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Gaussian processes (GPs) are commonly used for prediction and inference for spatial data analyses. However, since estimation and prediction tasks have cubic time and quadratic memory complexity in number of locations, GPs are difficult to…

Methodology · Statistics 2024-06-05 Mohamed A. Abba , Brian J. Reich , Reetam Majumder , Brandon Feng

Let u = {u(t, x), t $\in$ [0, T ], x $\in$ R d } be the solution to the linear stochastic heat equation driven by a fractional noise in time with correlated spatial structure. We study various path properties of the process u with respect…

Probability · Mathematics 2015-01-28 Ciprian A. Tudor , Yimin Xiao

By applying a genetic algorithm in a cascade approach of increasing accuracy, we calculate the composition and structure of MgMOx clusters at realistic temperatures and oxygen pressures. The stable and metastable systems are identified by…

The conformational states of a semiflexible polymer enclosed in a compact domain of typical size $a$ are studied as stochastic realizations of paths defined by the Frenet equations under the assumption that stochastic "curvature" satisfies…

Soft Condensed Matter · Physics 2019-07-17 Pavel Castro-Villarreal , J. E. Ramírez

We report results of molecular-dynamics simulations of a model polymer melt consisting of short non-entangled chains in the supercooled state above the critical temperature of mode-coupling theory (MCT). To analyse the dynamics of the…

Soft Condensed Matter · Physics 2007-05-23 M. Aichele , J. Baschnagel

We present a nonlinear (in the sense of McKean) generalization of Hamiltonian Monte Carlo (HMC) termed nonlinear HMC (nHMC) capable of sampling from nonlinear probability measures of mean-field type. When the underlying confinement…

Probability · Mathematics 2023-09-22 Nawaf Bou-Rabee , Katharina Schuh

We investigate the influence of an infinite dimensional Gaussian noise on the bubbling phenomenon for the stochastic harmonic map flow $u(t,\cdot ):\mathbb{D}^2\to\mathbb{S}^2$, from the two-dimensional unit disc onto the sphere. The…

Probability · Mathematics 2018-11-09 Antoine Hocquet

We review our joint work on the scaling limits of disordered systems, linking the notion of disorder relevance/irrelevance to that of sub/super-criticality of singular SPDEs. This line of research culminated in the construction of the…

Probability · Mathematics 2026-01-27 Francesco Caravenna , Rongfeng Sun , Nikos Zygouras

We consider the stable directed polymer in Poisson random environment in dimension 1+1, under the intermediate disorder regime. We show that, under a diffusive scaling involving different parameters of the system, the normalized…

Probability · Mathematics 2024-01-10 Min Wang

Monte Carlo sampling of the canonical distribution presents a formidable challenge when the potential energy landscape is characterized by a large number of local minima separated by high barriers. The principal observation of this work is…

Statistical Mechanics · Physics 2022-05-03 Matthew Grasinger

The collective behaviour, in respect of stochastic resonance, has been studied in globally coupled oscillators (with fractional-order intrinsic and external damping), driven by a sinusoidal force which is either noise-free or…

Statistical Mechanics · Physics 2021-03-02 Vishwamittar

Given the significance of physical measures in understanding the complexity of dynamical systems as well as the noisy nature of real-world systems, investigating the stability of physical measures under noise perturbations is undoubtedly a…

Dynamical Systems · Mathematics 2025-06-24 Weiwei Qi , Zhongwei Shen , Yingfei Yi

We prove that the stochastic heat flow Caravenna Sun Zygouras (2023), Tsai (2024) is a black noise in the sense of Tsirelson (2004). As a corollary, the 2d stochastic heat equation driven by a mollified spacetime white noise becomes…

Probability · Mathematics 2025-07-16 Yu Gu , Li-Cheng Tsai

We study the stochastic heat flow with constant initial data and analyze its spatial average on the scale of $\varepsilon\ll1$. We prove that the logarithm of the averaged process satisfies a pointwise central limit theorem: After being…

Probability · Mathematics 2026-03-04 Yu Gu , Li-Cheng Tsai

In this paper, we discuss an extension of the Split Hamiltonian Monte Carlo (Split HMC) method for Gaussian process model (GPM). This method is based on splitting the Hamiltonian in a way that allows much of the movement around the state…

Computation · Statistics 2012-07-17 Shiwei Lan , Babak Shahbaba

Hamiltonian Monte Carlo (HMC) has become routinely used for sampling from posterior distributions. Its extension Riemann manifold HMC (RMHMC) modifies the proposal kernel through distortion of local distances by a Riemannian metric. The…

Computation · Statistics 2017-02-21 Akihiko Nishimura , David Dunson

We consider the stochastic heat equation which includes a fractional power of the Laplacian of order $\alpha \in (1, 2]$ and it is driven by a nonlinear space-time Gaussian white noise. We study two types of power variations for the…

Probability · Mathematics 2025-04-28 Christian Olivera , C. Tudor

The frequency-dependent mean free paths (MFPs) of vibrational heat carriers in amorphous silicon are predicted from the length dependence of the spectrally decomposed heat current (SDHC) obtained from non-equilibrium molecular dynamics…

Computational Physics · Physics 2016-05-31 K. Sääskilahti , J. Oksanen , J. Tulkki , A. J. H. McGaughey , S. Volz

We consider a general class of SPDEs in $\mathbb{R}^d$ driven by a Gaussian spatially homogeneous noise which is white in time. We provide sufficient conditions on the coefficients and the spectral measure associated to the noise ensuring…

Probability · Mathematics 2012-06-18 Lluis Quer-Sardanyons

We consider the evolution of a quantum simple harmonic oscillator in a general Gaussian state under simultaneous time-continuous weak position and momentum measurements. We deduce the stochastic evolution equations for position and momentum…

Quantum Physics · Physics 2022-03-16 Tathagata Karmakar , Philippe Lewalle , Andrew N. Jordan
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