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When numerically solving partial differential equations, for a given problem and operating condition, adaptive mesh refinement (AMR) has proven its efficiency to automatically build a discretization achieving a prescribed accuracy at low…

This work presents a multi-layered methodology for efficiently accelerating multimodal foundation models (MFMs). It combines hardware and software co-design of transformer blocks with an optimization pipeline that reduces computational and…

We present a reformulation of QM/MM as a fully quantum mechanical theory of interacting subsystems, all treated at the level of density functional theory (DFT). For the MM subsystem, which lacks orbitals, we assign an ad hoc electron…

We present a polarizable embedding quantum mechanics/molecular mechanics (QM/MM) framework for ground- and excited-state Complete Active Space Self-Consistent Field (CASSCF) calculations on molecules within complex environments, such as…

Chemical Physics · Physics 2024-11-20 Tommaso Nottoli , Mattia Bondanza , Filippo Lipparini , Benedetta Mennucci

Quantum-mechanically-driven charge polarization and charge transfer are ubiquitous in biomolecular systems, controlling reaction rates, allosteric interactions, ligand-protein binding, membrane transport, and dynamically-driven structural…

Chemical Physics · Physics 2021-06-09 Susan R. Atlas

Adaptive lattice Boltzmann methods (LBMs) are based on velocity discretizations that self-adjust to local macroscopic conditions such as velocity and temperature. While this feature improves the accuracy and the stability of LBMs for large…

Computational Physics · Physics 2020-11-04 C. Coreixas , J. Latt

Atomic force microscopy (AFM) enables high-resolution imaging and quantitative force measurement, which is critical for understanding nanoscale mechanical, chemical, and biological interactions. In dynamic AFM modes, however, interaction…

Instrumentation and Detectors · Physics 2025-06-10 Simon Laflamme , Bugrahan Guner , Omur E. Dagdeviren

Regional climate information at kilometer scales is essential for assessing the impacts of climate change, but generating it with global climate models is too expensive due to their high computational costs. Machine learning models offer a…

Atmospheric and Oceanic Physics · Physics 2026-04-07 Kevin Debeire , Aytaç Paçal , Pierre Gentine , Luis Medrano-Navarro , Nils Thuerey , Veronika Eyring

Adaptive representations are increasingly indispensable for reducing the in-memory and on-disk footprints of large-scale data. Usual solutions are designed broadly along two themes: reducing data precision, e.g., through compression, or…

Graphics · Computer Science 2022-07-15 Harsh Bhatia , Duong Hoang , Nate Morrical , Valerio Pascucci , Peer-Timo Bremer , Peter Lindstrom

Hybrid quantum mechanics/molecular mechanics (QM/MM) simulations have advanced the field of computational chemistry tremendously. However, they require the partitioning of a system into two different regions that are treated at different…

Chemical Physics · Physics 2022-04-28 Bettina Lier , Peter Poliak , Philipp Marquetand , Julia Westermayr , Chris Oostenbrink

In this work, the Immersed Boundary Method (IBM) with feedback forcing introduced by Goldstein et al. (1993) and often referred in the literature as the Virtual Boundary Method (VBM), is addressed. The VBM has been extensively applied both…

Numerical Analysis · Mathematics 2021-10-25 Michele Girfoglio , Giovanni Stabile , Andrea Mola , Gianluigi Rozza

We formulate an atomistic-to-continuum coupling method based on blending atomistic and continuum forces. Our precise choice of blending mechanism is informed by theoretical predictions. We present a range of numerical experiments studying…

Numerical Analysis · Mathematics 2015-06-15 Xingjie Helen Li , Mitchell Luskin , Christoph Ortner , Alexander V. Shapeev

In modern computer experiment applications, one often encounters the situation where various models of a physical system are considered, each implemented as a simulator on a computer. An important question in such a setting is determining…

Methodology · Statistics 2023-05-08 John C. Yannotty , Thomas J. Santner , Richard J. Furnstahl , Matthew T. Pratola

A stable added-mass partitioned (AMP) algorithm is developed for fluid-structure interaction (FSI) problems involving viscous incompressible flow and compressible elastic-solids. The AMP scheme remains stable and second-order accurate even…

Numerical Analysis · Mathematics 2018-12-11 Daniel A. Serino , Jeffrey W. Banks , William D. Henshaw , Donald W. Schwendeman

Large pre-trained language models contain societal biases and carry along these biases to downstream tasks. Current in-processing bias mitigation approaches (like adversarial training) impose debiasing by updating a model's parameters,…

Computation and Language · Computer Science 2023-06-21 Deepak Kumar , Oleg Lesota , George Zerveas , Daniel Cohen , Carsten Eickhoff , Markus Schedl , Navid Rekabsaz

Universal machine-learning interatomic potentials (uMLIPs) enable reactive molecular simulations with near-DFT accuracy, yet applying them efficiently to large, realistic condensed-phase systems remains computationally demanding. Here we…

Materials Science · Physics 2026-03-25 Yu Miyazaki , Atsuhiro Tomita , Akihide Hayashi , So Takamoto , Mizuki Takemoto , Hodaka Mori

Additive manufacturing (AM) techniques hold promise but face significant challenges in process planning and optimization. The large temporal and spatial variations in temperature that can occur in layer-wise AM lead to thermal excursions,…

Systems and Control · Electrical Eng. & Systems 2025-01-22 Mikhail Khrenov , William Frieden Templeton , Sneha Prabha Narra

Molecular simulations of the forced unfolding and refolding of biomolecules or molecular complexes allow to gain important kinetic, structural and thermodynamic information about the folding process and the underlying energy landscape. In…

Soft Condensed Matter · Physics 2021-05-26 Marco Oestereich , Jürgen Gauss , Gregor Diezemann

Simulating physical systems is essential in engineering, but analytical solutions are limited to straightforward problems. Consequently, numerical methods like the Finite Element Method (FEM) are widely used. However, the FEM becomes…

Machine Learning · Computer Science 2026-01-30 Niklas Freymuth , Philipp Dahlinger , Tobias Würth , Simon Reisch , Luise Kärger , Gerhard Neumann

Quantum Error Mitigation (QEM) enables the extraction of high-quality results from the presently-available noisy quantum computers. In this approach, the effect of the noise on observables of interest can be mitigated using multiple…

Quantum Physics · Physics 2023-11-23 Ivan Henao , Jader P. Santos , Raam Uzdin