arXiv subjects

Martin Hairer

Publications and source records attributed to Martin Hairer.

At least 37 records · Page 2Linked to original sources

arXiv2024

Renormalisation in the presence of variance blowup

We show that if one drives the KPZ equation by the derivative of a space-time white noise smoothened out at scale $\varepsilon \ll 1$ and multiplied by $\varepsilon^{3/4}$ then, as $\varepsilon \to 0$, solutions converge to the Cole-Hopf solutions to the KPZ equation driven by space-time white noise. In the same vein, we also show that if one drives an SDE by fractional Brownian motion with Hurst parameter $H < 1/4$, smoothened out at scale $\varepsilon \ll 1$ and multiplied by $\varepsilon^{1/4-H}$ then, as $\varepsilon \to 0$, solutions converge to an SDE driven by white noise. The mechanism giving rise to both results is the same, but the proof techniques differ substantially.

math.PR↗

arXiv2024

Periodic space-time homogenisation of the $ϕ^4_2$ equation

We consider the homogenisation problem for the $ϕ^4_2$ equation on the torus $\mathbb{T}^2$, namely the behaviour as $\varepsilon \to 0$ of the solutions to the equation suggestively written as $$ \partial_t u_\varepsilon - \nabla\cdot {A}(x/\varepsilon,t/\varepsilon^2) \nabla u_\varepsilon = -u^3_\varepsilon +ξ$$ where $ξ$ denotes space-time white noise and $A: \mathbb{T}^2\times \mathbb{R}$ is uniformly elliptic, periodic and Hölder continuous. When the noise is regularised at scale $δ\ll 1$ we show that any joint limit $\varepsilon,δ\to 0$ recovers the classical dynamical $ϕ^4_2$ model. In certain regimes or if the regularisation is chosen in a specific way adapted to the problem, we show that the counterterms can be chosen as explicit local functions of $A$.

math.AP↗

arXiv2024

Lower bounds on the top Lyapunov exponent for linear PDEs driven by the 2D stochastic Navier-Stokes equations

We consider the top Lyapunov exponent associated to the advection-diffusion and linearised Navier-Stokes equations on the two-dimensional torus. The velocity field is given by the stochastic Navier-Stokes equations driven by a non-degenerate white-in-time noise with a power-law correlation structure. We show that the top Lyapunov exponent is bounded from below by a negative power of the diffusion parameter. This partially answers a conjecture of Doering and Miles and provides a first lower bound on the Batchelor scale in terms of the diffusivity. The proof relies on a robust analysis of the projective process associated to the linear equation, through its spectral median dynamics. We introduce a probabilistic argument to show that high-frequency states for the projective process are unstable under stochastic perturbations, leading to a Lyapunov drift condition and quantitative-in-diffusivity estimates.

math.PR↗

arXiv2024

Scaling limit of the KPZ equation with non-integrable spatial correlations

We study the large scale fluctuations of the KPZ equation in dimensions $d \geq 3$ driven by Gaussian noise that is white in time Gaussian but features non-integrable spatial correlation with decay rate $κ\in (2, d)$ and a suitable limiting profile. We show that its scaling limit is described by the corresponding additive stochastic heat equation. In contrast to the case of compactly supported covariance, the noise in the stochastic heat equation retains spatial correlation with covariance $|x|^{-κ}$. Surprisingly, the noise driving the limiting equation turns out to be the scaling limit of the noise driving the KPZ equation so that, under a suitable coupling, one has convergence in probability, unlike in the case of integrable correlations where fluctuations are enhanced in the limit and convergence is necessarily weak.

math.PR↗

arXiv2024

Stochastic quantisation of Yang-Mills-Higgs in 3D

We define a state space and a Markov process associated to the stochastic quantisation equation of Yang-Mills-Higgs (YMH) theories. The state space $\mathcal{S}$ is a nonlinear metric space of distributions, elements of which can be used as initial conditions for the (deterministic and stochastic) YMH flow with good continuity properties. Using gauge covariance of the deterministic YMH flow, we extend gauge equivalence $\sim$ to $\mathcal{S}$ and thus define a quotient space of "gauge orbits" $\mathfrak{O}$. We use the theory of regularity structures to prove local in time solutions to the renormalised stochastic YMH flow. Moreover, by leveraging symmetry arguments in the small noise limit, we show that there is a unique choice of renormalisation counterterms such that these solutions are gauge covariant in law. This allows us to define a canonical Markov process on $\mathfrak{O}$ (up to a potential finite time blow-up) associated to the stochastic YMH flow.

math.PR↗

arXiv2024

Discretisation of regularity structures

We introduce a general framework allowing to apply the theory of regularity structures to discretisations of stochastic PDEs. The approach pursued in this article is that we do not focus on any one specific discretisation procedure. Instead, we assume that we are given a scale $\varepsilon > 0$ and a "black box" describing the behaviour of our discretised objects at scales below $\varepsilon $.

math.PR↗

arXiv2024

A scaling limit of the 2D parabolic Anderson model with exclusion interaction

We consider the (discrete) parabolic Anderson model $\partial u(t,x)/\partial t=Δu(t,x) +ξ_t(x) u(t,x)$, $t\geq 0$, $x\in \mathbb{Z}^d$. Here, the $ξ$-field is $\mathbb{R}$-valued, acting as a dynamic random environment, and $Δ$ represents the discrete Laplacian. We focus on the case where $ξ$ is given by a rescaled symmetric simple exclusion process which converges to an Ornstein--Uhlenbeck process. By scaling the Laplacian diffusively and considering the equation on a torus, we demonstrate that in dimension $d=2$, when a suitably renormalized version of the above equation is considered, the sequence of solutions converges in law. This resolves an open problem from~\cite{EH23}, where a similar result was shown in the three-dimensional case. The novel contribution in the present work is the establishment of a gradient bound on the transition probability of a fixed but arbitrary number of labelled exclusion particles.

math.PR↗

arXiv2024

A Dynamical Yukawa$_{2}$ Model

We prove local (in space and time) well-posedness for a mildly regularised version of the stochastic quantisation of the Yukawa$_{2}$ Euclidean field theory with a self-interacting boson. Our regularised dynamic is still singular but avoids non-local divergences, allowing us to use a version of the Da Prato--Debussche argument. This model is a test case for a non-commutative probability framework for formulating the kind of singular SPDEs arising in the stochastic quantisation of field theories mixing both bosons and fermions.

math.PR↗

arXiv2023

The BPHZ Theorem for Regularity Structures via the Spectral Gap Inequality

We provide a relatively compact proof of the BPHZ theorem for regularity structures of decorated trees in the case where the driving noise satisfies a suitable spectral gap property, as in the Gaussian case. This is inspired by the recent work [LOTT21] in the multi-index setting, but our proof relies crucially on a novel version of the reconstruction theorem for a space of "pointed Besov modelled distributions". As a consequence, the analytical core of the proof is quite short and self-contained, which should make it easier to adapt the proof to different contexts (such as the setting of discrete models).

math.PR↗

arXiv2023

Spectral gap for projective processes of linear SPDEs

This work studies the angular component $ π_{t} = u_{t} / \| u_{t} \| $ associated to the solution $ u $ of a vector-valued linear hyperviscous SPDE on a $d$-dimensional torus $$\mathrm{d} u^α =- ν^α (- Δ)^{\mathbf{a} } u^α \mathrm{d} t + (u \cdot \mathrm{d} W)^α \;,\quad α\in \{ 1, \dots, m \} $$ for $ u \colon \mathbb{T}^{d} \to \mathbb{R}^{m} $, $ \mathbf{a} \geqslant 1 $ and a sufficiently smooth and non-degenerate noise $ W $. We provide conditions for existence, as well as uniqueness and spectral gaps (if $ \mathbf{a} > d/2$) of invariant measures for $ π$ in the projective space. Our proof relies on the introduction of a novel Lyapunov functional for $π_{t}$, based on the study of dynamics of the ``energy median'': the energy level $M$ at which projections of $u$ onto frequencies with energies less or more than $M$ have about equal $L^2$ norm. This technique is applied to obtain -- in an infinite-dimensional setting without order preservation -- lower bounds on top Lyapunov exponents of the equation, and their uniqueness via Furstenberg-Khasminskii formulas.

math.PR↗

arXiv2023

Regularity Structures on Manifolds and Vector Bundles

We develop a generalisation of the original theory of regularity structures, [Hai14], which is able to treat SPDEs on manifolds with values in vector bundles. Assume $M$ is a Riemannian manifold and $E\to M$ and $F^i\to M$ are vector bundles (with a metric and connection), this theory allows to solve subcritical equations of the form $$ \partial_t u + \mathcal{L}u = \sum_{i=0}^m G_i(u, \nabla u,\ldots, \nabla^n u)ξ_i\ , $$ where $u$ is a (generalised) section of $E$, $\mathcal{L}$ is a uniformly elliptic operator on $E$ of order strictly greater than $n$, the $ξ_i$ are $F^i$-valued random distributions (e.g. $F^i$-valued white noises), and the $G_i:E\times TM^*\otimes E \times\ldots\times (TM^*)^{\otimes n} \otimes E \to L(F^i ,E)$ are local functions. We apply our framework to three example equations which illustrate that when $\mathcal{L}$ is a Laplacian it is possible in most cases to renormalise such equations by adding spatially homogeneous counterterms and we discuss in which cases more sophisticated renormalisation procedures (involving the curvature of the underlying manifold) are required.

math.PR↗

arXiv2023

The Brownian Web as a random $\mathbb R$-tree

Motivated by [G. Cannizzaro, M. Hairer, Comm. Pure Applied Math., '22], we provide a construction of the Brownian Web (see [Tóth B., Werner W., Probab. Theory Related Fields, '98] and [L. R. G. Fontes, M. Isopi, C. M. Newman, and K. Ravishankar, Ann. Probab., '04]), i.e. a family of coalescing Brownian motions starting from every point in $\mathbb R^2$, as a random variable taking values in the space of (spatial) $\mathbb R$-trees. This gives a stronger topology than the classical one {(i.e.\ Hausdorff convergence on closed sets of paths)}, thus providing us with more continuous functions of the Brownian Web and ruling out a number of potential pathological behaviours. Along the way, we introduce a modification of the topology of spatial $\mathbb R$-trees in [T. Duquesne, J.-F. Le Gall, Probab. Theory Related Fields, '05] and [M. T. Barlow, D. A. Croydon, T. Kumagai, Ann. Probab. '17] which makes it a complete separable metric space and could be of independent interest. We determine some properties of the characterisation of the Brownian Web in this context (e.g.\ its box-counting dimension) and recover some which were determined in earlier works, such as duality, special points and convergence of the graphical representation of coalescing random walks.

math.PR↗

arXiv2023

An Introduction to Stochastic PDEs

These notes are based on a series of lectures given first at the University of Warwick in spring 2008 and then at the Courant Institute, Imperial College London, and EPFL. It is an attempt to give a reasonably self-contained presentation of the basic theory of stochastic partial differential equations, taking for granted basic measure theory, functional analysis and probability theory, but nothing else. The approach taken in these notes is to focus on semilinear parabolic problems driven by additive noise. These can be treated as stochastic evolution equations in some infinite-dimensional Banach or Hilbert space that usually have nice regularising properties and they already form a very rich class of problems with many interesting properties. Furthermore, this class of problems has the advantage of allowing to completely pass under silence many subtle problems arising from stochastic integration in infinite-dimensional spaces.

math.PR↗

arXiv2023

Directed mean curvature flow in noisy environment

We consider the directed mean curvature flow on the plane in a weak Gaussian random environment. We prove that, when started from a sufficiently flat initial condition, a rescaled and recentred solution converges to the Cole-Hopf solution of the KPZ equation. This result follows from the analysis of a more general system of nonlinear SPDEs driven by inhomogeneous noises, using the theory of regularity structures. However, due to inhomogeneity of the noise, the "black box" result developed in the series of works [Hai14, BHZ19, CH16, BCCH21] cannot be applied directly and requires significant extension to infinite-dimensional regularity structures. Analysis of this general system of SPDEs gives two more interesting results. First, we prove that the solution of the quenched KPZ equation with a very strong force also converges to the Cole-Hopf solution of the KPZ equation. Second, we show that a properly rescaled and renormalised quenched Edwards-Wilkinson model in any dimension converges to the stochastic heat equation.

math.PR↗

arXiv2023

Global existence for perturbations of the 2D stochastic Navier-Stokes equations with space-time white noise

We prove global in time well-posedness for perturbations of the 2D stochastic Navier-Stokes equations \begin{equation*} \partial_t u + u \cdot \nabla u = Δu - \nabla p + ζ+ ξ \;, \quad u (0, \cdot) = u_{0}(\cdot) \;, \quad \mathrm{div} (u) = 0 \;, \end{equation*} driven by additive space-time white noise $ ξ$, with perturbation $ ζ$ in the Hölder-Besov space $\mathcal{C}^{-2 + 3κ} $, periodic boundary conditions and initial condition $ u_{0} \in \mathcal{C}^{-1 + κ} $ for any $ κ>0 $. The proof relies on an energy estimate which in turn builds on a dynamic high-low frequency decomposition and tools from paracontrolled calculus. Our argument uses that the solution to the linear equation is a $ \log$-correlated field, yielding a double exponential growth bound on the solution. Notably, our method does not rely on any explicit knowledge of the invariant measure to the SPDE, hence the perturbation $ ζ$ is not restricted to the Cameron-Martin space of the noise, and the initial condition may be anticipative. Finally, we introduce a notion of weak solution that leads to well-posedness for all initial data $u_{0}$ in $ L^{2} $, the critical space of initial conditions.

math.PR↗

arXiv2022

The $Φ_3^4$ measure has sub-Gaussian tails

We provide a very simple argument showing that the $Φ^4_3$ measure does have quartic exponential tails, as expected from its formal expression. This shows that the corresponding moment problem is well-posed and provides a simple path to observing non-Gaussianity of the measure.

math.PR↗

arXiv2022

Generating diffusions with fractional Brownian motion

We study fast / slow systems driven by a fractional Brownian motion $B$ with Hurst parameter $H\in (\frac 13, 1]$. Surprisingly, the slow dynamic converges on suitable timescales to a limiting Markov process and we describe its generator. More precisely, if $Y^\varepsilon$ denotes a Markov process with sufficiently good mixing properties evolving on a fast timescale $\varepsilon \ll 1$, the solutions of the equation $$ dX^\varepsilon = \varepsilon^{\frac 12-H} F(X^\varepsilon,Y^\varepsilon)\,dB+F_0(X^\varepsilon,Y^\varepsilon)\,dt\; $$ converge to a regular diffusion without having to assume that $F$ averages to $0$, provided that $H< \frac 12$. For $H > \frac 12$, a similar result holds, but this time it does require $F$ to average to $0$. We also prove that the $n$-point motions converge to those of a Kunita type SDE. One nice interpretation of this result is that it provides a continuous interpolation between the homogenisation theorem for random ODEs with rapidly oscillating right-hand sides ($H=1$) and the averaging of diffusion processes ($H= \frac 12$).

math.PR↗

arXiv2022

The work of Hugo Duminil-Copin

The past decade has seen tremendous progress in our understanding of the behaviour of many probabilistic models at or near their "critical point". On the 5th of July 2022, Hugo Duminil-Copin was awarded the Fields medal for the crucial role he played in many of these developments. In this short review article, we will try to put his work into context and present a small selection of his results.

math.PR↗