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Rovibrational states of the four dimers formed by the light and the heavy isotopologues of the methane and the water molecules are computed using a potential energy surface taken from the literature. The general rovibrational energy-level…

Chemical Physics · Physics 2017-08-07 János Sarka , Attila G. Császár , Edit Mátyus

Benchmark-quality rovibrational data are reported for the methane dimer from variational nuclear motion computations using an ab initio intermolecular potential energy surface reported by [M. P. Metz et al., Phys. Chem. Chem. Phys., 2019,…

Chemical Physics · Physics 2024-06-11 Alberto Martín Santa Daría , Gustavo Avila , Edit Mátyus

We present a novel energy-based numerical analysis of semilinear diffusion-reaction boundary value problems. Based on a suitable variational setting, the proposed computational scheme can be seen as an energy minimisation approach. More…

Numerical Analysis · Mathematics 2022-02-16 Mario Amrein , Pascal Heid , Thomas P. Wihler

We discuss refinement criteria for the Berger-Rigoutsos (block-based) refinement algorithm in our numerical relativity code GR-Athena++ in the context of binary black hole merger simulations. We compare three different strategies: the…

General Relativity and Quantum Cosmology · Physics 2024-04-29 Alireza Rashti , Maitraya Bhattacharyya , David Radice , Boris Daszuta , William Cook , Sebastiano Bernuzzi

Offline black-box optimization aims to maximize a black-box function using an offline dataset of designs and their measured properties. Two main approaches have emerged: the forward approach, which learns a mapping from input to its value,…

Machine Learning · Computer Science 2025-01-03 Can Sam Chen , Christopher Beckham , Zixuan Liu , Xue Liu , Christopher Pal

Due to the black-box nature of inverters and the wide variation range of operating points, it is challenging to on-line predict and adaptively enhance the stability of inverter-based systems. To solve this problem, this paper provides a…

Systems and Control · Electrical Eng. & Systems 2024-12-02 Yang Li , Xiangyang Wu , Zhikang Shuai , Junbin Fang , Lili He , Yi Lei , Z. John Shen

A method is developed for solving quasilinear convection diffusion problems starting on a coarse mesh where the data and solution-dependent coefficients are unresolved, the problem is unstable and approximation properties do not hold. The…

Numerical Analysis · Mathematics 2015-02-10 Sara Pollock

One of the main challenges in numerically solving partial differential equations is finding a discretisation for the computational domain that balances the accurate representation of the underlying field with computational efficiency.…

Fluid Dynamics · Physics 2026-04-24 Miha Rot , Gregor Kosec

Black-box variational inference (BBVI) now sees widespread use in machine learning and statistics as a fast yet flexible alternative to Markov chain Monte Carlo methods for approximate Bayesian inference. However, stochastic optimization…

Machine Learning · Statistics 2025-09-22 Manushi Welandawe , Michael Riis Andersen , Aki Vehtari , Jonathan H. Huggins

Kinetic energy equipartition is a premise for many deterministic and stochastic molecular dynamics methods that aim at sampling a canonical ensemble. While this is expected for real systems, discretization errors introduced by the numerical…

Computational Physics · Physics 2019-04-29 Ana J. Silveira , Charlles R. A. Abreu

Optimizing high-dimensional and complex black-box functions is crucial in numerous scientific applications. While Bayesian optimization (BO) is a powerful method for sample-efficient optimization, it struggles with the curse of…

Machine Learning · Computer Science 2025-07-08 Taeyoung Yun , Kiyoung Om , Jaewoo Lee , Sujin Yun , Jinkyoo Park

The use of reduced and mixed precision computing has gained increasing attention in high-performance computing (HPC) as a means to improve computational efficiency, particularly on modern hardware architectures like GPUs. In this work, we…

Computational Engineering, Finance, and Science · Computer Science 2025-05-28 Bálint Siklósi , Pushpender K. Sharma , David J. Lusher , István Z. Reguly , Neil D. Sandham

Port-Hamiltonian systems provide an energy-based modeling paradigm for dynamical input-state-output systems. At their core, they fulfill an energy balance relating stored, dissipated and supplied energy. To accurately resolve this energy…

Numerical Analysis · Mathematics 2024-12-17 Andreas Bartel , Manuel Schaller

Port-Hamiltonian systems provide a highly-structured framework for modeling of physical systems. By definition, they encode a balance equation relating energy changes to supplied and dissipated energy. Capturing this energy balance in…

Numerical Analysis · Mathematics 2026-05-15 Aashutosh Sharma , Andreas Bartel , Manuel Schaller

This paper proposes an original adaptive refinement framework using Radial Basis Functions-generated Finite Differences method. Node distributions are generated with a Poisson Disk Sampling-based algorithm from a given continuous density…

Numerical Analysis · Mathematics 2020-05-12 Jure Slak , Gregor Kosec

In this paper we present a refined Radial Basis Function-generated Finite Difference (RBF-FD) solution for a non-Newtonian fluid in a closed differentially heated cavity. The non-Newtonian behaviour is modelled with the Ostwald-de Waele…

Numerical Analysis · Mathematics 2025-03-24 Miha Rot , Gregor Kosec

Peculiarities of the intermolecular rovibrational quantum dynamics of the methane-argon complex are studied using a new, ab initio potential energy surface [Y. N. Kalugina, S. E. Lokshtanov, V. N. Cherepanov, and A. A. Vigasin, J. Chem.…

Chemical Physics · Physics 2019-06-26 Dávid Ferenc , Edit Mátyus

We show in this article how perturbative approaches~from our work with Hitrik (see also the work by Anantharaman-Macia) and the {\em black box} strategy from~ our work with Zworski allow to obtain decay rates for Kelvin-Voigt damped wave…

Analysis of PDEs · Mathematics 2020-06-18 Nicolas Burq

This paper presents an evolvable conditional diffusion method such that black-box, non-differentiable multi-physics models, as are common in domains like computational fluid dynamics and electromagnetics, can be effectively used for guiding…

Machine Learning · Computer Science 2025-06-18 Zhao Wei , Chin Chun Ooi , Abhishek Gupta , Jian Cheng Wong , Pao-Hsiung Chiu , Sheares Xue Wen Toh , Yew-Soon Ong

This work develops and illustrates a new method of calculating "chemically accurate" electronic wavefunctions (and energies) via a truncated full configuration interaction (CI) procedure which arguably circumvents the large matrix…

Chemical Physics · Physics 2022-12-21 Stephen J. Cotton
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