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Related papers: A variational method for $\Phi^4_3$

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A new method called "variational sampling" is proposed to estimate integrals under probability distributions that can be evaluated up to a normalizing constant. The key idea is to fit the target distribution with an exponential family model…

Computation · Statistics 2013-10-15 Alexis Roche

Variational methods are employed in situations where exact Bayesian inference becomes intractable due to the difficulty in performing certain integrals. Typically, variational methods postulate a tractable posterior and formulate a lower…

Machine Learning · Statistics 2019-06-12 Nikolaos Gianniotis , Christoph Schnörr , Christian Molkenthin , Sanjay Singh Bora

We consider a parabolic optimal control problem with an initial measure control. The cost functional consists of a tracking term corresponding to the observation of the state at final time. Instead of a regularization term in the cost…

Optimization and Control · Mathematics 2020-08-18 Evelyn Herberg , Michael Hinze

We construct the $\Phi^4_3$ measure on a periodic three dimensional box as an absolutely continuous perturbation of a random shift of the Gaussian free field. The shifted measure is constructed via Girsanov's theorem and the relevant…

Probability · Mathematics 2020-05-21 Nikolay Barashkov , Massimiliano Gubinelli

The usual renormalization procedure for the variational approximation with a trial Gaussian ansatz for the $\lap$ model in 3+1 dimensions is re-analysed as a departing framework for the investigation of the parameters of the model. The…

High Energy Physics - Phenomenology · Physics 2015-07-03 Fabio L. Braghin

We study the $O(4)$-symmetric $ \Phi^4 $-theory in the scaling region of the broken phase using the standard and a Symanzik improved action with infinite bare self-coupling $\lambda$. A high precision Monte Carlo simulation is performed by…

High Energy Physics - Lattice · Physics 2009-10-22 Meinulf Göckeler , Hans A. Kastrup , Thomas Neuhaus , Frank Zimmermann

The main goal of this paper is the study of two kinds of nonlinear problems depending on parameters in unbounded domains. Using a nonstandard variational approach, we first prove the existence of bounded solutions for nonlinear eigenvalue…

Analysis of PDEs · Mathematics 2016-04-04 Said El Manouni , Hichem Hajaiej , Patrick Winkert

In this paper we study a perturbative approach to the problem of quantization of measures in the plane. Motivated by the fact that, as the number of points tends to infinity, hexagonal lattices are asymptotically optimal from an energetic…

Analysis of PDEs · Mathematics 2018-09-18 Emanuele Caglioti , François Golse , Mikaela Iacobelli

We study optimal design problems involving variational inequalities with unilateral conditions in the domain and pointwise boundary observation. We use regularizing and penalization tehniques in the setting of the Hamiltonian approach to…

Optimization and Control · Mathematics 2025-12-30 Cornel Marius Murea , Dan Tiba

We show that the minimization problem of any non-convex and non-lower semi-continuous function on a compact convex subset of a locally convex real topological vector space can be studied via an associated convex and lower semi-continuous…

Functional Analysis · Mathematics 2016-10-12 J. -B. Bru , W. de Siqueira Pedra

In this short note, we prove that conformal classes which are small perturbations of a product conformal class on a product with a standard sphere admit a metric extremal for some Laplace eigenvalue. As part of the arguments we obtain…

Differential Geometry · Mathematics 2019-09-09 Henrik Matthiesen

The Laplace eigenvalue problem on circular sectors has eigenfunctions with corner singularities. Standard methods may produce suboptimal approximation results. To address this issue, a novel numerical algorithm that enhances standard…

Numerical Analysis · Mathematics 2025-05-16 Thomas Apel , Philipp Zilk

This work introduces the minimax Laplace transform method, a modification of the cumulant-based matrix Laplace transform method developed in "User-friendly tail bounds for sums of random matrices" (arXiv:1004.4389v6) that yields both upper…

Probability · Mathematics 2011-07-22 Alex Gittens , Joel A. Tropp

Let $p$ be an odd prime, and suppose $f$ is an $L^2$-normalised newform for $\Gamma_0(p^n)$ with bounded spectral parameters and trivial central character. We prove the optimal $L^4$-norm bound $\lVert f \rVert_4…

Number Theory · Mathematics 2026-02-24 Marius Fischer

For a given wave function one can define a quantity $\mu_E$ having a meaning of its inverse spatial size. The Laplace transform of the distribution function $P(\mu_E)$ is calculated analytically for a 1D disordered sample with a finite…

Condensed Matter · Physics 2015-06-25 I. V. Kolokolov

Matrix concentration inequalities provide a direct way to bound the typical spectral norm of a random matrix. The methods for establishing these results often parallel classical arguments, such as the Laplace transform method. This work…

Information Theory · Computer Science 2014-04-29 Joel A. Tropp , Richard Y. Chen

We consider a simply supported plate with constant thickness, defined on an unknown multiply connected domain. We optimize its shape according to some given performance functional. Our method is of fixed domain type, easy to be implemented,…

Optimization and Control · Mathematics 2019-09-13 Dan Tiba , Cornel Marius Murea

In this paper we study the mixed virtual element approximation to an elliptic optimal control problem with boundary observations. The objective functional of this type of optimal control problem contains the outward normal derivatives of…

Numerical Analysis · Mathematics 2023-12-19 Minghui Yang , Zhaojie Zhou

The maximum (or minimum) generalized eigenvalue of symmetric positive semidefinite matrices that depend on optimization variables often appears as objective or constraint functions in structural topology optimization when we consider…

Optimization and Control · Mathematics 2024-05-09 Akatsuki Nishioka , Yoshihiro Kanno

An estimation method is proposed for a wide variety of discrete time stochastic processes that have an intractable likelihood function but are otherwise conveniently specified by an integral transform such as the characteristic function,…

Statistics Theory · Mathematics 2009-09-29 T. Merkouris