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Related papers: Rough Interfaces Beyond the Gaussian Approximation

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An analytically tractable model for Gaussian multiuser channels with fading is studied, and the capacity region of this model is found to be a good approximation of the capacity region of the original Gaussian network. This work extends the…

Information Theory · Computer Science 2009-05-16 Rony EL Haddad , Brian Smith , Sriram Vishwanath

We calculate non-Gaussianities in the bispectrum and trispectrum arising from the cubic term in the local expansion of the scalar curvature perturbation. We compute to three-loop order and for general momenta. A procedure for evaluating the…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-28 Joseph Bramante , Jason Kumar

The limitations of three-dimensional semi-classical gravity are explored in the context of a conformally invariant theory for a self-interacting scalar field. The analysis of the theory's scaling behaviour reveals that scalar-loop effects…

General Relativity and Quantum Cosmology · Physics 2009-10-31 George Tsoupros

We provide a new approach to approximate emulation of large computer experiments. By focusing expressly on desirable properties of the predictive equations, we derive a family of local sequential design schemes that dynamically define the…

Methodology · Statistics 2014-10-13 Robert B. Gramacy , Daniel W. Apley

The aim of this work is to investigate gravity-capillary waves resonantly excited by two topographic obstacles in a shallow water channel. By considering the weakly nonlinear regime the forced fifth-order Korteweg-de Vries equation arises…

Fluid Dynamics · Physics 2021-03-09 Marcelo V. Flamarion , Roberto Ribeiro-Jr

The evolution of an initially prepared distribution of micron sized colloidal particles, trapped at a fluid interface and under the action of their mutual capillary attraction, is analyzed by using Brownian dynamics simulations. At a…

Soft Condensed Matter · Physics 2011-11-29 J. Bleibel , A. Dominguez , M. Oettel , S. Dietrich

In this paper we provide explicit upper bounds on some distances between the (law of the) output of a random Gaussian NN and (the law of) a random Gaussian vector. Our results concern both shallow random Gaussian neural networks with…

Laplace approximation is a very useful tool in Bayesian inference and it claims a nearly Gaussian behavior of the posterior. \cite{SpLaplace2022} established some rather accurate finite sample results about the quality of Laplace…

Statistics Theory · Mathematics 2023-05-17 Vladimir Spokoiny

We present a high precision Monte Carlo study of various universal amplitude ratios of the three dimensional Ising spin model. Using state of the art simulation techniques we studied the model close to criticality in both phases. Great care…

High Energy Physics - Lattice · Physics 2008-11-26 M. Caselle , M. Hasenbusch

We characterize the fundamental limits of transmission of information over a Gaussian multiple access channel (MAC) with the use of variable-length feedback codes and under a non-vanishing error probability formalism. We develop new…

Information Theory · Computer Science 2018-01-10 Lan V. Truong , Vincent Y. F. Tan

We investigate non-linear scaling relations for two-dimensional gravitational collapse in an expanding background using a 2D TreePM code and study the strongly non-linear regime ($\bar\xi \leq 200$) for power law models. Evolution of these…

Astrophysics · Physics 2007-05-23 S. Ray , J. S. Bagla , T. Padmanabhan

We report large-scale simulations of the three-dimensional Edwards-Anderson Ising spin glass system using the recently introduced multi-overlap Monte Carlo algorithm. In this approach the temperature is fixed and two replica are coupled…

Disordered Systems and Neural Networks · Physics 2017-09-27 Wolfhard Janke , Bernd A. Berg , Alain Billoire

We study the 3D Edwards-Anderson model with binary interactions by Monte Carlo simulations. Direct evidence of finite-size scaling is provided, and the universal finite-size scaling functions are determined. Using an iterative extrapolation…

Disordered Systems and Neural Networks · Physics 2007-05-23 Matteo Palassini , Sergio Caracciolo

This work presents Direct Numerical Simulations of capillary wave turbulence solving the full 3D Navier Stokes equations of a two-phase flow. When the interface is locally forced at large scales, a statistical stationary state appears after…

Fluid Dynamics · Physics 2014-07-21 Luc Deike , Daniel Fuster , Michaël Berhanu , Eric Falcon

The underwater acoustic channel is characterized by a path loss that depends not only on the transmission distance, but also on the signal frequency. As a consequence, transmission bandwidth depends on the transmission distance, a feature…

Information Theory · Computer Science 2016-11-17 Daniel E. Lucani , Milica Stojanovic , Muriel Médard

Effect of interfacial disturbances on instabilities of buoyant/thermocapillary convective flows in rectangular cavities is studied in a series of numerical experiments. The computations are carried out for several two-liquid two-layer…

Fluid Dynamics · Physics 2022-04-19 Alexander Gelfgat

For a SU(N) Yang-Mills theory, we present variational calculations using gaussian wave functionals combined with an approximate projection on gauge invariant states. The projection amounts to correcting the energy of the gaussian states by…

High Energy Physics - Phenomenology · Physics 2009-10-31 C. Heinemann , E. Iancu , C. Martin , D. Vautherin

The effect of viscosity on the wave resistance experienced by a 2d perturbation moving at uniform velocity over the free surface of a fluid is investigated. The analysis is based on Rayleigh's linearized theory of capillary-gravity waves.…

Soft Condensed Matter · Physics 2009-10-31 Denis Richard , Elie Raphael

We propose an adaptive importance sampling scheme for Gaussian approximations of intractable posteriors. Optimization-based approximations like variational inference can be too inaccurate while existing Monte Carlo methods can be too slow.…

Computation · Statistics 2025-02-04 Willem van den Boom , Andrea Cremaschi , Alexandre H. Thiery

Monte Carlo methods have become increasingly relevant for control of non-differentiable systems, approximate dynamics models and learning from data. These methods scale to high-dimensional spaces and are effective at the non-convex…

Machine Learning · Computer Science 2022-10-10 Joe Watson , Jan Peters