MATH 304 Linear Algebra Lecture 35: Matrix exponentials. • Initial value problem for a linear ODE: dy dt = 2y , y (0) = 3. Solution: y (t) = 3e 2t . • Initial value problem for a system of linear ODEs: ( dx = 2x + 3y , dt x(0) = 2, y (0) = 1. dy = x + 4y , dt The system can be rewritten in vector form d x 2 3 x . , where A = =A 1 4 y dt y 2 x(t) tA . =e Solution: 1 y (t) What is e tA ? Exponential function Exponential function: f (x) = exp x = e x , x ∈ R. Principal property: e x+y = e x · e y . x n x . Definition 1. e = lim 1 + n→∞ n 1 n ≈ 2.7182818. In particular, e = lim 1 + n→∞ n x2 xn Definition 2. e = 1 + x + + ··· + + ··· 2! n! x Definition 3. f (x) = e x is the unique solution of the initial value problem f ′ = f , f (0) = 1. Matrix exponentials Definition. For any square matrix A let 1 1 exp A = e A = I + A + A2 + · · · + An + · · · 2! n! Matrix exponential is a limit of matrix polynomials. Remark. Let A(1) , A(2) , . . . be a sequence of n×n (n) matrices, A(n) = (aij ). The sequence converges to (n) an n×n matrix B = (bij ) if aij → bij as n → ∞, i.e., if each entry converges. Theorem The matrix exp A is well defined, i.e., the series converges. Properties of matrix exponentials Theorem 1 If AB = BA then e A e B = e B e A = e A+B . Corollary (a) e tA e sA = e sA e tA = e (t+s)A , t, s ∈ R; (b) e O = I ; (c) (e A )−1 = e −A . Theorem 2 d tA e = Ae tA = e tA A. dt tn n t2 2 Indeed, e = I + tA + A + · · · + A + · · · , 2! n! and the series can be differentiated term by term. t n−1 d tn d tn n n A = = A An . dt n! dt n! (n − 1)! tA Lemma Let A be an n×n matrix and x ∈ Rn . Then the vector function v(t) = e tA x satisfies v′ = Av. d dv = e tA x = Ae tA x = A e tA x = Av. Proof: dt dt Theorem For any t0 ∈ R and x0 ∈ Rn the initial value problem dv = Av, v(t0 ) = x0 dt has a unique solution v(t) = e (t−t0 )A x0 . Indeed, v(t) = e (t−t0 )A x0 = e tA e −t0 A x0 = e tA x, where x = e −t0 A x0 is a constant vector. Evaluation of matrix exponentials Example. A = diag(a1 , a2 , . . . , ak ). An = diag(a1n , a2n , . . . , akn ), n = 1, 2, 3, . . . e A = I + A + 2!1 A2 + · · · + n!1 An + · · · = diag(b1 , b2 , . . . , bk ), where bi = 1 + ai + 2!1 ai2 + 3!1 ai3 + · · · = e ai . Theorem 1 If A = diag(a1 , a2 , . . . , ak ) then e A = diag(e a1 , e a2 , . . . , e ak ). e tA = diag(e a1 t , e a2 t , . . . , e ak t ). Theorem 2 If A = UBU −1 , then e tA = Ue tB U −1 . Example. A = 2 3 . 1 4 The eigenvalues of A: λ1 = 1, λ2 = 5. 3 1 Eigenvectors: v1 = , v2 = . −1 1 Therefore A = UBU −1 , where 3 1 1 0 , U= . B= 0 5 −1 1 Then −1 t 3 1 3 1 e 0 e tA = Ue tB U −1 = −1 1 −1 1 0 e 5t t 5t t 3e e 3e + e 5t −3e t + 3e 5t 1 1 −1 1 = =4 . −e t e 5t 4 1 3 −e t + e 5t e t + 3e 5t Problem. Solve a system of differential equations ( dx dt = 2x + 3y , dy dt = x + 4y subject to initial conditions x(0) = 2, y (0) = 1. The unique solution: x(t) 2 = e tA x0 , where A = y (t) 1 t 3e + e 5t −3e t e tA = 41 −e t + e 5t et ( x(t) = 43 e t + 54 e 5t , =⇒ y (t) = − 14 e t + 54 e 5t . 3 2 , x0 = . 4 1 + 3e 5t + 3e 5t 0 1 0 Example. A = 0 0 1, a Jordan block. 0 0 0 0 0 1 2 A = 0 0 0, A3 = O, An = O for n ≥ 3. 0 0 0 1 1 12 1 e A = I + A + A2 = 0 1 1, 2 0 0 1 1 t 21 t 2 2 t e tA = I + tA + A2 = 0 1 t . 2 0 0 1 1 1 Example. A = , another Jordan block. 0 1 1 2 1 3 1 n A2 = , A3 = , An = . 0 1 0 1 0 1 tn n t2 2 a(t) b(t) tA , e = I +tA+ A + · · · + A + · · · = 0 a(t) 2! n! where a(t) = 1 + t + 2 3 t2 2! + t3 3! + · · · = et, b(t) = t + 2 t2! + 3 t3! + · · · = te t . t t e te Thus e tA = . 0 et λ 1 Example. A = , a general Jordan block. 0 λ 0 1 We have that A = λI + B, where B = . 0 0 Since (λI )B = B(λI ), it follows that e A = e λI e B . Similarly, e tA = e tλI e tB . λt e 0 e tλI = = e λt I , 0 e λt 1 t . B 2 = O =⇒ e tB = I + tB = 0 1 λt λt e te Thus e tA = e tλI e tB = . 0 e λt Problem. Solve a system of differential equations ( dx dt = 2x + y , dy dt = 2y subject to initial conditions x(0) = y (0) = 1. The unique solution: x(t) 2 1 1 = e tA x0 , where A = , x0 = . y (t) 0 2 1 2t 2t e te 1 t e tA = = e 2t 2t 0 e 0 1 ( x(t) = e 2t (1 + t), =⇒ y (t) = e 2t .