東京大学 新領域創成科学研究科 メディカル情報生命専攻 2024年1月実施 問題11
Author
zephyr , 祭音Myyura (with the help of an anonymous contributor)
Description
A quantum state of a 1-qubit quantum computer can be represented by a 2 × 2 2 \times 2 2 × 2 complex matrix ρ = 1 2 ( 1 + a b − i c b + i c 1 − a ) \rho = \frac{1}{2} \begin{pmatrix} 1 + a & b - ic \\ b + ic & 1 - a \end{pmatrix} ρ = 2 1 ( 1 + a b + i c b − i c 1 − a ) called a density matrix. Here, i = − 1 i = \sqrt{-1} i = − 1 is the imaginary unit that satisfies i 2 = − 1 i^2 = -1 i 2 = − 1 and a , b , c a, b, c a , b , c are real numbers that satisfy a 2 + b 2 + c 2 ≤ 1 a^2 + b^2 + c^2 \leq 1 a 2 + b 2 + c 2 ≤ 1 . By measuring the qubit represented by matrix ρ \rho ρ in the computational basis (also called the Z-basis), we observe state 0 or state 1 with probabilities p 0 = 1 + a 2 p_0 = \frac{1 + a}{2} p 0 = 2 1 + a and p 1 = 1 − a 2 p_1 = \frac{1 - a}{2} p 1 = 2 1 − a , which are the diagonal elements of matrix ρ \rho ρ , respectively. Answer the following questions with mathematical derivation.
Show that all the eigenvalues of matrix ρ \rho ρ are non-negative real numbers.
Answer the probability that state 0 is observed by measurement in the computational basis after applying quantum gate operation H = 1 2 ( 1 1 1 − 1 ) H = \frac{1}{\sqrt{2}} \begin{pmatrix} 1 & 1 \\ 1 & -1 \end{pmatrix} H = 2 1 ( 1 1 1 − 1 ) to quantum state ρ \rho ρ .
Answer the probability that state 0 is observed by measurement in the computational basis after applying quantum gate operation Y = ( 0 − i i 0 ) Y = \begin{pmatrix} 0 & -i \\ i & 0 \end{pmatrix} Y = ( 0 i − i 0 ) to quantum state ρ \rho ρ .
Let ρ ′ = 1 2 ( 1 + a ′ b ′ − i c ′ b ′ + i c ′ 1 − a ′ ) \rho' = \frac{1}{2} \begin{pmatrix} 1 + a' & b' - ic' \\ b' + ic' & 1 - a' \end{pmatrix} ρ ′ = 2 1 ( 1 + a ′ b ′ + i c ′ b ′ − i c ′ 1 − a ′ ) be the quantum state after applying quantum gate operation U = ( u 00 ′ + i u 00 ′ ′ u 01 ′ + i u 01 ′ ′ u 10 ′ + i u 10 ′ ′ u 11 ′ + i u 11 ′ ′ ) U = \begin{pmatrix} u_{00}' + iu_{00}'' & u_{01}' + iu_{01}'' \\ u_{10}' + iu_{10}'' & u_{11}' + iu_{11}'' \end{pmatrix} U = ( u 00 ′ + i u 00 ′′ u 10 ′ + i u 10 ′′ u 01 ′ + i u 01 ′′ u 11 ′ + i u 11 ′′ ) to quantum state ρ \rho ρ . Compute a ′ 2 + b ′ 2 + c ′ 2 a'^2 + b'^2 + c'^2 a ′2 + b ′2 + c ′2 .
1个量子比特量子计算机的量子态可以表示为一个 2 × 2 2 \times 2 2 × 2 的复数矩阵 ρ = 1 2 ( 1 + a b − i c b + i c 1 − a ) \rho = \frac{1}{2} \begin{pmatrix} 1 + a & b - ic \\ b + ic & 1 - a \end{pmatrix} ρ = 2 1 ( 1 + a b + i c b − i c 1 − a ) ,称为密度矩阵。这里,i = − 1 i = \sqrt{-1} i = − 1 是满足 i 2 = − 1 i^2 = -1 i 2 = − 1 的虚数单位,a , b , c a, b, c a , b , c 是满足 a 2 + b 2 + c 2 ≤ 1 a^2 + b^2 + c^2 \leq 1 a 2 + b 2 + c 2 ≤ 1 的实数。通过在计算基(也称为Z基)中测量由矩阵 ρ \rho ρ 表示的量子比特,我们以概率 p 0 = 1 + a 2 p_0 = \frac{1 + a}{2} p 0 = 2 1 + a 和 p 1 = 1 − a 2 p_1 = \frac{1 - a}{2} p 1 = 2 1 − a 观察到状态0或状态1,分别对应密度矩阵 ρ \rho ρ 的对角元素。用数学推导回答以下问题。
证明矩阵 ρ \rho ρ 的所有特征值都是非负实数。
在对量子态 ρ \rho ρ 施加量子门操作 H = 1 2 ( 1 1 1 − 1 ) H = \frac{1}{\sqrt{2}} \begin{pmatrix} 1 & 1 \\ 1 & -1 \end{pmatrix} H = 2 1 ( 1 1 1 − 1 ) 后,在计算基中测量观察到状态0的概率是多少。
在对量子态 ρ \rho ρ 施加量子门操作 Y = ( 0 − i i 0 ) Y = \begin{pmatrix} 0 & -i \\ i & 0 \end{pmatrix} Y = ( 0 i − i 0 ) 后,在计算基中测量观察到状态0的概率是多少。
设 ρ ′ = 1 2 ( 1 + a ′ b ′ − i c ′ b ′ + i c ′ 1 − a ′ ) \rho' = \frac{1}{2} \begin{pmatrix} 1 + a' & b' - ic' \\ b' + ic' & 1 - a' \end{pmatrix} ρ ′ = 2 1 ( 1 + a ′ b ′ + i c ′ b ′ − i c ′ 1 − a ′ ) 是施加量子门操作 U = ( u 00 ′ + i u 00 ′ ′ u 01 ′ + i u 01 ′ ′ u 10 ′ + i u 10 ′ ′ u 11 ′ + i u 11 ′ ′ ) U = \begin{pmatrix} u_{00}' + iu_{00}'' & u_{01}' + iu_{01}'' \\ u_{10}' + iu_{10}'' & u_{11}' + iu_{11}'' \end{pmatrix} U = ( u 00 ′ + i u 00 ′′ u 10 ′ + i u 10 ′′ u 01 ′ + i u 01 ′′ u 11 ′ + i u 11 ′′ ) 后的量子态。计算 a ′ 2 + b ′ 2 + c ′ 2 a'^2 + b'^2 + c'^2 a ′2 + b ′2 + c ′2 。
Kai
解题思路
这道题目涉及量子计算中的密度矩阵和量子门操作,需要运用线性代数和复数运算的知识。我们将逐步解答每个小问:
求密度矩阵的特征值,证明它们是非负实数。
计算 Hadamard 门(H 门)操作后的测量概率。
计算 Y 门操作后的测量概率。
计算一般量子门 U 操作后的密度矩阵参数。
每个小问都需要详细的数学推导。
1. Show that all the eigenvalues of matrix ρ \rho ρ are non-negative real numbers
To find the eigenvalues of ρ \rho ρ , we need to solve the characteristic equation:
det ( ρ − λ I ) = 0 \det(\rho - \lambda I) = 0 det ( ρ − λ I ) = 0
det ( ( 1 + a 2 − λ b − i c 2 b + i c 2 1 − a 2 − λ ) ) = 0 \det\left(\begin{pmatrix} \frac{1+a}{2} - \lambda & \frac{b-ic}{2} \\ \frac{b+ic}{2} & \frac{1-a}{2} - \lambda \end{pmatrix}\right) = 0 det ( ( 2 1 + a − λ 2 b + i c 2 b − i c 2 1 − a − λ ) ) = 0
( 1 + a 2 − λ ) ( 1 − a 2 − λ ) − ( b − i c 2 ) ( b + i c 2 ) = 0 (\frac{1+a}{2} - \lambda)(\frac{1-a}{2} - \lambda) - (\frac{b-ic}{2})(\frac{b+ic}{2}) = 0 ( 2 1 + a − λ ) ( 2 1 − a − λ ) − ( 2 b − i c ) ( 2 b + i c ) = 0
λ 2 − λ + 1 − a 2 − b 2 − c 2 4 = 0 \lambda^2 - \lambda + \frac{1-a^2-b^2-c^2}{4} = 0 λ 2 − λ + 4 1 − a 2 − b 2 − c 2 = 0
The solutions to this quadratic equation are:
λ = 1 ± 1 − ( 1 − a 2 − b 2 − c 2 ) 2 = 1 ± a 2 + b 2 + c 2 2 \lambda = \frac{1 \pm \sqrt{1-(1-a^2-b^2-c^2)}}{2} = \frac{1 \pm \sqrt{a^2+b^2+c^2}}{2} λ = 2 1 ± 1 − ( 1 − a 2 − b 2 − c 2 ) = 2 1 ± a 2 + b 2 + c 2
Since a 2 + b 2 + c 2 ≤ 1 a^2 + b^2 + c^2 \leq 1 a 2 + b 2 + c 2 ≤ 1 , we have 0 ≤ a 2 + b 2 + c 2 ≤ 1 0 \leq \sqrt{a^2+b^2+c^2} \leq 1 0 ≤ a 2 + b 2 + c 2 ≤ 1 . Therefore, both eigenvalues are real and non-negative.
2. Probability of observing state 0 after applying H gate
The Hadamard gate operation transforms ρ \rho ρ to H ρ H † H\rho H^\dagger H ρ H † . Let's calculate this:
H ρ H † = 1 2 ( 1 1 1 − 1 ) ( 1 + a b − i c b + i c 1 − a ) ( 1 1 1 − 1 ) = 1 4 ( ( 1 + a ) + ( b + i c ) + ( b − i c ) + ( 1 − a ) ( 1 + a ) − ( b + i c ) + ( b − i c ) − ( 1 − a ) ( 1 + a ) + ( b + i c ) − ( b − i c ) − ( 1 − a ) ( 1 + a ) − ( b + i c ) − ( b − i c ) + ( 1 − a ) ) = 1 2 ( 1 + b a − i c a + i c 1 − b ) \begin{aligned}
H\rho H^\dagger &= \frac{1}{2}\begin{pmatrix} 1 & 1 \\ 1 & -1 \end{pmatrix} \begin{pmatrix} 1+a & b-ic \\ b+ic & 1-a \end{pmatrix} \begin{pmatrix} 1 & 1 \\ 1 & -1 \end{pmatrix} \\
&= \frac{1}{4}\begin{pmatrix} (1+a)+(b+ic)+(b-ic)+(1-a) & (1+a)-(b+ic)+(b-ic)-(1-a) \\ (1+a)+(b+ic)-(b-ic)-(1-a) & (1+a)-(b+ic)-(b-ic)+(1-a) \end{pmatrix} \\
&= \frac{1}{2}\begin{pmatrix} 1+b & a-ic \\ a+ic & 1-b \end{pmatrix}
\end{aligned} H ρ H † = 2 1 ( 1 1 1 − 1 ) ( 1 + a b + i c b − i c 1 − a ) ( 1 1 1 − 1 ) = 4 1 ( ( 1 + a ) + ( b + i c ) + ( b − i c ) + ( 1 − a ) ( 1 + a ) + ( b + i c ) − ( b − i c ) − ( 1 − a ) ( 1 + a ) − ( b + i c ) + ( b − i c ) − ( 1 − a ) ( 1 + a ) − ( b + i c ) − ( b − i c ) + ( 1 − a ) ) = 2 1 ( 1 + b a + i c a − i c 1 − b )
The probability of observing state 0 is the top-left element of this matrix:
p 0 = 1 + b 2 p_0 = \frac{1+b}{2} p 0 = 2 1 + b
3. Probability of observing state 0 after applying Y gate
Similarly, for the Y gate:
Y ρ Y † = ( 0 − i i 0 ) ( 1 + a b − i c b + i c 1 − a ) ( 0 i − i 0 ) = ( 1 − a − b − i c − b + i c 1 + a ) \begin{aligned}
Y\rho Y^\dagger &= \begin{pmatrix} 0 & -i \\ i & 0 \end{pmatrix} \begin{pmatrix} 1+a & b-ic \\ b+ic & 1-a \end{pmatrix} \begin{pmatrix} 0 & i \\ -i & 0 \end{pmatrix} \\
&= \begin{pmatrix} 1-a & -b-ic \\ -b+ic & 1+a \end{pmatrix}
\end{aligned} Y ρ Y † = ( 0 i − i 0 ) ( 1 + a b + i c b − i c 1 − a ) ( 0 − i i 0 ) = ( 1 − a − b + i c − b − i c 1 + a )
The probability of observing state 0 is:
p 0 = 1 − a 2 p_0 = \frac{1-a}{2} p 0 = 2 1 − a
4. Compute a ′ 2 + b ′ 2 + c ′ 2 a'^2 + b'^2 + c'^2 a ′2 + b ′2 + c ′2 after applying U gate (by zephyr)
Let U = ( u 00 ′ + i u 00 ′ ′ u 01 ′ + i u 01 ′ ′ u 10 ′ + i u 10 ′ ′ u 11 ′ + i u 11 ′ ′ ) U = \begin{pmatrix} u_{00}' + iu_{00}'' & u_{01}' + iu_{01}'' \\ u_{10}' + iu_{10}'' & u_{11}' + iu_{11}'' \end{pmatrix} U = ( u 00 ′ + i u 00 ′′ u 10 ′ + i u 10 ′′ u 01 ′ + i u 01 ′′ u 11 ′ + i u 11 ′′ ) and U † = ( u 00 ′ − i u 00 ′ ′ u 10 ′ − i u 10 ′ ′ u 01 ′ − i u 01 ′ ′ u 11 ′ − i u 11 ′ ′ ) U^\dagger = \begin{pmatrix} u_{00}' - iu_{00}'' & u_{10}' - iu_{10}'' \\ u_{01}' - iu_{01}'' & u_{11}' - iu_{11}'' \end{pmatrix} U † = ( u 00 ′ − i u 00 ′′ u 01 ′ − i u 01 ′′ u 10 ′ − i u 10 ′′ u 11 ′ − i u 11 ′′ )
We need to calculate U ρ U † U\rho U^\dagger U ρ U † . This is a complex calculation, so let's break it down:
U ρ = ( ( u 00 ′ + i u 00 ′ ′ ) ( 1 + a ) + ( u 01 ′ + i u 01 ′ ′ ) ( b + i c ) ( u 00 ′ + i u 00 ′ ′ ) ( b − i c ) + ( u 01 ′ + i u 01 ′ ′ ) ( 1 − a ) ( u 10 ′ + i u 10 ′ ′ ) ( 1 + a ) + ( u 11 ′ + i u 11 ′ ′ ) ( b + i c ) ( u 10 ′ + i u 10 ′ ′ ) ( b − i c ) + ( u 11 ′ + i u 11 ′ ′ ) ( 1 − a ) ) U\rho = \begin{pmatrix} (u_{00}'+iu_{00}'')(1+a)+(u_{01}'+iu_{01}'')(b+ic) & (u_{00}'+iu_{00}'')(b-ic)+(u_{01}'+iu_{01}'')(1-a) \\ (u_{10}'+iu_{10}'')(1+a)+(u_{11}'+iu_{11}'')(b+ic) & (u_{10}'+iu_{10}'')(b-ic)+(u_{11}'+iu_{11}'')(1-a) \end{pmatrix} U ρ = ( ( u 00 ′ + i u 00 ′′ ) ( 1 + a ) + ( u 01 ′ + i u 01 ′′ ) ( b + i c ) ( u 10 ′ + i u 10 ′′ ) ( 1 + a ) + ( u 11 ′ + i u 11 ′′ ) ( b + i c ) ( u 00 ′ + i u 00 ′′ ) ( b − i c ) + ( u 01 ′ + i u 01 ′′ ) ( 1 − a ) ( u 10 ′ + i u 10 ′′ ) ( b − i c ) + ( u 11 ′ + i u 11 ′′ ) ( 1 − a ) )
Now, multiplying this by U † U^\dagger U † and focusing on the diagonal elements:
ρ ′ = U ρ U † = ( 1 + a ′ 2 b ′ − i c ′ 2 b ′ + i c ′ 2 1 − a ′ 2 ) \rho' = U\rho U^\dagger = \begin{pmatrix} \frac{1+a'}{2} & \frac{b'-ic'}{2} \\ \frac{b'+ic'}{2} & \frac{1-a'}{2} \end{pmatrix} ρ ′ = U ρ U † = ( 2 1 + a ′ 2 b ′ + i c ′ 2 b ′ − i c ′ 2 1 − a ′ )
Where:
a ′ = ( ∣ u 00 ∣ 2 − ∣ u 01 ∣ 2 ) ( 1 + a ) + ( u 00 ′ u 01 ′ + u 00 ′ ′ u 01 ′ ′ ) 2 b + ( u 00 ′ u 01 ′ ′ − u 00 ′ ′ u 01 ′ ) 2 c + ( ∣ u 10 ∣ 2 − ∣ u 11 ∣ 2 ) ( 1 − a ) \begin{aligned}
a' &= (|u_{00}|^2-|u_{01}|^2)(1+a) + (u_{00}'u_{01}'+u_{00}''u_{01}'')2b \\
&+ (u_{00}'u_{01}''-u_{00}''u_{01}')2c + (|u_{10}|^2-|u_{11}|^2)(1-a)
\end{aligned} a ′ = ( ∣ u 00 ∣ 2 − ∣ u 01 ∣ 2 ) ( 1 + a ) + ( u 00 ′ u 01 ′ + u 00 ′′ u 01 ′′ ) 2 b + ( u 00 ′ u 01 ′′ − u 00 ′′ u 01 ′ ) 2 c + ( ∣ u 10 ∣ 2 − ∣ u 11 ∣ 2 ) ( 1 − a )
b ′ = ( u 00 ′ u 10 ′ + u 00 ′ ′ u 10 ′ ′ ) ( 1 + a ) + ( u 01 ′ u 11 ′ + u 01 ′ ′ u 11 ′ ′ ) ( 1 − a ) + ( u 00 ′ u 11 ′ + u 00 ′ ′ u 11 ′ ′ + u 01 ′ u 10 ′ + u 01 ′ ′ u 10 ′ ′ ) b − ( u 00 ′ u 11 ′ ′ − u 00 ′ ′ u 11 ′ − u 01 ′ u 10 ′ ′ + u 01 ′ ′ u 10 ′ ) c \begin{aligned}
b' &= (u_{00}'u_{10}'+u_{00}''u_{10}'')(1+a) + (u_{01}'u_{11}'+u_{01}''u_{11}'')(1-a) \\
&+ (u_{00}'u_{11}'+u_{00}''u_{11}''+u_{01}'u_{10}'+u_{01}''u_{10}'')b - (u_{00}'u_{11}''-u_{00}''u_{11}'-u_{01}'u_{10}''+u_{01}''u_{10}')c
\end{aligned} b ′ = ( u 00 ′ u 10 ′ + u 00 ′′ u 10 ′′ ) ( 1 + a ) + ( u 01 ′ u 11 ′ + u 01 ′′ u 11 ′′ ) ( 1 − a ) + ( u 00 ′ u 11 ′ + u 00 ′′ u 11 ′′ + u 01 ′ u 10 ′ + u 01 ′′ u 10 ′′ ) b − ( u 00 ′ u 11 ′′ − u 00 ′′ u 11 ′ − u 01 ′ u 10 ′′ + u 01 ′′ u 10 ′ ) c
c ′ = ( u 00 ′ u 10 ′ ′ − u 00 ′ ′ u 10 ′ ) ( 1 + a ) + ( u 01 ′ u 11 ′ ′ − u 01 ′ ′ u 11 ′ ) ( 1 − a ) + ( u 00 ′ u 11 ′ ′ − u 00 ′ ′ u 11 ′ − u 01 ′ u 10 ′ ′ + u 01 ′ ′ u 10 ′ ) b + ( u 00 ′ u 11 ′ + u 00 ′ ′ u 11 ′ ′ − u 01 ′ u 10 ′ − u 01 ′ ′ u 10 ′ ′ ) c \begin{aligned}
c' &= (u_{00}'u_{10}''-u_{00}''u_{10}')(1+a) + (u_{01}'u_{11}''-u_{01}''u_{11}')(1-a) \\
&+ (u_{00}'u_{11}''-u_{00}''u_{11}'-u_{01}'u_{10}''+u_{01}''u_{10}')b + (u_{00}'u_{11}'+u_{00}''u_{11}''-u_{01}'u_{10}'-u_{01}''u_{10}'')c
\end{aligned} c ′ = ( u 00 ′ u 10 ′′ − u 00 ′′ u 10 ′ ) ( 1 + a ) + ( u 01 ′ u 11 ′′ − u 01 ′′ u 11 ′ ) ( 1 − a ) + ( u 00 ′ u 11 ′′ − u 00 ′′ u 11 ′ − u 01 ′ u 10 ′′ + u 01 ′′ u 10 ′ ) b + ( u 00 ′ u 11 ′ + u 00 ′′ u 11 ′′ − u 01 ′ u 10 ′ − u 01 ′′ u 10 ′′ ) c
Now, we need to compute a ′ 2 + b ′ 2 + c ′ 2 a'^2 + b'^2 + c'^2 a ′2 + b ′2 + c ′2 . This is a very long and complex calculation. However, we can use a property of unitary matrices: U U † = I UU^\dagger = I U U † = I . This implies that the transformation ρ → U ρ U † \rho \to U\rho U^\dagger ρ → U ρ U † preserves the trace and the purity of the density matrix.
The purity of a density matrix is defined as Tr ( ρ 2 ) = 1 + a 2 + b 2 + c 2 2 \text{Tr}(\rho^2) = \frac{1+a^2+b^2+c^2}{2} Tr ( ρ 2 ) = 2 1 + a 2 + b 2 + c 2 .
Since this quantity is preserved under unitary transformations, we have:
1 + a 2 + b 2 + c 2 2 = 1 + a ′ 2 + b ′ 2 + c ′ 2 2 \frac{1+a^2+b^2+c^2}{2} = \frac{1+a'^2+b'^2+c'^2}{2} 2 1 + a 2 + b 2 + c 2 = 2 1 + a ′2 + b ′2 + c ′2
Therefore:
a ′ 2 + b ′ 2 + c ′ 2 = a 2 + b 2 + c 2 a'^2 + b'^2 + c'^2 = a^2 + b^2 + c^2 a ′2 + b ′2 + c ′2 = a 2 + b 2 + c 2
This result shows that the sum of squares of the parameters in the density matrix is invariant under unitary transformations.
4. Compute a ′ 2 + b ′ 2 + c ′ 2 a'^2 + b'^2 + c'^2 a ′2 + b ′2 + c ′2 after applying U gate (by an anonymous contributor)
Note that
det P = 1 − a 2 − b 2 − c 2 4 \det P = \frac{1 - a^2 - b^2 - c^2}{4} det P = 4 1 − a 2 − b 2 − c 2
det P ′ = det ( U P U ∗ ) = det ( P U ∗ U ) = det P = 1 − a 2 − b 2 − c 2 4 \det P' = \det(UPU^*) = \det(PU^*U) = \det P = \frac{1 - a^2 - b^2 - c^2}{4} det P ′ = det ( U P U ∗ ) = det ( P U ∗ U ) = det P = 4 1 − a 2 − b 2 − c 2
and
det P ′ = 1 − a ′ 2 − b ′ 2 − c ′ 2 4 \det P' = \frac{1 - a'^2 - b'^2 - c'^2}{4} det P ′ = 4 1 − a ′2 − b ′2 − c ′2
Therefore,
a ′ 2 + b ′ 2 + c ′ 2 = a 2 + b 2 + c 2 a'^2 + b'^2 + c'^2 = a^2 + b^2 + c^2 a ′2 + b ′2 + c ′2 = a 2 + b 2 + c 2
Knowledge
难点思路
第 4 小问的计算过程非常复杂,直接计算会非常繁琐。关键是要认识到酉变换的性质,即它保持密度矩阵的纯度不变。这样可以大大简化计算。
解题技巧和信息
在处理密度矩阵时,要注意其特殊性质:Hermitian(自伴)、半正定、迹为 1。
量子门操作可以表示为 U ρ U † U\rho U^\dagger U ρ U † ,其中 U U U 是酉矩阵。
酉变换保持密度矩阵的迹和纯度不变,意味着新态的 a ′ 2 + b ′ 2 + c ′ 2 a'^2 + b'^2 + c'^2 a ′2 + b ′2 + c ′2 保持不变。这是解决复杂问题的关键。
在计算复杂的矩阵乘法时,可以先关注最终需要的元素,而不必计算整个矩阵。
Hadamard 门 H H H 将计算基的状态均匀地混合到对角线基。测量概率可以通过变换后的密度矩阵来计算。
Pauli-Y 门 Y Y Y 交换计算基的状态并引入相位因子。
重点词汇
density matrix 密度矩阵
eigenvalue 特征值
quantum gate 量子门
Hadamard gate H 门
unitary transformation 酉变换
purity 纯度
trace 迹
参考资料
Nielsen, M. A., & Chuang, I. L. (2010). Quantum Computation and Quantum Information: 10th Anniversary Edition. Cambridge University Press. Chapter 2 and 4.
Wilde, M. M. (2017). Quantum Information Theory. Cambridge University Press. Chapter 3.