Equality of real and complex Markov-Bernstein constants

From papers

Let hC++n{\boldsymbol{h}} \in {\mathbb C}_{++}^n, and define

M(h)=maxp1, pPhp(),M_{\, \ell}({\boldsymbol{h}}) = \max_{\|p\|_{\infty} \le 1,\ p \in {\cal P}_{{\boldsymbol{h}}}} \bigl\|p^{\,(\ell)}\bigr\|_{\infty},

with

M,n=maxhDnM(h).M_{\, \ell,n}=\max_{{\boldsymbol{h}}\in{\cal D}_n}M_{\,\ell}({\boldsymbol{h}}).

For a real positive vector hIn=(0,1]n{\boldsymbol{h}}\in{\cal I}_n=(0,1]^n, define

m(h)=maxp1, pRPhp(),m_{\,\ell}({\boldsymbol{h}})=\max_{\|p\|_{\infty}\le 1,\ p\in{\cal RP}_{{\boldsymbol{h}}}}\bigl\|p^{\,(\ell)}\bigr\|_{\infty},

with

m,n=maxhInm(h).m_{\,\ell,n}=\max_{{\boldsymbol{h}}\in{\cal I}_n}m_{\,\ell}({\boldsymbol{h}}).

The equality conjecture. For all ,nN\ell,n\in{\mathbb N}, we have

m,n=M,n.m_{\,\ell,n}=M_{\,\ell,n}.

This asserts that allowing complex exponential parameters does not increase the sharp \ell-th derivative Markov-Bernstein constant beyond the value attained by real exponential polynomials. The source presents this as its main conjecture; no resolution is supplied here.

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Sources & referencesView supporting material

Primary source

Vladimir Yu. Protasov, “Generalized Markov-Bernstein inequalities and stability of dynamical systems”, arXiv:2209.12250 (2022).

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