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Recently, we have established and used the generalized Littlewood theorem concerning contour integrals of the logarithm of analytical function to obtain a few new criteria equivalent to the Riemann hypothesis. Here, the same theorem is…

General Mathematics · Mathematics 2022-04-28 Sergey K. Sekatskii

A family of partial functions of a class of algebras $\mathsf{K}$ is said to be an implicit operation of $\mathsf{K}$ when it is defined by a first order formula and it is preserved by homomorphisms. In this work, we develop the theory of…

Rings and Algebras · Mathematics 2026-04-24 Luca Carai , Miriam Kurtzhals , Tommaso Moraschini

The Implicit and Inverse Function Theorems are special cases of a general Implicit/Inverse Function Theorem which can be easily derived from either theorem. The theorems can thus be easily deduced from each other via the generalized…

Classical Analysis and ODEs · Mathematics 2015-10-09 Bruce Blackadar

We study estimation of a multivariate function $f:{\bf R}^d \to {\bf R}$ when the observations are available from function $Af$, where $A$ is a known linear operator. Both the Gaussian white noise model and density estimation are studied.…

Statistics Theory · Mathematics 2009-04-21 Jussi Klemelä , Enno Mammen

We prove an implicit function theorem for Keller C^k_c-maps from arbitrary real or complex topological vector spaces to Frechet spaces, imposing only a certain metric estimate on the partial differentials. As a tool, we show the…

Functional Analysis · Mathematics 2007-05-23 Helge Glockner

Given a simplicial complex $K$ and an injective function $f$ from the vertices of $K$ to $\mathbb{R}$, we consider algorithms that extend $f$ to a discrete Morse function on $K$. We show that an algorithm of King, Knudson and Mramor can be…

Computational Geometry · Computer Science 2021-03-26 Benjamin Holmgren , Bradley McCoy , Brittany Fasy , David Millman

Implicit sampling is a weighted sampling method that is used in data assimilation, where one sequentially updates estimates of the state of a stochastic model based on a stream of noisy or incomplete data. Here we describe how to use…

Numerical Analysis · Mathematics 2016-01-20 Matthias Morzfeld , Xuemin Tu , Jon Wilkening , Alexandre J. Chorin

In this work the implicit function theorem is used for searching local symbolic resolution of differential equations. General results of existence for first order equations are proven and some examples, one relative to cavitation in a…

Numerical Analysis · Mathematics 2025-10-20 Gianluca Argentini

The paper studies coincidence points of parameterized set-valued mappings (multifunctions), which provide an extended framework to cover several important topics in variational analysis and optimization that include the existence of…

Optimization and Control · Mathematics 2022-03-23 Aram V. Arutyunov , Boris S. Mordukhovich , Sergey E. Zhukovskiy

Using geometric considerations, we provide a clear derivation of the integral representation for the error function, known as the Craig formula. We calculate the corresponding power series expansion and prove the convergence. The same…

Data Analysis, Statistics and Probability · Physics 2023-06-16 Dmitri Martila , Stefan Groote

It is often useful to perform integration over learned functions represented by neural networks. However, this integration is usually performed numerically, as analytical integration over learned functions (especially neural networks) is…

Machine Learning · Computer Science 2023-12-27 Ryan Kortvelesy

In this paper, we propose a geometric Hamilton-Jacobi theory for systems of implicit differential equations. In particular, we are interested in implicit Hamiltonian systems, described in terms of Lagrangian submanifolds of $TT^*Q$…

Mathematical Physics · Physics 2018-03-14 O. Esen , M. de León , C. Sardón

Numerical integration over the implicitly defined domains is challenging due to topological variances of implicit functions. In this paper, we use interval arithmetic to identify the boundary of the integration domain exactly, thus getting…

Numerical Analysis · Mathematics 2024-12-20 Tianhui Yang , Ammar Qarariyah , Hongmei Kang , Jiansong Deng

Based on the computation of a superset of the implicit support, implicitization of a parametrically given hyper-surface is reduced to computing the nullspace of a numeric matrix. Our approach exploits the sparseness of the given parametric…

Algebraic Geometry · Mathematics 2014-11-12 Ioannis Emiris , Tatjana Kalinka , Christos Konaxis

Measurable cones, with linear and measurable functions as morphisms, are a model of intuitionistic linear logic and of call-by-name probabilistic PCF which accommodates "continuous data types" such as the real line. So far however, they…

Logic in Computer Science · Computer Science 2025-01-15 Thomas Ehrhard , Guillaume Geoffroy

In this text we prove that if X is a reduced non-archimedean analytic space and f is a analytic function on a dense Zariski-open subspace of X whose zero-locus is closed in X, then f is a meromorphic function on X. As a corollary, we deduce…

Algebraic Geometry · Mathematics 2025-07-11 Antoine Ducros

We present first a brief review of the existing literature on shape optimization, stressing the recent use of Hamiltonian systems in topology optimization. In the second section, we collect some preliminaries on the implicit parametrization…

Optimization and Control · Mathematics 2022-11-23 Cornel Marius Murea , Dan Tiba

Given two Morse functions $f, \mu$ on a compact manifold $M$, we study the Morse homology for the Lagrange multiplier function on $M \times {\mathbb R}$ which sends $(x, \eta)$ to $f(x) + \eta \mu(x)$. Take a product metric on $M \times…

Geometric Topology · Mathematics 2014-10-20 Stephen Schecter , Guangbo Xu

In Mathematical Morphology for grey-level functions, an image is analysed by another image named the structuring function. This structuring function is translated over the image domain and summed to the image. However, in an image…

Image and Video Processing · Electrical Eng. & Systems 2025-10-15 Guillaume Noyel

The paper studies several approaches to numerical integration over a domain defined implicitly by an indicator function such as the level set function. The integration methods are based on subdivision, moment--fitting, local…

Numerical Analysis · Mathematics 2016-01-26 Maxim Olshanskii , Danil Safin