


7) Prove that every square matrix satisfies its characteristic equation. Use this result to find the inverse of [012123311].


8) Find the eigen values and eigen vectors of the matrix [862674243].


9) Show that the characteristic roots of an upper or lower triangular matrix are just the diagonal elements of the matrix.


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