final sample

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I. (15 points) Ture or False I. Only determine true or false. No explanation required. (a) A scalar multiple of an elementary matrix is still an elementary matrix. (b) The union of two subspaces of a vector space V is still a subspace. (c) If A M m×n (F ), then rank(A) m and rank(A) n. (d) If A M n×n (F ) has an eigenvalue 0 with multiplicity r, then rankA = n - r. (e) The basis of the zero vector space is {0}. (f) There is no onto linear transformation from F 10 to M 3×4 (F ). II. (15 points) True or False II. Determine true or false and give explanations (i.e., a sketch of proof or a counterexample). (a) If λ 1 2 are distinct eignevalues of a linear operator T, then E λ 1 E λ 2 = {0}. (b) If A M n×n (F ) and the sum of all row vectors of A is equal to 0 F n , then det A = 0. (c) If A, B M n×n (F ), then det(A + B) = det A + det B. III. (15 points) (a) Write down the definition of “A matrix A is invertible”. (b) Suppose A, B M n×n (R) and A is invertible. Let λ> 0. Prove that for λ sufficiently large, λA + B is an invertible matrix. IV. (15 points) (a) Write down the definition of subspaces. (b) Prove that the subset S M n×n (F ) consisting of n × n matrices A satisfying Tr(A) = 0 is a subspace of M n×n (F ). (c) What is the dimension of this subspace? When n = 2, give a basis of this subspace. V. (10 points) Calculate the determinant of A = -1 2+ a 3 1 - a a 1 3a 2 -1+ a . Here a is a complex number such that a 2 = -2. Your results may contain a. VI. (15 points) Let k be a real number. Consider the matrix A = 3 k - 1 k +1 1 M 2×2 (R). (0.1) (a) Calculate the characteristic polynomial of A. (b) For what values of k does A have distinct real eigenvalues? Prove your statement. (c) For what values of k is A diagonalizable (as real matrices)? 1

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  • I. (15 points) Ture or False I. Only determine true or false. No explanation required.

    (a) A scalar multiple of an elementary matrix is still an elementary matrix.

    (b) The union of two subspaces of a vector space V is still a subspace.

    (c) If A Mmn(F ), then rank(A) m and rank(A) n.(d) If A Mnn(F ) has an eigenvalue 0 with multiplicity r, then rankA = n r.(e) The basis of the zero vector space is {0}.(f) There is no onto linear transformation from F10 to M34(F ).

    II. (15 points) True or False II. Determine true or false and give explanations (i.e.,

    a sketch of proof or a counterexample).

    (a) If 1, 2 are distinct eignevalues of a linear operator T, then E1 E2 = {0}.(b) If A Mnn(F ) and the sum of all row vectors of A is equal to 0 Fn, then

    detA = 0.

    (c) If A,B Mnn(F ), then det(A+B) = detA+ detB.III. (15 points)

    (a) Write down the definition of A matrix A is invertible.

    (b) Suppose A,B Mnn(R) and A is invertible. Let > 0. Prove that for sufficiently large, A+B is an invertible matrix.

    IV. (15 points)

    (a) Write down the definition of subspaces.

    (b) Prove that the subset S Mnn(F ) consisting of n n matrices A satisfyingTr(A) = 0 is a subspace of Mnn(F ).

    (c) What is the dimension of this subspace? When n = 2, give a basis of this

    subspace.

    V. (10 points) Calculate the determinant of A =

    1 2 + a 3

    1 a a 13a 2 1 + a

    . Herea is a complex number such that a2 = 2. Your results may contain a.

    VI. (15 points) Let k be a real number. Consider the matrix

    A =

    3 k 1k + 1 1

    M22(R). (0.1)

    (a) Calculate the characteristic polynomial of A.

    (b) For what values of k does A have distinct real eigenvalues? Prove your statement.

    (c) For what values of k is A diagonalizable (as real matrices)?

    1

  • VII. (15 points) Let n 2. Prove that the determinant of

    A =

    x 0 0 0 a01 x 0 0 a10 1 x 0 a2...

    ......

    ......

    0 0 0 x an10 0 0 1 an

    M(n+1)(n+1)(F ). (0.2)

    is equal to anxn + an1x

    n1 + + a1x + a0. (Hint: Use induction on n 2. Let thedeterminant be f(n). Use cofactor expansion along the first column to find a relation

    between f(n) and f(n 1).)VIII*. (Optional, 10 bonus points) Suppose A,B Mmn(F ). Prove that rank(A+

    B) rank(A) + rank(B). (Hint: consider the column vectors of A + B, A, B and therelation between rank and the number of linearly independent column vectors.

    2