答案1
我已經複製了你想要的輸出的 80%。我用過XCharter-數學以及書法字體 Asana Math。
\documentclass[12pt]{article}
\usepackage{fontspec}
\usepackage{unicode-math}
\setmainfont{XCharter}
\setmathfont{XCharter-Math.otf}
\setmathfont[range={cal,bfcal},
Alternate,
Scale=MatchUppercase]
{Asana Math}
\begin{document}
\textbf{Semimeasures.} A semimeasure is a probability measure $P$ over infinite and finite sequences $\mathcal{X}^{\infty}\cup \mathcal{X}^*$ for some finite alphabet $X$ assumed to be $\{0,1\}$ (most statements hold for arbitrary finite $\mathcal{X}$). Let $\mu(x)$ be the probability that an (in)finite sequence starts with $x.$ While proper distributions satisfy $\sum_{a\in \mathcal{X}}\mu(xa)=\mu(x)$, semimeasures exhibit probability gaps and satisfy $\sum_{\alpha\in \mathcal{X}}\mu(xa)\leq\mu(x).$
\textbf{Turing Machines}. A Turing Machine (TM) takes a string of symbols $z$ as an input, and outputs a string of symbols $x$ (after reading $z$ and halting), i.e. $T(z)=x.$ For convenience we define the output string at computation step s as $T^s(z)=x$ which may be the empty string $\epsilon$ We adopt similar notation for Universal Turing Machines $U$. Monotone TMs (see Definition 1 below) are special TMs that can incrementally build the output string while incrementally reading the input program, which is a convenient practical property we exploit in our experiments.
\end{document}
答案2
Tt 的 arxiv,因此您可以下載完整的 tex 原始碼並使用完全相同的字體和样式,只需使用您在問題中放入的連結並單擊TeX 原始碼右側邊欄中的連結。