Publications related to Discrete stochastic heat equation driven by fractional noise : Feynman-Kac representation and asymptotic behavior

Related publications (29)

The ABCD of topological recursion

Kontsevich and Soibelman reformulated and slightly generalised the topological recursion of [43], seeing it as a quantisation of certain quadratic Lagrangians in T*V for some vector space V. KS topological recursion is a procedure which takes as initial da ...

Academic Press Inc Elsevier Science2024

Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective

Victor Panaretos, Leonardo Vincenzo Santoro, Neda Mohammadi Jouzdani

We consider the problem of nonparametric estimation of the drift and diffusion coefficients of a Stochastic Differential Equation (SDE), based on n independent replicates {Xi(t) : t is an element of [0 , 1]}13 d B(t), where alpha is an element of {0 , 1} a ...

Elsevier2024

Hilbert series, the Higgs mechanism, and HEFT

Brian Quinn Henning

We expand Hilbert series technologies in effective field theory for the inclusion of massive particles, enabling, among other things, the enumeration of operator bases for non-linearly realized gauge theories. We find that the Higgs mechanism is manifest a ...

Springer Nature2023

Symmetry in design and decoding of polar-like codes

Kirill Ivanov

The beginning of 21st century provided us with many answers about how to reach the channel capacity. Polarization and spatial coupling are two techniques for achieving the capacity of binary memoryless symmetric channels under low-complexity decoding algor ...

EPFL2022

Intrinsic area near the origin for self-similar growth-fragmentations and related random surfaces

François Gaston Ged

We study the behaviour of a natural measure defined on the leaves of the genealogical tree of some branching processes, namely self-similar growth-fragmentation processes. Each particle, or cell, is attributed a positive mass that evolves in continuous tim ...

2022

Functional registration and local variations: Identifiability, rank, and tuning

Victor Panaretos, Anirvan Chakraborty

We develop theory and methodology for the problem of nonparametric registration of functional data that have been subjected to random deformation (warping) of their time scale. The separation of this phase variation ("horizontal" variation) from the amplit ...

2021

The probability of intransitivity in dice and close elections

Jan Hazla

We study the phenomenon of intransitivity in models of dice and voting. First, we follow a recent thread of research for n-sided dice with pairwise ordering induced by the probability, relative to 1/2, that a throw from one die is higher than the other. We ...

2020

Entanglement Entropy from Nonequilibrium Work

Jonathan D'Emidio

The Renyi entanglement entropy in quantum many-body systems can be viewed as the difference in free energy between partition functions with different trace topologies. We introduce an external field lambda that controls the partition function topology, all ...

AMER PHYSICAL SOC2020

Functional relations in nineteen-vertex models with domain-wall boundaries

Alexander Huyberechts, Aleksi Antoine Bossart

This work is concerned with functional properties shared by partition functions of nineteen-vertex models with domain-wall boundary conditions. In particular, we describe both Izergin-Korepin and Fateev-Zamolodchikov models with the aforementioned boundary ...

2019

Accelerating path integral evaluation of equilibrium and kinetic isotope effects

Konstantin Karandashev

Investigating the effect of isotope substitution on equilibrium and kinetic properties of molecules has become an important tool for estimating the importance of nuclear quantum effects. In this work, we discuss calculating both equilibrium and kinetic iso ...

EPFL2018

Mirrored Langevin Dynamics

Volkan Cevher, Ya-Ping Hsieh, Ali Kavis, Paul Thierry Yves Rolland

We consider the problem of sampling from constrained distributions, which has posed significant challenges to both non-asymptotic analysis and algorithmic design. We propose a unified framework, which is inspired by the classical mirror descent, to derive ...

2018

Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures

Raphaël Huser, Emeric Rolland Georges Thibaud

Gaussian scale mixtures are constructed as Gaussian processes with a random variance. They have non-Gaussian marginals and can exhibit asymptotic dependence unlike Gaussian processes, which are asymptotically independent except in the case of perfect depen ...

Elsevier Sci Ltd2017

Gaussian versus Sparse Stochastic Processes : Construction, Regularity, Compressibility

Julien René Fageot

Although our work lies in the field of random processes, this thesis was originally motivated by signal processing applications, mainly the stochastic modeling of sparse signals. We develop a mathematical study of the innovation model, under which a signal ...

EPFL2017

Generalized Pickands constants and stationary max-stable processes

Sebastian Engelke

Pickands constants play a crucial role in the asymptotic theory of Gaussian processes. They are commonly defined as the limits of a sequence of expectations involving fractional Brownian motions and, as such, their exact value is often unknown. Recently, D ...

Springer Verlag2017

Optimal solution and asymptotic properties of a stochastic control problem arising in sailboat trajectory optimization

Carlo Ciccarella

We study the optimal strategy for a sailboat to reach an upwind island under the hypothesis that the wind direction fluctuates according to a Brownian motion and the wind speed is constant. The work is motivated by a concrete problem which typically arises ...

EPFL2017

Partition function on spheres: How to use zeta function regularization

Alexander Monin

It is known that not all summation methods are linear and stable. Zeta function regularization is in general nonlinear. However, in some cases formal manipulations with zeta function regularization (assuming linearity of sums) lead to correct results. We c ...

American Physical Society2016

Bayesian uncertainty management in temporal dependence of extremes

Anthony Christopher Davison, Thomas Lugrin

Both marginal and dependence features must be described when modelling the extremes of a stationary time series. There are standard approaches to marginal modelling, but long-and short-range dependence of extremes may both appear. In applications, an assum ...

Springer Verlag2016

SHAPE: Linear-Time Camera Pose Estimation With Quadratic Error-Decay

Martin Vetterli, Adam James Scholefield, Alireza Ghasemi

We propose a novel camera pose estimation or perspective-n-point (PnP) algorithm, based on the idea of consistency regions and half-space intersections. Our algorithm has linear time-complexity and a squared reconstruction error that decreases at least qua ...

Ieee2016

Feynman-Kac representation for the parabolic Anderson model driven by fractional noise

Thomas Mountford, Kamran Kalbasi

We consider the parabolic Anderson model driven by fractional noise: partial derivative/partial derivative t u(t,x) = k Delta u(t,x) + u(t,x)partial derivative/partial derivative t W(t,x) x is an element of Z(d), t >= 0, where k > 0 is a diffusion constant ...

Academic Press Inc Elsevier Science2015

A Unified Formulation of Gaussian Versus Sparse Stochastic Processes-Part II: Discrete-Domain Theory

Michaël Unser, Pouya Dehghani Tafti, Hagay Kirshner, Arash Amini

This paper is devoted to the characterization of an extended family of continuous-time autoregressive moving average (CARMA) processes that are solutions of stochastic differential equations driven by white Levy innovations. These are completely specified ...

Ieee-Inst Electrical Electronics Engineers Inc2014