保持平行对的矩阵上的线性映射
Linear maps on matrices preserving parallel pairs
AI总结:
该研究刻画了矩阵空间上保持平行对与TEA对的线性映射,明确了一般维数下的映射形式,并完成了2×2矩阵特殊情形的完整分类。
摘要:
对于(实或复)$m\times n$矩阵$A$和$B$,若存在满足$|μ|=1$的标量$μ$(对应TEA情形下$μ=1$)使得$\\|A+ μB\\| = \\|A\\| + \\|B\\|$,则称二者关于谱范数$\\|\cdot\\|$是平行的(分别称为达到三角等式的,简称TEA)。我们研究$m\times n$矩阵上保持平行对(分别为TEA对)的线性映射$T$,即当$A$和$B$平行(分别为TEA)时,$T(A)$和$T(B)$也平行(分别为TEA)。\n 研究表明,当$m,n \ge 2$且$(m,n) \ne (2,2)$时,非零线性映射$T$保持TEA对当且仅当它是线性等距映射的正倍数,即$T$具有如下形式:\n $$(1) \quad A \mapsto γUAV \quad \quad \text{或} \quad \quad (2) \quad A \mapsto γUA^{t} V \quad (\text{该情形下}, m = n),$$ 其中$γ$为正数,$U$和$V$为尺寸适配的酉矩阵(或实正交矩阵)。保持平行对的线性映射则包括具有形式(1)、(2),或如下形式的映射:\n $$ (3) \\ A \mapsto f(A) Z$$\n 其中$f$为线性泛函,$Z$为固定矩阵。\n $(m,n) = (2,2)$的情形更为复杂。存在作用于$2\times 2$矩阵的线性映射,它们保持平行对或TEA对,但不具有上述形式(1)、(2)或(3)。我们借助矩阵群中的精细计算与技巧,给出了这类映射的完整刻画。
英文摘要:
Two (real or complex) $m\times n$ matrices $A$ and $B$ are said to be parallel (resp. triangle equality attaining, or TEA in short) with respect to the spectral norm $\|\cdot\|$ if $\|A+ μB\| = \|A\| + \|B\|$ for some scalar $μ$ with $|μ|=1$ (resp. $μ=1$). We study linear maps $T$ on $m\times n$ matrices preserving parallel (resp. TEA) pairs, i.e., $T(A)$ and $T(B)$ are parallel (resp. TEA) whenever $A$ and $B$ are parallel (resp. TEA). It is shown that when $m,n \ge 2$ and $(m,n) \ne (2,2)$, a nonzero linear map $T$ preserving TEA pairs if and only if it is a positive multiple of a linear isometry, namely, $T$ has the form $$(1) \quad A \mapsto γUAV \quad \quad \text{or} \quad \quad (2) \quad A \mapsto γUA^{t} V \quad (\text{in this case}, m = n),$$ for a positive number $γ$, and unitary (or real orthogonal) matrices $U$ and $V$ of appropriate sizes. Linear maps preserving parallel pairs are those carrying form (1), (2), or the form $$ (3) \ A \mapsto f(A) Z$$ for a linear functional $f$ and a fixed matrix $Z$. The case when $(m,n) = (2,2)$ is more complicated. There are linear maps of $2\times 2$ matrices preserving parallel pairs or TEA pairs neither of the form (1), (2) nor (3) above. Complete characterization of such maps is given with some intricate computation and techniques in matrix groups.
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