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We propose convenient inferential methods for potentially nonstationary multivariate unobserved components models with fractional integration and cointegration. Based on finite-order ARMA approximations in the state space representation,…

Econometrics · Economics 2020-11-10 Tobias Hartl , Roland Weigand

We study a longstanding problem in lattice QCD at low temperature and nonzero quark chemical potential on an onset of the quark number density at $\mu=m_\pi/2$. We introduce a physical parametrization of the eigenvalues in the reduction…

High Energy Physics - Lattice · Physics 2012-05-01 Keitaro Nagata

We present a first-principles method to compute radiation properties of ultra-high quality factor photonic crystal cavities. Our Frequency-domain Approach for Radiation (FAR) can compute the far-field radiation pattern and quality factor of…

In this paper, we consider nonconvex decentralised optimisation and learning over a network of distributed agents. We develop an ADMM algorithm based on the Randomised Block Coordinate Douglas-Rachford splitting method which enables agents…

Optimization and Control · Mathematics 2025-07-31 Behnam Mafakheri , Jonathan H. Manton , Iman Shames

We compute by Monte Carlo methods the individual distributions of the $k$th smallest Dirac operator eigenvalues in QCD, and compare them with recent analytical predictions. We do this for both massless and massive quarks in an SU(3) gauge…

High Energy Physics - Lattice · Physics 2009-10-31 P. H. Damgaard , U. M. Heller , R. Niclasen , K. Rummukainen

Unbiased stochastic sampling of the one- and two-body reduced density matrices is achieved in full configuration interaction quantum Monte Carlo with the introduction of a second, "replica" ensemble of walkers, whose population evolves in…

Computational Physics · Physics 2015-09-02 Robert E. Thomas , Daniel Opalka , Catherine Overy , Peter J. Knowles , Ali Alavi , George H. Booth

Partial differential equations (PDEs) with near singular solutions pose significant challenges for traditional numerical methods, particularly in complex geometries where mesh generation and adaptive refinement become computationally…

Numerical Analysis · Mathematics 2025-07-24 Yangtao Deng , Qiaolin He , Xiaoping Wang

Quantum-enhanced auxiliary field quantum Monte Carlo (QC-AFQMC) uses output from a quantum computer to increase the accuracy of its classical counterpart. The algorithm requires the estimation of overlaps between walker states and a trial…

In this work we investigate the ground state and the dissipative quantum dynamics of interacting charged particles in an external potential at finite temperature. The recently devised time-dependent quantum Monte Carlo (TDQMC) method allows…

Quantum Physics · Physics 2025-01-29 Ivan P. Christov

Quantum Monte-Carlo (QMC) simulations involving fermions have the notorious sign problem. Some well-known exceptions of the auxiliary field QMC algorithm rely on the factorizibility of the fermion determinant. Recently, a fermionic QMC…

Strongly Correlated Electrons · Physics 2009-02-06 Congjun Wu , Shou-Cheng Zhang

We introduce a new numerical technique -- bosonic auxiliary-field Monte Carlo (bAFMC) -- which allows to calculate the thermal properties of large lattice-boson systems within a systematically improvable semiclassical approach, and which is…

Strongly Correlated Electrons · Physics 2017-08-02 Daniele Malpetti , Tommaso Roscilde

Characteristic mode (CM) analysis poses challenges in computational electromagnetics (CEM) as it calls for efficient solutions of dense generalized eigenvalue problems (GEP). Multilevel fast multipole algorithm (MLFMA) can greatly reduce…

Numerical Analysis · Mathematics 2014-12-10 Qi I. Dai , Jun Wei Wu , Ling Ling Meng , Weng Cho Chew , Wei E. I. Sha

For adaptive mixed finite element methods (AMFEM), we first introduce the data oscillation to analyze, without the restriction that the inverse of the coefficient matrix of the partial differential equations (PDEs) is a piecewise polynomial…

Numerical Analysis · Mathematics 2011-01-07 Shaohong Du , Xiaoping Xie

We show how Adjoint Algorithmic Differentiation (AAD) allows an extremely efficient calculation of correlation Risk of option prices computed with Monte Carlo simulations. A key point in the construction is the use of binning to…

Computational Finance · Quantitative Finance 2010-04-13 Luca Capriotti , Mike Giles

The biomedical field is beginning to explore the use of quantum machine learning (QML) for tasks traditionally handled by classical machine learning, especially in predicting ADME (absorption, distribution, metabolism, and excretion)…

Quantum Physics · Physics 2026-02-26 Kangyu Zheng , Tianfan Fu , Zhiding Liang

Ab-initio quantum Monte Carlo (QMC) methods are a state-of-the-art computational approach to obtaining highly accurate many-body wave functions. Although QMC methods are widely used in physics and chemistry to compute ground-state energies,…

Chemical Physics · Physics 2022-01-21 Kousuke Nakano , Abhishek Raghav , Sandro Sorella

Quantum computing is a promising way to systematically solve the longstanding computational problem, the ground state of a many-body fermion system. Many efforts have been made to realise certain forms of quantum advantage in this problem,…

Quantum Physics · Physics 2023-08-09 Xiaosi Xu , Ying Li

Indirect imaging problems in biomedical optics generally require repeated evaluation of forward models of radiative transport, for which Monte Carlo is accurate yet computationally costly. We develop a novel approach to reduce this…

Computational Physics · Physics 2020-07-10 Callum M. Macdonald , Simon Arridge , Samuel Powell

We demonstrate an adaptive sampling approach for computing the probability of a rare event for a set of three-dimensional airplane geometries under various flight conditions. We develop a fully automated method to generate parameterized…

Computational Engineering, Finance, and Science · Computer Science 2021-09-09 Runda Ji , Qiqi Wang

We investigate the phase diagram and the mechanism for the sign problem to appear in finite density QCD at strong coupling in a combined framework of the auxiliary field Monte-Carlo (AFMC) and the chiral angle fixing (CAF) methods. When…

High Energy Physics - Lattice · Physics 2013-11-22 Terukazu Ichihara , Takashi Z. Nakano , Akira Ohnishi