2022-12-16

Mathematical expression in LaTeX

What is LaTeX

LaTeX is a markup language that can beautifully output documents containing complex structures such as mathematical expressions, and is often used in scientific fields such as mathematics and physics. Mathematical expressions can be represented in LaTeX text by inserting a string between the symbols $ and $.

Mathematical expressions in LaTeX

Mathematical expression LaTeX
\equiv $\equiv$
\approx $\approx$
\fallingdotseq $\fallingdotseq$
\risingdotseq $\risingdotseq$
\sim $\simeq
\geq $\geq
\geqq $\geqq
\leq $\leq
\leqq $\leqq
\gg $\gg
\ll $\ll
\N $\N
\Z $\Z
\R $\R
\exist $\exist
\forall $\forall
\times $\times
\ast $\ast
\div $\div
\pm $\pm
\mp $\mp
\oplus $\oplus
\ominus $\ominus
\otimes $\otimes
\oslash $\oslash
\circ $\circ
\ltimes $\ltimes
\rtimes $\rtimes
\in $\in
\ni $\ni
\notin $\notin
\subset $\subset
\supset $\supset
\subseteq $\subseteq
\supseteq $\supseteq
\nsubseteq $\nsubseteq
\nsupseteq $\nsupseteq
\cap $\cap
\cup $\cup
\emptyset $\emptyset
\varnothing $\varnothing
\parallel $\parallel
x^2 $x^2$
x^{10} $x^{10}$
x^{y+1} $x^{y+1}$
x_i $x_i$
x_i^2 $x_i^2$
_n C _r $_n C _r$
\mathrm{e}^x $\mathrm{e}^x$
\pi $\pi$
\alpha $\alpha$
\beta $\beta$
\gamma $\gamma$
\mu $\mu$
\nu $\nu$
\theta $\theta$
\eta $\eta$
\delta $\delta$
\zeta $\zeta$
\ell $\ell$
\epsilon $\epsilon$
\sigma $\sigma$
\lambda $\lambda$
\tau $\tau$
\omega $\omega$
\phi $\phi$
\chi $\chi$
\nabla $\nabla$
\psi $\psi$
\kappa $\kappa$
\xi $\xi$
\varepsilon $\varepsilon$
\vartheta $\vartheta$
\varpi $\varpi$
\varsigma $\varsigma$
\varphi $\varphi$
\Gamma $\Gamma$
\Delta $\Delta$
\Omega $\Omega$
\to $\to$
\rightarrow $\rightarrow$
\Rightarrow $\Rightarrow$
\leftarrow $\leftarrow$
\Leftarrow $\Leftarrow$
\leftrightarrow $\leftrightarrow$
\Leftrightarrow $\Leftrightarrow$
\models $\models$
\cdots $\cdots$
\sin(x) $\sin(x)$
\cos(x) $\cos(x)$
\tan(x) $\tan(x)$
\neq $\neq$
x_1, x_2, \cdots, x_n $x_1, x_2, \cdots, x_n$
\dot{x} $\dot{x}$
\ddot{x} $\ddot{x}$
\vec{x} $\vec{x}$
\hat{x} $\hat{x}$
\bar{x} $\bar{x}$
\tilde{x} $\tilde{x}$
\overrightarrow{x} $\overrightarrow{x}$
\overleftarrow{x} $\overleftarrow{x}$
\infty $\infty$
\int $\int$
\lim $\lim$
\lim_{n\to \infty} a_n $\lim_{n\to \infty} a_n$
\mathrm{d} x $\mathrm{d} x$
F(x)=\int f(x) \mathrm{d} x $F(x) = \int f(x) \mathrm{d} x$
\sqrt{x} $\sqrt{x}$
\sqrt[n]{a} $\sqrt[n]{a}$
\int_{-\infty}^{\infty} \mathrm{e}^{-x^2} \mathrm{d} x $\int_{-\infty}^{\infty} \mathrm{e}^{-x^2} \mathrm{d} x$
\sum $\sum$
\sum_i^N x_i $\sum_i^N x_i$
\prod $\prod$
\prod_i x_i $\prod_i x_i$
\frac{1}{2} $\frac{1}{2}$
\sum_{k=0}^\infty \frac{h^k f^{k}(x)}{k!} $\sum_{k=0}^\infty \frac{h^k f^{k}(x)}{k!}$
a \mathrm{a} $a \mathrm{a}$
\left( \right) $\left \right)$
\left( \frac{x}{y} \right) $\left( \frac{x}{y} \right)$
\left[ \frac{x}{y} \right] $\left[ \frac{x}{y} \right]$
\left( \frac{x}{y} \right. $\left( \frac{x}{y} \right.$
\partial $\partial$
\frac{\partial f}{\partial x} $\frac{\partial f}{\partial x}$
\\ $\\$
\quad $\quad$
\underset{k}{\textrm{argmax}} $\underset{k}{\textrm{argmax}}$
\textrm{precision} × \textrm{recall} $\textrm{precision} × \textrm{recall}$

Differential

\left. \frac{dy}{dx} \right|_{x=1}
$$
\left. \frac{dy}{dx} \right|_{x=1}
$$

Multiline Equation

\begin{aligned} (x+y)^2 &= (x+y) (x+y) \\ &= x(x+y) + y (x+y) \\ &= x^2 + xy + yx + y^2 \\ &= x^2 + 2xy+y^2 \end{aligned}
$$
\begin{aligned}
  (x+y)^2 &= (x+y) (x+y) \\
  &= x(x+y) + y (x+y) \\
  &= x^2 + xy + yx + y^2 \\
  &= x^2 + 2xy+y^2
\end{aligned}
$$

Matrix

\begin{pmatrix} a & b\\ c & d \end{pmatrix}
$$
\begin{pmatrix}
  a & b\\
  c & d
\end{pmatrix}
$$
\begin{bmatrix} a & b\\ c & d \end{bmatrix}
\begin{bmatrix}
a & b\\
c & d
\end{bmatrix}
\begin{Vmatrix} a & b \\ c & d \end{Vmatrix}
$$
\begin{Vmatrix}
  a & b \\
  c & d
\end{Vmatrix}
$$
\left( \begin{array}{c} (x^{1})^T\\ \vdots\\ (x^{N})^T\\ \end{array} \right)
$$
\left(
  \begin{array}{c}
    (x^{1})^T\\
    \vdots\\
    (x^{N})^T\\
  \end{array}
\right)
$$
A = \left( \begin{array}{ccccc} 1 & 1 & 4 & 5 & 1 \\ 1 & 0 & 5 & 0 & 4 \\ 4 & 5 & 1 & 4 & 0 \end{array} \right)
$$
A = \left(
  \begin{array}{ccccc}
    1 & 1 & 4 & 5 & 1 \\
    1 & 0 & 5 & 0 & 4 \\
    4 & 5 & 1 & 4 & 0
  \end{array}
\right)
$$
\begin{pmatrix} a_{11} & \cdots & a_{1i} & \cdots & a_{1n}\\ \vdots & \ddots & & & \vdots \\ a_{i1} & & a_{ii} & & a_{in} \\ \vdots & & & \ddots & \vdots \\ a_{n1} & \cdots & a_{ni} & \cdots & a_{nn} \end{pmatrix} \times \begin{vmatrix} a_{11} & \cdots & a_{1i} & \cdots & a_{1n}\\ \vdots & \ddots & & & \vdots \\ a_{i1} & & a_{ii} & & a_{in} \\ \vdots & & & \ddots & \vdots \\ a_{n1} & \cdots & a_{ni} & \cdots & a_{nn} \end{vmatrix}
$$
\begin{pmatrix}
  a_{11} & \cdots & a_{1i} & \cdots & a_{1n}\\
  \vdots & \ddots &        &        & \vdots \\
  a_{i1} &        & a_{ii} &        & a_{in} \\
  \vdots &        &        & \ddots & \vdots \\
  a_{n1} & \cdots & a_{ni} & \cdots & a_{nn}
\end{pmatrix}

\times

\begin{vmatrix}
  a_{11} & \cdots & a_{1i} & \cdots & a_{1n}\\
  \vdots & \ddots &        &        & \vdots \\
  a_{i1} &        & a_{ii} &        & a_{in} \\
  \vdots &        &        & \ddots & \vdots \\
  a_{n1} & \cdots & a_{ni} & \cdots & a_{nn}
\end{vmatrix}
$$

Conditional Branch

f(x) = \left\{ \begin{array}{ll} 1 & (x = 1) \\ 0 & (otherwise) \end{array} \right.
$$
f(x) = \left\{
  \begin{array}{ll}
    1 & (x = 1) \\
    0 & (otherwise)
  \end{array}
\right.
$$

Equation Number

\tag{1.0.2} x_i = \sigma (W_i + \beta)
$$
\tag{1.0.2}
x_i = \sigma (W_i + \beta)
$$

Linear Programming

\begin{equation*} \begin{aligned} & \text{minimize} & {\bf c}^T{\bf x} \\ & \text{s.t.} & A{\bf x} \le {\bf b} \\ & & {\bf x} \ge {\bf 0} \\ \end{aligned} \end{equation*}
$$
\begin{equation*}
  \begin{aligned}
    & \text{minimize}
      & {\bf c}^T{\bf x} \\
    & \text{s.t.}
      & A{\bf x} \le {\bf b} \\
      & & {\bf x} \ge {\bf 0} \\
  \end{aligned}
\end{equation*}
$$

Simplex Method

\begin{array}{rrrrrrr} x_3 & = & 1 & + & x_1 & - & x_2 \\ x_4 & = & 3 & - & x_1 & & \\ x_5 & = & 2 & & & - & x_2 \\ \hline z & = & & & x_1 & + & x_2 \end{array}
$$
\begin{array}{rrrrrrr}
  x_3 & = & 1 & + & x_1 & - & x_2 \\
  x_4 & = & 3 & - & x_1 &   &     \\
  x_5 & = & 2 &   &     & - & x_2 \\ \hline
  z   & = &   &   & x_1 & + & x_2
\end{array}
$$

Ryusei Kakujo

researchgatelinkedingithub

Weave the future of cities through data

Transportation modeling/ Urban planning/ Machine learning/ Computer science/ GIS