#153 #163 Maxwell’s equations

Author: kanition

Pictures/chap08/time-varyingE-field.eps

@@ -7029,4 +7029,29 @@ @book{OpticsChinese
   month     = {6},
   isbn      = {978-7121364679},
   address   = {北京}
-}
+}
+
+@book{hass2023,
+  author    = {Hass, Joel and Heil, Christopher and Bogacki, Przemyslaw and Weir, Maurice},
+  title     = {{Thomas' Calculus Early Transcendentals, SI Units}},
+  abstract  = {{For 3-semester or 4-quarter courses in Calculus for students majoring in mathematics, engineering, or science.Clarity and precision
+               Thomas' Calculus: Early Transcendentals goes beyond memorizing formulas and routine procedures to help students develop deeper understanding. It guides students to a level of 
+               mathematical proficiency and maturity needed for the course, with support for those who require it through its balance of clear and intuitive explanations, current applications 
+               and generalized concepts. The 15th Edition meets the needs of students with increasingly varied levels of readiness for the calculus sequence. This revision also adds exercises, 
+               revises figures and narrative for clarity, and updates many applications with modern topics.Hallmark features of this titleKey topics are presented both informally and formally.
+               Results are carefully stated and proved throughout, and proofs are clearly explained and motivated.Strong exercise sets feature a wide range from skills problems to applied and 
+               theoretical problems.Writing exercises ask students to explore and explain various concepts and applications. A list of questions at the end of each chapter asks them to review and 
+               summarize what they have learned.Technology exercises in each section ask students to use the calculator or computer when solving the problems. Computer Explorations offer exercises 
+               requiring a computer algebra system such as Maple or Mathematica.Annotations within examples guide students through the problem solution and emphasize that each step in a mathematical 
+               argument is justified.New and updated features of this title Many narrative clarifications and revisions have been made throughout the text.A new appendix on Determinants and Gradient 
+               Descent has been added, covering many topics relevant to students interested in Machine Learning and Neural Networks.Many updated graphics and figures have been enhanced to bring out 
+               clear visualization and mathematical correctness.Many exercise instructions have been clarified, such as suggesting where the use of a calculator may be needed.Notation of inverse 
+               trig functions has been changed throughout the text to favor arcsin notation over sin^{-1}, etc.
+               }},
+  pages     = {1224},
+  publisher = {Pearson Deutschland},
+  year      = {2023},
+  isbn      = {9781292725901},
+  url       = {https://elibrary.pearson.de/book/99.150005/9781292457628},
+  edition   = {15th}
+}

Pictures/chap08/time-varyingE-field.svg

@@ -354,7 +354,7 @@ \subsection{法向量的偏导数}\label{sub:法向量的偏导数}
 法线的微分变化量$\displaystyle\frac{\partial \bm n}{\partial u}$和
 $\displaystyle\frac{\partial \bm n}{\partial v}$由微分几何学
 中\keyindex{曲面的外恩加滕公式}{Weingarten formula of surfaces}{surface\ 曲面}给出
-\sidenote{译者注：得名于德国数学家Julius Weingarten(1836-1910)。
+\sidenote{译者注：得名于德国数学家Julius Weingarten (1836-1910)。
     相关简要推导详见译者整理补充的\refsec{译者补充：微分几何基础}。
     注意该公式其实隐含了对$\bm n$的规范化要求。
     下面所提的曲面的第一基本形式、第二基本形式也是微分几何学中的概念。}：

bibliography.bib

@@ -342,7 +342,7 @@ \subsection{混叠}\label{sub:混叠}
 事实上，\keyindex{采样定理}{sampling theorem}{}准确告诉我们所需的采样率。
 该定理说只要均匀样本点的频率$\omega_s$大于信号中出现的最大频率$\omega_0$的两倍，
 就能从样本中完美重建原始信号。该最小采样频率称为\keyindex{奈奎斯特频率}{Nyquist frequency}{frequency\ 频率}
-\sidenote{译者注：得名于瑞典裔美国物理学家哈里·奈奎斯特(Harry Nyquist, 1889-1976)，通讯理论的奠基者之一。}。
+\sidenote{译者注：得名于瑞典裔美国物理学家哈里·奈奎斯特(Harry Nyquist, 1889-1976)。}。
 
 对于非带限信号（$\omega_0=\infty$），不可能以足够高的采样率执行完美重建。
 非带限信号有无限支撑的频谱，所以无论其频谱副本隔得多远（即无论我们用多高的采样率），

content/chap0302.tex

@@ -164,7 +164,7 @@ \subsection{评估样本模式：偏差}\label{sub:评价样本模式：偏差}
 
 只靠偏差并不一定是好的度量：一些低偏差点集表现出样本的聚集性，
 其中两个或以上样本可能靠得很近。\refsec{Sobol采样器}的Sobol采样器
-\sidenote{译者注：得名于立陶宛裔俄罗斯数学家Ilya Meyerovich Sobol(1926-)。
+\sidenote{译者注：得名于立陶宛裔俄罗斯数学家Ilya Meyerovich Sobol (1926-)。
 原文对“Sobol”这一名称均加上了撇号，译文将其略去了，下同。}
 尤其困扰于该问题——见\reffig{7.36}，它展示了其前两维的图示。
 直觉上，靠得太近的样本不能很好地利用采样资源：

content/chap0701.tex

@@ -34,7 +34,7 @@ \subsection{Hammersley和Halton序列}\label{sub:Hammersley和Halton序列}
 因此，数字$d_i(a)$对倒根的贡献为$\displaystyle\frac{d_i(a)}{b^i}$.
 
 最简单的低偏差序列之一是van der Corput序列
-\sidenote{译者注：得名自荷兰数学家Johannes Gaultherus van der Corput(1890-1975)。}，
+\sidenote{译者注：得名自荷兰数学家Johannes Gaultherus van der Corput (1890-1975)。}，
 它是由2进制倒根函数给出的1D序列：
 \begin{align*}
     x_a=\varPhi_2(a)\, .