Eufisky - The lost book

美国数学月刊无穷乘积与西西新年祝福题

若$a_i$是超越方程\[\left( {\cos x} \right)\left( {\cosh x} \right) + 1 = 0\]的正实数根从小到大排成的数列, 求证:

$$\sum_{i=1}^{\infty}{a_{i}^{-6}\left(\frac{\sin a_i-\sinh a_i}{\cos a_i+\cosh a_i}\right)^2}=\frac{1}{80}.$$


首先可以肯定,这个方程里$a_i$肯定是解不出的.其次我们有\[{\left( {\sinh {a_i}} \right)^2} = {\left( {\cosh {a_i}} \right)^2} - 1 = \frac{1}{{{{\cos }^2}{a_i}}} - 1 = {\tan ^2}{a_i} \Rightarrow \sinh {a_i} = \left| {\tan {a_i}} \right|.\]
当$\sinh {a_i} = \tan {a_i}$时,我们有\[{\left( {\frac{{\sin {a_i} - \sinh {a_i}}}{{\cos {a_i} + \cosh {a_i}}}} \right)^2} = {\left( {\frac{{\sin {a_i} - \tan {a_i}}}{{\cos {a_i} - \frac{1}{{\cos {a_i}}}}}} \right)^2} = {\tan ^2}\frac{{{a_i}}}{2}.\]
当$\sinh {a_i} = -\tan {a_i}$时,我们有\[{\left( {\frac{{\sin {a_i} - \sinh {a_i}}}{{\cos {a_i} + \cosh {a_i}}}} \right)^2} = {\left( {\frac{{\sin {a_i} + \tan {a_i}}}{{\cos {a_i} - \frac{1}{{\cos {a_i}}}}}} \right)^2} = {\cot ^2}\frac{{{a_i}}}{2}.\]事实上,两种情况都会出现.接下来大家一起来思考下哈!

以下几个也是不同寻常的题,正是因为莫名其妙、不明觉厉才想一探究竟,希望大家一起来玩!


1、求无穷积分$$\int_{1/2}^{+\infty}{\int_{1/2}^{+\infty}{\int_{1/2}^{+\infty}{\frac{dxdydz}{\prod\limits_{cyc}{\left[242x^5-\left(y-1\right)^5-\left(z+1\right)^5\right]}}}}}.$$


2、设\[{\left( {1 + \frac{1}{x}} \right)^x} = e\left( {1 - \sum\limits_{k = 1}^\infty  {\frac{{{d_k}}}{{{{\left( {\frac{{11}}{{12}} + x} \right)}^k}}}} } \right),\]求
\[{\sum\limits_{k = 1}^\infty  {\frac{1}{{1 + d_k^2}}} }.\]


(2017年10月AMM征解题)求证

\[\prod\limits_{j \ge 1} {{e^{ - 1/j}}\left( {1 + \frac{1}{j} + \frac{1}{{2{j^2}}}} \right)} = \frac{{{e^{\pi /2}} + {e^{ - \pi /2}}}}{{\pi {e^\gamma }}}.\]

\[{x_n} = \prod\limits_{k = 1}^n {\left( {1 + \frac{1}{k} + \frac{1}{{2{k^2}}}} \right)} = \prod\limits_{k = 1}^n {\frac{{{{\left( {2k + 1} \right)}^2} + 1}}{{{{\left( {2k} \right)}^2}}}} ,\]
\begin{align*}\frac{{\prod\limits_{k = 1}^{2n} {\left( {1 + \frac{1}{{{k^2}}}} \right)} }}{{{x_n}}} &= \frac{{\prod\limits_{k = 1}^{2n} {\frac{{{k^2} + 1}}{{{k^2}}}} }}{{\prod\limits_{k = 1}^n {\frac{{{{\left( {2k + 1} \right)}^2} + 1}}{{{{\left( {2k} \right)}^2}}}} }} = \frac{{\left( {{1^2} + 1} \right)\left( {{2^2} + 1} \right)\left( {{4^2} + 1} \right) \cdots \left[ {{{\left( {2n} \right)}^2} + 1} \right]}}{{{1^2}{3^2} \cdots {{\left( {2n - 1} \right)}^2}\left[ {{{\left( {2n + 1} \right)}^2} + 1} \right]}}\\&= 2\prod\limits_{k = 1}^n {\left( {1 + \frac{1}{{4{k^2}}}} \right) \cdot } {\left[ {\frac{{\left( {2n} \right)!!}}{{\left( {2n - 1} \right)!!}}} \right]^2}\frac{1}{{4{n^2} + 4n + 2}},\end{align*}
由Wallis公式可知
\[\mathop {\lim }\limits_{n \to \infty } {\left[ {\frac{{\left( {2n} \right)!!}}{{\left( {2n - 1} \right)!!}}} \right]^2}\frac{1}{{2n + 1}} = \frac{\pi }{2}.\]
由$\mathrm{sinh} x$的无穷乘积
\[\frac{{\sinh \left( {\pi x} \right)}}{{\pi x}} = \prod\limits_{k = 1}^\infty {\left( {1 + \frac{{{x^2}}}{{{k^2}}}} \right)} \]
可知
\[\prod\limits_{k = 1}^\infty {\left( {1 + \frac{1}{{{k^2}}}} \right)} = \frac{{{e^\pi } - {e^{ - \pi }}}}{{2\pi }},\quad \prod\limits_{k = 1}^\infty {\left( {1 + \frac{1}{{4{k^2}}}} \right)} = \frac{{{e^{\pi /2}} - {e^{ - \pi /2}}}}{\pi },\]
而调和数列
\[{H_n} = \sum\limits_{k = 1}^n {\frac{1}{k}} = \ln n + \gamma + o\left( 1 \right),\]
\[\mathop {\lim }\limits_{n \to \infty } n\prod\limits_{k = 1}^n {{e^{ - 1/k}}} = {e^{ - \gamma }}.\]
因此所求积分为
\[\frac{{\frac{{{e^\pi } - {e^{ - \pi }}}}{{2\pi }}}}{{{e^\gamma } \times \frac{\pi }{2} \times \frac{{{e^{\pi /2}} - {e^{ - \pi /2}}}}{\pi }}} = \frac{{{e^{\pi /2}} + {e^{ - \pi /2}}}}{{\pi {e^\gamma }}}.\]
 
事实上,我们还有
\begin{align*}\cosh \left( {\pi x} \right) &= \prod\limits_{n = 1}^\infty {\left( {1 + \frac{{4{x^2}}}{{{{\left( {2n - 1} \right)}^2}}}} \right)} ,&\frac{{\sinh \left( {\pi x} \right)}}{{\pi x}} &= \prod\limits_{n = 1}^\infty {\left( {1 + \frac{{{x^2}}}{{{n^2}}}} \right)} ,\\\cos \left( {\pi x} \right) &= \prod\limits_{n = 1}^\infty {\left( {1 - \frac{{4{x^2}}}{{{{\left( {2n - 1} \right)}^2}}}} \right)} ,&\frac{{\sin \left( {\pi x} \right)}}{{\pi x}} &= \prod\limits_{n = 1}^\infty {\left( {1 - \frac{{{x^2}}}{{{n^2}}}} \right)} ,\end{align*}
 
另外
\begin{align*}\sqrt 2 \sin \left( {\frac{{x + 1}}{4}\pi } \right) &= \prod\limits_{n = 0}^\infty {\left( {1 + \frac{{{{\left( { - 1} \right)}^n}x}}{{2n + 1}}} \right)} ,\\\sqrt {x + 1} \sin \left( {\frac{{\sqrt {x + 1} }}{2}\pi } \right) &= \prod\limits_{n = 0}^\infty {\left( {1 - \frac{x}{{4{n^2} - 1}}} \right)} ,\\- \sqrt {x - 1} \mathrm{csch}\left( {\frac{\pi }{2}} \right)\sin \left( {\frac{{\sqrt {x - 1} }}{2}\pi } \right) &= \prod\limits_{n = 0}^\infty {\left( {1 - \frac{x}{{4{n^2} + 1}}} \right)} ,\\- \sqrt { - x - 1} \mathrm{csch}\left( {\frac{\pi }{{\sqrt a }}} \right)\sin \left( {\frac{{\sqrt { - x - 1} }}{{\sqrt a }}\pi } \right) &= \prod\limits_{n = 0}^\infty {\left( {1 + \frac{x}{{a{n^2} + 1}}} \right)} ,\\\frac{{{e^{ - \gamma x}}}}{{\Gamma \left( {1 + x} \right)}} &= \prod\limits_{n = 1}^\infty {\frac{{1 + x/n}}{{{e^{x/n}}}}},\end{align*}
 
对于求和,我们有
\begin{align*}\sum\limits_{n = 1}^\infty {\frac{1}{{{n^2} - {x^2}}}} &= \frac{1}{{2{x^2}}} - \frac{\pi }{{2x}}\cot \left( {\pi x} \right),&&\left| x \right| < \infty \\\sum\limits_{n = 1}^\infty {\frac{1}{{{{\left( {{n^2} - {x^2}} \right)}^2}}}} &= - \frac{1}{{2{x^4}}} - \frac{{{\pi ^2}}}{{4{x^2}}}\mathrm{csc}^2\left( {\pi x} \right) + \frac{\pi }{{4{x^3}}}\cot \left( {\pi x} \right),&&\left| x \right| < \infty \\\sum\limits_{n = 1}^\infty {\frac{1}{{{{\left( {2n - 1} \right)}^2} - {x^2}}}} &= \frac{\pi }{{4x}}\tan \left( {\frac{\pi }{2}x} \right),&& \left| x \right| < \infty \\\sum\limits_{n = 1}^\infty {\frac{1}{{{{\left[ {{{\left( {2n - 1} \right)}^2} - {x^2}} \right]}^2}}}} &= \frac{{{\pi ^2}}}{{16{x^2}}}\sec \left( {\frac{\pi }{2}x} \right) - \frac{\pi }{{8{x^3}}}\tan \left( {\frac{\pi }{2}x} \right),&&\left| x \right| < \infty \\\sum\limits_{n = 1}^\infty {\frac{1}{{{n^2} + {x^2}}}} &= \frac{\pi }{{2x}}\coth \left( {\pi x} \right) - \frac{1}{{2{x^2}}}, &&\left| x \right| < \infty\\\sum\limits_{n = 1}^\infty {\frac{1}{{{{\left( {2n - 1} \right)}^2} + {x^2}}}} &= \frac{\pi }{{4x}}\tanh \left( {\frac{\pi }{2}x} \right),&&\left| x \right| < \infty\end{align*}
其中$\mathrm{sinh}x=\frac{e^x-e^{-x}}2,\mathrm{cosh}x=\frac{e^x+e^ {-x}}2,\mathrm{csch}x=\frac2{e^x-e^ {-x}},\mathrm{tanh}x=\frac{e^x-e^ {-x}}{e^x+e^ {-x}},\mathrm{coth}x=\frac{e^x+e^ {-x}}{e^x-e^ {-x}}$.
The Weierstrass factorization theorem. Sometimes called the Weierstrass product/factor theorem.
 
Let $f$ be an entire function, and let $\{a_n\}$ be the non-zero zeros of $ƒ$ repeated according to multiplicity; suppose also that $ƒ''$ has a zero at $z= 0$ of order $m\geq 0$ (a zero of order $m=0$ at $z=0$ means $f(0)\neq 0$.
Then there exists an entire function $g$ and a sequence of integers $\{p_n\}$ such that
 
\[f(z)=z^m e^{g(z)} \prod_{n=1}^\infty E_{p_n}\left(\frac{z}{a_n}\right).\]
 
====Examples of factorization====
 
\begin{align*}\sin \pi z &= \pi z \prod_{n\neq 0} \left(1-\frac{z}{n}\right)e^{z/n} = \pi z\prod_{n=1}^\infty \left(1-\left(\frac{z}{n}\right)^2\right)\\\cos \pi z &= \prod_{q \in \mathbb{Z}, \, q \; \text{odd} } \left(1-\frac{2z}{q}\right)e^{2z/q} = \prod_{n=0}^\infty \left( 1 - \left(\frac{z}{n+\tfrac{1}{2}} \right)^2 \right) \end{align*}
 
The cosine identity can be seen as special case of
\[\frac{1}{\Gamma(s-z)\Gamma(s+z)} = \frac{1}{\Gamma(s)^2}\prod_{n=0}^\infty \left( 1 - \left(\frac{z}{n+s} \right)^2 \right)\]
for $s=\tfrac{1}{2}$.
 
Mittag-Leffler's theorem.
 
== Pole expansions of meromorphic functions ==
Here are some examples of pole expansions of meromorphic functions:
 
\begin{align*}\frac{1}{\sin(z)}&= \sum_{n \in \mathbb{Z}} \frac{(-1)^n}{z-n\pi}= \frac{1}{z} + 2z\sum_{n=1}^\infty (-1)^n \frac{1}{z^2 - (n\,\pi)^2},\\\cot(z) &\equiv \frac{\cos (z)}{\sin (z)}= \sum_{n \in \mathbb{Z}} \frac{1}{z-n\pi}= \frac{1}{z} + 2z\sum_{k=1}^\infty \frac{1}{z^2 - (k\,\pi)^2},\\\frac{1}{\sin^2(z)} &= \sum_{n \in \mathbb{Z}} \frac{1}{(z-n\,\pi)^2},\\\frac{1}{z \sin(z)}&= \frac{1}{z^2} + \sum_{n \neq 0} \frac{(-1)^n}{\pi n(z-\pi n)}= \frac{1}{z^2} + \sum_{n=1}^\infty \frac{(-1)^n}{n\,\pi} \frac{2z}{z^2 - (n\,\pi)^2}.\end{align*}

 

好题

设$a,b>0$,而$\displaystyle \int_0^{\infty}{\frac{tdt}{\sqrt[3]{\left( a^3+t^3 \right) \left( b^3+t^3 \right) ^2}}}$.证明:
(1) $\displaystyle I\left( a,b \right) =I\left( \frac{a+2b}{3},\sqrt[3]{b\frac{a^2+ab+b^2}{3}} \right)$.
 
(2) 数列$\{a_n\},\{b_n\}$满足$a_0=a,b_0=b$,且满足$a_{n+1}=\frac{a+2b}{3},b_{n+1}=\sqrt[3]{b_n\frac{a_n^2+a_nb_n+b_n^2}{3}}$,求证$\lim_{n\to\infty}a_n=\lim_{n\to\infty}b_n=\frac{I(1,1)}{I(a,b)}$.
 
线性系统理论代数基础,韩京清:http://book.ixueshu.com/book/15b7a59545f6afe2.html
 
http://book.ixueshu.com/book/b9f03de828640dda.html
 
Ramanujan's golden ratio equation
\begin{align*}R\left( e^{-2\pi} \right) &=\frac{e^{-\frac{2\pi}{5}}}{1+\frac{e^{-2\pi}}{1+\frac{e^{-4\pi}}{1+\ddots}}}=\sqrt{\frac{5+\sqrt{5}}{2}}-\phi ,\\R\left( e^{-2\sqrt{5}\pi} \right) &=\frac{e^{-\frac{2\pi}{\sqrt{5}}}}{1+\frac{e^{-2\pi \sqrt{5}}}{1+\frac{e^{-4\pi \sqrt{5}}}{1+\ddots}}}=\frac{\sqrt{5}}{1+\left( 5^{3/4}\left( \phi -1 \right) ^{5/2}-1 \right) ^{1/5}}-\phi ,\end{align*}
其中$\phi=\frac{1+\sqrt5}{2}$为黄金分割数(golden ratio).
 
\begin{align*}R(q) & = q^{\frac{1}{5}}\prod_{n=1}^\infty \frac{(1-q^{5n-1})(1-q^{5n-4})}{(1-q^{5n-2})(1-q^{5n-3})} \\ &= \cfrac{q^{1/5}}{1+\cfrac{q}{1+\cfrac{q^2}{1+\cfrac{q^3}{1+\ddots}}}}.\end{align*}
 
Ramanujan–Sato series,https://en.wikipedia.org/wiki/Ramanujan%E2%80%93Sato_series
\[\frac{1}{\pi} = \frac{2 \sqrt 2}{99^2} \sum_{k=0}^\infty \frac{(4k)!}{k!^4} \frac{26390k+1103}{396^{4k}}.\]
Chudnovsky algorithm,https://en.wikipedia.org/wiki/Chudnovsky_algorithm
\[\frac{1}{\pi} = 12 \sum^\infty_{k=0} \frac{(-1)^k (6k)! (545140134k + 13591409)}{(3k)!(k!)^3 \left(640320\right)^{3k + 3/2}}.\]此公式对$\pi$有非常好的计算性能.
 
Ramanujan's Hypergeometric Identity,http://mathworld.wolfram.com/RamanujansHypergeometricIdentity.html
 
$$\sum_{k=-\infty}^\infty 2^k = 0.$$
 
Plot the graphs of the functions $$f(x)=\dfrac{2(x^2+|x|-6)}{3(x^2+|x|+2)}+\sqrt{16-x^2}$$ and $$g(x)=\dfrac{2(x^2+|x|-6)}{3(x^2+|x|+2)}-\sqrt{16-x^2}$$ in $x\in[-4,4]$ on the same plane. 
 
 
![enter image description here][1]
 
 
  [1]: http://i.stack.imgur.com/9PdtB.jpg
 
\[\sum_{n=1}^{\infty} \frac{n^{13}}{e^{2\pi n} - 1} = \frac{1}{24}.\]
 
美丽有两种,一种是全新的数学工具;一种是时刻浮现在脑海里你甜美的笑容。

sinx小于x小于tanx,Young不等式,等周问题
张筑生,谢惠民

https://math.stackexchange.com/a/411763/165013 


https://math.stackexchange.com/a/842310/165013 


https://math.stackexchange.com/a/2323155/165013 


https://math.stackexchange.com/a/718750/165013 


https://math.stackexchange.com/a/83952/165013 


https://math.stackexchange.com/a/61727/165013
 
 
 
乌班图下安装TeXLive2017:
 

分栏的列表环境

\begin{multicols}{2}
    \begin{enumerate}
        \item Item 1
        \item Item 2
        \item Item 3
        \item This is item number 4
        \item This is item number 5
        \item This is item number 6
    \end{enumerate}
\end{multicols}

\documentclass[12pt,a4paper]{article}
\begin{document}
\begin{enumerate}
  \begin{minipage}{0.3\linewidth}   
    \item Item 1
    \item Item 2
    \item Item 3
  \end{minipage}
  \begin{minipage}{0.6\linewidth}
    \item This is item number 4
    \item This is item number 5
    \item This is item number 6       
  \end{minipage}
\end{enumerate}
\end{document}

\documentclass{article}
\usepackage{multicol}
\usepackage{amsmath}

\begin{document}
\begin{enumerate}
    \item Determinar la transpuesta de cada una de las sigientes matrices. Adem\'as si la matriz es cuadrada, calcular su traza.
    \begin{multicols}{2}
        \begin{enumerate}
            \item   
            $\left( \begin{matrix}
            -4 & 2 \\
            5 & -1
            \end{matrix} \right)$
            \item           
            $\left( \begin{matrix}
            0 & 8 & -6 \\
            3 & 4 & 7 
            \end{matrix} \right)$
            \item 
            $\left( \begin{matrix}
            -3 & 9 \\
            0 & -2 \\
            6 & 1 
            \end{matrix} \right)$
            \item 
            $\left( \begin{matrix}
            10 & 0 & -8 \\
            2 & -4 & 3 \\
            -5 & 7 & 6 
            \end{matrix} \right)$
        \end{enumerate}
    \end{multicols}
\end{enumerate}
\end{document}

一个网页版介绍:http://www.ctex.org/documents/shredder/tex_frame.html

特殊图案:加载bclogo宏包,\bcours(熊),\bccrayon(铅笔),\bcicosaedre(多面体)

LaTeX技巧693:安装 MathTime Professional 2 数学字体

LaTeX技巧693:安装 MathTime Professional 2 数学字体

【版权问题】
 
首先,这是一款商业字体,版权归PCTeX公司所以。全套字体售价$140,我认为对追求完美的用户而言,绝对是物有所值。我认为那种 “(汉)字是老祖宗遗产,拿字体来卖钱不合理” 的言论是非常无耻的。会写这个字是一回事、怎么写这个字又是另一回事,“设计字体、把字体制作成字体文件”是非常辛苦的工作。在桌面系统上,对字体的版权保护没有实际可行的方法,还没有见过针对字体的版权管理系统(DRM: Digital Rights Manager),想用某个字体把它copy-and-paste就行了。Adobe刚搞出Type1的时候弄了一个AFM(Adobe Font Manager),专门用来管理字体,并以此卖字体、大把大把赚钱。Apple和M$就不爽了,弄了一个TrueType,结果Adobe就不搞AFM了。真正的“字体保护”恐怕只在印刷工业界才能看到,通常会和排版系统捆绑在一起。
 
我想说的是,虽然桌面领域字体版权保护不常提起,但是这个mtpro2字体是有版权的。最低限度的,我希望大家不要用于商业领域。如果这个帖子侵犯了您的合法权益,请和我联系,我会将获取Math Time Pro 2 字体的部分去掉,仅仅讨论如何安装字体。另外,如果这个字体的授权能够更灵活一些,比如针对教育界多用户的版本,每个人出几十块钱买一份,合着一起用还是蛮划算的。(选自:http://bbs.sjtu.edu.cn/bbscon?board=TeX_LaTeX&file=M.1246297039.A)
 
【字体下载】
 
MathTimePro2 fonts
 
或者
 
http://pixtex.googlecode.com/files/pixtex-pctex-MahTimeProII-fonts.7z
 
【安装方法】(milksea)
 
texmf 目录中的内容是字体文件和对应的宏包、文档;templates 目录中是测试示例(MTPro2 LaTeX test.tex)和几个英文文章模板,可以在安装后编译测试。如果要方便以后看例子,可以把此目录复制到 texmf\doc\fonts\mtpro2 目录中。
 
1、把 texmf 目录中的内容按结构复制到本地的 texmf 目录(对 TeX Live 就是 texmf-local,对 CTeX 套装就是 localtexmf,等等),事实上其中的 tpm 和 dvips 两个子目录可以删去;
2、命令行运行 texhash;
3. a、对 TeX Live,命令行运行
updmap-sys –enable Map=mtpro2.map
updmap –enable Map=mtpro2.map
b、对 MiKTeX(CTeX 套装、MiCTeX 等),命令行运行
initexmf –edit-config-file updmap
在弹出的 updmap.cfg 文件末尾添加一行
Map mtpro2.map
然后存盘退出。如果不行再运行 updmap。
4、完成,可以编译 templates 目录中的测试文件进行测试了!
 
【字体效果图】
 
http://www.pctex.com/mtpro2.html
 
不推荐 CTeX 套装作为入门
 
1. CTeX 封装的 MikTeX 在实现 XeTeX 以及字体库的时候有一些问题,前者导致运行 XeLaTeX 异常缓慢,后者导致使用一些数学字体的时候会报错。
2. CTeX 封装的默认编辑器 WinEdt 是闭源软件,实际上是在使用盗版软件。
3. CTeX 封装的默认编辑器 WinEdt 修改了默认编码为 GBK, 这将在后续使用过程中产生很多问题,对初学者来说是不良的。
4. CTeX 封装的默认编辑器 WinEdt 集成了太多的功能,并且修改了很多 LaTeX 的默认行为,对于初学者来说,这些未经通告的默认行为修改对于其对 LaTeX 的理解是不良的。
5. CTeX 套装的 2.9.2.164 版本至今已经超过一年未更新,aloft 老大似乎也没有更新的愿望,事实上也没有必要再更新了。
6. CTeX 由于封装 MikTeX 而只能运行于 Windows 平台。
 
顺带:
CTeX 是因为 CJK 包的字体配置复杂,为了免去入门用户的配置成本而推出的。
而现在因为 XeTeX 引擎以及 xeCJK 宏包的出现,CJK 包已经成为过去。并且使用 zhm 可以与 CJK 结合方便地动态配置字体。因此 CTeX 曾经的优势实际上已经不成为优势,并且因其引起的各种国内期刊模板的老旧问题正不断成为阻碍中国 TeX 社区进步的恼人因素。
 

 

曲面积分计算

(2012年中科院考研题)设$\rho (x,y,z)$是原点$O$到椭球面$\frac{x^2}2+\frac{y^2}2+z^2=1$的上半部分(即满足$z\geq 0$的部分) $\Sigma$的任一点$(x,y,z)$处的切面的距离,求积分\[\iint_\Sigma \frac z{\rho (x,y,z)}dS.\]
 
所求积分为
 
\[I=\iint_{\Sigma}{\frac{z}{\rho \left( x,y,z \right)}dS}=\frac{1}{2}\iint_{\Sigma}{z\sqrt{x^2+y^2+z^2}dS}.\]
 
记$z=\varphi (x,y), (x,y)\in D$,其中$D$为$x^2+y^2=2$.首先有
 
\begin{align*}dS&=\sqrt{1+\left(\frac{\partial \varphi}{\partial x}\right)^2+\left(\frac{\partial \varphi}{\partial x}\right)^2}dxdy=\sqrt{1+\left(\frac{-x}{2z}\right)^2+\left(\frac{-y}{2z}\right)^2}dxdy\\&=\frac1{2z}\sqrt{x^2+y^2+4z^2}dxdy.\end{align*}
 
因此
 
\begin{align*}I&=\iint_{\Sigma}{\frac{z}{\rho \left( x,y,z \right)}dS}=\frac{1}{2}\iint_{\Sigma}{z\sqrt{x^2+y^2+z^2}dS}\\&=\frac{1}{4}\iint_D\sqrt{x^2+y^2+z^2}\sqrt{x^2+y^2+4z^2}dxdy=\frac{1}{4}\iint_D\sqrt{1+\frac{x^2}2+\frac{y^2}2}\sqrt{4-x^2-y^2}dxdy\\&=\frac14\int_0^{2\pi}d\theta\int_0^{\sqrt{2}}r\sqrt{1+\frac{r^2}2}\sqrt{4-r^2}dr=\frac\pi4\int_0^{\sqrt{2}}\sqrt{1+\frac{u}2}\sqrt{4-u}du\\&=\frac\pi{4\sqrt{2}}\int_0^{\sqrt{2}}\sqrt{8+2u-u^2}du=\frac{\sqrt{2}\pi}{16}\left(\sqrt{10-6\sqrt{2}}+9\arcsin \frac{\sqrt 2-1}3+2\sqrt{2}+9\arcsin \frac13\right).\end{align*}
这是因为
\begin{align*}&\int{\sqrt{8+2u-u^2}du}=u\sqrt{8+2u-u^2}-\int{\frac{u-u^2}{\sqrt{8+2u-u^2}}du}\\&=u\sqrt{8+2u-u^2}-\int{\frac{\left( 8+2u-u^2 \right) -8-u}{\sqrt{8+2u-u^2}}du}\\&=u\sqrt{8+2u-u^2}-\int{\sqrt{8+2u-u^2}du}+\int{\frac{8+u}{\sqrt{8+2u-u^2}}du}\\&=\left( u-1 \right) \sqrt{8+2u-u^2}-\int{\sqrt{8+2u-u^2}du}+\int{\frac{9}{\sqrt{9-\left( u-1 \right) ^2}}du}\\&=\left( u-1 \right) \sqrt{8+2u-u^2}-\int{\sqrt{8+2u-u^2}du}+9\arcsin \frac{u-1}{3}+C,\end{align*}
$$\int{\sqrt{8+2u-u^2}du}=\frac{u-1}{2}\sqrt{8+2u-u^2}+\frac{9}{2}\arcsin \frac{u-1}{3}+C.$$

 

国外论坛好题

Sylvester equation https://en.wikipedia.org/wiki/Sylvester_equation
To seek the maximum value of $S=x_1x_2+x_2x_3+\cdots+x_nx_1$ on this domain:
 
补充:这是Ky Fan-Tausski-Todd inequality,参考Converses of two inequalities of Ky Fan, O. Taussky, and J. Todd以及这里
 
$x_1+x_2+\cdots+x_n=0$ and 
$x_1^2+x_2^2+\cdots+x_n^2=1$.
 
I have made some trivial observations:
 
1) $S\in[-1,1)$ by the rearrangement inequality.
 
2) We can make $S$ arbitrarily close to $1$ by increasing $n$.
 
3) An equivalent problem is to minimise $(x_1-x_2)^2+\cdots+(x_n-x_1)^2$.
 
But does the maximum have a meaningful closed form  for each $n$?
I propose to do a discrete Fourier transform. To this end put $\omega:=e^{2\pi i/n}$. In the following  all sums are over ${\mathbb Z}_n$, unless indicated otherwise. Let
$$y_k:={1\over n}\sum_l x_l\omega^{-kl}\ .$$
Since the $x_l$ are real we have $$y_{-k}=\overline{y_k}\tag{1}$$ for all $k$, furthermore $y_0=\sum_lx_l=0$. One has Parseval's formula
$$n\sum_k y_k\overline{ y_k}=\sum_l x_l^2=1\tag{2}$$
and the inversion formula
$$x_j=\sum_k y_k\omega^{jk}\ .\tag{3}$$
Using $(3)$ one computes
$$S=\sum_j x_jx_{j+1}=\ldots=n\sum_k|y_k|^2\omega^k\ .\tag{4}$$
At this point we have to distinguish the cases (a) $n=2m$, and (b) $n=2m+1$.
 
(a) If $n=2m$ then $\omega^m=-1$, and $(4)$ gives
$$\eqalign{S&=n\left(\sum_{k=1}^{m-1}|y_k|^2(\omega^k+\omega^{-k}) \ +|y_m|^2\omega^m\right)\cr
&=n\left(\sum_{k=1}^{m-1}|y_k|^2\>2\cos{2k\pi\over n} \ -|y_m|^2\right)\ .\cr}$$
Given the conditions $(1)$ and $(2)$ it is easily seen that the optimal admissible choice of the $y_k$ is $$y_1=y_{-1}={1\over\sqrt{2n}}\>,\qquad y_k=0\quad(k\ne\pm1)\ .\tag{5}
$$  This leads to
$$S_{\rm opt}=\cos{2\pi\over n}\ .$$
In particular when $n=4$ one obtains $S_{\rm opt}=0$, as indicated in Zubzub's answer.
 
(b) If $n=2m+1$ then $(4)$ gives
$$S=2n\sum_{k=1}^m |y_k|^2\cos{2k\pi\over n}\ ,$$
and the choice $(5)$ leads again to
$$S_{\rm opt}=\cos{2\pi\over n}\ .$$

In particular when $n=3$ one obtains $S_{\rm opt}=-{1\over2}$, and when $n=5$ one obtains $S_{\rm opt}=\cos{2\pi\over5}\doteq0.309$, as indicated in Zubzub's answer.

见:https://math.stackexchange.com/questions/2213960/optimising-x-1x-2x-2x-3-cdotsx-nx-1-given-certain-constraints


Let $$
A=\left[ \begin{matrix}
A_1& A_3\\
0& A_2\\
\end{matrix} \right]\quad \text{and} \quad B=\left[ \begin{array}{c}
B_1\\
B_2\\
\end{array} \right],
$$and for any eigenvalue $s$ of $A$, we have
$$
\mathrm{rank}\,\left[ A-sI_n,B \right] =n.
$$
Prove there are a real matrix $K\in \mathbb{R}^{r\times n}$ and invertible matrix $T\in \mathbb{R}^{n\times n}$, such that
$$
T\left( A+BK \right) T^{-1}=\left[ \begin{matrix}
A_1& 0\\
0& \bar{A}_2\\
\end{matrix} \right] ,\qquad TB=\left[ \begin{array}{c}
\bar{B}_1\\
B_2\\
\end{array} \right],
$$
where $A\in \mathbb{R}^{n\times n},B\in \mathbb{R}^{n\times r}$. Meanwhile,  $\bar{A}_2$ and $\bar{B}_1$ is real matrix of the proper dimension, $\bar{A}_2$ and $A_1$ Have eigenvalues that are not identical to each other.
 
This problem is about controllability of linear system and pole assignment, so I think we may try controllability canonical form, or let $K=(K_1,K_2)$, then determine the $K_1,K_2$ and $T$, but it seems so difficult.

The statement about the rank of $\left[A - s\,I, B\right]$ implies that the pair $(A,B)$ is [controllable](https://en.wikipedia.org/wiki/Hautus_lemma). Therefore the poles of the resulting matrix should be able to be placed anywhere. The similarity transformation should allow us to separate the eigenvalues/modes and therefore achieve the stated goal
 
$$
T \left(A + B\,K\right) T^{-1} = 
\begin{bmatrix}
A_1 & 0 \\ 0 & \bar{A}_2
\end{bmatrix}, \quad 
T\,B = 
\begin{bmatrix}
\bar{B}_1 \\ B_2
\end{bmatrix},
$$
 
given that
 
$$
A = 
\begin{bmatrix}
A_1 & A_3 \\ 0 & A_2
\end{bmatrix}, \quad
B = 
\begin{bmatrix}
B_1 \\ B_2
\end{bmatrix}.
$$
 
For solving this it is easier to separate the problem in smaller problems. For this I will define $T$ and $K$ as
 
$$
T = 
\begin{bmatrix}
T_1 & T_2 \\ T_3 & T_4
\end{bmatrix}, \quad
K = 
\begin{bmatrix}
K_1 & K_2
\end{bmatrix}.
$$
 
The last goal requires
 
$$
T\,B = 
\begin{bmatrix}
T_1\,B_1 + T_2\,B_2 \\ T_3\,B_1 + T_4\,B_2
\end{bmatrix} = 
\begin{bmatrix}
\bar{B}_1 \\ B_2
\end{bmatrix}.
$$
 
The bottom half of this goal might have infinitely many solution if there is any overlap in the span of $B_1$ and $B_2$. But this problem should be solvable in general, in which case $T_3=0$ and $T_4=I$ should always solve it. Using this then the inverse of $T$ can shown to be
 
$$
T^{-1} = 
\begin{bmatrix}
T_1 & T_2 \\ 0 & I
\end{bmatrix}^{-1} = 
\begin{bmatrix}
T_1^{-1} & -T_1^{-1}\,T_2 \\ 0 & I
\end{bmatrix}.
$$
 
Since nothing is specified about $\bar{B}_1$ then $T_1$ and $T_2$ could be anything for now as long as $T_1$ is invertible. The left hand side of the first goal can now be written as
 
$$
T \left(A + B\,K\right) T^{-1} = 
\begin{bmatrix}
T_1\,A_1\,T_1^{-1} + \bar{B}_1\,K_1\,T_1^{-1} & T_1\,A_3 + T_2\,A_2 - T_1\,A_1\,T_1^{-1}\,T_2 + \bar{B}_1\left(K_2 - K_1\,T_1^{-1}\,T_2\right) \\
B_2\,K_1\,T_1^{-1} & A_2 + B_2\left(K_2 - K_1\,T_1^{-1}\,T_2\right)
\end{bmatrix}.
$$
 
It can be shown that the top and bottom left half can be set equal to the goal by using $T_1=I$ and $K_1=0$. This allows the top and bottom right of the first goal equation to be simplified to
 
$$
\begin{bmatrix}
A_3 + T_2\,A_2 - A_1\,T_2 + \bar{B}_1\,K_2 \\
A_2 + B_2\,K_2
\end{bmatrix} = 
\begin{bmatrix}
0 \\
\bar{A}_2
\end{bmatrix}.
$$
 
For the bottom half of this equation you could just use a pole placement algorithm to find $K_2$, such that none of the poles match those of $A_1$. This should be possible since the pair $(A_2,B_2)$ should be controllable. The top half can then be rewritten as
 
$$
A_3 + T_2\,\bar{A}_2 - A_1\,T_2 + B_1\,K_2 = 0,
$$
 
which can be transformed into a [Sylvester equation](https://en.wikipedia.org/wiki/Sylvester_equation)
 
$$
A\,X + X\,B = C,
$$
 
with $X = T_2$, $A = -A_1$, $B = \bar{A}_2$ and $C = -A_3 - B_1\,K_2$. This equation has an unique solution for $X$ when $A$ and $-B$ do not have a common eigenvalue. This is an identical constraint as mentioned by your problem statement.
 
So to solve this problem you can first do a pole placement with the pair $(A_2,B_2)$ to find $K_2$, avoiding the eigenvalues of $A_1$. And then solve a Sylvester equation after substituting in this obtained $K_2$ in order to find $T_2$. Using these values then the final solution can then be expressed using
 
$$
T = 
\begin{bmatrix}
I & T_2 \\ 0 & I
\end{bmatrix}, \quad
K = 
\begin{bmatrix}
0 & K_2
\end{bmatrix}.
$$

 

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阅读全文

一个偏微分方程求解

$$\frac{\partial J}{\partial t}=\frac{1}{4}\left( \frac{\partial J}{\partial x} \right) ^2-x^2-\frac{1}{2}x^4 \tag 1$$
$$\frac{\partial^2 J}{\partial t\partial x}=\frac{1}{2} \frac{\partial J}{\partial x}\frac{\partial^2 J}{\partial x^2} -2x-2x^3$$
Change of function :
$$\frac{\partial J}{\partial x}=u(x,t)\quad\to\quad \frac{\partial u}{\partial t} -\frac{1}{2} u\frac{\partial u}{\partial x}= -2x-2x^3 \tag 2$$
Characteristic system of equations :
$$\frac{dt}{1}=\frac{dx}{-\frac{1}{2} u}=\frac{du}{-2x-2x^3}$$
First family of characteristic curves, from $\quad -2\frac{dx}{ u}=\frac{du}{-2x-2x^3} :$
$$2udu-(8x+8x^3)dx=0 \quad\to\quad u^2-4x^2-2x^4=c_1$$
Second family of characteristic curves, from $\frac{dt}{1}=\frac{dx}{-\frac{1}{2} u} :$
$$dx+\frac{u}{2}dt=0=dx+\frac{\sqrt{c_1+4x^2+2x^4}}{2}dt$$
$$dt+\frac{2dx}{\sqrt{c_1+4x^2+2x^4}}=0 \quad\to\quad t+\int\frac{2dx}{\sqrt{c_1+4x^2+2x^4}}=c_2 $$
The integral can be expressed on closed form. The formula involves a special function, namely the Elliptic Integral of the first kind :
http://www.wolframalpha.com/input/?i=integrate+2%2Fsqrt(C%2B4+x%5E2%2B2+x%5E4)&x=0&y=0
 
[![enter image description here][1]][1]
 
In interest of space and in order to make easier the writing, this big formula will be symbolized as :
$$\int\frac{2dx}{\sqrt{c_1+4x^2+2x^4}}=\Psi\left(c_1,x\right)$$
Where $\Psi$ is the above known function. Thus the second family of characteristic curves is :
$$ t+\Psi\left(c_1,x\right)=c_2$$
 
The general solution of the PDE $(2)$ is expressed on the form of the implicit equation :
$$F\left(\left(u^2-4x^2-2x^4\right) \:,\: \left(t+\Psi\left(u^2-4x^2-2x^4\:,\:x\right)\right) \right)=0$$
where $F$ is any differentiable function of two variables.
 
The function $F$ might be determined according to a boundary condition which has to be derived from a given boundary condition of Eq.$(1)$. Nevertheless it appears doubtful to find a closed form for $F$ considering the complicated function $\Psi$.
 
Supposing that the function $F$ be determined, which is optimistic, a more difficult step comes after, to go from $u(x,t)$ to $J(x,y)$, which suppose possible to find a closed form for $\int u(x,t)dx$.
 
 
  [1]: https://i.stack.imgur.com/DLyqp.jpg
 
对于实矩阵$A=\left[ \begin{matrix}A_1& A_3\\0& A_2\\\end{matrix} \right] $
 
 

曲线积分的计算

写出圆周的单层位势$$U(a,b)=\int_{x^2+y^2=R^2}\ln \frac 1{\sqrt{(x-a)^2+(y-b)^2}}ds,\quad \text{其中}\,  a^2+b^2\neq R^2$$


解.不妨设$R>0$,否则考察$-R$.令$x=R\cos\theta,y=R\sin\theta$,则$$ds=\sqrt{\left[x'(\theta)\right]^2+\left[y'(\theta)\right]^2}d\theta=Rd\theta.$$因此

\begin{align*}U(a,b)&=R\int_0^{2\pi}\ln \frac 1{\sqrt{(R\cos\theta-a)^2+(R\sin\theta-b)^2}}d\theta\\&=R\int_0^{2\pi}\ln \frac 1{\sqrt{R^2+a^2+b^2-2aR\cos\theta-2bR\sin\theta}}d\theta\\&=-\frac R2\int_0^{2\pi}\ln \left(R^2+a^2+b^2-2R\sqrt{a^2+b^2}\sin(\theta+\varphi)\right)d\theta,\quad \text{其中}\, \tan\varphi=\frac ab\\&=-\frac R2\int_0^{2\pi}\ln \left(R^2+a^2+b^2-2R\sqrt{a^2+b^2}\cos\theta\right)d\theta\\&=-\frac R2\int_0^{\pi}\ln \left(R^2+a^2+b^2-2R\sqrt{a^2+b^2}\cos\theta\right)d\theta-\frac R2\int_\pi^{2\pi}\ln \left(R^2+a^2+b^2-2R\sqrt{a^2+b^2}\cos\theta\right)d\theta\\&=-\frac R2\int_0^{\pi}\ln \left(R^2+a^2+b^2-2R\sqrt{a^2+b^2}\cos\theta\right)d\theta-\frac R2\int_0^\pi\ln \left(R^2+a^2+b^2+2R\sqrt{a^2+b^2}\cos\theta\right)d\theta.\end{align*}

中间几步注意到了对积分变量进行诸如$u=\theta+c$的变换改变积分上下限,而$\sin x$和$\cos x$的最小周期为$2\pi$.因此仍等于$0$到$2\pi$上的积分.

再由比较常见的Poisson积分公式有$$\int_0^\pi\ln (a\pm b\cos x)dx=\pi\ln\frac{a+\sqrt{a^2-b^2}}{2},\quad a\geq b\geq 0$$此公式证明只需把积分看成是关于$b$的函数,对$b$求导即可.

由此得$$\int_0^\pi\ln \left(a^2\pm 2ab\cos x+b^2\right)dx=\begin{cases}2\pi\ln a,&a\geq b\geq 0\\2\pi\ln b,&b\geq a\geq 0\end{cases}$$因此所求积分为

$$U(a,b)=\begin{cases}-2\pi |R|\ln |R|,& a^2+b^2<R^2\\-\pi |R|\ln \left(a^2+b^2\right),& a^2+b^2>R^2\end{cases}$$


在惯性系内一不受外力作用的刚性飞行器绕固定点转动的动态可用Euler方程描述\begin{align*}J_1\dot\omega_1&=(J_2-J_3)\omega_2\omega_3,\\J_2\dot\omega_2&=(J_3-J_1)\omega_3\omega_1,\\J_3\dot\omega_3&=(J_1-J_2)\omega_1\omega_2.\end{align*}其中$\omega_1,\omega_2,\omega_3$为刚体转动角速度的投影, $J_1,J_2,J_3$为惯性主轴的转动惯量且$J_1,J_2,J_3$均大于$0$.

(1)研究

保福寺烟酒僧的搬砖日常

前阵子忙着硕转博考试复习,去找了下Boss,给我一篇机器学习领域计算凸包的文章 Stratifying High-Dimensional Data Based on Proximity to the Convex Hull Boundary(基于接近凸包边界的高维数据分层)