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丘成桐大学生数学竞赛2013年分析与方程团体赛试题参考解答

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S.-T.YauCollege Student Mathematics Contests 2013

 

Analysis and Differential Equations Team

 

Please solve 5 out of the following 6 problems.

 

 

 

1. Supppose \lap=\sed{z\in\bbC;|z|<1} is the open unit disk in the complex plane. Show that for any holomorphic function f:\lap\to \lap , \bee\label{1.eq} \frac{|f‘(z)|}{1-|f(z)|^2}\leq\frac{1}{1-|z|^2}, \eee for all z in \lap . If equality holds in \eqref{1.eq} for some z_0\in \lap , show that f\in \Aut(\lap) and that \bex \frac{|f‘(z)|}{1-|f(z)|^2}=\frac{1}{1-|z|^2}, \eex for all z\in\lap .

 

Solution: This is just the Schwarz-Pick Lemma. For any z\in \lap , consider the mapping \beex \bea \varphi:\lap\to \lap,&\quad\xi\mapsto\cfrac{-\xi+z}{1-\bar z\xi};\\ f:\lap\to \lap,&\quad\eta\mapsto f(\eta);\\ \psi:\lap\to\lap,&\quad\zeta\mapsto \cfrac{-\zeta+f(z)}{1-\overline{f(z)}\zeta}. \eea \eeex Then \psi\circ f\circ \varphi:\lap\to\lap with 0 being fixed. By Schwarz Lemma, \beex \bea |(\psi\circ f\circ \varphi)‘(0)|&\leq 1,\\ |\psi‘(f(z))|\cdot |f‘(z)|\cdot |\varphi‘(0)|&\leq 1,\\ \cfrac{1}{1-|f(z)|^2}\cdot |f‘(z)|\cdot (1-|z|^2)&\leq 1,\\ \cfrac{|f‘(z)|}{1-|f(z)|^2}&\leq\cfrac{1}{1-|z|^2}. \eea \eeex And the equality holds for some z_0\in \lap , iff (\varphi^{-1}=\varphi,\psi^{-1}=\psi ) \beex \bea \psi\circ f\circ \varphi&\in \Aut(\lap),\\ f=\psi\circ(\psi\circ f\circ \varphi)\circ \varphi&\in \Aut(\lap). \eea \eeex

 

 

 

2. Let f be a function of bounded variation on [a,b] , f_1 its generalized derivative as a measure, i.e. \bex f(x)-f(a)=\int_a^x f_1(y)\rd y \eex for every x\in [a,b] and f_1(x) is an integrable function on [a,b] . Let f‘ be its weak derivative as a generalized function, i.e. \bex \int_a^b f(x)g‘(x)\rd x=-\int_a^bf‘(x)g(x)\rd x, \eex for every smooth g(x) on [a,b] , g(a)=g(b)=0 . Show that

(1) If f is absolutely continuous, then f‘=f_1 .

(2) If the weak derivative f‘ of f is an integrable function on [a,b] , then f(x) is equal to an absolutely continuous function outside a set of measure zero.

 

Solution:

(1) If f is absolutely continuous, then \beex \bea \int_a^b f(x)g‘(x)\rd x&=\int_a^b \sez{f(a)+\int_a^x f_1(y)\rd y}g‘(x)\rd x\\ &=-\int_a^b \frac{\rd }{\rd x} \sez{f(a)+\int_a^x f_1(y)\rd y}g(x)\rd x\\ &=-\int_a^b f_1(x)g(x)\rd x. \eea \eeex Thus, \bex \int_a^b [f‘(x)-f_1(x)]g(x)\rd x=0. \eex Approximation arguments then yields that f‘=f_1 .

(2) Let \bex g(x)=f(a)+\int_a^xf‘(t)\rd t. \eex Then g is absolutely continuous. Since f‘=g‘ \ae (weak derivative), and f(a)=g(a) , we have f=g \ae as desired.

 

 

 

3. Show that the convex hull of the roots of any polynomial contains all its critical points as well as all the zeros of higher derivatives of the polynomial. Here the convex hull of a given bounded set in the plane is the smallest convex set containing the given set in the plane.

 

Solution: Let \bex p(z)=b\prod_{i=1}^n (z-a_i) \eex be a polynomial of degree n (b\neq 0 ). For z satisfying p‘(z)=0 ,

(1) if p(z)=0 , then z=a_i for some i=1,2,\cdots,n ;

(2) if p(z)\neq 0 , then \beex \bea 0&=\cfrac{p‘(z)}{p(z)}=\sum_{i=1}^n\cfrac{1}{z-a_i} =\sum_{i=1}^n\cfrac{\bar z-\bar a_i}{|z-a_i|^2},\\ z\sum_{i=1}^n \cfrac{1}{|z-a_i|^2} &=\sum_{i=1}^n \cfrac{1}{|z-a_i|^2}a_i,\\ z&=\sum_{i=1}^n \cfrac{\cfrac{1}{|z-a_i|^2}}{\sum_{j=1}^n \cfrac{1}{|z-a_j|^2}}a_i. \eea \eeex Inductively, we have also that the zeros of higher derivatives of p(z) are all in the convex hull of \sed{a_i}_{i=1}^n .

 

 

 

4. Let D\subset \bbR^3 be open domain. Show that every smooth field {\bf F}=(P,Q,R) over D can be written as {\bf F}={\bf F}_1+{\bf F}_2 such that \bex \rot {\bf F}_1={\bf 0},\quad \Div {\bf F}_2=0, \eex where \bex \rot {\bf F}=\sex{\frac{\p R}{\p y}-\frac{\p Q}{\p z},\frac{\p P}{\p z}-\frac{\p R}{\p x},\frac{\p Q}{\p x}-\frac{\p P}{\p y}},\quad \Div {\bf F}=\frac{\p P}{\p x}+\frac{\p Q}{\p y}+\frac{\p R}{\p z}. \eex

 

Solution: The following Poisson equation \bex \sedd{\ba{ll} \lap u=\Div {\bf F},&\mbox{in }D\\ u=0,&\mbox{on }\p D \ea} \eex has a unique solution u . Setting \bex {\bf F_1}=\n u,\quad {\bf F_2}={\bf F}-{\bf F_1}. \eex Then \rot {\bf F_1}={\bf0} , \Div {\bf F_2}=\Div {\bf F}-\Div{\bf F_1}=\Div{\bf F}-\lap u=0 .

 

 

 

5. Let \scrH be a Hilbert space and A a compact self-adjoint linear operator over \scrH . Show that there exists an ortho-normal basis of \scrH consisting of eigenvectors \varphi_n of A with non-zero eigenvalues \lm_n such that every vector \xi\in \scrH can be written as: \bex \xi=\sum_k c_k\varphi_k+\xi‘, \eex where \xi‘\in \ker A , i.e., A\xi‘=0 . We also have \bex A\xi=\sum_k \lm_kc_k\varphi_k. \eex If there are infinitely many eigenvalues then \dps{\lim_{n\to\infty}\lm_n=0} .

 

Solution: This is the classical result in Functional Analysis.

 

 

 

6. A function f:\bbR\to \bbR is called convex if \bex f(\lm x+(1-\lm)x‘)\leq \lm f(x)+(1-\lm)f(x‘) \eex for 0\leq \lm\leq 1 and each x,x‘\in\bbR , and is called strictly convex if \bex f(\lm x+(1-\lm)x‘)<\lm f(x)+(1-\lm)f(x‘) \eex for 0<\lm<1 . We assume |f(x)|<\infty whenever |x|<\infty .

(1) Show that a convex function f is continuous and the function \bex g(y)=\max_{x\in\bbR} [xy-f(x)] \eex is a well-defined convex function over \bbR .

(2) Show that a convex function f is differentiable except at most countably many points.

(3) f is differentiable everywhere if both f and g are strictly convex.

 

Solution:

(1) Without loss of generality, we need only to prove that f is continuous at 0 . Noticing that \beex \bea &\quad f(x)=f(x\cdot 1+(1-x)\cdot 0)\leq x\cdot f(1)+(1-x)\cdot f(0)\\ &\ra f(x)-f(0)\leq x\cdot [f(1)-f(0)],\\ &\quad f(0)=f\sex{\cfrac{x}{x+1}\cdot (-1)+\cfrac{1}{x+1}\cdot x} \leq \cfrac{x}{x+1}\cdot f(-1)+\cfrac{1}{x+1}\cdot f(x) \\ &\ra f(x)-f(0)\geq x\cdot [f(0)-f(-1)], \eea \eeex we have \bex x\cdot [f(0)-f(-1)]\leq f(x)-f(0)\leq x\cdot [f(1)-f(0)], \eex which implies the continuity of f .

(2) It is easy to see that f is differentiable from left and from right, and the set where f is not differentiable \bex Z=\sed{(f_-‘(a),f_+‘(a));\ f_-‘(a)<f_+‘(a)} \eex is countable (Compare with the set \bbQ ).

(3) Fix y\in\bbR . If there exists an x_0 such that f‘(x_0)=y , then \beex \bea &\quad f(x)-f(x_0)\geq y(x-x_0)\\ &\ra xy-f(x)\leq x_0y-f(x_0). \eea \eeex Otherwise, we would have an x_0 such that \bex f_-‘(x_0)\leq y\leq f_+‘(x_0)\quad (f_-‘(x_0)<f_+‘(x_0)). \eex In this case, \beex \bea x<x_0&\ra \cfrac{f(x)-f(x_0)}{x-x_0}\leq f_-‘(x_0)\leq y\ra xy-f(x)\leq x_0y-f(x_0),\\ x>x_0&\ra \cfrac{f(x)-f(x_0)}{x-x_0}\geq f_-‘(x_0)\leq y\ra xy-f(x)\leq x_0y-f(x_0). \eea \eeex Thus g is well defined and the maximum is achieved at x_0 .

(4) For 0\leq \tt\leq 1 , y<y‘ , \beex \bea &\quad x((1-\tt)y+\tt y‘)-f(x)\\ &=(1-\tt)[xy-f(x)]+\tt[xy‘-f(x)]\\ &\leq (1-\tt)g(y)+\tt g(y‘). \eea \eeex This verifies the convexity of g .

(5) We prove the third statement by contradiction. Suppose that f is strictly convex and and is not differentiable at some x_0 . Then for f_-‘(x_0)<y<f_+‘(x_0) , \bex g(y)=x_0y-f(x_0), \eex which is linear, contradicting to the strict convexity of g

 

来自: 第5卷第276期_丘成桐大学生数学竞赛2013年分析与方程团体赛试题参考解答 [3448--3456]

丘成桐大学生数学竞赛2013年分析与方程团体赛试题参考解答,布布扣,bubuko.com

丘成桐大学生数学竞赛2013年分析与方程团体赛试题参考解答

原文:http://www.cnblogs.com/zhangzujin/p/3597210.html

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