English
Related papers

Related papers: Efficient implementation of Gauss collocation and …

200 papers

Hamiltonian Monte Carlo (HMC) is a powerful tool for Bayesian statistical inference due to its potential to rapidly explore high dimensional state space, avoiding the random walk behavior typical of many Markov Chain Monte Carlo samplers.…

Applied to the master equation, the usual numerical integration methods, such as Runge-Kutta, become inefficient when the rates associated with various transitions differ by several orders of magnitude. We introduce an integration scheme…

Statistical Mechanics · Physics 2009-11-07 Ronald Dickman

Advances in information technology have led to extremely large datasets that are often kept in different storage centers. Existing statistical methods must be adapted to overcome the resulting computational obstacles while retaining…

Methodology · Statistics 2021-11-12 Qiong Zhang , Jiahua Chen

Fractional boundary value problems are often used to model complex systems and processes characterized by memory effects and anomalous diffusion. In this paper, we consider fractional boundary value problems involving the Riesz-Caputo…

Numerical Analysis · Mathematics 2026-05-18 Chiara Sorgentone , Enza Pellegrino , Francesca Pitolli

Metric space magnitude, an active field of research in algebraic topology, is a scalar quantity that summarizes the effective number of distinct points that live in a general metric space. The {\em weighting vector} is a closely-related…

Machine Learning · Computer Science 2021-06-03 Eric Bunch , Jeffery Kline , Daniel Dickinson , Suhaas Bhat , Glenn Fung

Hamiltonian splitting methods are an established technique to derive stable and accurate integration schemes in molecular dynamics, in which additional accuracy can be gained using force gradients. For rigid bodies, a tradition exists in…

Statistical Mechanics · Physics 2008-04-10 Ramses van Zon , Igor P. Omelyan , Jeremy Schofield

This article proposes a formalism which unifies Hamiltonian simulation techniques from different fields. This formalism leads to a competitive method to construct the Hamiltonian simulation with a comprehensible, simple-to-implement circuit…

Quantum Physics · Physics 2025-01-22 Robin Ollive , Stephane Louise

The optimal implementation of quantum gates for closed $N$-qubit systems is one of the key challenges for practical realization of many quantum information processing tasks. In the present article, based on the generalized Bloch vectors…

Quantum Physics · Physics 2026-05-26 Elena R. Loubenets , Sergey Kuznetsov

We develop a partial Hamiltonian framework to obtain reductions and closed-form solutions via first integrals of current value Hamiltonian systems of ordinary differential equations (ODEs). The approach is algorithmic and applies to many…

Optimization and Control · Mathematics 2014-08-20 R. Naz , F. M. Mahomed , Azam Chaudhry

We are concerned with the efficient implementation of symplectic implicit Runge-Kutta (IRK) methods applied to systems of (non-necessarily Hamiltonian) ordinary differential equations by means of Newton-like iterations. We pay particular…

Numerical Analysis · Mathematics 2017-03-23 Mikel Antoñana , Joseba Makazaga , Ander Murua

Recent years have seen an increasing amount of research devoted to the development of so-called resonance-based methods for dispersive nonlinear partial differential equations. In many situations, this new class of methods allows for…

Numerical Analysis · Mathematics 2024-07-22 Georg Maierhofer , Katharina Schratz

The numerical efficiency of different schemes for solving the Liouville-von Neumann equation within multilevel Redfield theory has been studied. Among the tested algorithms are the well-known Runge-Kutta scheme in two different…

Chemical Physics · Physics 2009-11-06 Ivan Kondov , Ulrich Kleinekathoefer , Michael Schreiber

Gaussian wavepacket dynamics has proven to be a useful semiclassical approximation for quantum simulations of high-dimensional systems with low anharmonicity. Compared to Heller's original local harmonic method, the variational Gaussian…

Numerical Analysis · Mathematics 2024-09-26 Roya Moghaddasi Fereidani , Jiří JL Vaníček

We introduce a family of fourth order two-step methods that preserve the energy function of canonical polynomial Hamiltonian systems. Each method in the family may be viewed as a correction of a linear two-step method, where the correction…

Numerical Analysis · Mathematics 2012-06-08 Luigi Brugnano , Felice Iavernaro , Donato Trigiante

Gating is a key technique used for integrating information from multiple sources by long short-term memory (LSTM) models and has recently also been applied to other models such as the highway network. Although gating is powerful, it is…

Computation and Language · Computer Science 2018-06-19 Chao Zhang , Philip Woodland

We deal with the efficient parallelization of Bayesian global optimization algorithms, and more specifically of those based on the expected improvement criterion and its variants. A closed form formula relying on multivariate Gaussian…

Machine Learning · Statistics 2016-09-12 Sébastien Marmin , Clément Chevalier , David Ginsbourger

A fourth-order finite volume embedded boundary (EB) method is presented for the unsteady Stokes equations. The algorithm represents complex geometries on a Cartesian grid using EB, employing a technique to mitigate the "small cut-cell"…

Numerical Analysis · Mathematics 2022-09-08 Nathaniel Overton-Katz , Xinfeng Gao , Stephen Guzik , Oscar Antepara , Daniel T. Graves , Hans Johansen

Explicit Runge-Kutta schemes with large stable step sizes are developed for integration of high order spectral difference spatial discretization on quadrilateral grids. The new schemes permit an effective time step that is substantially…

Numerical Analysis · Mathematics 2013-07-16 M. Parsani , D. I. Ketcheson , W. Deconinck

We present new results building on the conservative deterministic spectral method for the space inhomogeneous Boltzmann equation developed by Gamba and Tharkabhushaman. This approach is a two-step process that acts on the weak form of the…

Numerical Analysis · Mathematics 2012-11-06 Irene M. Gamba , Jeffrey R. Haack

To speed up Gaussian process inference, a number of fast kernel matrix-vector multiplication (MVM) approximation algorithms have been proposed over the years. In this paper, we establish an exact fast kernel MVM algorithm based on exact…

Machine Learning · Statistics 2025-08-05 Nicolas Langrené , Xavier Warin , Pierre Gruet
‹ Prev 1 3 4 5 6 7 10 Next ›