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Related papers: Series expansion for a stochastic sandpile

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The gradient expansion of the kinetic energy functional, when applied for atoms or finite systems, usually grossly overestimates the energy in the fourth order and generally diverges in the sixth order. We avoid the divergence of the…

Quantum Physics · Physics 2015-08-28 A. Sergeev , R. Jovanovic , S. Kais , F. H. Alharbi

Stochastic processes are often represented through orthonormal series expansions, a framework originating in the classical works of Lo\`eve and Karhunen and widely used for simulation and numerical approximation. While truncation error in…

Statistics Theory · Mathematics 2026-03-30 Oleksandr Mokliachuk

We summarize our recent determination [1] of the spectral density of the Wilson operator in the p-regime of Wilson chiral perturbation theory. We discuss the range of validity of our formula and a possible extension to our computation in…

High Energy Physics - Lattice · Physics 2011-08-10 S. Necco , A. Shindler

Fixed-point equations with Lipschitz operators have been studied for more than a century, and are central to problems in mathematical optimization, game theory, economics, and dynamical systems, among others. When the Lipschitz constant of…

Optimization and Control · Mathematics 2025-11-12 Jelena Diakonikolas

Almost every numerical task can be cast as extrapolation with respect to the fidelity or tolerance parameters of a consistent numerical method. This perspective enables probabilistic uncertainty quantification and optimal experimental…

Methodology · Statistics 2026-04-03 Chris. J. Oates , Richard Howey , Toni Karvonen

System identification based on Koopman operator theory has grown in popularity recently. Spectral properties of the Koopman operator of a system were proven to relate to properties like invariant sets, stability, periodicity, etc. of the…

Optimization and Control · Mathematics 2021-10-27 Nibodh Boddupalli

We formulate an "action principle" for the operator product expansion (OPE) describing how a given OPE coefficient changes under a deformation induced by a marginal or relevant operator. Our action principle involves no ad-hoc regulator or…

High Energy Physics - Theory · Physics 2018-03-14 Stefan Hollands

We analyze the properties of a class of improved lattice topological charge density operators, constructed by a smearing-like procedure. By optimizing the choice of the parameters introduced in their definition, we find operators having (i)…

High Energy Physics - Lattice · Physics 2009-10-28 C. Christou , A. Di Giacomo , H. Panagopoulos , E. Vicari

To model recurrent interaction events in continuous time, an extension of the stochastic block model is proposed where every individual belongs to a latent group and interactions between two individuals follow a conditional inhomogeneous…

Methodology · Statistics 2023-08-30 Catherine Matias , Tabea Rebafka , Fanny Villers

Polynomial Chaos Expansions represent a powerful tool to simulate stochastic models of dynamical systems. Yet, deriving the expansion's coefficients for complex systems might require a significant and non-trivial manipulation of the model,…

Computation · Statistics 2012-11-13 Lorenzo Fagiano , Mustafa Khammash

We present an algorithm for constructing the Wilson operator product expansion (OPE) for perturbative interacting quantum field theory in general Lorentzian curved spacetimes, to arbitrary orders in perturbation theory. The remainder in…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Stefan Hollands

We construct generally applicable small-loss rate expansions for the density operator of an open system. Successive terms of those expansions yield characteristic loss rates for dissipation processes. Three applications are presented in…

Quantum Physics · Physics 2009-11-06 X. X. Yi , C. Li , J. C. Su

Building surrogate models with uncertainty quantification capabilities is essential for many engineering applications where randomness, such as variability in material properties, is unavoidable. Polynomial Chaos Expansion (PCE) is widely…

Computational Engineering, Finance, and Science · Computer Science 2025-11-04 Bahador Bahmani , Ioannis G. Kevrekidis , Michael D. Shields

In this paper, models that approximate stochastic processes from the space $Sub_\varphi(\Omega)$ with given reliability and accuracy in $L_p(T)$ are considered for some specific functions $\varphi(t)$. For processes that are decomposited in…

Statistics Theory · Mathematics 2025-03-25 Oleksandr Mokliachuk

We consider a Schroedinger operator with random potential distributed according to a Poisson process. We show that expectations of matrix elements of the resolvent as well as the density of states can be approximated to arbitrary precision…

Mathematical Physics · Physics 2023-02-13 David Hasler , Jannis Koberstein

The time-ordered product framework of quantum field theory can also be used to understand salient phenomena in stochastic biochemical networks. It is used here to derive Gillespie's Stochastic Simulation Algorithm (SSA) for chemical…

Quantitative Methods · Quantitative Biology 2015-06-11 Eric Mjolsness

In this thesis an iterative scheme for the construction of operator product expansion (OPE) coefficients is applied to determine low order coefficients in perturbation theory for a specific toy model. We use the approach to quantum field…

Mathematical Physics · Physics 2009-07-01 Jan Holland

A method for the construction of approximate analytical expressions for the stationary marginal densities of general stochastic search processes is proposed. By the marginal densities, regions of the search space that with high probability…

Artificial Intelligence · Computer Science 2008-01-30 Arturo Berrones

Given an initial distribution of sand in an Abelian sandpile, what final state does it relax to after all possible avalanches have taken place? In d >= 3, we show that this problem is P-complete, so that explicit simulation of the system is…

Condensed Matter · Physics 2015-06-25 Cristopher Moore , Martin Nilsson

We consider a class of linear integral operators with impulse responses varying regularly in time or space. These operators appear in a large number of applications ranging from signal/image processing to biology. Evaluating their action on…

Numerical Analysis · Mathematics 2016-04-18 Paul Escande , Pierre Weiss