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Computational studies that use block-structured adaptive mesh refinement (AMR) approaches suffer from unnecessarily high mesh resolution in regions adjacent to important solution features. This deficiency limits the performance of AMR…

Computational Physics · Physics 2022-03-02 Brandon Gusto , Tomasz Plewa

Emerging quantum hardware provides new possibilities for quantum simulation. While much of the research has focused on simulating closed quantum systems, the real-world quantum systems are mostly open. Therefore, it is essential to develop…

Quantum Physics · Physics 2024-02-14 Huo Chen , Niladri Gomes , Siyuan Niu , Wibe Albert de Jong

We develop a new approach for efficient and scalable simulations of measurement and control of quantum systems built upon existing phase-space methods, namely the Truncated Wigner Approximation (TWA). We benchmark against existing…

Quantum Physics · Physics 2024-09-04 Kaiwen Zhu , Zain Mehdi , Joseph J. Hope , Simon A. Haine

This paper presents novel refinement sensors for the application to adaptive mesh and algorithm refinement (AMAR) with kinetic models, such as discrete velocity and lattice Boltzmann methods. While refinement criteria for AMAR based on…

Fluid Dynamics · Physics 2026-03-17 R. M. Strässle , S. A. Hosseini , I. V. Karlin

In this paper we propose a new class of Dynamic Mixture Models (DAMMs) being able to sequentially adapt the mixture components as well as the mixture composition using information coming from the data. The information driven nature of the…

Methodology · Statistics 2023-01-12 Leopoldo Catania

Data fusion models based on Coupled Matrix and Tensor Factorizations (CMTF) have been effective tools for joint analysis of data from multiple sources. While the vast majority of CMTF models are based on the strictly multilinear…

Machine Learning · Computer Science 2025-06-17 Carla Schenker , Xiulin Wang , David Horner , Morten A. Rasmussen , Evrim Acar

A novel strategy is proposed to improve the accuracy of state estimation and reconstruction from low-fidelity models and sparse data from sensors. This strategy combines ensemble Data Assimilation (DA) and Machine Learning (ML) tools,…

Fluid Dynamics · Physics 2025-01-31 Miguel M. Valero , Marcello Meldi

We show how thermodynamic properties of molecular models can be computed over a large, multidimensional parameter space by combining multistate reweighting analysis with a linear basis function approach. This approach reduces the…

Chemical Physics · Physics 2016-05-18 Levi N. Naden , Michael R. Shirts

Binding free energies are a key element in understanding and predicting the strength of protein--drug interactions. While classical free energy simulations yield good results for many purely organic ligands, drugs including transition metal…

An adpative integration technique for time advancement of particle motion in the context of coupled computational fluid dynamics (CFD) - discrete element method (DEM) simulations is presented in this work. CFD-DEM models provide an accurate…

Computational Physics · Physics 2018-02-28 Hariswaran Sitaraman , Ray Grout

This paper is committed to investigate an extension of the classical adaptive biasing force method, which is used to compute the free energy related to the Boltzmann-Gibbs measure and a reaction coordinate function. The issue of this…

Probability · Mathematics 2017-11-08 Houssam AlRachid , Tony Lelievre

Mixed-precision quantization mostly predetermines the model bit-width settings before actual training due to the non-differential bit-width sampling process, obtaining sub-optimal performance. Worse still, the conventional static…

Artificial Intelligence · Computer Science 2023-02-10 Yingchun Wang , Jingcai Guo , Song Guo , Weizhan Zhang

We recently proposed a method coupling quantum mechanics (QM) methods and molecular density functional theory (MDFT) to describe mixed quantum-classical systems [J. Chem. Phys. 161, 014113 (2024)]. This approach is particularly appropriate…

Chemical Physics · Physics 2025-11-21 Maxime Labat , Guillaume Jeanmairet , Emmanuel Giner

Atomic force microscopy (AFM) is a key tool for characterising nanoscale structures, with functionalised tips now offering detailed images of the atomic structure. In parallel, AFM simulations using the particle probe model provide a…

Materials Science · Physics 2025-09-03 Jie Huang , Niko Oinonen , Fabio Priante , Filippo Federici Canova , Lauri Kurki , Chen Xu , Adam S. Foster

State and input constraints are ubiquitous in control system design. One recently developed tool to deal with these constraints is control barrier functions (CBF) which transform state constraints into conditions in the input space.…

Systems and Control · Electrical Eng. & Systems 2022-09-07 Xiao Tan , Dimos V. Dimarogonas

The Alchemical Transfer Method (ATM) is herein validated against the relative binding free energies of a diverse set of protein-ligand complexes. We employed a streamlined setup workflow, a bespoke force field, and the AToM-OpenMM software…

Chemical Physics · Physics 2023-08-21 Lieyang Chen , Yujie Wu , Chuanjie Wu , Ana Silveira , Woody Sherman , Huafeng Xu , Emilio Gallicchio

This study presents an advanced numerical framework that integrates experimentally acquired Atomic Force Microscope (AFM) data into high-fidelity simulations for adhesive rough contact problems, bridging the gap between experimental physics…

Computational Engineering, Finance, and Science · Computer Science 2025-04-04 Maria Rosaria Marulli , Jacopo Bonari , Pasqualantonio Pingue , Marco Paggi

Powder Bed Fusion (PBF) is a type of Additive Manufacturing (AM) technology that builds parts in a layer-by-layer fashion out of a bed of metal powder via the selective melting action of a laser or electron beam heat source. The technology…

Systems and Control · Electrical Eng. & Systems 2020-01-09 Nathaniel Wood , David Hoelzle

The development of quantum image representation and quantum measurement techniques has made quantum image processing research a hot topic. In this paper, a novel Adaptive Quantum Scaling Model (AQSM) is first proposed for scrambling…

Quantum Physics · Physics 2025-04-01 Zheng Xing , Chan-Tong Lam , Xiaochen Yuan , Sio-Kei Im , Penousal Machado

Several Bayesian estimation based heuristics have been developed to perform quantum state tomography (QST). Their ability to quantify uncertainties using region estimators and include a priori knowledge of the experimentalists makes this…

Quantum Physics · Physics 2021-09-16 Syed Muhammad Kazim , Ahmad Farooq , Junaid ur Rehman , Hyundong Shin