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Clustering of large-scale structure provides significant cosmological information through the power spectrum of density perturbations. Additional information can be gained from higher-order statistics like the bispectrum, especially to…

Cosmology and Nongalactic Astrophysics · Physics 2015-03-09 Marcel Schmittfull , Tobias Baldauf , Uroš Seljak

Stochastic Structural Stability Theory (SSST) provides an autonomous, deterministic, nonlinear dynamical system for evolving the statistical mean state of a turbulent system. In this work SSST is applied to the problem of understanding the…

Fluid Dynamics · Physics 2014-12-30 Brian F. Farrell , Petros J. Ioannou

Gravitationally collapsed objects are known to be biased tracers of an underlying density contrast. Using symmetry arguments, generalised biasing schemes have recently been developed to relate the halo density contrast $\delta_h$ with the…

Cosmology and Nongalactic Astrophysics · Physics 2018-02-14 Dipak Munshi

We introduce the Gaussian transform (GT), an optimal transport inspired iterative method for denoising and enhancing latent structures in datasets. Under the hood, GT generates a new distance function (GT distance) on a given dataset by…

Machine Learning · Computer Science 2020-06-23 Kun Jin , Facundo Mémoli , Zhengchao Wan

This paper presents a method for estimating significant wave height (Hs) from sparse S_pectral P_oint using a T_ransformer-based approach (SPT). Based on empirical observations that only a minority of spectral points with strong power…

Signal Processing · Electrical Eng. & Systems 2026-01-09 Yi Zhou , Li Wang , Hang Su , Tian Wang

We investigate the relation between the regularized multi-propagator method, called "Reg PT", and the standard perturbation theory. Reg PT is one of the most successful models to describe nonlinear evolution of dark matter fluctuations.…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-15 Naonori S. Sugiyama , Toshifumi Futamase

The abundance of large and heterogeneous systems is rendering contemporary data more pervasive, intricate, and with a non-regular structure. With classical techniques facing troubles to deal with the irregular (non-Euclidean) domain where…

Signal Processing · Electrical Eng. & Systems 2023-12-25 Samuel Rey

The expansion of global electricity distribution systems necessitates the deployment of massive infrastructure. Assessing its implications from a spatial and material perspective requires an understanding of the core drivers of a…

Physics and Society · Physics 2026-02-17 Emile Emery , Joseph Le Bihan , José Halloy

We develop a new approach to Vlasov Perturbation Theory (VPT) that solves for the hierarchy of cumulants of the phase-space distribution function to arbitrarily high truncation order in the context of cosmological structure formation driven…

Cosmology and Nongalactic Astrophysics · Physics 2025-03-03 Mathias Garny , Roman Scoccimarro

Distribution grids refer to the part of the power grid that delivers electricity from substations to the loads. Structurally a distribution grid is operated in one of several radial/tree-like topologies that are derived from an original…

Optimization and Control · Mathematics 2016-03-08 Deepjyoti Deka , Scott Backhaus , Michael Chertkov

Recently a number of analytic prescriptions for computing the non-linear matter power spectrum have appeared in the literature. These typically involve resummation or closure prescriptions which do not have a rigorous error control, thus…

Cosmology and Nongalactic Astrophysics · Physics 2009-11-06 Jordan Carlson , Martin White , Nikhil Padmanabhan

We apply high-order many-body perturbation theory for the calculation of ground-state energies of closed-shell nuclei using realistic nuclear interactions. Using a simple recursive formulation, we compute the perturbative energy…

Nuclear Theory · Physics 2010-02-03 Robert Roth , Joachim Langhammer

Approximations to the exact solutions for gravitational instability in the expanding Universe are extremely useful for understanding the evolution of large--scale structure. We report on a series of tests of Newtonian Lagrangian…

Astrophysics · Physics 2007-05-23 T. Buchert , A. L. Melott , A. G. Weiss

We apply the BRST approach, previously developed for higher spin field theories, to gauge invariant Lagrangian construction for antisymmetric massive and massless bosonic fields in arbitrary d-dimensional curved space. The obtained theories…

High Energy Physics - Theory · Physics 2009-03-31 I. L. Buchbinder , V. A. Krykhtin , L. L. Ryskina

We propose a sparse grids based adaptive noise reduction strategy for electrostatic particle-in-cell (PIC) simulations. Our approach is based on the key idea of relying on sparse grids instead of a regular grid in order to increase the…

Logarithmic perturbation theory (LPT) is developed and applied to quasinormal modes (QNMs) in open systems. QNMs often do not form a complete set, so LPT is especially convenient because summation over a complete set of unperturbed states…

Mathematical Physics · Physics 2009-10-30 P. T. Leung , Y. T. Liu , W. M. Suen , C. Y. Tam , K. Young

The leading order terms in a curvature expansion of the surface tension, the Tolman length (first order), and rigidities (second order) have been shown to play an important role in the description of nucleation processes. This work presents…

Soft Condensed Matter · Physics 2020-01-29 Philipp Rehner , Ailo Aasen , Øivind Wilhelmsen

The thermodynamics of massless phi^4-theory is studied within screened perturbation theory (SPT). In this method the perturbative expansion is reorganized by adding and subtracting a mass term in the Lagrangian. We analytically calculate…

High Energy Physics - Phenomenology · Physics 2009-11-07 Jens. O Andersen , Michael Strickland

In many real world applications, data are characterized by a complex structure, that can be naturally encoded as a graph. In the last years, the popularity of deep learning techniques has renewed the interest in neural models able to…

Machine Learning · Computer Science 2020-04-20 Matteo Tiezzi , Giuseppe Marra , Stefano Melacci , Marco Maggini , Marco Gori

We consider stochastic approximations of sampling algorithms, such as Stochastic Gradient Langevin Dynamics (SGLD) and the Random Batch Method (RBM) for Interacting Particle Dynamcs (IPD). We observe that the noise introduced by the…

Probability · Mathematics 2023-10-10 Aniket Das , Dheeraj Nagaraj , Anant Raj