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20102026
most citedAlgebraic arctic curves in the domain-wall six-vertex model

16 citations · 48 across the 45 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

math.NA2024

Efficient computation of \lowercase{}-centralities and nonbacktracking centrality for temporal networks

Vanni Noferini, Spyridon Vrontos, Ryan Wood

We discuss efficient computation of -centralities and nonbacktracking centralities for time-evolving networks with nonnegative weights. We present a node-level formula for its c…

math.GR2024

Smith forms of matrices in Companion Rings, with group theoretic and topological applications

Vanni Noferini, Gerald Williams

Let be a commutative ring and a monic polynomial. The commutative ring of polynomials in the companion matrix of , where , is…

math.NA2024

Para-Hermitian rational matrices

Froilán Dopico, Vanni Noferini, María C. Quintana +1

In this paper we study para-Hermitian rational matrices and the associated structured rational eigenvalue problem (REP). Para-Hermitian rational matrices are square rational matric…

math.NA2024

Riemann-Oracle: A general-purpose Riemannian optimizer to solve nearness problems in matrix theory

Miryam Gnazzo, Vanni Noferini, Lauri Nyman +1

We propose an extremely versatile approach to address a large family of matrix nearness problems, possibly with additional linear constraints. Our method is based on splitting a ma…

math.RA2024

Rosenbrock's Theorem on System Matrices over Elementary Divisor Domains

Froilán Dopico, Vanni Noferini, Ion Zaballa

Rosenbrock's theorem on polynomial system matrices is a classical result in linear systems theory that relates the Smith-McMillan form of a rational matrix with the Smith forms…

cs.SI2024

Efficient computation of Katz centrality for very dense networks via negative parameter Katz

Vanni Noferini, Ryan Wood

Katz centrality (and its limiting case, eigenvector centrality) is a frequently used tool to measure the importance of a node in a network, and to rank the nodes accordingly. One r…