一、前言
在对高阶行列式进行计算的时候,其中一种计算方式就是“升阶”,也就是将原来的 $n$ 阶行列式升为 $n+1$ 阶行列式。
那么,什么样的行列式可以尝试升阶操作?怎么进行升阶操作?升阶之后该怎么进行接下来的计算呢?
在本文中,「荒原之梦考研数学」将就以上问题为同学们详细讲解。
二、正文
什么是升阶法?
对于下面的 $n \times n$ 阶的行列式(行列式一定是“方”的,行数和列数不相等的行列式没有数学意义):
$$
\begin{vmatrix} K \end{vmatrix} = \begin{vmatrix}
a_{11} & a_{12} & \cdots & a_{1n} \\
a_{12} & a_{22} & \cdots & a_{2n} \\ \vdots & \vdots & \ddots & \vdots \\
a_{n1} & a_{n2} & \cdots & a_{nn}
\end{vmatrix}
$$
我们可以通过给其添加的如下橙色部分所示的行和列的方式,对行列式的阶数进行扩展,因为按照第一列对下面的行列式进行展开,所得的值和原来的行列式 $\begin{vmatrix} K \end{vmatrix}$ 一样:
$$
\begin{vmatrix} K_{1} \end{vmatrix} = \begin{vmatrix}
\textcolor{orange}{1} & \textcolor{orange}{b_{1}} & \textcolor{orange}{b_{2}} & \textcolor{orange}{\cdots} & \textcolor{orange}{b_{n}} \\
\textcolor{orange}{0} & a_{11} & a_{12} & \cdots & a_{1n} \\
\textcolor{orange}{0} & a_{21} & a_{22} & \cdots & a_{2n} \\
\textcolor{orange}{\vdots} & \vdots & \vdots & \ddots & \vdots \\
\textcolor{orange}{0} & a_{n1} & a_{n2} & \cdots & a_{n n}
\end{vmatrix}
$$
当然,按照类似的思路,也可以将行列式 $\begin{vmatrix} K \end{vmatrix}$ 扩展成如下的等价形式:
$$
\begin{vmatrix} K_{2} \end{vmatrix} = \begin{vmatrix}
\textcolor{orange}{1} & \textcolor{orange}{0} & \textcolor{orange}{0} & \textcolor{orange}{\cdots} & \textcolor{orange}{0} \\
\textcolor{orange}{b_{1}} & a_{11} & a_{12} & \cdots & a_{1n} \\
\textcolor{orange}{b_{2}} & a_{21} & a_{22} & \cdots & a_{2n} \\
\textcolor{orange}{\vdots} & \vdots & \vdots & \ddots & \vdots \\
\textcolor{orange}{b_{n}} & a_{n1} & a_{n2} & \cdots & a_{n n}
\end{vmatrix}
$$
即:
$$
\begin{vmatrix} K \end{vmatrix} = \begin{vmatrix} K_{1} \end{vmatrix} = \begin{vmatrix} K_{2} \end{vmatrix}
$$
怎么计算升阶之后的矩阵?
一般情况下:
[1]. 如果将行列式 $\begin{vmatrix} K \end{vmatrix}$ 升阶为 $\begin{vmatrix} K_{1} \end{vmatrix}$, 则要寻求将 $\begin{vmatrix} K_{1} \end{vmatrix}$ 转化为上三角行列式;
[2]. 如果将行列式 $\begin{vmatrix} K \end{vmatrix}$ 升阶为 $\begin{vmatrix} K_{2} \end{vmatrix}$, 则要寻求将 $\begin{vmatrix} K_{2} \end{vmatrix}$ 转化为下三角行列式。
什么样的矩阵适合用升阶法?
一般情况下,满足下面特征的行列式都可以尝试升阶操作:
[1]. 原行列式的阶数大于三阶(小于或者等于三阶的行列式直接展开,计算速度更快);
[2]. 原行列式中除了主对角线元素之外,每一行或者每一列中都有很多相同或者相似的元素——事实上,在升阶时,$b_{1}$, $b_{2}$, $\cdots$, $b_{n}$ 的取值往往就是所在位置对应的原行列式的行或者列中出现次数最多的元素取值。
更多升阶形式
当然,我们也可以将行列式 $\begin{vmatrix} K \end{vmatrix}$ 扩展为如下所示的行列式 $\begin{vmatrix} K_{3} \end{vmatrix}$ 和行列式 $\begin{vmatrix} K_{4} \end{vmatrix}$, 即:
$$
\begin{vmatrix} K_{3} \end{vmatrix} = \begin{vmatrix}
\textcolor{orange}{b_{1}} & \textcolor{orange}{b_{2}} & \textcolor{orange}{\cdots} & \textcolor{orange}{b_{n}} & \textcolor{orange}{1} \\
a_{11} & a_{12} & \cdots & a_{1n} & \textcolor{orange}{0} \\
a_{21} & a_{22} & \cdots & a_{2n} & \textcolor{orange}{0} \\
\vdots & \vdots & \vdots & \ddots & \vdots \\
a_{n1} & a_{n2} & \cdots & a_{n n} & \textcolor{orange}{0}
\end{vmatrix}
$$
$$
\begin{vmatrix} K_{4} \end{vmatrix} = \begin{vmatrix}
\textcolor{orange}{0} & \textcolor{orange}{0} & \textcolor{orange}{0} & \textcolor{orange}{\cdots} & \textcolor{orange}{1} \\
a_{11} & a_{12} & \cdots & a_{1n} & \textcolor{orange}{b_{1}} \\
a_{21} & a_{22} & \cdots & a_{2n} & \textcolor{orange}{b_{2}} \\
\vdots & \vdots & \ddots & \vdots & \textcolor{orange}{\vdots} \\
a_{n1} & a_{n2} & \cdots & a_{n n} & \textcolor{orange}{b_{n}}
\end{vmatrix}
$$
一般情况下:
[1]. 如果将行列式 $\begin{vmatrix} K \end{vmatrix}$ 升阶为 $\begin{vmatrix} K_{3} \end{vmatrix}$, 则要寻求将 $\begin{vmatrix} K_{3} \end{vmatrix}$ 转化为反上三角行列式;
[2]. 如果将行列式 $\begin{vmatrix} K \end{vmatrix}$ 升阶为 $\begin{vmatrix} K_{4} \end{vmatrix}$, 则要寻求将 $\begin{vmatrix} K_{4} \end{vmatrix}$ 转化为反下三角行列式。
例题一
题目
$$
\begin{aligned}
\begin{vmatrix} D \end{vmatrix} \\ \\
= & \begin{vmatrix}
1+a & 1 & 1 & 1 \\
1 & 1-a & 1 & 1 \\
1 & 1 & 1+b & 1 \\
1 & 1 & 1 & 1-b
\end{vmatrix} = ?
\end{aligned}
$$
难度评级:
解析
在本题中,我们采用升阶的方式完成对行列式 $\begin{vmatrix} D \end{vmatrix}$ 的求解:在原行列式的最左侧扩展一列 $(\textcolor{black}{\colorbox{orange}{1}}, \textcolor{black}{\colorbox{orange}{0}}, \textcolor{black}{\colorbox{orange}{0}}, \textcolor{black}{\colorbox{orange}{0}})^{\top}$, 同时,由于原行列式的第 $1$ 列有三个取值为 $1$ 的元素,第 $2$ 列有三个取值为 $1$ 的元素,第 $3$ 列有三个取值为 $1$ 的元素,所以,我们在原行列式的最顶部扩展一行 $(\textcolor{black}{\colorbox{orange}{1}}, \textcolor{black}{\colorbox{orange}{1}}, \textcolor{black}{\colorbox{orange}{1}}, \textcolor{black}{\colorbox{orange}{1}})$, 即:
$$
\begin{aligned}
\begin{vmatrix} D \end{vmatrix} \\ \\
= & \begin{vmatrix}
\textcolor{black}{\colorbox{orange}{1}} & \textcolor{black}{\colorbox{orange}{1}} & \textcolor{black}{\colorbox{orange}{1}} & \textcolor{black}{\colorbox{orange}{1}} & \textcolor{black}{\colorbox{orange}{1}} \\
\textcolor{black}{\colorbox{orange}{0}} & 1+a & 1 & 1 & 1 \\
\textcolor{black}{\colorbox{orange}{0}} & 1 & 1-a & 1 & 1 \\
\textcolor{black}{\colorbox{orange}{0}} & 1 & 1 & 1+b & 1 \\
\textcolor{black}{\colorbox{orange}{0}} & 1 & 1 & 1 & 1-b
\end{vmatrix} \\ \\
& \Rightarrow \textcolor{gray}{\text{ 第 2,3,4,5 行依次减第 1 行 }} \\ \\
= & \textcolor{yellow}{ \begin{vmatrix}
1 & 1 & 1 & 1 & 1 \\
-1 & a & 0 & 0 & 0 \\
– 1 & 0 & -a & 0 & 0 \\
– 1 & 0 & 0 & b & 0 \\
– 1 & 0 & 0 & 0 & -b
\end{vmatrix} }
\end{aligned}
$$
Note
在接下来的运算中,我们让令上面这个行列式的第 $1$ 列,由 $\begin{pmatrix}
zhaokaifeng.com
1 \\
\textcolor{springgreen}{-1} \\
\textcolor{springgreen}{-1} \\
\textcolor{springgreen}{-1} \\
\textcolor{springgreen}{-1}
\end{pmatrix}$ 变成 $\begin{pmatrix}
1 \\
\textcolor{orangered}{0} \\
\textcolor{orangered}{0} \\
\textcolor{orangered}{0} \\
\textcolor{orangered}{0}
\end{pmatrix}$——这一运算过程中,会用到《矩阵/行列式消 $0$ 的一个优化策略》这篇文章中首次提出的方法。
当 $ab \neq 0$ 时(即 $a \neq 0$ 且 $b \neq 0$),有:
$$
\begin{aligned}
\begin{vmatrix} D \end{vmatrix} \\ \\
= & \textcolor{yellow}{ \begin{vmatrix}
1 & 1 & 1 & 1 & 1 \\
\textcolor{springgreen}{-1} & a & 0 & 0 & 0 \\
\textcolor{springgreen}{-1} & 0 & -a & 0 & 0 \\
\textcolor{springgreen}{-1} & 0 & 0 & b & 0 \\
\textcolor{springgreen}{-1} & 0 & 0 & 0 & -b
\end{vmatrix} } \\ \\
\Rightarrow & \textcolor{gray}{第 \ 1 \ 列加上第 \ 2 \ 列的 \ \textcolor{tan}{\frac{1}{a}} \ 倍} \\ \\
= & \begin{vmatrix}
1+\textcolor{tan}{\frac{1}{a}} & 1 & 1 & 1 & 1 \\
\textcolor{orangered}{0} & a & 0 & 0 & 0 \\
\textcolor{springgreen}{-1} & 0 & -a & 0 & 0 \\
\textcolor{springgreen}{-1} & 0 & 0 & b & 0 \\
\textcolor{springgreen}{-1} & 0 & 0 & 0 & -b
\end{vmatrix} \\ \\
\Rightarrow & \textcolor{gray}{第 \ 1 \ 列减去第 \ 3 \ 列的 \ \textcolor{tan}{\frac{1}{a}} \ 倍} \\ \\
= & \begin{vmatrix}
1+\textcolor{tan}{\frac{1}{a}} – \textcolor{tan}{\frac{1}{a}} & 1 & 1 & 1 & 1 \\
\textcolor{orangered}{0} & a & 0 & 0 & 0 \\
\textcolor{orangered}{0} & 0 & -a & 0 & 0 \\
\textcolor{springgreen}{-1} & 0 & 0 & b & 0 \\
\textcolor{springgreen}{-1} & 0 & 0 & 0 & -b
\end{vmatrix} \\ \\
\Rightarrow & \textcolor{gray}{第 \ 1 \ 列加上第 \ 4 \ 列的 \ \textcolor{tan}{\frac{1}{b}} \ 倍} \\ \\
= & \begin{vmatrix}
1+\textcolor{tan}{\frac{1}{a}} – \textcolor{tan}{\frac{1}{a}} + \textcolor{tan}{\frac{1}{b}} & 1 & 1 & 1 & 1 \\
\textcolor{orangered}{0} & a & 0 & 0 & 0 \\
\textcolor{orangered}{0} & 0 & -a & 0 & 0 \\
\textcolor{orangered}{0} & 0 & 0 & b & 0 \\
\textcolor{springgreen}{-1} & 0 & 0 & 0 & -b
\end{vmatrix} \\ \\
\Rightarrow & \textcolor{gray}{第 \ 1 \ 列减去第 \ 5 \ 列的 \ \textcolor{tan}{\frac{1}{b}} \ 倍} \\ \\
= & \begin{vmatrix}
1 + \textcolor{tan}{\frac{1}{a}} – \textcolor{tan}{\frac{1}{a}} + \textcolor{tan}{\frac{1}{b}} – \textcolor{tan}{\frac{1}{b}} & 1 & 1 & 1 & 1 \\
\textcolor{orangered}{0} & a & 0 & 0 & 0 \\
\textcolor{orangered}{0} & 0 & -a & 0 & 0 \\
\textcolor{orangered}{0} & 0 & 0 & b & 0 \\
\textcolor{orangered}{0} & 0 & 0 & 0 & -b
\end{vmatrix} \\ \\
= & \begin{vmatrix}
1 & 1 & 1 & 1 & 1 \\
\textcolor{orangered}{0} & a & 0 & 0 & 0 \\
\textcolor{orangered}{0} & 0 & -a & 0 & 0 \\
\textcolor{orangered}{0} & 0 & 0 & b & 0 \\
\textcolor{orangered}{0} & 0 & 0 & 0 & -b
\end{vmatrix} \\ \\
= & \begin{vmatrix}
\cancel{1} & \cancel{1} & \cancel{1} & \cancel{1} & \cancel{1} \\
\textcolor{orangered}{\cancel{0}} & a & 0 & 0 & 0 \\
\textcolor{orangered}{\cancel{0}} & 0 & -a & 0 & 0 \\
\textcolor{orangered}{\cancel{0}} & 0 & 0 & b & 0 \\
\textcolor{orangered}{\cancel{0}} & 0 & 0 & 0 & -b
\end{vmatrix} \\ \\
= & \begin{vmatrix}
\textcolor{black}{\colorbox{orange}{a}} & 0 & 0 & 0 \\
0 & \textcolor{black}{\colorbox{orange}{-a}} & 0 & 0 \\
0 & 0 & \textcolor{white}{\colorbox{green}{b}} & 0 \\
0 & 0 & 0 & \textcolor{white}{\colorbox{green}{-b}}
\end{vmatrix} \\ \\
= & \ \textcolor{springgreen}{\boldsymbol{ a^{2} b^{2} }}
\end{aligned}
$$
当 $ab = 0$ 时,说明 $a = 0$ 或者 $b = 0$, 且 $a^{2} b^{2} = 0$.
这里假设仅有 $a = 0$(其他情况结果相同), 则:
$$
\begin{aligned}
\begin{vmatrix} D \end{vmatrix} \\ \\
= & \textcolor{yellow}{ \begin{vmatrix}
1 & 1 & 1 & 1 & 1 \\
-1 & a & 0 & 0 & 0 \\
-1 & 0 & -a & 0 & 0 \\
-1 & 0 & 0 & b & 0 \\
-1 & 0 & 0 & 0 & -b
\end{vmatrix} } \\ \\
= & \begin{vmatrix}
1 & 1 & 1 & 1 & 1 \\
\textcolor{orange}{-1} & \textcolor{orange}{0} & \textcolor{orange}{0} & \textcolor{orange}{0} & \textcolor{orange}{0} \\
\textcolor{orange}{-1} & \textcolor{orange}{0} & \textcolor{orange}{0} & \textcolor{orange}{0} & \textcolor{orange}{0} \\
-1 & 0 & 0 & b & 0 \\
-1 & 0 & 0 & 0 & -b
\end{vmatrix} \\ \\
= & \begin{vmatrix}
1 & 1 & 1 & 1 & 1 \\
\textcolor{red}{0} & \textcolor{red}{0} & \textcolor{red}{0} & \textcolor{red}{0} & \textcolor{red}{0} \\
0 & 0 & 0 & 0 & 0 \\
-1 & 0 & 0 & b & 0 \\
-1 & 0 & 0 & 0 & -b
\end{vmatrix} \\ \\
= & \ \textcolor{springgreen}{\boldsymbol{0}} = \textcolor{springgreen}{\boldsymbol{a^{2} b^{2}}}
\end{aligned}
$$
综上可知:
$$
\textcolor{springgreen}{
\boldsymbol{
\begin{vmatrix} D \end{vmatrix} = a^{2} b^{2}
}
}
$$
例题二
题目
$$
\begin{aligned}
\begin{vmatrix} D \end{vmatrix} \\ \\
= & \begin{vmatrix}
a+b+2c & b & a \\
c & a+c+2b & a \\
c & b & b+c+2a
\end{vmatrix} = \ ?
\end{aligned}
$$
难度评级:
解析
在本题中,我们采用升阶的方式完成对行列式 $\begin{vmatrix} D \end{vmatrix}$ 的求解:在原行列式的最左侧扩展一列 $(\textcolor{black}{\colorbox{orange}{1}}, \textcolor{black}{\colorbox{orange}{0}}, \textcolor{black}{\colorbox{orange}{0}}, \textcolor{black}{\colorbox{orange}{0}})^{\top}$, 同时,由于原行列式的第 $1$ 列有两个取值为 $c$ 的元素,第 $2$ 列有两个取值为 $b$ 的元素,第 $3$ 列有两个取值为 $a$ 的元素,所以,我们在原行列式的最顶部扩展一行 $(\textcolor{black}{\colorbox{orange}{1}}, \textcolor{black}{\colorbox{orange}{c}}, \textcolor{black}{\colorbox{orange}{b}}, \textcolor{black}{\colorbox{orange}{a}})$, 即:
$$
\begin{aligned}
\begin{vmatrix} D \end{vmatrix} \\ \\
= & \begin{vmatrix}
a+b+2c & b & a \\
c & a+c+2b & a \\
c & b & b+c+2a
\end{vmatrix} \\ \\
= & \begin{vmatrix}
\textcolor{black}{\colorbox{orange}{1}} & \textcolor{black}{\colorbox{orange}{c}} & \textcolor{black}{\colorbox{orange}{b}} & \textcolor{black}{\colorbox{orange}{a}} \\
\textcolor{black}{\colorbox{orange}{0}} & a+b+2c & b & a \\
\textcolor{black}{\colorbox{orange}{0}} & c & a+c+2b & a \\
\textcolor{black}{\colorbox{orange}{0}} & c & b & b+c+2a
\end{vmatrix} \\ \\
\Rightarrow & \textcolor{gray}{\text{ 第 2,3,4 行依次减第 1 行 }} \\ \\
= & \textcolor{yellow}{ \begin{vmatrix}
1 & c & b & a \\
-1 & a+b+c & 0 & 0 \\
-1 & 0 & a+b+c & 0 \\
-1 & 0 & 0 & a+b+c
\end{vmatrix} }
\end{aligned}
$$
于是,当 $a+b+c$ $\neq$ $0$ 时,有:
$$
\begin{aligned}
\begin{vmatrix} D \end{vmatrix} \\ \\
= & \textcolor{yellow}{ \begin{vmatrix}
1 & c & b & a \\
\textcolor{springgreen}{-1} & a+b+c & 0 & 0 \\
\textcolor{springgreen}{-1} & 0 & a+b+c & 0 \\
\textcolor{springgreen}{-1} & 0 & 0 & a+b+c
\end{vmatrix} } \\ \\
\Rightarrow & \textcolor{gray}{第 \ 1 \ 列加上第 \ 2 \ 列的 \ \textcolor{tan}{\frac{1}{a+b+c}} \ 倍} \\ \\
= & \begin{vmatrix}
1 + \frac{\textcolor{pink}{c}}{\textcolor{tan}{a+b+c}} & \textcolor{pink}{c} & b & a \\
\textcolor{red}{0} & a+b+c & 0 & 0 \\
\textcolor{springgreen}{-1} & 0 & a+b+c & 0 \\
\textcolor{springgreen}{-1} & 0 & 0 & a+b+c
\end{vmatrix} \\ \\
\Rightarrow & \textcolor{gray}{第 \ 1 \ 列加上第 \ 3 \ 列的 \ \textcolor{tan}{\frac{1}{a+b+c}} \ 倍} \\ \\
= & \begin{vmatrix}
1 + \frac{\textcolor{pink}{c}}{\textcolor{tan}{a+b+c}} + \frac{\textcolor{pink}{b}}{\textcolor{tan}{a+b+c}} & c & \textcolor{pink}{b} & a \\
\textcolor{red}{0} & a+b+c & 0 & 0 \\
\textcolor{red}{0} & 0 & a+b+c & 0 \\
\textcolor{springgreen}{-1} & 0 & 0 & a+b+c
\end{vmatrix} \\ \\
\Rightarrow & \textcolor{gray}{第 \ 1 \ 列加上第 \ 4 \ 列的 \ \textcolor{tan}{\frac{1}{a+b+c}} \ 倍} \\ \\
= & \begin{vmatrix}
1 + \frac{\textcolor{pink}{c}}{\textcolor{tan}{a+b+c}} + \frac{\textcolor{pink}{b}}{\textcolor{tan}{a+b+c}} + \frac{\textcolor{pink}{a}}{\textcolor{tan}{a+b+c}} & c & b & \textcolor{pink}{a} \\
\textcolor{red}{0} & a+b+c & 0 & 0 \\
\textcolor{red}{0} & 0 & a+b+c & 0 \\
\textcolor{red}{0} & 0 & 0 & a+b+c
\end{vmatrix} \\ \\
= & \begin{vmatrix}
1 + \frac{\textcolor{pink}{c} + \textcolor{pink}{b} + \textcolor{pink}{a}}{\textcolor{tan}{a+b+c}} & c & b & a \\
\textcolor{red}{0} & a+b+c & 0 & 0 \\
\textcolor{red}{0} & 0 & a+b+c & 0 \\
\textcolor{red}{0} & 0 & 0 & a+b+c
\end{vmatrix} \\ \\
= & \begin{vmatrix}
1 + \frac{\textcolor{pink}{a} + \textcolor{pink}{b} + \textcolor{pink}{c}}{\textcolor{tan}{a+b+c}} & c & b & a \\
\textcolor{red}{0} & a+b+c & 0 & 0 \\
\textcolor{red}{0} & 0 & a+b+c & 0 \\
\textcolor{red}{0} & 0 & 0 & a+b+c
\end{vmatrix} \\ \\
= & \begin{vmatrix}
2 & c & b & a \\
\textcolor{red}{0} & a+b+c & 0 & 0 \\
\textcolor{red}{0} & 0 & a+b+c & 0 \\
\textcolor{red}{0} & 0 & 0 & a+b+c
\end{vmatrix} \\ \\
= & 2 \begin{vmatrix}
a+b+c & 0 & 0 \\
0 & a+b+c & 0 \\
0 & 0 & a+b+c
\end{vmatrix} \\ \\
= & \ \textcolor{springgreen}{\boldsymbol{ 2 (a+b+c)^{3} }}
\end{aligned}
$$
当 $a + b + c$ $=$ $0$ 时:
$$
\begin{aligned}
\begin{vmatrix} D \end{vmatrix} \\ \\
= & \textcolor{yellow}{ \begin{vmatrix}
1 & c & b & a \\
-1 & a+b+c & 0 & 0 \\
– 1 & 0 & a+b+c & 0 \\
– 1 & 0 & 0 & a+b+c
\end{vmatrix} } \\ \\
= & \begin{vmatrix}
1 & c & b & a \\
\textcolor{orange}{-1} & \textcolor{orange}{0} & \textcolor{orange}{0} & \textcolor{orange}{0} \\
\textcolor{orange}{-1} & \textcolor{orange}{0} & \textcolor{orange}{0} & \textcolor{orange}{0} \\
\textcolor{orange}{-1} & \textcolor{orange}{0} & \textcolor{orange}{0} & \textcolor{orange}{0}
\end{vmatrix} \\ \\
= & \begin{vmatrix}
1 & c & b & a \\
-1 & 0 & 0 & 0 \\
\textcolor{red}{0} & \textcolor{red}{0} & \textcolor{red}{0} & \textcolor{red}{0} \\
\textcolor{red}{0} & \textcolor{red}{0} & \textcolor{red}{0} & \textcolor{red}{0}
\end{vmatrix} \\ \\
= & \ \textcolor{springgreen}{\boldsymbol{0}} = \textcolor{springgreen}{\boldsymbol{2 (a+b+c)^{3}}}
\end{aligned}
$$
综上可知:
$$
\textcolor{springgreen}{
\boldsymbol{
\begin{vmatrix} D \end{vmatrix} = 2 (a+b+c)^{3}
}
}
$$
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