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This article is concerned with a data-driven divide-and-conquer strategy to construct symbolic abstractions for interconnected control networks with unknown mathematical models. We employ a notion of alternating bisimulation functions (ABF)…

Systems and Control · Electrical Eng. & Systems 2023-09-15 Abolfazl Lavaei

We give a formal treatment of simple type theories, such as the simply-typed $\lambda$-calculus, using the framework of abstract clones. Abstract clones traditionally describe first-order structures, but by equipping them with additional…

Logic in Computer Science · Computer Science 2024-04-03 Nathanael Arkor , Dylan McDermott

Using tools provided by the theory of abstract convexity, we extend conditions for zero duality gap to the context of nonconvex and nonsmooth optimization. Mimicking the classical setting, an abstract convex function is the upper envelope…

Functional Analysis · Mathematics 2020-09-15 Hoa T. Bui , Regina S. Burachik , Alexander Y. Kruger , David T. Yost

Semidefinite programs (SDPs) are a framework for exact or approximate optimization that have widespread application in quantum information theory. We introduce a new method for using reductions to construct integrality gaps for SDPs. These…

Quantum Physics · Physics 2019-03-18 Aram W. Harrow , Anand Natarajan , Xiaodi Wu

In this paper, we propose a compositional approach for the construction of finite abstractions (a.k.a. finite Markov decision processes (MDPs)) for networks of discrete-time stochastic control subsystems that are not necessarily…

Systems and Control · Electrical Eng. & Systems 2020-02-12 Abolfazl Lavaei , Sadegh Soudjani , Majid Zamani

Mixed-dimensional partial differential equations (PDEs) are characterized by coupled operators defined on domains of varying dimensions and pose significant computational challenges due to their inherent ill-conditioning. Moreover, the…

Numerical Analysis · Mathematics 2025-05-14 Nunzio Dimola , Nicola Rares Franco , Paolo Zunino

We derive parameter-robust quasi-optimal error estimates for mixed finite element methods for the nonlinear Darcy--Forchheimer equations with mixed boundary conditions. Using the framework of operator preconditioning, we also design…

Numerical Analysis · Mathematics 2026-02-25 Rishi Das , Harsha Hutridurga , Amiya K. Pani , Ricardo Ruiz-Baier

We develop Algebraic Phase Theory (APT), an axiomatic framework for extracting intrinsic algebraic structure from phase based analytic data. From minimal admissible phase input we prove a general phase extraction theorem that yields…

Rings and Algebras · Mathematics 2026-02-18 Joe Gildea

In this paper, the algebraic Bethe ansatz with periodic boundary conditions is used to investigate trigonometric vertex models associated with the fundamental representations of the non-exceptional Lie algebras. This formulation allow us to…

Exactly Solvable and Integrable Systems · Physics 2011-02-16 A. Lima-Santos

We present quasi-diagonal preconditioners for piecewise polynomial discretizations of pseudodifferential operators of order minus two in any space dimension. Here, quasi-diagonal means diagonal up to a sparse transformation. Considering…

Numerical Analysis · Mathematics 2018-06-22 Thomas Führer , Norbert Heuer

Abstract argumentation frameworks (AFs) provide a formal setting to analyze many forms of reasoning with conflicting information. While the expressiveness of general infinite AFs make them a tempting tool for modeling many kinds of…

Artificial Intelligence · Computer Science 2025-08-26 Uri Andrews , Luca San Mauro

This work presents a tensorial approach to constructing data-driven reduced-order models corresponding to semi-discrete partial differential equations with canonical Hamiltonian structure. By expressing parameter-varying operators with…

Numerical Analysis · Mathematics 2025-05-14 Arjun Vijaywargiya , Shane A. McQuarrie , Anthony Gruber

We show that neural networks with activations satisfying a Riccati-type ordinary differential equation condition, an assumption arising in recent universal approximation results in the uniform topology, produce Pfaffian outputs on analytic…

Machine Learning · Computer Science 2026-03-04 Bahman Gharesifard

This article deals with the computation of guaranteed lower bounds of the error in the framework of finite element (FE) and domain decomposition (DD) methods. In addition to a fully parallel computation, the proposed lower bounds separate…

Numerical Analysis · Mathematics 2016-06-22 Valentine Rey , Pierre Gosselet , Christian Rey

Results on approximate deduction in the context of the calculus of evidence of Dempster-Shafer and the theory of interval probabilities are reported. Approximate conditional knowledge about the truth of conditional propositions was assumed…

Artificial Intelligence · Computer Science 2013-04-12 Enrique H. Ruspini

A new domain decomposition preconditioner is introduced for efficiently solving linear systems Ax = b with a symmetric positive definite matrix A. The particularity of the new preconditioner is that it is not necessary to have access to the…

Numerical Analysis · Mathematics 2021-06-23 Nicole Spillane

Eigenvalue problems for semidefinite operators with infinite dimensional kernels appear for instance in electromagnetics. Variational discretizations with edge elements have long been analyzed in terms of a discrete compactness property. As…

Numerical Analysis · Mathematics 2013-06-24 Snorre Harald Christiansen , Ragnar Winther

A system of polynomial ordinary differential equations (ODEs) is specified via a vector of multivariate polynomials, or vector field, $F$. A safety assertion $\psi\rightarrow[F]\phi$ means that the trajectory of the system will lie in a…

Logic in Computer Science · Computer Science 2020-03-31 Michele Boreale

A generalisation of the notion of a Rota-Baxter operator is proposed. This generalisation consists of two operators acting on an associative algebra and satisfying equations similar to the Rota-Baxter equation. Rota-Baxter operators of any…

Quantum Algebra · Mathematics 2015-03-18 Tomasz Brzeziński

Abstract Dialectical Frameworks (ADFs) are argumentation frameworks where each node is associated with an acceptance condition. This allows us to model different types of dependencies as supports and attacks. Previous studies provided a…

Artificial Intelligence · Computer Science 2019-07-24 João Alcântara , Samy Sá , Juan Acosta-Guadarrama
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