单位雅可比矩阵解析映射的参数化与反演

T. Sadykov
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引用次数: 0

摘要

设$x=(x_1,\ldots,x_n)\in{\rm\bf C}^n$是复变量的向量,用$a=(a_{jk}我们研究了映射族$$f=(f_1,\ldots,f_n):{\rm\bf C}^n\rightarrow{\rm \bf C}^n,\quad f[A,\varphi](x):=x+\varphi_{jk}x_k\右),\quad j=1,\ldots,n$$,其Jacobian与任何$x$的非零常数相同,使得所有$f_j$都是明确定义的。设$U$是一个平方矩阵,使得映射$f[U,\varphi](x)$的雅可比矩阵对于任何$x$以及对于任何分析函数$\varphi\in\mathcal{O}(\Omega)都是非零常数。$我们证明了任何这样的矩阵$U$都是唯一定义的,直到矩阵的适当置换相似性,通过将维数$n$划分为$m$正整数的和以及$m$元素上的置换。对于任何$d=2,3,\ldots$,我们构造了$n$-平方矩阵的参数族$H(s),s\in{\rm\bf C}^n$,使得对于上面的任何矩阵$U$,由Hadamard乘积$U\odot H(s。我们证明了任何这样的映射是多项式可逆的,并为其逆提供了一个显式递归公式。
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Parameterizing and Inverting Analytic Mappings with Unit Jacobian
Let $x=(x_1,\ldots,x_n)\in {\rm \bf C}^n$ be a vector of complex variables, denote by $A=(a_{jk})$ a square matrix of size $n\geq 2,$ and let $\varphi\in\mathcal{O}(\Omega)$ be an analytic function defined in a nonempty domain $\Omega\subset {\rm \bf C}.$ We investigate the family of mappings $$ f=(f_1,\ldots,f_n):{\rm \bf C}^n\rightarrow {\rm \bf C}^n, \quad f[A,\varphi](x):=x+\varphi(Ax) $$ with the coordinates $$ f_j : x \mapsto x_j + \varphi\left(\sum\limits_{k=1}^n a_{jk}x_k\right), \quad j=1,\ldots,n $$ whose Jacobian is identically equal to a nonzero constant for any $x$ such that all of $f_j$ are well-defined. Let $U$ be a square matrix such that the Jacobian of the mapping $f[U,\varphi](x)$ is a nonzero constant for any $x$ and moreover for any analytic function $\varphi\in\mathcal{O}(\Omega).$ We show that any such matrix $U$ is uniquely defined, up to a suitable permutation similarity of matrices, by a partition of the dimension $n$ into a sum of $m$ positive integers together with a permutation on $m$ elements. For any $d=2,3,\ldots$ we construct $n$-parametric family of square matrices $H(s), s\in {\rm \bf C}^n$ such that for any matrix $U$ as above the mapping $x+\left((U\odot H(s))x\right)^d$ defined by the Hadamard product $U\odot H(s)$ has unit Jacobian. We prove any such mapping to be polynomially invertible and provide an explicit recursive formula for its inverse.
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