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Autonomous labs enable the integration of automated experiment execution, data analysis and decision making. The main challenge remains the integration of diverse data streams from multiple instruments, where the data is often heterogeneous…

We present a minimal model for simulating dynamics of assorted lipid assemblies in a computationally efficient manner. Our model is particle-based and consists of coarse-grained beads put together on a modular platform to give generic…

Chemical Physics · Physics 2019-10-15 John M. A. Grime , Jesper J. Madsen

Shape optimization is of great significance in structural engineering, as an efficient geometry leads to better performance of structures. However, the application of gradient-based shape optimization for structural and architectural design…

Mathematical Software · Computer Science 2023-06-30 Gaoyuan Wu

The simulation of large nonlinear dynamical systems, including systems generated by discretization of hyperbolic partial differential equations, can be computationally demanding. Such systems are important in both fluid and kinetic…

Plasma Physics · Physics 2021-06-14 Alexander Engel , Graeme Smith , Scott E. Parker

The ever-increasing power of supercomputers coupled with highly scalable simulation codes have made molecular dynamics an indispensable tool in applications ranging from predictive modeling of materials to computational design and discovery…

Computational Engineering, Finance, and Science · Computer Science 2020-02-25 Henry Chan , Badri Narayanan , Mathew Cherukara , Troy D. Loeffler , Michael G. Sternberg , Anthony Avarca , Subramanian K. R. S. Sankaranarayanan

Active learning (AL) can drastically accelerate materials discovery; its power has been shown in various classes of materials and target properties. Prior efforts have used machine learning models for the optimal selection of physical…

Materials Science · Physics 2021-10-18 David E. Farache , Juan C. Verduzco , Zachary D. McClure , Saaketh Desai , Alejandro Strachan

Gradient matching is a promising tool for learning parameters and state dynamics of ordinary differential equations. It is a grid free inference approach, which, for fully observable systems is at times competitive with numerical…

Machine Learning · Statistics 2018-04-11 Nico S. Gorbach , Stefan Bauer , Joachim M. Buhmann

Molecular dynamics (MD) simulations are essential tools in computational chemistry and drug discovery, offering crucial insights into dynamic molecular behavior. However, their utility is significantly limited by substantial computational…

Chemical Physics · Physics 2025-09-04 Bin Feng , Jiying Zhang , Xinni Zhang , Zijing Liu , Yu Li

We examine the challenge of performing accurate electronic structure calculations at high pressures by comparing the results of all-electron full potential linearized augmented-plane-wave calculations with those of the projector augmented…

Computational Physics · Physics 2018-01-11 Kanchan Sarkar , Mehmet Topsakal , N. A. W. Holzwarth , Renata M. Wentzcovitch

Obtainable computational efficiency is evaluated when using an Adaptive Mesh Refinement (AMR) strategy in time accurate simulations governed by sets of conservation laws. For a variety of 1D, 2D, and 3D hydro- and magnetohydrodynamic…

Astrophysics · Physics 2009-11-10 R. Keppens , M. Nool , G. Toth , J. P. Goedbloed

It is well known that the classical energetically consistent micropolar model has limits in simulating the frequency band structure of packed granular materials (see Merkel et al., 2011). It is here shown that if a standard continualization…

Soft Condensed Matter · Physics 2021-04-27 Andrea Bacigalupo , Luigi Gambarotta

In this paper, a methodology for fine scale modeling of large scale structures is proposed, which combines the variational multiscale method, domain decomposition and model order reduction. The influence of the fine scale on the coarse…

Computational Engineering, Finance, and Science · Computer Science 2023-07-06 Philipp Diercks , Karen Veroy , Annika Robens-Radermacher , Jörg F. Unger

Collision detection plays a key role in the simulation of interacting rigid bodies. However, owing to its computational complexity current methods typically prioritize either maximizing processing speed or fidelity to real-world behaviors.…

Robotics · Computer Science 2023-03-03 Simone Asci , Angadh Nanjangud

Many recently introduced enhanced sampling techniques are based on biasing coarse descriptors (collective variables) of a molecular system on the fly. Sometimes the calculation of such collective variables is expensive and becomes a…

Computational Physics · Physics 2015-09-01 Marco Jacopo Ferrarotti , Sandro Bottaro , Andrea Pérez-Villa , Giovanni Bussi

Discrete-time stochastic systems with continuous spaces are hard to verify and control, even with MDP abstractions due to the curse of dimensionality. We propose an abstraction-based framework with robust dynamic programming mappings that…

Systems and Control · Electrical Eng. & Systems 2026-05-13 Ruohan Wang , Siyuan Liu , Zhiyong Sun , Sofie Haesaert

Computational systems and methods are often being used in biological research, including the understanding of cancer and the development of treatments. Simulations of tumor growth and its response to different drugs are of particular…

A key task in the field of modeling and analyzing nonlinear dynamical systems is the recovery of unknown governing equations from measurement data only. There is a wide range of application areas for this important instance of system…

Dynamical Systems · Mathematics 2019-04-11 Patrick Gelß , Stefan Klus , Jens Eisert , Christof Schütte

A common approach to modeling dispersion interactions and overcoming the inaccurate description of long-range correlation effects in electronic structure calculations is the use of pairwise-additive potentials, as in the…

Materials Science · Physics 2024-07-10 Heikki Muhli , Tapio Ala-Nissila , Miguel A. Caro

Molecular dynamics (MD) simulation is essential for various scientific domains but computationally expensive. Learning-based force fields have made significant progress in accelerating ab-initio MD simulation but are not fast enough for…

Machine Learning · Computer Science 2023-08-29 Xiang Fu , Tian Xie , Nathan J. Rebello , Bradley D. Olsen , Tommi Jaakkola

Chemical multisensor devices need calibration algorithms to estimate gas concentrations. Their possible adoption as indicative air quality measurements devices poses new challenges due to the need to operate in continuous monitoring modes…

Artificial Intelligence · Computer Science 2020-02-14 S. De Vito , E. Esposito , M. Salvato , O. Popoola , F. Formisano , R. Jones , G. Di Francia