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In this two-part paper, we propose a general algorithmic framework for the minimization of a nonconvex smooth function subject to nonconvex smooth constraints. The algorithm solves a sequence of (separable) strongly convex problems and…

Multiagent Systems · Computer Science 2016-01-18 Gesualdo Scutari , Francisco Facchinei , Lorenzo Lampariello , Peiran Song

Consider an open quantum system governed by a Gorini, Kossakowski, Sudarshan, Lindblad (GKSL) master equation with two times-scales: a fast one, exponentially converging towards a linear subspace of quasi-equilibria; a slow one resulting…

Quantum Physics · Physics 2023-09-08 François-Marie Le Régent , Pierre Rouchon

Let $A$ be a non-negative self-adjoint operator in a Hilbert space $\mathcal{H}$ and $A_{0}$ be some densely defined closed restriction of $A_{0}$, $A_{0}\subseteq A \neq A_{0}$. It is of interest to know whether $A$ is the unique…

Mathematical Physics · Physics 2007-05-23 Vadym Adamyan

Adjoint-based sensitivity analysis methods are powerful tools for engineers who use flow simulations for design. However, the conventional adjoint method breaks down for scale-resolving simulations like large-eddy simulation (LES) or direct…

For a {bounded} non-negative self-adjoint operator acting in a complex, infinite-dimensional, separable Hilbert space H and possessing a dense range R we propose a new approach to characterisation of phenomenon concerning the existence of…

Functional Analysis · Mathematics 2013-12-24 Yury Arlinskii , Valentin Zagrebnov

The non-backtracking operator was recently shown to give a redemption for spectral clustering in sparse graphs. In this paper we consider non-backtracking operator for Ising model on a general graph with a general coupling distribution by…

Disordered Systems and Neural Networks · Physics 2014-09-12 Pan Zhang

As deep learning applications continue to deploy increasingly large artificial neural networks, the associated high energy demands are creating a need for alternative neuromorphic approaches. Optics and photonics are particularly compelling…

Optics · Physics 2025-08-19 Nicola Dal Cin , Florian Marquardt , Clara C. Wanjura

One proves here the backward uniqueness of solutions to stochastic semilinear parabolic equations and also for the tamed Navier-Stokes equations driven by linearly multiplicative Gaussian noises. Applications to approximate controllability…

Probability · Mathematics 2018-06-18 V. Barbu , M. Röckner

We introduce a framework to prove propagation of chaos for interacting particle systems with singular, density-dependent interactions, a classical challenge in mean-field theory. Our approach is to define the dynamics implicitly via a…

Analysis of PDEs · Mathematics 2025-07-22 Qian Qi

Given an overcomplete dictionary $A$ and a signal $b = Ac^*$ for some sparse vector $c^*$ whose nonzero entries correspond to linearly independent columns of $A$, classical sparse signal recovery theory considers the problem of whether…

Machine Learning · Computer Science 2020-01-01 Daniel P. Robinson , Rene Vidal , Chong You

A partially hyperbolic dynamical system is said to have the quasi-shadowing property if every pseudotrajectory can be shadowed by a sequence of points $(x_n)_{n\in \Z}$ such that $x_{n+1}$ is obtained from the image of $x_n$ by moving it by…

Dynamical Systems · Mathematics 2020-10-20 Lucas Backes , Davor Dragicevic

We have developed the {\it general method} for the description of {\it separatrix chaos}, basing on the analysis of the separatrix map dynamics. Matching it with the resonant Hamiltonian analysis, we show that, for a given amplitude of…

Chaotic Dynamics · Physics 2007-11-01 S. M. Soskin , R. Mannella , O. M. Yevtushenko

We study the large time behavior of solutions to fully nonlinear parabolic equations of Hamilton-Jacobi-Bellman type arising typically in stochastic control theory with control both on drift and diffusion coefficients. We prove that, as…

Probability · Mathematics 2014-10-07 Andrea Cosso , Marco Fuhrman , Huyen Pham

The vector space of the multi-indexed sequences over a field and the vector space of the sequences with finite support are dual to each other, with respect to a \textit{scalar product}, which we used to define \textit{orthogonals} in these…

Dynamical Systems · Mathematics 2021-05-12 Ramamonjy Andriamifidisoa , Juanito Andrianjanahary

We present a simplified computational rule for the back-propagation formulas for artificial neural networks. In this work, we provide a generic two-step rule for the back-propagation algorithm in matrix notation. Moreover, this rule…

Neural and Evolutionary Computing · Computer Science 2023-05-17 Ahmed Boughammoura

We provide a simple recipe for obtaining all self-adjoint extensions, together with their resolvent, of the symmetric operator $S$ obtained by restricting the self-adjoint operator $A:\D(A)\subseteq\H\to\H$ to the dense, closed with respect…

Mathematical Physics · Physics 2008-03-28 Andrea Posilicano

The present paper aims at providing a numerical strategy to deal with PDE-constrained optimization problems solved with the adjoint method. It is done through out a unified formulation of the constraint PDE and the adjoint model. The…

Optimization and Control · Mathematics 2017-12-01 Gino I. Montecinos , Juan Lopez-Rios , Jaime H. Ortega , Rodrigo Lecaros

A new version of classical S-procedure in system theory is proposed based on duality in the space of positive definite matrices and introduction of matrix Lagrange multipliers. A new proof and extension of the recent results of T.Iwasaki,…

Optimization and Control · Mathematics 2007-05-23 Alexander L. Fradkov

Convergence is proven for Schwarz-like methods applied to degenerate elliptic-parabolic equations with a $p$-structure. This family of PDEs, e.g., arises when modelling nonlinear diffusion processes. The Schwarz-like approximation methods…

Numerical Analysis · Mathematics 2026-05-07 Monika Eisenmann , Eskil Hansen

By using the Hadamard matrix product concept, this paper introduces two generalized matrix formulation forms of numerical analogue of nonlinear differential operators. The SJT matrix-vector product approach is found to be a simple,…

Computational Engineering, Finance, and Science · Computer Science 2024-09-21 W. Chen