Consider a general system of linear ODE with two variables.
X ˙ ( t ) = A X ( t ) \dot{X}(t)=AX(t) X ˙ ( t ) = A X ( t ) , X ∈ R 2 X\in R^2 X ∈ R 2 , A ∈ M ( 2 , R ) A\in M(2,R) A ∈ M ( 2 , R )
The solution can be expressed via exponent of the matrix ( A t ) (At) ( A t ) :
X ( t ) = e A t X ( 0 ) X(t)=e^{At}X(0) X ( t ) = e A t X ( 0 ) , where e A t = ∑ n = 0 + ∞ t n n ! A n e^{At}=\sum\limits_{n=0}^{+\infty}\frac{t^n}{n!}A^n e A t = n = 0 ∑ + ∞ n ! t n A n
2. Let A = ( − 1 3 − 3 5 ) A=\begin{pmatrix}-1 & 3 \\ -3 & 5\end{pmatrix} A = ( − 1 − 3 3 5 ) . The characteristic polinomial of A is λ 2 − 4 λ + 4 = ( λ − 2 ) 2 \lambda^2-4\lambda+4=(\lambda-2)^2 λ 2 − 4 λ + 4 = ( λ − 2 ) 2 .
By the Cayley–Hamilton theorem we have ( A − 2 I ) 2 = 0 (A-2I)^2=0 ( A − 2 I ) 2 = 0 . Then
e A t = e 2 t I e ( A − 2 I ) t = e 2 t ∑ n = 0 + ∞ t n n ! ( A − 2 I ) n = e 2 t ( I + t ( A − 2 I ) ) e^{At}=e^{2tI}e^{(A-2I)t}=e^{2t}\sum\limits_{n=0}^{+\infty}\frac{t^n}{n!}(A-2I)^n=e^{2t}(I+t(A-2I)) e A t = e 2 t I e ( A − 2 I ) t = e 2 t n = 0 ∑ + ∞ n ! t n ( A − 2 I ) n = e 2 t ( I + t ( A − 2 I ))
e A t = e 2 t ( 1 − 3 t 3 t − 3 t 1 + 3 t ) e^{At}=e^{2t}\begin{pmatrix}1-3t & 3t \\ -3t & 1+3t\end{pmatrix} e A t = e 2 t ( 1 − 3 t − 3 t 3 t 1 + 3 t )
Answer . X ( t ) = e A t X ( 0 ) = e 2 t ( 1 − 3 t 3 t − 3 t 1 + 3 t ) X ( 0 ) X(t)=e^{At}X(0)=e^{2t}\begin{pmatrix}1-3t & 3t \\ -3t & 1+3t\end{pmatrix}X(0) X ( t ) = e A t X ( 0 ) = e 2 t ( 1 − 3 t − 3 t 3 t 1 + 3 t ) X ( 0 ) .
3. Let A = ( 4 − 5 5 − 4 ) A=\begin{pmatrix}4 & -5 \\ 5 & -4\end{pmatrix} A = ( 4 5 − 5 − 4 ) . The characteristic polinomial of A is λ 2 + 9 = 0. \lambda^2+9=0. λ 2 + 9 = 0.
By the Cayley–Hamilton theorem we have A 2 + 9 I = 0 A^2+9I=0 A 2 + 9 I = 0 , i.e. A 2 = − 9 I A^2=-9I A 2 = − 9 I . Then
e A t = ∑ n = 0 + ∞ t 2 n ( 2 n ) ! A 2 n + ∑ n = 0 + ∞ t 2 n + 1 ( 2 n + 1 ) ! A 2 n + 1 = ∑ n = 0 + ∞ ( − 9 ) n t 2 n ( 2 n ) ! I + ∑ n = 0 + ∞ ( − 9 ) n t 2 n + 1 ( 2 n + 1 ) ! A = ∑ n = 0 + ∞ ( − 1 ) n ( 3 t ) 2 n ( 2 n ) ! I + 1 3 ∑ n = 0 + ∞ ( − 1 ) n ( 3 t ) 2 n + 1 ( 2 n + 1 ) ! A = cos ( 3 t ) I + 1 3 sin ( 3 t ) A e^{At}=\sum\limits_{n=0}^{+\infty}\frac{t^{2n}}{(2n)!}A^{2n}+\sum\limits_{n=0}^{+\infty}\frac{t^{2n+1}}{(2n+1)!}A^{2n+1}=\sum\limits_{n=0}^{+\infty}\frac{(-9)^n t^{2n}}{(2n)!}I+\sum\limits_{n=0}^{+\infty}\frac{(-9)^nt^{2n+1}}{(2n+1)!}A=\sum\limits_{n=0}^{+\infty}(-1)^n \frac{(3t)^{2n}}{(2n)!}I+\frac{1}{3}\sum\limits_{n=0}^{+\infty}(-1)^n\frac{(3t)^{2n+1}}{(2n+1)!}A=\cos(3t)I+\frac{1}{3}\sin(3t)A e A t = n = 0 ∑ + ∞ ( 2 n )! t 2 n A 2 n + n = 0 ∑ + ∞ ( 2 n + 1 )! t 2 n + 1 A 2 n + 1 = n = 0 ∑ + ∞ ( 2 n )! ( − 9 ) n t 2 n I + n = 0 ∑ + ∞ ( 2 n + 1 )! ( − 9 ) n t 2 n + 1 A = n = 0 ∑ + ∞ ( − 1 ) n ( 2 n )! ( 3 t ) 2 n I + 3 1 n = 0 ∑ + ∞ ( − 1 ) n ( 2 n + 1 )! ( 3 t ) 2 n + 1 A = cos ( 3 t ) I + 3 1 sin ( 3 t ) A
e A t = 1 3 ( 3 cos 3 t + 4 sin 3 t − 5 sin 3 t 5 sin 3 t 3 cos 3 t − 4 sin 3 t ) e^{At}=\frac{1}{3}\begin{pmatrix}3\cos 3t +4\sin 3t & -5\sin 3t \\ 5\sin 3t & 3\cos 3t -4\sin 3t\end{pmatrix} e A t = 3 1 ( 3 cos 3 t + 4 sin 3 t 5 sin 3 t − 5 sin 3 t 3 cos 3 t − 4 sin 3 t )
Answer . X ( t ) = e A t X ( 0 ) = 1 3 ( 3 cos 3 t + 4 sin 3 t − 5 sin 3 t 5 sin 3 t 3 cos 3 t − 4 sin 3 t ) X ( 0 ) X(t)=e^{At}X(0)=\frac{1}{3}\begin{pmatrix}3\cos 3t +4\sin 3t & -5\sin 3t \\ 5\sin 3t & 3\cos 3t -4\sin 3t\end{pmatrix}X(0) X ( t ) = e A t X ( 0 ) = 3 1 ( 3 cos 3 t + 4 sin 3 t 5 sin 3 t − 5 sin 3 t 3 cos 3 t − 4 sin 3 t ) X ( 0 )
1. Assume that the matrix A has two different real roots λ 1 \lambda_1 λ 1 and λ 2 \lambda_2 λ 2 . The characteristic polinomial of A is λ 2 − ( λ 1 + λ 2 ) λ + λ 1 λ 2 = 0 \lambda^2-(\lambda_1+\lambda_2)\lambda+\lambda_1\lambda_2=0 λ 2 − ( λ 1 + λ 2 ) λ + λ 1 λ 2 = 0 . By the Cayley–Hamilton theorem we have A 2 − ( λ 1 + λ 2 ) A + λ 1 λ 2 I = 0 A^2-(\lambda_1+\lambda_2)A+\lambda_1\lambda_2I=0 A 2 − ( λ 1 + λ 2 ) A + λ 1 λ 2 I = 0 . Let X 1 X_1 X 1 and X 2 X_2 X 2 be the eigenvectors of the matrix A, corresponding to the eigenvalues λ 1 \lambda_1 λ 1 and λ 2 \lambda_2 λ 2 respectively. They form a basis of the vector space R 2 R^2 R 2 , hence X ( 0 ) = c 1 X 1 + c 2 X 2 X(0)=c_1X_1+c_2X_2 X ( 0 ) = c 1 X 1 + c 2 X 2 with some unknown coefficients c 1 c_1 c 1 and c 2 c_2 c 2 . Then
e A t X i = ∑ n = 0 + ∞ t n n ! A n X i = ∑ n = 0 + ∞ t n n ! λ i n X i = e λ i t X i e^{At}X_i=\sum\limits_{n=0}^{+\infty}\frac{t^n}{n!}A^nX_i=\sum\limits_{n=0}^{+\infty}\frac{t^n}{n!}\lambda_i^nX_i=e^{\lambda_it}X_i e A t X i = n = 0 ∑ + ∞ n ! t n A n X i = n = 0 ∑ + ∞ n ! t n λ i n X i = e λ i t X i . So
X ( t ) = e A t X ( 0 ) = e A t ( c 1 X 1 + c 2 X 2 ) = c 1 e λ 1 t X 1 + c 2 e λ 2 t X 2 X(t)=e^{At}X(0)=e^{At}(c_1X_1+c_2X_2)=c_1e^{\lambda_1t}X_1+c_2e^{\lambda_2t}X_2 X ( t ) = e A t X ( 0 ) = e A t ( c 1 X 1 + c 2 X 2 ) = c 1 e λ 1 t X 1 + c 2 e λ 2 t X 2
Notice that
( λ 1 I − A ) X ( 0 ) = ( λ 1 I − A ) ( c 1 X 1 + c 2 X 2 ) = c 2 ( λ 1 − λ 2 ) X 2 (\lambda_1 I-A)X(0)=(\lambda_1 I-A)(c_1 X_1+c_2 X_2)=c_2(\lambda_1-\lambda_2) X_2 ( λ 1 I − A ) X ( 0 ) = ( λ 1 I − A ) ( c 1 X 1 + c 2 X 2 ) = c 2 ( λ 1 − λ 2 ) X 2
( λ 2 I − A ) X ( 0 ) = ( λ 2 I − A ) ( c 1 X 1 + c 2 X 2 ) = c 1 ( λ 2 − λ 1 ) X 1 (\lambda_2 I-A)X(0)=(\lambda_2 I-A)(c_1 X_1+c_2 X_2)=c_1(\lambda_2-\lambda_1) X_1 ( λ 2 I − A ) X ( 0 ) = ( λ 2 I − A ) ( c 1 X 1 + c 2 X 2 ) = c 1 ( λ 2 − λ 1 ) X 1
therefore,
c 2 X 2 = 1 λ 1 − λ 2 ( λ 1 I − A ) X ( 0 ) c_2X_2=\frac{1}{\lambda_1-\lambda_2}(\lambda_1 I-A)X(0) c 2 X 2 = λ 1 − λ 2 1 ( λ 1 I − A ) X ( 0 ) ,
c 1 X 1 = 1 λ 2 − λ 1 ( λ 2 I − A ) X ( 0 ) c_1X_1=\frac{1}{\lambda_2-\lambda_1}(\lambda_2 I-A)X(0) c 1 X 1 = λ 2 − λ 1 1 ( λ 2 I − A ) X ( 0 ) and
X ( t ) = c 1 e λ 1 t X 1 + c 2 e λ 2 t X 2 = e λ 1 t 1 λ 1 − λ 2 ( λ 1 I − A ) X ( 0 ) + e λ 2 t 1 λ 2 − λ 1 ( λ 2 I − A ) X ( 0 ) X(t)=c_1e^{\lambda_1t}X_1+c_2e^{\lambda_2t}X_2=e^{\lambda_1t}\frac{1}{\lambda_1-\lambda_2}(\lambda_1 I-A)X(0)+e^{\lambda_2t}\frac{1}{\lambda_2-\lambda_1}(\lambda_2 I-A)X(0) X ( t ) = c 1 e λ 1 t X 1 + c 2 e λ 2 t X 2 = e λ 1 t λ 1 − λ 2 1 ( λ 1 I − A ) X ( 0 ) + e λ 2 t λ 2 − λ 1 1 ( λ 2 I − A ) X ( 0 )
If we take A = ( − 4 2 5 / 2 2 ) A=\begin{pmatrix}-4 & 2 \\ 5/2 & 2\end{pmatrix} A = ( − 4 5/2 2 2 ) , then the characteristic polynomial equals to λ 2 + 2 λ − 13 \lambda^2+2\lambda-13 λ 2 + 2 λ − 13 , its roots are λ 1 = − 1 + 14 \lambda_1=-1+\sqrt{14} λ 1 = − 1 + 14 and λ 2 = − 1 − 14 \lambda_2=-1-\sqrt{14} λ 2 = − 1 − 14 .
X ( t ) = e λ 1 t 1 λ 1 − λ 2 ( λ 1 I − A ) X ( 0 ) + e λ 2 t 1 λ 2 − λ 1 ( λ 2 I − A ) X ( 0 ) X(t)=e^{\lambda_1t}\frac{1}{\lambda_1-\lambda_2}(\lambda_1 I-A)X(0)+e^{\lambda_2t}\frac{1}{\lambda_2-\lambda_1}(\lambda_2 I-A)X(0) X ( t ) = e λ 1 t λ 1 − λ 2 1 ( λ 1 I − A ) X ( 0 ) + e λ 2 t λ 2 − λ 1 1 ( λ 2 I − A ) X ( 0 ) implies
X ( t ) = e ( − 1 + 14 ) t 2 14 ( ( − 1 + 14 ) I − A ) X ( 0 ) − e ( − 1 − 14 ) t 2 14 ( ( − 1 − 14 ) I − A ) X ( 0 ) X(t)=\frac{e^{(-1+\sqrt{14})t}}{2\sqrt{14}}((-1+\sqrt{14}) I-A)X(0)-\frac{e^{(-1-\sqrt{14})t}}{2\sqrt{14}}((-1-\sqrt{14}) I-A)X(0) X ( t ) = 2 14 e ( − 1 + 14 ) t (( − 1 + 14 ) I − A ) X ( 0 ) − 2 14 e ( − 1 − 14 ) t (( − 1 − 14 ) I − A ) X ( 0 )
X ( t ) = e − t 14 ( ( 14 cosh 14 t ) I − ( I + A ) sinh 14 t ) X ( 0 ) X(t)=\frac{e^{-t}}{\sqrt{14}}((\sqrt{14}\cosh\sqrt{14}t) I-(I+A)\sinh \sqrt{14}t)X(0) X ( t ) = 14 e − t (( 14 cosh 14 t ) I − ( I + A ) sinh 14 t ) X ( 0 )
X ( t ) = e − t ( ( cosh 14 t ) I − sinh 14 t 14 ( I + A ) ) X ( 0 ) X(t)=e^{-t}((\cosh\sqrt{14}t) I-\frac{\sinh \sqrt{14}t}{\sqrt{14}}(I+A))X(0) X ( t ) = e − t (( cosh 14 t ) I − 14 s i n h 14 t ( I + A )) X ( 0 )
Answer . X ( t ) = e − t ( ( cosh 14 t ) I − sinh 14 t 14 ( I + A ) ) X ( 0 ) X(t)=e^{-t}((\cosh\sqrt{14}t) I-\frac{\sinh \sqrt{14}t}{\sqrt{14}}(I+A))X(0) X ( t ) = e − t (( cosh 14 t ) I − 14 s i n h 14 t ( I + A )) X ( 0 )
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