Matrix and tensor rigidity and $L_p$-approximation (2010.14801v2)
Abstract: In this paper we apply methods originated in Complexity theory to some problems of Approximation. We notice that the construction of Alman and Williams that disproves the rigidity of Walsh-Hadamard matrices, provides good $\ell_p$-approximation for $p<2$. It follows that the first $n$ functions of Walsh system can be approximated with an error $n{-\delta}$ by a linear space of dimension $n{1-\delta}$: $$ d_{n{1-\delta}}({w_1,\ldots,w_n}, L_p[0,1]) \le n{-\delta},\quad p\in[1,2),\;\delta=\delta(p)>0. $$ We do not know if this is possible for the trigonometric system. We show that the algebraic method of Alon--Frankl--R\"odl for bounding the number of low-signum-rank matrices, works for tensors: almost all signum-tensors have large signum-rank and can't be $\ell_1$-approximated by low-rank tensors. This implies lower bounds for $\Theta_m$~ -- the error of $m$-term approximation of multivariate functions by sums of tensor products $u1(x_1)\cdots ud(x_d)$. In particular, for the set of trigonometric polynomials with spectrum in $\prod_{j=1}d[-n_j,n_j]$ and of norm $|t|\infty\le 1$ we have $$ \Theta_m(\mathcal T(n_1,\ldots,n_d)\infty,L_1[-\pi,\pi]d) \ge c_1(d)>0,\quad m\le c_2(d)\frac{\prod n_j}{\max{n_j}}. $$ Sharp bounds follow for classes of dominated mixed smoothness: $$ \Theta_m(W{(r,r,\ldots,r)}_p,L_q[0,1]d)\asymp m{-\frac{rd}{d-1}},\quad\mbox 2\le p\le\infty,\; 1\le q\le 2. $$