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Many exact Markov chain Monte Carlo algorithms have been developed for posterior inference in Bayesian nonparametric models which involve infinite-dimensional priors. However, these methods are not generic and special methodology must be…

Computation · Statistics 2014-05-22 Jim E. Griffin

We introduce a non-linear differential flow equation for density matrices that provides a monotonic decrease of the free energy and reaches a fixed point at the Gibbs thermal state. We use this equation to build a variational approach for…

Superconductivity · Physics 2020-11-04 Tao Shi , Eugene Demler , J. Ignacio Cirac

The Hartree-Fock-Bogoliubov approximation is very useful for treating both long- and short-range correlations in finite quantum fermion systems, but it must be extended in order to describe detailed spectroscopic properties. One problem is…

Nuclear Theory · Physics 2017-08-23 L. M. Robledo , G. F. Bertsch

We consider model order reduction of a nonlinear cable-mass system modeled by a 1D wave equation with interior damping and dynamic boundary conditions. The system is driven by a time dependent forcing input to a linear mass-spring system at…

Optimization and Control · Mathematics 2018-11-27 Belinda A. Batten , Hesam Shoori , John R. Singler , Madhuka H. Weerasinghe

The theory of nonlinear balanced truncation provides a system-theoretic framework for model reduction that preserves important properties such as stability, controllability, and observability. We present a scalable algorithm for computing…

Optimization and Control · Mathematics 2026-04-28 Nicholas A. Corbin , Boris Kramer

We consider a class of finite element approximations for fourth-order parabolic equations that can be written as a system of second-order equations by introducing an auxiliary variable. In our approach, we first solve a variational problem…

Numerical Analysis · Mathematics 2021-06-30 Sana Keita , Abdelaziz Beljadid , Yves Bourgault

This paper investigates the time fractional sine-Gordon equation whose solution exhibits a weak singularity of type t^{\alpha}. By means of the Alikhanov formula we derive a fully discrete, linearized scheme. Using the more general…

Numerical Analysis · Mathematics 2026-01-29 Chang Hou , Hu Chen

We discuss effective field theory treatments of the problem of three particles interacting via short-range forces (range R >> a_2, with a_2 the two-body scattering length). We show that forming a once-subtracted scattering equation yields a…

Other Condensed Matter · Physics 2009-04-17 L. Platter , D. R. Phillips

We propose an efficient numerical method to compute the $k$-space second Chern number in four-dimensional (4D) topological systems. Our approach employs an adaptive mesh refinement scheme to evaluate the Brillouin-zone integral, which…

Mesoscale and Nanoscale Physics · Physics 2026-03-30 Xiang Liu , Xiao-Xia Yi , Zheng-Rong Liu , Rui Chen , Bin Zhou

Nonlinear balanced truncation is a model order reduction technique that reduces the dimension of nonlinear systems in a manner that accounts for either open- or closed-loop observability and controllability aspects of the system. A…

Optimization and Control · Mathematics 2024-04-23 Boris Kramer , Serkan Gugercin , Jeff Borggaard , Linus Balicki

The time evolution of $\ell$-spin reduced density operators is studied for a class of Heisenberg-type quantum spin models with long-range interactions. In the framework of the quantum Bogoliubov-Born-Green-Kirkwood-Yvon (BBGKY) hierarchy,…

Statistical Mechanics · Physics 2012-02-08 Rytis Paškauskas , Michael Kastner

We study truncations of hierarchical equations of motion (HEOM) for finite-dimensional open quantum systems. We prove that for finite-dimensional approximations constructed with a Schur-complement type of terminator, the spectrum converges…

Quantum Physics · Physics 2026-04-27 Vasilii Vadimov

In a two-dimensional Bose-Einstein condensate the reduction in dimensionality fundamentally influences collisions between the atoms. In the crossover regime from three to two dimensions several scattering parameters have been considered.…

Statistical Mechanics · Physics 2009-11-10 Christopher Gies , M. D. Lee , D. A. W. Hutchinson

We extend a previously proposed rotation and truncation scheme to optimize quantum Anderson impurity calculations with exact diagonalization [PRB 90, 085102 (2014)] to density-matrix renormalization group (DMRG) calculations. The method…

Strongly Correlated Electrons · Physics 2019-10-02 Y. Lu , X. Cao , P. Hansmann , M. W. Haverkort

In this paper, we present a theoretical analysis of the model reduction algorithm for linear switched systems. This algorithm is a reminiscence of the balanced truncation method for linear parameter varying systems. Specifically in this…

Optimization and Control · Mathematics 2013-03-19 Mihaly Petreczky , Rafael Wisniewski , John Leth

In this work, a new compact sixth order accurate finite difference scheme for the two and three-dimensional Helmholtz equation is presented. The main significance of the proposed scheme is that its sixth order leading truncation error term…

Numerical Analysis · Mathematics 2024-09-23 Neelesh Kumar , Ritesh Kumar Dubey

In this study, we consider the numerical solution of large systems of linear equations obtained from the stochastic Galerkin formulation of stochastic partial differential equations. We propose an iterative algorithm that exploits the…

Numerical Analysis · Mathematics 2016-05-18 Kookjin Lee , Howard C. Elman

We assess the validity of a single step Godunov scheme for the solution of the magneto-hydrodynamics equations in more than one dimension. The scheme is second-order accurate and the temporal discretization is based on the dimensionally…

Instrumentation and Methods for Astrophysics · Physics 2014-11-20 A. Mignone , P. Tzeferacos

This paper presents a novel model order reduction framework tailored for fully nonlinear stochastic dynamics without lifting them to quadratic systems and without using linearization techniques. By directly leveraging structural properties…

Probability · Mathematics 2025-08-05 Martin Redmann

This paper proposes a data-driven model reduction approach on the basis of noisy data. Firstly, the concept of data reduction is introduced. In particular, we show that the set of reduced-order models obtained by applying a Petrov-Galerkin…

Optimization and Control · Mathematics 2022-02-01 Azka Muji Burohman , Bart Besselink , Jacquelien M. A. Scherpen , M. Kanat Camlibel