Chapter 9

Functions of Matrices

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Problem 9.1.1

Consider the 2×22 \times 2 nonnormal matrix

A=(3−41−1). A = \begin{pmatrix} 3 & -4 \\ 1 & -1 \end{pmatrix}.

Calculate AnA^n, where n∈Nn \in \mathbb {N}.

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Problem 9.1.2

Consider the 2×22 \times 2 matrix A=(ajk)A = (a_{jk}) over the complex numbers. Find exp(A)\mathrm{exp}\left(A\right).

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Problem 9.1.3
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(i)

Consider the 2×22 \times 2 matrix

A=(a11a120a22). A = \begin{pmatrix} a_{11} & a_{12} \\ 0 & a_{22} \end{pmatrix}.

Find exp(tA)\mathrm{exp}\left(tA\right).

(ii)

Let α,β∈R\alpha , \beta \in \mathbb {R} and

M(α,β)=(α−ββα). M(\alpha ,\beta ) = \begin{pmatrix} \alpha & -\beta \\ \beta & \alpha \end{pmatrix}.

Calculate exp(M(α,β))\mathrm{exp}\left(M(\alpha ,\beta )\right).

Problem 9.1.4

Consider the 2×22 \times 2 unitary matrix

U=(0110). U = \begin{pmatrix} 0 & 1 \\ 1 & 0 \end{pmatrix}.

Can we find an α∈R\alpha \in \mathbb {R} such that U=exp(αA)U = \mathrm{exp}\left(\alpha A\right), where

A=(01−10)? A = \begin{pmatrix} 0 & 1 \\ -1 & 0 \end{pmatrix}?
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Problem 9.1.5

Let HH be a hermitian matrix, i.e. H=H∗H = H^*. Now U:=eiHU := e^{iH} is a unitary matrix. Let

H=(abb‾a),a∈R,  b∈C H = \begin{pmatrix} a & b \\ \overline{b} & a \end{pmatrix}, \qquad a \in \mathbb {R}, \; b \in \mathbb {C}

with b≠0b \neq 0.

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(i)

Calculate eiHe^{iH} using the normalized eigenvectors of HH to construct a unitary matrix VV such that V∗HVV^*HV is a diagonal matrix.

(ii)

Specify aa, bb such that we find the unitary matrix

U=(0110). U = \begin{pmatrix} 0 & 1 \\ 1 & 0 \end{pmatrix}.
Problem 9.1.6

Let z∈Cz \in \mathbb {C}. Let AA, BB be n×nn \times n matrices over C\mathbb {C}. We say that BB is invariant with respect to AA if

ezABe−zA=B. e^{zA}Be^{-zA} = B.

Obviously e−zAe^{-zA} is the inverse of ezAe^{zA}. Show that, if this condition is satisfied, one has [A,B]=0n[A,B] = 0_n. If ezAe^{zA} would be unitary we have UBU∗=BUBU^* = B.

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Problem 9.1.7

Let z∈Cz \in \mathbb {C}.

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(i)

Consider the 2×22 \times 2 matrices

A=(0110),B=(b11b12b12b11). A = \begin{pmatrix} 0 & 1 \\ 1 & 0 \end{pmatrix}, \qquad B = \begin{pmatrix} b_{11} & b_{12} \\ b_{12} & b_{11} \end{pmatrix}.

Calculate exp(zA)\mathrm{exp}\left(zA\right), exp(−zA)\mathrm{exp}\left(-zA\right) and exp(zA)Bexp(−zA)\mathrm{exp}\left(zA\right)B\mathrm{exp}\left(-zA\right). Calculate the commutator [A,B][A,B].

(ii)

Consider the 2×22 \times 2 matrices

C=(0−ii0),D=(d11d12−d12d11). C = \begin{pmatrix} 0 & -i \\ i & 0 \end{pmatrix}, \qquad D = \begin{pmatrix} d_{11} & d_{12} \\ -d_{12} & d_{11} \end{pmatrix}.

Calculate exp(zC)\mathrm{exp}\left(zC\right), exp(−zC)\mathrm{exp}\left(-zC\right) and exp(zC)Dexp(−zC)\mathrm{exp}\left(zC\right)D\mathrm{exp}\left(-zC\right). Calculate the commutator [C,D][C,D].

(iii)

Consider the 2×22 \times 2 matrices

E=(0100),F=(f11f120f11). E = \begin{pmatrix} 0 & 1 \\ 0 & 0 \end{pmatrix}, \qquad F = \begin{pmatrix} f_{11} & f_{12} \\ 0 & f_{11} \end{pmatrix}.

Calculate exp(zE)\mathrm{exp}\left(zE\right), exp(−zE)\mathrm{exp}\left(-zE\right) and exp(zE)Fexp(−zE)\mathrm{exp}\left(zE\right)F\mathrm{exp}\left(-zE\right). Calculate the commutator [E,F][E,F].

Problem 9.1.8

Let σ1\sigma_1, σ2\sigma_2, σ3\sigma_3 be the Pauli spin matrices. Consider the 2×22 \times 2 matrix

U(α,β,γ)=e−iασ3/2e−iβσ2/2e−iγσ3/2 U(\alpha ,\beta ,\gamma ) = e^{-i\alpha \sigma _3/2}e^{-i\beta \sigma _2/2}e^{-i\gamma \sigma _3/2}

where α\alpha, β\beta, γ\gamma are the three Euler angles with the range 0≤α<2π0 \leq \alpha < 2\pi, 0≤β≤π0 \leq \beta \leq \pi and 0≤γ<2π0 \leq \gamma < 2\pi. Show that

U(α,β,γ)=(e−iα/2cos⁡(β/2)e−iγ/2−e−iα/2sin⁡(β/2)eiγ/2e−iα/2sin⁡(β/2)e−iγ/2eiα/2cos⁡(β/2)eiγ/2).(1) U(\alpha ,\beta ,\gamma ) = \begin{pmatrix} e^{-i\alpha /2}\cos (\beta /2)e^{-i\gamma /2} & -e^{-i\alpha /2}\sin (\beta /2)e^{i\gamma /2} \\ e^{-i\alpha /2}\sin (\beta /2)e^{-i\gamma /2} & e^{i\alpha /2}\cos (\beta /2)e^{i\gamma /2} \end{pmatrix}. \tag {1}
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Problem 9.1.9
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(i)

Let α∈R\alpha \in \mathbb {R}. Consider the 3×33 \times 3 symmetric matrix

A(α)=(00α000α00). A(\alpha ) = \begin{pmatrix} 0 & 0 & \alpha \\ 0 & 0 & 0 \\ \alpha & 0 & 0 \end{pmatrix}.

Find exp(A(α))\mathrm{exp}\left(A(\alpha )\right).

(ii)

Consider the 3×33 \times 3 matrix

B=(0−10101010). B = \begin{pmatrix} 0 & -1 & 0 \\ 1 & 0 & 1 \\ 0 & 1 & 0 \end{pmatrix}.

Let α∈R\alpha \in \mathbb {R}. Find exp(αB)\mathrm{exp}\left(\alpha B\right).

(iii)

Let a12,a13,a23∈Ra_{12}, a_{13}, a_{23} \in \mathbb {R}. Consider the skew-symmetric 3×33 \times 3 matrix

A(a12,a13,a23)=(0a12a13−a120a23−a13−a230). A(a_{12},a_{13},a_{23}) = \begin{pmatrix} 0 & a_{12} & a_{13} \\ -a_{12} & 0 & a_{23} \\ -a_{13} & -a_{23} & 0 \end{pmatrix}.

Find exp(A)\mathrm{exp}\left(A\right).

Problem 9.1.10

Let AA be an n×nn \times n matrix over C\mathbb {C} with A2=rAA^2 = rA, where r∈Cr \in \mathbb {C} and r≠0r \neq 0.

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(i)

Calculate ezAe^{zA}, where z∈Cz \in \mathbb {C}.

(ii)

Let U(z)=ezAU(z) = e^{zA}. Let z′∈Cz' \in \mathbb {C}. Calculate U(z)U(z′)U(z)U(z').

Problem 9.1.11

Can we find a 2×22 \times 2 matrix BB over the real numbers R\mathbb {R} such that

sin⁡(B)=(1401)?(1) \sin (B) = \begin{pmatrix} 1 & 4 \\ 0 & 1 \end{pmatrix}? \tag {1}
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Problem 9.1.12

Let AA be an n×nn \times n matrix over C\mathbb {C}. Assume that A2=cInA^2 = cI_n, where c∈Rc \in \mathbb {R}.

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(i)

Calculate exp(A)\mathrm{exp}\left(A\right).

(ii)

Apply the result to the 2×22 \times 2 matrix (z≠0z \neq 0)

B=(0z−z‾0). B = \begin{pmatrix} 0 & z \\ -\overline{z} & 0 \end{pmatrix}.

Thus BB is skew-hermitian, i.e. B‾T=−B\overline{B}^T = -B.

Problem 9.1.13

For any n×nn \times n matrix AA we have the identity

det⁡(exp(A))≡exp(tr⁡(A)). \operatorname {det}\left(\mathrm{exp}\left(A\right)\right) \equiv \mathrm{exp}\left(\operatorname {tr}(A)\right).
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(i)

Any n×nn \times n unitary matrix UU can be written as U=exp(iK)U = \mathrm{exp}\left(iK\right), where KK is a hermitian matrix. Assume that det⁡(U)=−1\operatorname {det}\left(U\right) = -1. What can be said about the trace of KK?

(ii)

Let

A=(237−2). A = \begin{pmatrix} 2 & 3 \\ 7 & -2 \end{pmatrix}.

Calculate det⁡(exp(A))\operatorname {det}\left(\mathrm{exp}\left(A\right)\right).

Problem 9.1.14

Let AA be an n×nn \times n matrix. Then exp(A)\mathrm{exp}\left(A\right) can also be calculated as

eA=lim⁡m→∞(In+Am)m. e^A = \lim _{m \to \infty } \left(I_n + \frac{A}{m}\right)^m.

Use this definition to show that det⁡(exp(A))≡exp(tr⁡(A))\operatorname {det}\left(\mathrm{exp}\left(A\right)\right) \equiv \mathrm{exp}\left(\operatorname {tr}(A)\right).

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Problem 9.1.15

Let AA, BB be n×nn \times n matrices. Then we have the identity

det⁡(eAeBe−Ae−B)≡exp(tr⁡([A,B])). \operatorname {det}\left(e^Ae^Be^{-A}e^{-B}\right) \equiv \mathrm{exp}\left(\operatorname {tr}([A,B])\right).

Show that det⁡(eAeBe−Ae−B)=1\operatorname {det}\left(e^Ae^Be^{-A}e^{-B}\right) = 1.

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Problem 9.1.16

The MacLaurin series for arctan⁡(z)\arctan (z) is defined as

arctan⁡(z)=z−z33+z55−z77+⋯=∑j=0∞(−1)jz2j+12j+1 \arctan (z) = z - \frac{z^3}{3} + \frac{z^5}{5} - \frac{z^7}{7} + \cdots = \sum _{j=0}^{\infty } \frac{(-1)^j z^{2j+1}}{2j+1}

which converges for all complex values of zz having absolute value less than 1, i.e. ∣z∣<1\left|z\right| < 1. Let AA be an n×nn \times n matrix. Thus the series expansion

arctan⁡(A)=A−A33+A55−A77+⋯=∑j=0∞(−1)jA2j+12j+1 \arctan (A) = A - \frac{A^3}{3} + \frac{A^5}{5} - \frac{A^7}{7} + \cdots = \sum _{j=0}^{\infty } \frac{(-1)^j A^{2j+1}}{2j+1}

is well-defined for AA if all eigenvalues λ\lambda of AA satisfy ∣λ∣<1\left|\lambda \right| < 1. Let

A=12(1111). A = \frac{1}{2} \begin{pmatrix} 1 & 1 \\ 1 & 1 \end{pmatrix}.

Does arctan⁡(A)\arctan (A) exist?

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Problem 9.1.17

Let AA, BB be n×nn \times n matrices over C\mathbb {C}. Assume that

[A,[A,B]]=[B,[A,B]]=0n.(1) [A,[A,B]] = [B,[A,B]] = 0_n. \tag {1}

Show that

eA+B=eAeBe−12[A,B](2a) e^{A+B} = e^A e^B e^{-\frac{1}{2}[A,B]} \tag {2a} eA+B=eBeAe+12[A,B].(2b) e^{A+B} = e^B e^A e^{+\frac{1}{2}[A,B]}. \tag {2b}

Use the technique of parameter differentiation, i.e. consider the matrix-valued function

f(ϵ):=eϵAeϵB f(\epsilon ) := e^{\epsilon A}e^{\epsilon B}

where ϵ\epsilon is a real parameter. Then take the derivative of ff with respect to ϵ\epsilon.

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Problem 9.1.18

Let AA, BB, C2C_2, , CmC_m, be n×nn \times n matrices over C\mathbb {C}. The Zassenhaus formula is given by

exp(A+B)=exp(A)exp(B)exp(C2)⋯exp(Cm)⋯ . \mathrm{exp}\left(A+B\right) = \mathrm{exp}\left(A\right)\mathrm{exp}\left(B\right)\mathrm{exp}\left(C_2\right) \cdots \mathrm{exp}\left(C_m\right) \cdots .

The left-hand side is called the disentangled form and the right-hand side is called the undisentangled form. Find C2,C3,…C_2, C_3, \ldots, using the comparison method. In the comparison method the disentangled and undisentangled forms are expanded in terms of an ordering scalar α\alpha and matrix coefficients of equal powers of α\alpha are compared. From

exp⁡(α(A+B))=exp⁡(αA)exp⁡(αB)exp⁡(α2C2)exp⁡(α3C3)⋯ \exp (\alpha (A+B)) = \exp (\alpha A)\exp (\alpha B)\exp (\alpha ^2 C_2)\exp (\alpha ^3 C_3) \cdots

we obtain

∑k=0∞αkk!(A+B)k=∑r0,r1,r2,r3,…=0∞αr0+r1+2r2+3r3+…r0!r1!r2!r3!⋯Ar0Br1C2r2C3r3⋯ . \sum _{k=0}^{\infty } \frac{\alpha ^k}{k!}(A+B)^k = \sum _{r_0,r_1,r_2,r_3,\ldots =0}^{\infty } \frac{\alpha ^{r_0+r_1+2r_2+3r_3+\ldots }}{r_0!r_1!r_2!r_3!\cdots } A^{r_0}B^{r_1}C_2^{r_2}C_3^{r_3} \cdots .
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(i)

Find C2C_2 and C3C_3.

(ii)

Assume that [A,[A,B]]=0n[A,[A,B]] = 0_n and [B,[A,B]]=0n[B,[A,B]] = 0_n. What conclusion can we draw for the Zassenhaus formula?

Problem 9.1.19

Let AA, BB be n×nn \times n matrices and t∈Rt \in \mathbb {R}. Show that

et(A+B)−etAetB=t22(BA−AB)+higher order terms in t.(1) e^{t(A+B)} - e^{tA}e^{tB} = \frac{t^2}{2}(BA-AB) + \text{higher order terms in } t. \tag {1}
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Problem 9.1.20

Let AA be an n×nn \times n matrix with A3=−AA^3 = -A and α∈R\alpha \in \mathbb {R}. Calculate exp⁡(αA)\exp (\alpha A).

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Problem 9.1.21

Let XX be an n×nn \times n matrix over C\mathbb {C}. Assume that X2=InX^2 = I_n. Let YY be an arbitrary n×nn \times n matrix over C\mathbb {C}. Let z∈Cz \in \mathbb {C}.

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(i)

Calculate exp⁡(zX)Yexp⁡(−zX)\exp (zX)Y\exp (-zX) using the Baker-Campbell-Hausdorff formula

ezXYe−zX=Y+z[X,Y]+z22![X,[X,Y]]+z33![X,[X,[X,Y]]]+⋯ . e^{zX}Ye^{-zX} = Y + z[X,Y] + \frac{z^2}{2!}[X,[X,Y]] + \frac{z^3}{3!}[X,[X,[X,Y]]] + \cdots .
(ii)

Calculate exp⁡(zX)Yexp⁡(−zX)\exp (zX)Y\exp (-zX) by first calculating exp⁡(zX)\exp (zX) and exp⁡(−zX)\exp (-zX) and then doing the matrix multiplication. Compare the two methods.

Problem 9.1.22

Let KK be a hermitian matrix. Then U:=exp(iK)U := \mathrm{exp}\left(iK\right) is a unitary matrix. A method to find the hermitian matrix KK from the unitary matrix UU is to consider the principal logarithm of a matrix A∈Cn×nA \in \mathbb {C}^{n \times n} with no eigenvalues on R−\mathbb {R}^- (the closed negative real axis). This logarithm is denoted by log⁡(A)\log (A) and is the unique matrix BB such that exp(B)=A\mathrm{exp}\left(B\right) = A and the eigenvalues of BB have imaginary parts lying strictly between −π-\pi and π\pi. For A∈Cn×nA \in \mathbb {C}^{n \times n} with no eigenvalues on R−\mathbb {R}^- we have the following integral representation

log⁡(s(A−In)+In)=∫0s(A−In)(t(A−In)+In)−1dt. \log (s(A-I_n)+I_n) = \int _0^s (A-I_n)(t(A-I_n)+I_n)^{-1}dt.

Thus with s=1s=1 we obtain

log⁡(A)=∫01(A−In)(t(A−In)+In)−1dt. \log (A) = \int _0^1 (A-I_n)(t(A-I_n)+I_n)^{-1}dt.

Find log⁡(U)\log (U) of the unitary matrix

U=12(1−111). U = \frac{1}{\sqrt{2}} \begin{pmatrix} 1 & -1 \\ 1 & 1 \end{pmatrix}.

First test whether the method can be applied.

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Problem 9.1.23

Consider the matrix (ζ∈R\zeta \in \mathbb {R})

S(ζ)=(cosh⁡(ζ)00sinh⁡(ζ)0cosh⁡(ζ)sinh⁡(ζ)00sinh⁡(ζ)cosh⁡(ζ)0sinh⁡(ζ)00cosh⁡(ζ)). S(\zeta ) = \begin{pmatrix} \cosh (\zeta ) & 0 & 0 & \sinh (\zeta ) \\ 0 & \cosh (\zeta ) & \sinh (\zeta ) & 0 \\ 0 & \sinh (\zeta ) & \cosh (\zeta ) & 0 \\ \sinh (\zeta ) & 0 & 0 & \cosh (\zeta ) \end{pmatrix}.
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(i)

Show that the matrix is invertible, i.e. find the determinant.

(ii)

Calculate the inverse of S(ζ)S(\zeta ).

(iii)

Calculate

A:=ddζS(ζ)∣ζ=0 A := \frac{d}{d\zeta }S(\zeta )\bigg|_{\zeta =0}

and then calculate exp⁡(ζA)\exp (\zeta A).

(iv)

Do the matrices S(ζ)S(\zeta ) form a group under matrix multiplication?

Problem 9.1.24

Let MM be an n×nn \times n matrix with mjk=1m_{jk} = 1 for all j,k=1,…,nj,k = 1,\ldots ,n. Let z∈Cz \in \mathbb {C}. Find exp(zM)\mathrm{exp}\left(zM\right). Then consider the special case zn=iπzn = i\pi.

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Problem 9.1.25

Let XX, YY be n×nn \times n matrices. Show that

[eX,Y]=∑k=1∞[Xk,Y]k!. [e^X,Y] = \sum _{k=1}^{\infty } \frac{[X^k,Y]}{k!}.
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Problem 9.1.26

Let AA, BB be n×nn \times n matrices over C\mathbb {C} and α∈C\alpha \in \mathbb {C}. The Baker-Campbell-Hausdorff formula states that

eαABe−αA=B+α[A,B]+α22![A,[A,B]]+⋯=∑j=0∞αjj!{Aj,B}=B~(α) e^{\alpha A}Be^{-\alpha A} = B + \alpha [A,B] + \frac{\alpha ^2}{2!}[A,[A,B]] + \cdots = \sum _{j=0}^{\infty } \frac{\alpha ^j}{j!}\{ A^j,B\} = \widetilde{B}(\alpha )

where [A,B]:=AB−BA[A,B] := AB-BA and {Aj,B}:=[A,{Aj−1,B}]\{ A^j,B\} := [A,\{ A^{j-1},B\} ] is the repeated commutator.

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(i)

Extend the formula to eαABke−αAe^{\alpha A}B^ke^{-\alpha A}, where k≥1k \geq 1.

(ii)

Extend the formula to eαAeBe−αAe^{\alpha A}e^Be^{-\alpha A}.

Problem 9.1.27

Consider the n×nn \times n matrix (n≥2n \geq 2)

A=(010…0001…0⋮⋮⋮⋱⋮000…1000…0). A = \begin{pmatrix} 0 & 1 & 0 & \ldots & 0 \\ 0 & 0 & 1 & \ldots & 0 \\ \vdots & \vdots & \vdots & \ddots & \vdots \\ 0 & 0 & 0 & \ldots & 1 \\ 0 & 0 & 0 & \ldots & 0 \end{pmatrix}.

Let f:R→Rf: \mathbb {R} \to \mathbb {R} be an analytic function. Calculate

f(0)In+f′(0)1!A+f′′(0)2!A2+⋯+fn−1(0)(n−1)!An−1 f(0)I_n + \frac{f'(0)}{1!}A + \frac{f''(0)}{2!}A^2 + \cdots + \frac{f^{n-1}(0)}{(n-1)!}A^{n-1}

where ′' denotes differentiation. Discuss.

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Problem 9.1.28

Let AA, BB be n×nn \times n matrices with A2=InA^2 = I_n and B2=InB^2 = I_n. Assume that [A,B]=0n[A,B] = 0_n. Let a,b∈Ca, b \in \mathbb {C}. Calculate eaA+bBe^{aA+bB}.

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Problem 9.1.29

Let AA, BB be n×nn \times n matrices with A2=InA^2 = I_n and B2=InB^2 = I_n. Assume that [A,B]+=0n[A,B]_+ = 0_n. Let a,b∈Ca, b \in \mathbb {C}. Calculate eaA+bBe^{aA+bB}.

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Problem 9.1.30
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(i)

Let AA, BB be n×nn \times n matrices over C\mathbb {C}. Assume that A2=InA^2 = I_n and B2=InB^2 = I_n. Find exp⁡(αA⊗βB)\exp (\alpha A \otimes \beta B), where α,β∈C\alpha , \beta \in \mathbb {C}.

(ii)

Let AA, BB, CC be n×nn \times n matrices over C\mathbb {C} such that A2=InA^2 = I_n, B2=InB^2 = I_n and C2=InC^2 = I_n. Furthermore assume that

[A,B]+=0n,[B,C]+=0n,[C,A]+=0n. [A,B]_+ = 0_n, \qquad [B,C]_+ = 0_n, \qquad [C,A]_+ = 0_n.

Let α,β,γ∈C\alpha , \beta , \gamma \in \mathbb {C}. Calculate eαA+βB+γCe^{\alpha A+\beta B+\gamma C} using

eαA+βB+γC=∑j=0∞(αA+βB+γC)jj!. e^{\alpha A+\beta B+\gamma C} = \sum _{j=0}^{\infty } \frac{(\alpha A+\beta B+\gamma C)^j}{j!}.
Problem 9.1.31

Let AA be an n×nn \times n matrix over C\mathbb {C}. Assume that all eigenvalues λ1,…,λn\lambda_1, \ldots , \lambda_n are pairwise distinct.

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(i)

Then etAe^{tA} can be calculated as follows (Lagrange interpolation)

etA=∑j=1neλjt∏k=1k≠jn(A−λkIn)(λj−λk). e^{tA} = \sum _{j=1}^{n} e^{\lambda _j t} \prod _{\substack {k=1 \\ k \neq j}}^{n} \frac{(A-\lambda _k I_n)}{(\lambda _j-\lambda _k)}.

Consider the Pauli spin matrix σ1\sigma_1. Calculate etAe^{tA} using this method.

(ii)

etAe^{tA} can also be calculated as follows (Newton interpolation)

etA=eλ1tIn+∑j=2n[λ1,…,λj]∏k=1j−1(A−λkIn). e^{tA} = e^{\lambda _1 t}I_n + \sum _{j=2}^{n} [\lambda _1,\ldots ,\lambda _j] \prod _{k=1}^{j-1} (A-\lambda _k I_n).

The divided differences [λ1,…,λj][\lambda_1,\ldots ,\lambda_j] depend on tt and are defined recursively by

[λ1,λ2]:=eλ1t−eλ2tλ1−λ2 [\lambda _1,\lambda _2] := \frac{e^{\lambda _1 t}-e^{\lambda _2 t}}{\lambda _1-\lambda _2} [λ1,…,λk+1]:=[λ1,…,λk]−[λ2,…,λk+1]λ1−λk+1,k≥2. [\lambda _1,\ldots ,\lambda _{k+1}] := \frac{[\lambda _1,\ldots ,\lambda _k]-[\lambda _2,\ldots ,\lambda _{k+1}]}{\lambda _1-\lambda _{k+1}}, \quad k \geq 2.

Calculate etσ1e^{t\sigma_1} using this method.

Problem 9.1.32

Let AA be an n×nn \times n matrix. The characteristic polynomial

det⁡(λIn−A)=λn+a1λn−1+⋯+an=p(λ) \det (\lambda I_n - A) = \lambda ^n + a_1\lambda ^{n-1} + \cdots + a_n = p(\lambda )

is closely related the resolvent (λIn−A)−1(\lambda I_n - A)^{-1} trough the formula

(λIn−A)−1=N1λn−1+N2λn−2+⋯+Nnλn+a1λn−1+⋯+an=N(λ)p(λ) (\lambda I_n - A)^{-1} = \frac{N_1\lambda ^{n-1}+N_2\lambda ^{n-2}+\cdots +N_n}{\lambda ^n+a_1\lambda ^{n-1}+\cdots +a_n} = \frac{N(\lambda )}{p(\lambda )}

where the adjugate matrix N(λ)N(\lambda ) is a polynomial in λ\lambda of degree n−1n-1 with constant n×nn \times n coefficient matrices N1,…,NnN_1,\ldots ,N_n. The Laplace transform of the matrix exponential is the resolvent

L(etA)=(λIn−A)−1. \mathcal{L}(e^{tA}) = (\lambda I_n - A)^{-1}.

The NkN_k matrices and aka_k coefficients may be computed recursively as follows

N1=In,a1=−11tr⁡(AN1) N_1 = I_n, \qquad a_1 = -\frac{1}{1}\operatorname {tr}(AN_1) N2=AN1+a1In,a2=−12tr⁡(AN2) N_2 = AN_1 + a_1I_n, \qquad a_2 = -\frac{1}{2}\operatorname {tr}(AN_2) ⋮ \vdots Nn=ANn−1+an−1In,an=−1ntr⁡(ANn) N_n = AN_{n-1} + a_{n-1}I_n, \qquad a_n = -\frac{1}{n}\operatorname {tr}(AN_n) 0n=ANn+anIn. 0_n = AN_n + a_nI_n.

Consider the 2×22 \times 2 unitary matrix

U=12(111−1). U = \frac{1}{\sqrt{2}} \begin{pmatrix} 1 & 1 \\ 1 & -1 \end{pmatrix}.

Find the NkN_k matrices and the coefficients aka_k and thus calculate the resolvent.

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Problem 9.1.33
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(i)

Let AA, BB be n×nn \times n matrices over C\mathbb {C}. Calculate eABeAe^ABe^A. Set f(ϵ)=eϵABeϵAf(\epsilon ) = e^{\epsilon A}Be^{\epsilon A}, where ϵ\epsilon is a real parameter. Then differentiate with respect to ϵ\epsilon. For ϵ=1\epsilon = 1 we have eABeAe^ABe^A.

(ii)

Let ϵ∈R\epsilon \in \mathbb {R}. Calculate the matrix-valued function

f(ϵ)=e−ϵσ2σ3eϵσ2. f(\epsilon ) = e^{-\epsilon \sigma _2}\sigma _3 e^{\epsilon \sigma _2}.

Differentiate the matrix-valued function ff with respect to ϵ\epsilon and solve the initial value problem of the resulting ordinary differential equation.

Problem 9.1.34

Let AA be an n×nn \times n matrix over C\mathbb {C}. Let TT be a nilpotent matrix over C\mathbb {C} satisfying T∗A+AT=0nT^*A + AT = 0_n. Show that (eT)∗AeT=A(e^T)^*Ae^T = A.

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Problem 9.1.35
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(i)

Let Π\Pi be an n×nn \times n projection matrix. Let ϵ∈R\epsilon \in \mathbb {R}. Calculate exp⁡(ϵΠ)\exp (\epsilon \Pi ).

(ii)

Let Π1,Π2,…,Πn\Pi_1, \Pi_2, \ldots , \Pi_n be n×nn \times n projection matrices. Assume that ΠjΠk=0n\Pi_j\Pi_k = 0_n (j≠kj \neq k) for all j,k=1,…,nj,k = 1,\ldots ,n. Let ϵj∈R\epsilon_j \in \mathbb {R} with j=1,…,nj = 1,\ldots ,n. Calculate

exp⁡(ϵ1Π1+ϵ2Π2+⋯+ϵnΠn). \exp (\epsilon _1\Pi _1+\epsilon _2\Pi _2+\cdots +\epsilon _n\Pi _n).

Assume additionally that Π1+Π2+⋯+Πn=In\Pi_1+\Pi_2+\cdots +\Pi_n = I_n. Simplify the result from (i) using this condition.

Problem 9.1.36

Let AA, BB be n×nn \times n matrices over C\mathbb {C}. Assume that AA and BB commute with the commutator [A,B][A,B]. Then

exp⁡(A+B)=exp⁡(A)exp⁡(B)exp⁡(−12[A,B]). \exp (A+B) = \exp (A)\exp (B)\exp \left(-\frac{1}{2}[A,B]\right).

Can this formula be applied to the matrices

C=(1000),D=(0100). C = \begin{pmatrix} 1 & 0 \\ 0 & 0 \end{pmatrix}, \qquad D = \begin{pmatrix} 0 & 1 \\ 0 & 0 \end{pmatrix}.
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Problem 9.1.37

Let ϵ∈R\epsilon \in \mathbb {R}. Let AA, BB be n×nn \times n matrices over C\mathbb {C}. Expand eϵAeϵBe−ϵAe−ϵBe^{\epsilon A}e^{\epsilon B}e^{-\epsilon A}e^{-\epsilon B} up to second order in ϵ\epsilon.

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Problem 9.1.38

Let α∈R\alpha \in \mathbb {R}. Consider the 2×22 \times 2 matrix

A(α)=(cos⁡(α)sin⁡(α)sin⁡(α)−cos⁡(α)). A(\alpha ) = \begin{pmatrix} \cos (\alpha ) & \sin (\alpha ) \\ \sin (\alpha ) & -\cos (\alpha ) \end{pmatrix}.
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(i)

Show that the matrix is orthogonal.

(ii)

Find the determinant of A(α)A(\alpha ). Is the matrix an element of SO(2,R)SO(2,\mathbb {R})?

(iii)

Do these matrices form a group under matrix multiplication?

(iv)

Calculate

X=ddαA(α)∣α=0. X = \frac{d}{d\alpha }A(\alpha )\bigg|_{\alpha =0}.

Calculate exp⁡(αX)\exp (\alpha X) and compare this matrix with A(α)A(\alpha ). Discuss.

(v)

Let β∈R\beta \in \mathbb {R} and

B(β)=(cos⁡(β)sin⁡(β)sin⁡(β)−cos⁡(β)). B(\beta ) = \begin{pmatrix} \cos (\beta ) & \sin (\beta ) \\ \sin (\beta ) & -\cos (\beta ) \end{pmatrix}.

Is the matrix A(α)⊗B(β)A(\alpha ) \otimes B(\beta ) orthogonal? Find the determinant of A(α)⊗A(α)A(\alpha ) \otimes A(\alpha ). Is this matrix an element of SO(4,R)SO(4,\mathbb {R})?

Problem 9.1.39

Let AA be a normal matrix with eigenvalues λ1,…,λn\lambda_1, \ldots , \lambda_n and corresponding normalized pairwise orthogonal eigenvectors u→1,…,u→n\overrightarrow {u}_1, \ldots , \overrightarrow {u}_n. Let w→,v→∈Cn\overrightarrow {w}, \overrightarrow {v} \in \mathbb {C}^{n} (column vectors). Find w→∗exp(A)v→\overrightarrow {w}^* \mathrm{exp}\left(A\right)\overrightarrow {v} by expanding w→\overrightarrow {w} and v→\overrightarrow {v} with respect to the basis u→j\overrightarrow {u}_j (j=1,…,nj = 1,\ldots ,n).

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Problem 9.1.40

Let BB be an n×nn \times n matrix with B2=InB^2 = I_n. Show that

exp⁡(−12iπ(B−In))≡B. \exp \left(-\frac{1}{2}i\pi (B-I_n)\right) \equiv B.
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Problem 9.1.41

Consider the 2×22 \times 2 nonnormal matrices

A=(0100),B=(0010)=A∗. A = \begin{pmatrix} 0 & 1 \\ 0 & 0 \end{pmatrix}, \qquad B = \begin{pmatrix} 0 & 0 \\ 1 & 0 \end{pmatrix} = A^*.

Are the matrices

exp(A),exp(B) \mathrm{exp}\left(A\right), \qquad \mathrm{exp}\left(B\right)

normal? Are the matrices sin⁡(A)\sin (A), sin⁡(B)\sin (B), cos⁡(A)\cos (A), cos⁡(B)\cos (B) normal?

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Problem 9.1.42

Let z∈Cz \in \mathbb {C}. Let AA be an n×nn \times n matrix over C\mathbb {C}. Assume that A3=zAA^3 = zA. Find exp(A)\mathrm{exp}\left(A\right).

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Problem 9.1.43

Let v→1\overrightarrow {v}_1, v→2\overrightarrow {v}_2 be an orthonormal set in C2\mathbb {C}^{2}. Consider the 2×22 \times 2 matrix

A=−iv→1v→1∗+iv→2v→2∗. A = -i\overrightarrow {v}_1\overrightarrow {v}_1^* + i\overrightarrow {v}_2\overrightarrow {v}_2^*.

Thus I2=v→1v→1∗+v→2v→2∗I_2 = \overrightarrow {v}_1\overrightarrow {v}_1^* + \overrightarrow {v}_2\overrightarrow {v}_2^*. Find KK such that exp(K)=A\mathrm{exp}\left(K\right) = A.

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Problem 9.1.44

Any 2×22 \times 2 matrix AA can be written as a linear combination of the Pauli spin matrices and the 2×22 \times 2 identity matrix I2I_2

A=aI2+bσ1+cσ2+dσ3 A = aI_2 + b\sigma _1 + c\sigma _2 + d\sigma _3

where a,b,c,d∈Ca,b,c,d \in \mathbb {C}.

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(i)

Find A2A^2 and A3A^3.

(ii)

Use the result from (i) to find all matrices AA such that A3=σ1A^3 = \sigma_1, i.e. calculate the third root σ13\sqrt[3]{\sigma_1}.

Problem 9.1.45

Let AA, BB, HH, KK be n×nn \times n matrices over C\mathbb {C}. Assume that A2=B2=0nA^2 = B^2 = 0_n. Let z∈Cz \in \mathbb {C}. Calculate

ez(A⊗B)(H⊗K)e−z(A⊗B) e^{z(A \otimes B)}(H \otimes K)e^{-z(A \otimes B)}

using the Baker-Campbell-Hausdorff formula.

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Problem 9.1.46
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(i)

Let AA, BB be n×nn \times n matrices over C\mathbb {C}, z∈Cz \in \mathbb {C} and u→,v→∈Cn\overrightarrow {u}, \overrightarrow {v} \in \mathbb {C}^{n}. Calculate

exp⁡(z(A⊗B))(u→⊗v→). \exp (z(A \otimes B))(\overrightarrow {u} \otimes \overrightarrow {v}).
(ii)

Simplify the result from (i) if A2=InA^2 = I_n and B2=InB^2 = I_n.

Problem 9.1.47

Let AA be an n×nn \times n matrix. Calculate

exp⁡(0nAA0n) \exp \begin{pmatrix} 0_n & A \\ A & 0_n \end{pmatrix}

using the identity

(0110)⊗A≡(0nAA0n). \begin{pmatrix} 0 & 1 \\ 1 & 0 \end{pmatrix} \otimes A \equiv \begin{pmatrix} 0_n & A \\ A & 0_n \end{pmatrix}.
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Problem 9.1.48
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(i)

Let A1,A2,…,AmA_1, A_2, \ldots , A_m be n×nn \times n matrices with Aj2=InA_j^2 = I_n for j=1,…,mj = 1,\ldots ,m. Let z∈Cz \in \mathbb {C}. Calculate

exp⁡(z(A1⊗A2⊗⋯⊗Am)). \exp (z(A_1 \otimes A_2 \otimes \cdots \otimes A_m)).
(ii)

Use the result from (i) to calculate exp⁡(−iθ(σ1⊗σ2⊗σ3))\exp (-i\theta (\sigma_1 \otimes \sigma_2 \otimes \sigma_3)), where θ∈R\theta \in \mathbb {R}.

Problem 9.1.49
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(i)

Let AA be an n×nn \times n matrix over C\mathbb {C} and Π\Pi be an m×mm \times m projection matrix. Let z∈Cz \in \mathbb {C}. Calculate

exp⁡(z(A⊗Π)). \exp (z(A \otimes \Pi )).
(ii)

Let A1A_1, A2A_2 be n×nn \times n matrices over C\mathbb {C}. Let Π1\Pi_1, Π2\Pi_2 be m×mm \times m projection matrices with Π1Π2=0n\Pi_1\Pi_2 = 0_n. Calculate

exp⁡(z(A1⊗Π1+A2⊗Π2)). \exp (z(A_1 \otimes \Pi _1 + A_2 \otimes \Pi _2)).
(iii)

Use the result from (ii) to find the unitary matrix

U(t)=exp⁡(−iH^t/ℏ) U(t) = \exp (-i\hat{H}t/\hbar )

where H^=ℏω(A1⊗Π1+A2⊗Π2)\hat{H} = \hbar \omega (A_1 \otimes \Pi_1 + A_2 \otimes \Pi_2) and we assume that A1A_1 and A2A_2 are hermitian matrices.

Problem 9.1.50

Let AA, BB be n×nn \times n matrices over C\mathbb {C}. Let u→\overrightarrow {u} be an eigenvector of AA and v→\overrightarrow {v} be an eigenvector of BB, respectively, i.e. Au→=λu→A\overrightarrow {u} = \lambda \overrightarrow {u}, Bv→=μv→B\overrightarrow {v} = \mu \overrightarrow {v}.

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(i)

Find eA⊗B(u→⊗v→)e^{A \otimes B}(\overrightarrow {u} \otimes \overrightarrow {v}).

(ii)

Find eA⊗In+In⊗B(u→⊗v→)e^{A \otimes I_n+I_n \otimes B}(\overrightarrow {u} \otimes \overrightarrow {v}).

(iii)

Find eA⊗In+In⊗B+A⊗B(u→⊗v→)e^{A \otimes I_n+I_n \otimes B+A \otimes B}(\overrightarrow {u} \otimes \overrightarrow {v}).

Problem 9.1.51

For every positive definite matrix AA, there is a unique positive definite matrix QQ such that Q2=AQ^2 = A. The matrix QQ is called the square root of AA. Can we find the square root of the matrix

B=12(5335)? B = \frac{1}{2} \begin{pmatrix} 5 & 3 \\ 3 & 5 \end{pmatrix}?
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Problem 9.1.52

Consider the 2×22 \times 2 matrix

A=(1112). A = \begin{pmatrix} 1 & 1 \\ 1 & 2 \end{pmatrix}.

The matrix is symmetric over R\mathbb {R} and the eigenvalues are positive. Thus the matrix is positive definite. Show that

X=15(2113),Y=(0111) X = \frac{1}{\sqrt{5}} \begin{pmatrix} 2 & 1 \\ 1 & 3 \end{pmatrix}, \qquad Y = \begin{pmatrix} 0 & 1 \\ 1 & 1 \end{pmatrix}

are square roots of AA. Discuss.

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Problem 9.1.53

Find the square root of the Pauli matrix σ1\sigma_1 applying the spectral theorem.

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Problem 9.1.54

Let AA be an n×nn \times n matrix over C\mathbb {C}. The n×nn \times n matrix BB over C\mathbb {C} is a square root of AA iff B2=AB^2 = A. The number of square roots of a given matrix AA may be zero, finite or infinite. Does the matrix

A=(0100) A = \begin{pmatrix} 0 & 1 \\ 0 & 0 \end{pmatrix}

admit a square root?

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Problem 9.1.55

Find a square root of the nonnormal 3×33 \times 3 matrix

A=(010000000) A = \begin{pmatrix} 0 & 1 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 0 \end{pmatrix}

i.e. find the matrices BB such that B2=AB^2 = A.

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Problem 9.1.56

Consider the two-dimensional rotation matrix

R(α)=(cos⁡(α)−sin⁡(α)sin⁡(α)cos⁡(α)) R(\alpha ) = \begin{pmatrix} \cos (\alpha ) & -\sin (\alpha ) \\ \sin (\alpha ) & \cos (\alpha ) \end{pmatrix}

with 0≤α≤π0 \leq \alpha \leq \pi. Find a square root R1/2(α)R^{1/2}(\alpha ) of R(α)R(\alpha ), i.e. a matrix SS such that S2=R(α)S^2 = R(\alpha ).

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Problem 9.1.57

Let V1V_1 be a hermitian n×nn \times n matrix. Let V2V_2 be a positive semidefinite n×nn \times n matrix. Let kk be a positive integer. Show that

tr⁡((V2V1)k) \operatorname {tr}((V_2V_1)^k)

can be written as tr⁡(Vk)\operatorname {tr}(V^k), where V:=V21/2V1V21/2V := V_2^{1/2}V_1V_2^{1/2}.

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Problem 9.1.58

Let AA, BB be n×nn \times n hermitian matrices. Then (Golden-Thompson inequality)

tr⁡(eA+B)≤tr⁡(eAeB). \operatorname {tr}(e^{A+B}) \leq \operatorname {tr}(e^Ae^B).

Let A=σ3A = \sigma_3 and B=σ1B = \sigma_1. Calculate the left and right-hand side of the inequality.

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Problem 9.1.59

Let AA be an n×nn \times n matrix over R\mathbb {R}. The (p,q)(p,q) Pade approximation to exp(A)\mathrm{exp}\left(A\right) is defined by

Rpq(A):=(Dpq(A))−1Npq(A) R_{pq}(A) := (D_{pq}(A))^{-1}N_{pq}(A)

where

Npq(A)=∑j=0p(p+q−j)!p!(p+q)!j!(p−j)!Aj,Dpq(A)=∑j=0q(p+q−j)!q!(p+q)!j!(q−j)!(−A)j. N_{pq}(A) = \sum _{j=0}^{p} \frac{(p+q-j)!p!}{(p+q)!j!(p-j)!}A^j, \qquad D_{pq}(A) = \sum _{j=0}^{q} \frac{(p+q-j)!q!}{(p+q)!j!(q-j)!}(-A)^j.

Nonsingularity of Dpq(A)D_{pq}(A) is assured if pp and qq are large enough or if the eigenvalues of AA are negative. Find the Pade approximation for the matrix

A=(0110) A = \begin{pmatrix} 0 & 1 \\ 1 & 0 \end{pmatrix}

and p=q=2p = q = 2. Compare with the exact solution.

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Problem 9.1.60

Let AA be an n×nn \times n matrix. We define the j−kj-k approximant of exp(A)\mathrm{exp}\left(A\right) by

fj,k(A):=(∑ℓ=0k1ℓ!(Aj)ℓ)j.(1) f_{j,k}(A) := \left(\sum _{\ell =0}^{k} \frac{1}{\ell !}\left(\frac{A}{j}\right)^{\ell }\right)^j. \tag {1}

We have the inequality

∥eA−fj,k(A)∥≤1jk(k+1)!∥A∥k+1e∥A∥(2) \left\| e^A-f_{j,k}(A)\right\| \leq \frac{1}{j^k(k+1)!}\left\| A\right\| ^{k+1}e^{\left\| A\right\| } \tag {2}

and fj,k(A)f_{j,k}(A) converges to eAe^A, i.e.

lim⁡j→∞fj,k(A)=lim⁡k→∞fj,k(A)=eA. \lim _{j \to \infty } f_{j,k}(A) = \lim _{k \to \infty } f_{j,k}(A) = e^A.

Let

A=(0100). A = \begin{pmatrix} 0 & 1 \\ 0 & 0 \end{pmatrix}.

Find f2,2(A)f_{2,2}(A) and eAe^A. Calculate the right-hand side of the inequality (2).

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Problem 9.1.61

The Denman-Beavers iteration for the square root of an n×nn \times n matrix AA with no eigenvalues on R−\mathbb {R}^- is

Yk+1=12(Yk+Zk−1),Zk+1=12(Zk+Yk−1) Y_{k+1} = \frac{1}{2}(Y_k+Z_k^{-1}), \qquad Z_{k+1} = \frac{1}{2}(Z_k+Y_k^{-1})

with k=0,1,2,…k = 0,1,2,\ldots and Z0=InZ_0 = I_n and Y0=AY_0 = A. The iteration has the properties that

lim⁡k→∞Yk=A1/2,lim⁡k→∞Zk=A−1/2 \lim _{k \to \infty } Y_k = A^{1/2}, \qquad \lim _{k \to \infty } Z_k = A^{-1/2}

and, for all kk,

Yk=AZk,YkZk=ZkYk,Yk+1=12(Yk+AYk−1). Y_k = AZ_k, \qquad Y_kZ_k = Z_kY_k, \qquad Y_{k+1} = \frac{1}{2}(Y_k+AY_k^{-1}).
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(i)

Show that the Denman-Beavers iteration be applied to the matrix

A=(1112). A = \begin{pmatrix} 1 & 1 \\ 1 & 2 \end{pmatrix}.
(ii)

Find Y1Y_1 and Z1Z_1.

Problem 9.2.1

Let z1,z2,z3∈Cz_1, z_2, z_3 \in \mathbb {C}. Consider the 2×22 \times 2 matrix

A(z1,z2,z3)=(z1z2z30). A(z_1,z_2,z_3) = \begin{pmatrix} z_1 & z_2 \\ z_3 & 0 \end{pmatrix}.

Calculate exp(A(z1,z2,z3))\mathrm{exp}\left(A(z_1,z_2,z_3)\right).

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Problem 9.2.2

Let α∈R\alpha \in \mathbb {R}. Calculate the vector in R2\mathbb {R}^{2}

exp⁡(α(0100))(10) \exp \left(\alpha \begin{pmatrix} 0 & 1 \\ 0 & 0 \end{pmatrix}\right) \begin{pmatrix} 1 \\ 0 \end{pmatrix}

in two different ways. Compare and discuss.

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Problem 9.2.3

Let AA, BB be n×nn \times n matrices.

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(i)

Show that

[eA,eB]=eAeB−eBeA=∑j,k=1∞1j!k![Aj,Bk]. [e^A,e^B] = e^Ae^B - e^Be^A = \sum _{j,k=1}^{\infty } \frac{1}{j!k!}[A^j,B^k].
(ii)

Assume that for all eigenvalues λ\lambda we have ℜ(λ)<0\Re (\lambda ) < 0. Let BB be an arbitrary n×nn \times n matrix over C\mathbb {C}. Let

R(t):=∫0∞etA∗BetAdt. R(t) := \int _0^{\infty } e^{tA^*}Be^{tA}dt.

Show that the matrix RR satisfies R(t)A+A∗R(t)=−BR(t)A + A^*R(t) = -B.

Problem 9.2.4

Let AA, BB be n×nn \times n matrices over C\mathbb {C}. Is tr⁡(eA⊗eB)=tr⁡(eA⊗B)\operatorname {tr}(e^A \otimes e^B) = \operatorname {tr}(e^{A \otimes B})? Prove or disprove.

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Problem 9.2.5
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(i)

Let A1,A2,…,ApA_1, A_2, \ldots , A_p be n×nn \times n matrices over C\mathbb {C}. The generalized Trotter formula is given by

exp⁡(∑j=1nAj)=lim⁡n→∞fn({Aj})(1) \exp \left(\sum _{j=1}^{n} A_j\right) = \lim _{n \to \infty } f_n(\left\{ A_j\right\} ) \tag {1}

where the nn-th approximant fn({Aj})f_n(\left\{ A_j\right\} ) is defined by

fn({Aj}):=(exp⁡(1nA1)exp⁡(1nA2)⋯exp⁡(1nAp))n. f_n(\left\{ A_j\right\} ) := \left(\exp \left(\frac{1}{n}A_1\right)\exp \left(\frac{1}{n}A_2\right) \cdots \exp \left(\frac{1}{n}A_p\right)\right)^n.

Let p=2p = 2 and

A1=(1001),A2=(0110). A_1 = \begin{pmatrix} 1 & 0 \\ 0 & 1 \end{pmatrix}, \qquad A_2 = \begin{pmatrix} 0 & 1 \\ 1 & 0 \end{pmatrix}.

Calculate the left and right-hand side of (1).

(ii)

Let AA, BB be n×nn \times n matrices over C\mathbb {C} with A2=B2=InA^2 = B^2 = I_n and [A,B]+=0n[A,B]_+ = 0_n. Let z∈Cz \in \mathbb {C}. The Lie-Trotter formula is given by

exp⁡(z(A+B))=lim⁡p→∞(ezA/pezB/p)p. \exp (z(A+B)) = \lim _{p \to \infty } \left(e^{zA/p}e^{zB/p}\right)^p.

Calculate ez(A+B)e^{z(A+B)} using the right-hand side. Note that

ezA/p=Incosh⁡(z/p)+Asinh⁡(z/p),ezB/p=Incosh⁡(z/p)+Bsinh⁡(z/p). e^{zA/p} = I_n\cosh (z/p) + A\sinh (z/p), \qquad e^{zB/p} = I_n\cosh (z/p) + B\sinh (z/p).
Problem 9.2.6
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(i)

Let AA, BB be n×nn \times n matrices with AB=BAAB = BA. Show that

cos⁡(A+B)≡cos⁡(A)cos⁡(B)−sin⁡(A)sin⁡(B). \cos (A+B) \equiv \cos (A)\cos (B) - \sin (A)\sin (B).
(ii)

Let x,y∈Rx, y \in \mathbb {R}. We know that sin⁡(x+y)≡sin⁡(x)cos⁡(y)+cos⁡(x)sin⁡(y)\sin (x+y) \equiv \sin (x)\cos (y) + \cos (x)\sin (y). Let

C=(1111),D=(0110). C = \begin{pmatrix} 1 & 1 \\ 1 & 1 \end{pmatrix}, \qquad D = \begin{pmatrix} 0 & 1 \\ 1 & 0 \end{pmatrix}.

Is sin⁡(C+D)=sin⁡(C)cos⁡(D)+cos⁡(C)sin⁡(D)\sin (C+D) = \sin (C)\cos (D) + \cos (C)\sin (D)? Prove or disprove.

Problem 9.2.7

Let AA, BB be n×nn \times n matrices over C\mathbb {C}. The Laplace transform L\mathcal{L} of the matrix exponential is the resolvent

L(etA)=(λIn−A)−1. \mathcal{L}(e^{tA}) = (\lambda I_n - A)^{-1}.
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(i)

Calculate L(etA⊗etB)\mathcal{L}(e^{tA} \otimes e^{tB}).

(ii)

Let L−1\mathcal{L}^{-1} be the inverse Laplace transform. Find

L−1((λIn−A)−1⊗(λIn−B)−1). \mathcal{L}^{-1}((\lambda I_n-A)^{-1} \otimes (\lambda I_n-B)^{-1}).
Problem 9.2.8

Let AA be an n×nn \times n matrix. The characteristic polynomial

det⁡(λIn−A)=λn+a1λn−1+⋯+an=p(λ) \det (\lambda I_n - A) = \lambda ^n + a_1\lambda ^{n-1} + \cdots + a_n = p(\lambda )

is closely related the resolvent (λIn−A)−1(\lambda I_n - A)^{-1} trough the formula

(λIn−A)−1=N1λn−1+N2λn−2+⋯+Nnλn+a1λn−1+⋯+an=N(λ)p(λ) (\lambda I_n - A)^{-1} = \frac{N_1\lambda ^{n-1}+N_2\lambda ^{n-2}+\cdots +N_n}{\lambda ^n+a_1\lambda ^{n-1}+\cdots +a_n} = \frac{N(\lambda )}{p(\lambda )}

where the adjugate matrix N(λ)N(\lambda ) is a polynomial in λ\lambda of degree n−1n-1 with constant n×nn \times n coefficient matrices N1,…,NnN_1,\ldots ,N_n. The Laplace transform of the matrix exponential is the resolvent

L(etA)=(λIn−A)−1. \mathcal{L}(e^{tA}) = (\lambda I_n - A)^{-1}.

The NkN_k matrices and aka_k coefficients may be computed recursively as follows

N1=In,a1=−11tr⁡(AN1) N_1 = I_n, \qquad a_1 = -\frac{1}{1}\operatorname {tr}(AN_1) N2=AN1+a1In,a2=−12tr⁡(AN2) N_2 = AN_1 + a_1I_n, \qquad a_2 = -\frac{1}{2}\operatorname {tr}(AN_2) ⋮ \vdots Nn=ANn−1+an−1In,an=−1ntr⁡(ANn) N_n = AN_{n-1} + a_{n-1}I_n, \qquad a_n = -\frac{1}{n}\operatorname {tr}(AN_n) 0n=ANn+anIn. 0_n = AN_n + a_nI_n.

Show that

tr⁡(L(etA))=1p(λ)dp(λ)dλ. \operatorname {tr}(\mathcal{L}(e^{tA})) = \frac{1}{p(\lambda )}\frac{dp(\lambda )}{d\lambda }.
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Problem 9.2.9

Let AA be an arbitrary n×nn \times n matrix. Can we conclude that exp(A∗)=(exp(A))∗\mathrm{exp}\left(A^*\right) = (\mathrm{exp}\left(A\right))^*?

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Problem 9.2.10

Let AA be an n×nn \times n matrix over C\mathbb {C}. Assume that AA is hermitian, i.e. A∗=AA^* = A. Thus AA has only real eigenvalues. Assume that A5+A3+A=3InA^5+A^3+A = 3I_n. Show that A=InA = I_n.

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Problem 9.2.11

Let AA, BB be n×nn \times n hermitian matrices. There exists n×nn \times n unitary matrices UU and VV (depending on AA and BB) such that

exp(iA)exp(iB)=exp(iUAU−1+iVBV−1). \mathrm{exp}\left(iA\right)\mathrm{exp}\left(iB\right) = \mathrm{exp}\left(iUAU^{-1}+iVBV^{-1}\right).

Consider n=2n = 2 and

A=(0110),B=12(111−1)  ⇒  [A,B]=2(0−110). A = \begin{pmatrix} 0 & 1 \\ 1 & 0 \end{pmatrix}, \qquad B = \frac{1}{\sqrt{2}} \begin{pmatrix} 1 & 1 \\ 1 & -1 \end{pmatrix} \; \Rightarrow \; [A,B] = \sqrt{2} \begin{pmatrix} 0 & -1 \\ 1 & 0 \end{pmatrix}.

Find UU and VV. Note that AA and BB are also unitary.

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Problem 9.2.12

Let AA, BB be n×nn \times n matrices over C\mathbb {C} such that [A,B]=A[A,B] = A. What can be said about the commutator [eA,eB][e^A,e^B]?

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Problem 9.2.13
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(i)

Let AA be an n×nn \times n nilpotent matrix. Is the matrix cos⁡(A)\cos (A) invertible?

(ii)

Let NN be a nilpotent n×nn \times n matrix with Nj=0nN^j = 0_n with j≥1j \geq 1. Is

ln⁡(In−N)=−(N+12N+⋯+1j−1Nj−1) \ln (I_n-N) = -\left(N+\frac{1}{2}N+\cdots +\frac{1}{j-1}N^{j-1}\right)

and exp⁡(ln⁡(In−N))=In−N\exp (\ln (I_n-N)) = I_n-N.

Problem 9.2.14

Let H=H1+H2+H3H = H_1+H_2+H_3 and H1H_1, H2H_2, H3H_3 be n×nn \times n hermitian matrices. Show that

e−βH=e−βH1/2e−βH2/2e−βH3e−βH2/2e−βH1/2+(−12β)3S e^{-\beta H} = e^{-\beta H_1/2}e^{-\beta H_2/2}e^{-\beta H_3}e^{-\beta H_2/2}e^{-\beta H_1/2} + \left(-\frac{1}{2}\beta \right)^3 S

where

S=16([[H2+H3,H1],H1+2H2+2H3]+[[H3,H2],H2+H3]). S = \frac{1}{6}([[H_2+H_3,H_1],H_1+2H_2+2H_3] + [[H_3,H_2],H_2+H_3]).
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Problem 9.2.15
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(i)

Let rr, ss be integers with r≥2r \geq 2 and s≥2s \geq 2. Let AA, BB be n×nn \times n matrices with Ar=0nA^r = 0_n and Bs=0nB^s = 0_n. Calculate exp(A⊗B)\mathrm{exp}\left(A \otimes B\right).

(ii)

Let AA, BB be the basis (given by n×nn \times n matrices) of the non-commutative two-dimensional Lie algebra with [A,B]=A[A,B] = A. Calculate exp⁡(A⊗In+In⊗A+B⊗B)\exp (A \otimes I_n+I_n \otimes A+B \otimes B).

(iii)

Let X1X_1, X2X_2, X3X_3 be the basis (given by n×nn \times n matrices) of a Lie algebra with the commutation relations

[X1,X2]=0n,[X1,X3]=X1,[X2,X3]=0n. [X_1,X_2] = 0_n, \qquad [X_1,X_3] = X_1, \qquad [X_2,X_3] = 0_n.

Calculate exp⁡(X1+X2+X3)\exp (X_1+X_2+X_3) and

exp⁡(X1⊗In⊗In+In⊗X2⊗In+In⊗In⊗X3+X1⊗X2⊗X3). \exp (X_1 \otimes I_n \otimes I_n+I_n \otimes X_2 \otimes I_n+I_n \otimes I_n \otimes X_3+X_1 \otimes X_2 \otimes X_3).
Problem 9.2.16

Consider the 3×33 \times 3 matrix

A=(101010101)=I3+B,B=(001000100). A = \begin{pmatrix} 1 & 0 & 1 \\ 0 & 1 & 0 \\ 1 & 0 & 1 \end{pmatrix} = I_3+B, \qquad B = \begin{pmatrix} 0 & 0 & 1 \\ 0 & 0 & 0 \\ 1 & 0 & 0 \end{pmatrix}.

Calculate exp(A)\mathrm{exp}\left(A\right) using eA=eI3eBe^A = e^{I_3}e^B.

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Problem 9.2.17

Let z∈Cz \in \mathbb {C}. Construct all 2×22 \times 2 matrices AA and BB over C\mathbb {C} such that

exp(zA)Bexp(−zA)=e−zB. \mathrm{exp}\left(zA\right)B\mathrm{exp}\left(-zA\right) = e^{-z}B.
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Problem 9.2.18

Let AA be an n×nn \times n matrix over C\mathbb {C}. Consider the Taylor series

(In+A)1/2=In+12A−12⋅4A2+1⋅32⋅4⋅6A3−⋯ (I_n+A)^{1/2} = I_n+\frac{1}{2}A-\frac{1}{2 \cdot 4}A^2+\frac{1 \cdot 3}{2 \cdot 4 \cdot 6}A^3-\cdots

and

(In+A)−1/2=In−12A+1⋅32⋅4A2−1⋅3⋅52⋅4⋅6A3+⋯ (I_n+A)^{-1/2} = I_n-\frac{1}{2}A+\frac{1 \cdot 3}{2 \cdot 4}A^2-\frac{1 \cdot 3 \cdot 5}{2 \cdot 4 \cdot 6}A^3+\cdots

What is the condition (the norm) on AA such that the Taylor series exist? Can it be applied to the matrix

A=(1111)? A = \begin{pmatrix} 1 & 1 \\ 1 & 1 \end{pmatrix}?

Note that for n=1n=1 we have the condition −1<A≤+1-1 < A \leq +1.

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Problem 9.2.19

Let UU be an n×nn \times n unitary matrix. Let H=U+U∗H = U+U^*. Calculate exp(zH)\mathrm{exp}\left(zH\right).

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Problem 9.2.20

Let AA, BB be n×nn \times n matrices over C\mathbb {C} and exp(A)exp(B)=exp(C)\mathrm{exp}\left(A\right)\mathrm{exp}\left(B\right) = \mathrm{exp}\left(C\right). Then the matrix CC can be given as an infinite series of commutators of AA and BB. Let z∈Cz \in \mathbb {C}. We write

exp⁡(zA)exp⁡(zB)=exp⁡(C(zA,zB)) \exp (zA)\exp (zB) = \exp (C(zA,zB))

where

C(zA,zB)=∑j=1∞cj(A,B)zj. C(zA,zB) = \sum _{j=1}^{\infty } c_j(A,B)z^j.

Show that the expansion up to fourth order is given by

c1(A,B)=A+B,c2(A,B)=12[A,B], c_1(A,B) = A+B, \qquad c_2(A,B) = \frac{1}{2}[A,B], c3(A,B)=112[A,[A,B]]−112[B,[A,B]],c4(A,B)=−124[A,[B,[A,B]]]. c_3(A,B) = \frac{1}{12}[A,[A,B]] - \frac{1}{12}[B,[A,B]], \qquad c_4(A,B) = -\frac{1}{24}[A,[B,[A,B]]].
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Problem 9.2.21

Let A1,…,AmA_1, \ldots , A_m be n×nn \times n matrices. Show that

eA1⋯eAm=exp⁡(12∑j<k[Aj,Ak])exp⁡(A1+⋯+Am) e^{A_1} \cdots e^{A_m} = \exp \left(\frac{1}{2}\sum _{j<k}[A_j,A_k]\right)\exp (A_1+\cdots +A_m)

if the matrices AjA_j (j=1,…,mj=1,\ldots ,m) satisfy

[[Aj,Ak],Aℓ]=0nfor all j,k,ℓ∈{1,…,m}. [[A_j,A_k],A_\ell ] = 0_n \quad \text{for all } j,k,\ell \in \left\{ 1,\ldots ,m\right\} .
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Problem 9.2.22

Let AA, BB, CC be n×nn \times n positive semidefinite matrices. We define

A∘B:=A1/2BA1/2 A \circ B := A^{1/2}BA^{1/2}

where A1/2A^{1/2} denotes the unique positive square root of AA. Is A∘(B∘C)=(A∘B)∘CA \circ (B \circ C) = (A \circ B) \circ C? Prove or disprove.

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Problem 9.2.23
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(i)

Let σ1\sigma_1 be the Pauli spin matrix. Show that

exp⁡(−12iπ(σ1−I2))=σ1. \exp \left(-\frac{1}{2}i\pi (\sigma _1-I_2)\right) = \sigma _1.
(ii)

Find all 2×22 \times 2 matrices AA and c∈Cc \in \mathbb {C} such that exp⁡(c(A−I2))=A\exp (c(A-I_2)) = A. Note that

exp⁡(c(A−I2))=exp⁡(cA)exp⁡(−cI2)=exp⁡(cA)(e−c00e−c). \exp (c(A-I_2)) = \exp (cA)\exp (-cI_2) = \exp (cA) \begin{pmatrix} e^{-c} & 0 \\ 0 & e^{-c} \end{pmatrix}.
Problem 9.2.24

Let AA, BB be real symmetric positive definite matrices. Show that

1det⁡(A)det⁡(A+B)≤exp(tr⁡(A−1B)). \frac{1}{\operatorname {det}\left(A\right)}\operatorname {det}\left(A+B\right) \leq \mathrm{exp}\left(\operatorname {tr}(A^{-1}B)\right).
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Problem 9.2.25

Let ϵ∈R\epsilon \in \mathbb {R}. Let In−ϵAI_n - \epsilon A be a positive definite matrix. Show that

exp⁡(tr⁡(ln⁡(In−ϵA)))=det⁡(In−ϵA) \exp (\operatorname {tr}(\ln (I_n-\epsilon A))) = \operatorname {det}\left(I_n-\epsilon A\right)

using the identity det⁡(eM)≡exp(tr⁡(M))\operatorname {det}\left(e^M\right) \equiv \mathrm{exp}\left(\operatorname {tr}(M)\right).

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Problem 9.2.26

Let v→\overrightarrow {v} be a normalized (column) vector in Cn\mathbb {C}^{n} and let AA be an n×nn \times n hermitian matrix. Is v→∗exp(A)v→≥exp(v→∗Av→)\overrightarrow {v}^*\mathrm{exp}\left(A\right)\overrightarrow {v} \geq \mathrm{exp}\left(\overrightarrow {v}^*A\overrightarrow {v}\right) for all normalized v→\overrightarrow {v}? Prove or disprove.

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Problem 9.2.27
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(i)

Let ϵ∈R\epsilon \in \mathbb {R}. Let AA be an n×nn \times n matrix over C\mathbb {C}. Find

lim⁡ϵ→0sinh⁡(2ϵA)sinh⁡(ϵ). \lim _{\epsilon \to 0} \frac{\sinh (2\epsilon A)}{\sinh (\epsilon )}.
(ii)

Assume that A2=InA^2 = I_n. Calculate

sinh⁡(2ϵA)sinh⁡(ϵ). \frac{\sinh (2\epsilon A)}{\sinh (\epsilon )}.
(iii)

Assume that A2=0nA^2 = 0_n. Calculate

sinh⁡(2ϵA)sinh⁡(ϵ). \frac{\sinh (2\epsilon A)}{\sinh (\epsilon )}.

Utilize the expansion

sinh⁡(2ϵA)=2ϵA+(2ϵ)33!A3+⋯ . \sinh (2\epsilon A) = 2\epsilon A + \frac{(2\epsilon )^3}{3!}A^3 + \cdots .
Problem 9.2.28

Let α>0\alpha > 0. Consider the 4×44 \times 4 matrix

A(α)=(000i/α00i00i00αi000). A(\alpha ) = \begin{pmatrix} 0 & 0 & 0 & i/\alpha \\ 0 & 0 & i & 0 \\ 0 & i & 0 & 0 \\ \alpha i & 0 & 0 & 0 \end{pmatrix}.

Show that exp⁡(πA(α))=−I4\exp (\pi A(\alpha )) = -I_4.

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Problem 9.2.29

Let VV be the 2×22 \times 2 matrix V=v0I2+v1σ1+v2σ2+v3σ3V = v_0I_2+v_1\sigma_1+v_2\sigma_2+v_3\sigma_3, where v0,v1,v2,v3∈Rv_0, v_1, v_2, v_3 \in \mathbb {R}. Consider the equation

exp⁡(iϵV)=(I2−iW)(I2+iW)−1 \exp (i\epsilon V) = (I_2-iW)(I_2+iW)^{-1}

where ϵ\epsilon is real. Show that WW as a function of VV is given by

W=−tan⁡(12ϵ(v0I2+v1σ1+v2σ2+v3σ3)). W = -\tan \left(\frac{1}{2}\epsilon (v_0I_2+v_1\sigma _1+v_2\sigma _2+v_3\sigma _3)\right).
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Problem 9.2.30

Let AA, BB be n×nn \times n matrices. Show that

eA⊗In+In⊗AeB⊗In+In⊗B=(eA⊗eB)(eB⊗eB)=(eAeB)⊗(eAeB). e^{A \otimes I_n+I_n \otimes A}e^{B \otimes I_n+I_n \otimes B} = (e^A \otimes e^B)(e^B \otimes e^B) = (e^Ae^B) \otimes (e^Ae^B).
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Problem 9.2.31

Let α∈R\alpha \in \mathbb {R} and Π\Pi be an n×nn \times n projection matrix. Let Q=Π1/2Q = \Pi^{1/2} be a square root of Π\Pi, i.e. Q2=ΠQ^2 = \Pi. Show that

U(α)=exp⁡(iαΠ1/2)=In+iαΠ1/2+(cos⁡(α)−1)Π+i(sin⁡(α)−α)ΠΠ1/2. U(\alpha ) = \exp (i\alpha \Pi ^{1/2}) = I_n + i\alpha \Pi ^{1/2} + (\cos (\alpha )-1)\Pi + i(\sin (\alpha )-\alpha )\Pi \Pi ^{1/2}.
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Problem 9.2.32

Let AA be an n×nn \times n matrix over R\mathbb {R}. Then we have the Taylor expansion

sin⁡(A):=∑k=0∞(−1)k(2k+1)!A2k+1,cos⁡(A):=∑k=0∞(−1)k(2k)!A2k. \sin (A) := \sum _{k=0}^{\infty } \frac{(-1)^k}{(2k+1)!}A^{2k+1}, \qquad \cos (A) := \sum _{k=0}^{\infty } \frac{(-1)^k}{(2k)!}A^{2k}.

To calculate sin⁡(A)\sin (A) and cos⁡(A)\cos (A) from a truncated Taylor series approximation is only worthwhile near the origin. We can use the repeated application of the double angle formula

cos⁡(2A)≡2cos⁡2(A)−In,sin⁡(2A)≡2sin⁡(A)cos⁡(A). \cos (2A) \equiv 2\cos ^2(A) - I_n, \qquad \sin (2A) \equiv 2\sin (A)\cos (A).

We can find sin⁡(A)\sin (A) and cos⁡(A)\cos (A) of a matrix AA from a suitably truncated Taylor series approximates as follows

S0=Taylor approximate to sin⁡(A/2k),C0=Taylor approximate to cos⁡(A/2k) S_0 = \text{Taylor approximate to } \sin (A/2^k), \qquad C_0 = \text{Taylor approximate to } \cos (A/2^k)

and the recursion

Sj=2Sj−1Cj−1,Cj=2Cj−12−In S_j = 2S_{j-1}C_{j-1}, \qquad C_j = 2C_{j-1}^2 - I_n

where j=1,2,…j = 1,2,\ldots. Here kk is a positive integer chosen so that, say ∥A∥∞≈2k\left\| A\right\|_{\infty } \approx 2^k. Apply this recursion to calculate sine and cosine of the 2×22 \times 2 matrix

A=(2112). A = \begin{pmatrix} 2 & 1 \\ 1 & 2 \end{pmatrix}.

Use k=2k=2.

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Problem 9.2.33

Let TT be the 2×22 \times 2 matrix

T=13(1111). T = \frac{1}{3} \begin{pmatrix} 1 & 1 \\ 1 & 1 \end{pmatrix}.

Calculate ln⁡(det⁡(I2−T))\ln (\operatorname {det}\left(I_2-T\right)) using the right-hand side of the identity

ln⁡(det⁡(I2−T))≡−∑k=1∞1ktr⁡(Tk). \ln (\operatorname {det}\left(I_2-T\right)) \equiv -\sum _{k=1}^{\infty } \frac{1}{k}\operatorname {tr}(T^k).
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