Entrywise transforms preserving matrix positivity and non-positivity

TL;DR

This paper characterizes functions that preserve positive definiteness when applied entrywise to matrices, providing a complete classification for fixed dimensions and extending to structured matrices and monotone maps.

Contribution

It offers a complete classification of entrywise sign preservers for fixed-dimensional matrices, including complex cases and structured matrices, extending classical results.

Findings

Sign preservers are positive scalar multiples of continuous automorphisms for matrices of size ≥3.

In the 2×2 case, sign preservers extend power functions.

Results connect to negativity-preserving transforms and monotone maps.

Abstract

We characterize real and complex functions which, when applied entrywise to square matrices, yield a positive definite matrix if and only if the original matrix is positive definite. We refer to these transformations as sign preservers. Compared to classical work on entrywise preservers of Schoenberg and others, we completely resolve this problem in the harder fixed dimensional setting, extending a similar recent classification of sign preservers obtained for matrices over finite fields. When the matrix dimension is fixed and at least $3$, we show that the sign preservers are precisely the positive scalar multiples of the continuous automorphisms of the underlying field. This is in contrast to the $2 \times 2$ case where the sign preservers are extensions of power functions. These results are built on our classification of $2 \times 2$ entrywise positivity preservers over broader complex domains. Our results yield a complementary connection with a work of Belton, Guillot, Khare, and Putinar (2023) on negativity-preserving transforms. We also extend our sign preserver results to matrices with a structure of zeros, as studied by Guillot, Khare, and Rajaratnam for the entrywise positivity preserver problem. Finally, in the spirit of sign preservers, we address a natural extension to monotone maps, classically studied by Loewner and many others.