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Mathematics

arXiv preprints from January 1, 2026 through July 20, 2026 — 08:48:05 EST

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Posted in math.GT · 2026-01-11 · Sergey A. Antonyan, Aura Lucina Kantún-Montiel, Jesús Eduardo Mata-Cano, Armando Mata-Romero

Characterizations of $G$-ANR spaces and inverse limits

In this paper we prove that, for a compact group $G$, a metrizable $G$-space is a $G$-ANR under the following asumptions: (1) if it dominates a $G$-ANR space through a fine $G$-homotopy equivalence; (2) if it is $G$-homotopy dense in a $G$-ANR; (3) if it contains a $G$-ANR as a $G$-homotopy dense subset; (4) if it is the inverse limit...

💬 0 commentsarXiv:2601.07027v1PDF
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Posted in math.AG · 2026-01-11 · Montserrat Teixidor I Bigas

Higher order Petri Loci

Denote by ${\mathcal P}_{g,d}^{r,k}$ the subset of the moduli space of curves of genus g consisting of those curves that have a linear series of degree d and dimension r for which the Petri map has kernel of dimension at least k. We show the existence of codimension k components of ${\mathcal P}_{g,d}^{r,k}$.

💬 0 commentsarXiv:2601.07026v1PDF
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Posted in math.NA · 2026-01-11 · Emine Celik, Eric Olson

A Relaxed Direct-insertion Downscaling Method For Discrete-in-time Data Assimilation

This paper improves the spectrally-filtered direct-insertion downscaling method for discrete-in-time data assimilation by introducing a relaxation parameter that overcomes a constraint on the observation frequency. Numerical simulations demonstrate that taking the relaxation parameter proportional to the time between observations...

💬 0 commentsarXiv:2601.07025v1PDF
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Posted in math.NA · 2026-01-11 · Andreas Langer

The Ill-Posed Foundations of Physics-Informed Neural Networks and Their Finite-Difference Variants

Physics-informed neural networks based on automatic differentiation (AD-PINNs) and their finite-difference counterparts (FD-PINNs) are widely used for solving partial differential equations (PDEs), yet their analytical properties remain poorly understood. This work provides a unified mathematical foundation for both formulations....

💬 0 commentsarXiv:2601.07017v1PDF
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Posted in math.CO · 2026-01-10 · Anshul Raj Singh

On a square packing conjecture of Erdős

Let $f(n)$ be the maximum sum of the sides of non-overlapping squares (or equilateral triangles) packed inside a unit square or (unit equilateral triangle). In this paper, we explore some properties of $f$ and examine how the square and triangle cases are similar. We prove that a conjecture of Erdős, which says that $f(k^2+1) = k$ for...

💬 0 commentsarXiv:2601.22163v1PDF
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Posted in math.OC · 2026-01-10 · Abhinav Raghuvanshi, Mayank Baranwal, Debasish Chatterjee

On a Gradient Approach to Chebyshev Center Problems with Applications to Function Learning

We introduce $\textsf{gradOL}$, the first gradient-based optimization framework for solving Chebyshev center problems, a fundamental challenge in optimal function learning and geometric optimization. $\textsf{gradOL}$ hinges on reformulating the semi-infinite problem as a finitary max-min optimization, making it amenable to...

💬 0 commentsarXiv:2601.06434v1PDF
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Posted in math.DG · 2026-01-10 · Juan Miguel Ruiz, Areli Vázquez Juárez

Isoperimetric estimates in the product of small and large volume manifolds

Let $(M^m,g)$, $(N^n,h)$ be closed Riemannian manifolds, $m,n\geq 2$, with concave isoperimetric profiles and volumes $V_M$, $V_N$ respectively. We consider a one parameter family of product manifolds of the same volume, $(X,G_λ)=(M^m\times N^n,λ^{2n}g+ λ^{-2m}h)$, $λ>0$, and estimate a lower bound for their isoperimetric profile for...

💬 0 commentsarXiv:2601.06421v1PDF
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Posted in math.AP · 2026-01-10 · Linfang Liu, Vando Narciso, Zhijian Yang

Dynamics for a viscoelastic beam equation with past history and nonlocal boundary dissipation

This article aims to study the long-time dynamics of the linear viscoelastic plate equation $\displaystyle{u_{tt}+Δ^2 u-\int_τ^tg(t-s)Δ^2u(s)ds=0}$ subject to nonlinear and nonlocal boundary conditions. This model, with $τ=0$, was first considered by Cavalcanti (Discrete Contin. Dyn. Syst., 8(3), 675-695, 2002), where results of...

💬 0 commentsarXiv:2601.06414v1PDF
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Posted in math.NA · 2026-01-10 · Ren-Cang Li, Ding Lu, Li Wang, Lei-Hong Zhang

An NPDo Approach for Principal Joint Block Diagonalization

Matrix joint block-diagonalization (JBD) frequently arises from diverse applications such as independent component analysis, blind source separation, and common principal component analysis (CPCA), among others. Particularly, CPCA aims at joint diagonalization, i.e., each block size being $1$-by-$1$. This paper is concerned with {\em...

💬 0 commentsarXiv:2601.06410v1PDF
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Posted in math.PR · 2026-01-10 · Xinru Liu, Danyu Yang

Integration of branched rough paths

When the one-form is $Lip\left(γ-1\right) $ with $γ>p\geq 1$, we construct the integral of a branched $p$-rough path, which defines another branched $p$-rough path. We derive a quantitative bound for this integral and prove that it depends continuously on the driving branched rough path in rough path metric. Moreover, we prove that...

💬 0 commentsarXiv:2601.06399v1PDF
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Posted in math.NA · 2026-01-10 · Zakaria Baba, Alexandre M. Bayen, Alexi Canesse, Maria Laura Delle Monache, Martin Drieux, Zhe Fu, Nathan Lichtlé, Zihe Liu, Hossein Nick Zinat Matin, Benedetto Piccoli

Supervised and Unsupervised Neural Network Solver for First Order Hyperbolic Nonlinear PDEs

We present a neural network-based method for learning scalar hyperbolic conservation laws. Our method replaces the traditional numerical flux in finite volume schemes with a trainable neural network while preserving the conservative structure of the scheme. The model can be trained both in a supervised setting with efficiently...

💬 0 commentsarXiv:2601.06388v1PDF
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Posted in math.PR · 2026-01-10 · Hélène Guérin, Nathalie Krell

Well-posedness of state-dependent rank-based interacting systems

We study the existence and uniqueness of rank-based interacting systems of stochastic differential equations. These systems can be seen as modifications with state-dependent coefficients of the Atlas model in mathematical finance. The coefficients of the underlying SDEs are possibly discontinuous. We first establish strong...

💬 0 commentsarXiv:2601.06383v1PDF
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Posted in math.HO · 2026-01-10 · Daniel Duarte

Crónica de un contraejemplo

In the 1960s, John Nash proposed a method to resolve singularities. Five decades of encouraging results could not prevent an unexpected ending: the method does not work in general. In this note (written in Spanish), we tell the story of the rise and fall of the Nash blowup.

💬 0 commentsarXiv:2601.06379v1PDF
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Posted in math.AG · 2026-01-10 · Giuliano Gagliardi, Johannes Hofscheier, Heath Pearson

Toricness and smoothness criteria for spherical varieties

We prove equivalent numerical conditions for a complete spherical variety to admit a toric structure, and for the smoothness of an arbitrary spherical variety along any given G-orbit. The conditions are in terms of spherical skeletons, a coarse ''subset'' of the Luna-Vust data of a spherical variety. Our smoothness criterion improves...

💬 0 commentsarXiv:2601.06376v1PDF
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Posted in math.CO · 2026-01-10 · Nikolai Parvatov

Uniform hypergraphs of girth $6$ and $8$ from generalized polygons

Let $ex_r(N,g)$ be the maximum number of edges in an $r$-uni\-form hypergraph on $N$ vertices with girth at least $g$. We are interested in the asymptotic behavior of this value when $N$ is increasing but parameters $g\in\{6,8\}$ and $r\geq3$ are fixed. It is shown that for some positive constants $c$ and $d$, any integer $r\geq3$ and...

💬 0 commentsarXiv:2601.06374v1PDF
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Posted in math.OC · 2026-01-10 · Corentin Juvigny, Antonín Novák, Jan Mandík, Zdeněk Hanzálek

Resource-constrained Project Scheduling with Time-of-Use Energy Tariffs and Machine States: A Logic-based Benders Decomposition Approach

In this paper, we investigate the Resource-Constrained Project Scheduling Problem (RCPSP) with Time-of-Use (TOU) energy tariffs and machine states, a variant of RCPSP for production scheduling, where energy price is part of the criteria and one highly energy-demanding machine can be in one of the following three states: proc, idle, or...

💬 0 commentsarXiv:2601.06542v2PDF
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Posted in math.PR · 2026-01-10 · Kazimierz Musial

Splitting of Liftings in Product Spaces II

Let $(X, \mfA,P)$ and $(Y, \mfB,Q)$ be two probability spaces, $R$ be their skew product on the product $σ$-algebra $\mfA\otimes\mfB$ and $\{(\mfA_y,S_y)\colon y\in{Y}\}$ be a $Q$-disintegration of $R$. Then let $\mfA\dd\mfB$ be the $σ$-algebra generated $\mfA\otimes\mfB$ and by the family $\mcM:=\{E\subset{X\times{Y}}\colon...

💬 0 commentsarXiv:2601.06538v2PDF
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Posted in math.CA · 2026-01-10 · Trinh Viet Duoc, Nguyen Van Trong

Exponential dichotomy and $(L^p,L^q)$-admissibility

We consider the notion of an exponential dichotomy with respect to a family of norms for an evolutionary family in a Banach space, and we characterize it by the admissibility of the pair $(L^p,L^q)$ for $p,q \in [1,\infty]$ with $p\ge q$. We then use this characterization to establish the robustness of an exponentially dichotomic...

💬 0 commentsarXiv:2601.06534v1PDF
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Posted in math.NT · 2026-01-10 · Pierre Dèbes

Hurwitz spaces and Inverse Galois Theory

Hurwitz spaces which parametrize branched covers of the line play a prominent role in inverse Galois theory. This paper surveys fifty years of works in this direction with emphasis on recent advances. Based on the Riemann-Hurwitz theory of covers, the geometric and arithmetic setup is first reviewed, followed by the semi-modern...

💬 0 commentsarXiv:2601.06532v2PDF
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Posted in math.DG · 2026-01-10 · Claudio Afeltra

Geometric structures arising from the deformation of groups of Heisenberg type

Motivated by the desire of finding a geometric interpretation to the Yamabe equation on groups of Heisenberg type, we define a geometric structure on manifolds modelled locally on these groups, which we call contact structure of Heisenberg type. In the case of the Heisenberg group is equivalent to contact Riemannian manifolds. We...

💬 0 commentsarXiv:2601.06526v1PDF
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Posted in math.AP · 2026-01-10 · Xin Liu, Marita Thomas, Edriss S. Titi

Plastic limit of a viscoplastic Burgers equation -- A toy model for sea-ice dynamics

We study the plastic Burgers equation in one space dimension, i.e., the Burgers equation featuring an additional term formally given by the p-Laplacian with p=1, or rather, by the multivalued subdifferential of the total variation functional. Our study highlights that the interplay of the advection term with the stresses given by the...

💬 0 commentsarXiv:2601.06489v1PDF
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Posted in math.AC · 2026-01-10 · Alessandro De Stefani, Linquan Ma, Matteo Varbaro

Herzog ideals and $F$-singularities

In this paper we study the connection between Herzog ideals (i.e., ideals with a squarefree Gröbner degeneration) and $F$-singularities. More precisely, we show that, in positive characteristic, homogeneous Herzog ideals define $F$-anti-nilpotent rings, and we inquire, in characteristic 0, on a surprising relationship between being...

💬 0 commentsarXiv:2601.06476v1PDF
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Posted in math-ph · 2026-01-10 · F. H. Haydarov, B. A. Omirov, U. A. Rozikov

Non-Linear Generalization of the DLR Equations: $q$-Specifications and $q$-Equilibrium Measures

We introduce a {\it non-linear} generalization of the classical Dobrushin-Lanford-Ruelle (DLR) framework by developing the concept of a $q$-specification and the associated $q$-equilibrium measures. These objects arise naturally from a family of non-linear $q$-stochastic operators acting on the space of probability measures. A...

💬 0 commentsarXiv:2601.06470v1PDF
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Posted in math.NT · 2026-01-10 · Kevin Calderon, Nikita Kalinin

Weighted error-sum identities for periodic continued fractions and their generalizations

For a purely $N$-periodic continued fraction $ξ=[\overline{a_0,a_1,\dots,a_{N-1}}]=[a_0,a_1,\cdots]$, with $a_k=a_{k+N}$ for all $k\ge 0$, and convergents $h_n/k_n=[a_0,a_1,\dots,a_n]$, we obtain explicit expressions for the weighted error sums $f_ξ(s)=\sum a_{n+1}\lvert h_n-ξk_n\rvert^s$ for $s>1$. A key observation is that, for each...

💬 0 commentsarXiv:2601.07862v1PDF