Application of deep learning methods to the study of magnetic phenomenaNowadays, methods and techniques of Machine Learning and Deep Learning are being used in various scientific areas. They help to automatize calculations without losing in quality. In this paper the…E. V. Vasiliev, D. Yu. Kapitan, A. O. Korol et al.·Nov 13, 2023SaveLearn
Poly-dodecahedrane: A new allotrope of carbonCarbon is the most important chemical element and the theoretical study of its new allotropes can be of great interest. In this study, regular dodecahedron (dodecahedrane) oligomers (n = 1, 3, 5, 7,…Siavash Hasanvandi, Elham Neisi, José M. De Sousa·Nov 11, 2023SaveLearn
B2G4: A synthetic data pipeline for the integration of Blender models in Geant4 simulation toolkitThe correctness and precision of particle physics simulation software, such as Geant4, is expected to yield results that closely align with real-world observations or well-established theoretical…Angel Bueno Rodriguez, Felix Sattler, Maximilian Perez Prada et al.·Nov 10, 2023SaveLearn
Effective Data-Driven Collective Variables for Free Energy Calculations from Metadynamics of PathsA variety of enhanced sampling methods predict multidimensional free energy landscapes associated with biological and other molecular processes as a function of a few selected collective variables…Lukas Müllender, Andrea Rizzi, Michele Parrinello et al.·Nov 9, 2023SaveLearn
Data Distillation for Neural Network Potentials toward Foundational DatasetMachine learning (ML) techniques and atomistic modeling have rapidly transformed materials design and discovery. Specifically, generative models can swiftly propose promising materials for targeted…Gang Seob Jung, Sangkeun Lee, Jong Youl Choi·Nov 9, 2023SaveLearn
Analytic and Monte Carlo Approximations to the Distribution of the First Passage Time of the Drifted Diffusion with Stochastic Resetting and Mixed Boundary ConditionsThis article introduces two techniques for computing the distribution of the absorption or first passage time of the drifted Wiener diffusion subject to Poisson resetting times, to an upper hard wall…Juan Magalang, Riccardo Turin, Javier Aguilar et al.·Nov 7, 2023SaveLearn
Comparison of Different Machine Learning Approaches to Predict Viscosity of Tri-n-Butyl Phosphate Mixtures Using Experimental DataTri-n-butyl phosphate (TBP) is a solvent that is commonly used in a variety of industries, including the nuclear and chemical industries, for its ability to dissolve and purify various inorganic…Faranak Hatami, Mousa Moradi·Nov 4, 2023SaveLearn
Automated atomistic simulations of dissociated dislocations with ab initio accuracyIn (M Hodapp and A Shapeev 2020 Mach. Learn.: Sci. Technol. 1 045005), we have proposed an algorithm that fully automatically trains machine-learning interatomic potentials (MLIPs) during large-scale…Laura Mismetti, Max Hodapp·Nov 3, 2023SaveLearn
Discrete unified gas kinetic scheme for the solution of electron Boltzmann transport equation with Callaway approximationElectrons are the carriers of heat and electricity in materials, and exhibit abundant transport phenomena such as ballistic, diffusive, and hydrodynamic behaviors in systems with different sizes. The…Meng Lian, Chuang Zhang, Zhaoli Guo et al.·Nov 3, 2023SaveLearn
A Theoretical Case Study of the Generalisation of Machine-learned PotentialsMachine-learned interatomic potentials (MLIPs) are typically trained on datasets that encompass a restricted subset of possible input structures, which presents a potential challenge for their…Yangshuai Wang, Shashwat Patel, Christoph Ortner·Nov 3, 2023SaveLearn
Dimension reduction for Nonlinear Schr\"odinger equationsWe discuss mathematical methods to derive Nonlinear Schr\"odinger equations (NLS) in "low dimensional" settings, i.e. the 3-dimensional physical space e.g. to 2 or 1 space dimensions. Beside from the…Peter Allmer·Nov 2, 2023SaveLearn
A time splitting spectral method for the Klein-Gordon-Maxwell systemWe discuss a time-splitting spectral method for the solution of the Klein--Gordon--Maxwell system in quantum electrodynamics. The convergence in Hilbert space is proven theoretically and charge…Peter Allmer·Nov 2, 2023SaveLearn
Numerical Solution of the Non-polynomial Schr\"odinger EquationStarting from the 3D Gross-Pitaevskii equation we revisit the dimensional reduction to an effective one-dimensional wave-equation that describes the longitudinal dynamics of a Bose condensate in an…Peter Allmer·Nov 2, 2023SaveLearn
Resource-aware Research on Universe and Matter: Call-to-Action in Digital TransformationGiven the urgency to reduce fossil fuel energy production to make climate tipping points less likely, we call for resource-aware knowledge gain in the research areas on Universe and Matter with…Ben Bruers, Marilyn Cruces, Markus Demleitner et al.·Nov 2, 2023SaveLearn
A short-time drift propagator approach to the Fokker-Planck equationThe Fokker-Planck equation is a partial differential equation that describes the evolution of a probability distribution over time. It is used to model a wide range of physical and biological…Wisit Mangthas, Waipot Ngamsaad·Nov 1, 2023SaveLearn
Efficient Full-frequency GW Calculations using a Lanczos MethodThe GW approximation is widely used for reliable and accurate modeling of single-particle excitations. It also serves as a starting point for many theoretical methods, such as its use in the…Weiwei Gao, Zhao Tang, Jijun Zhao et al.·Oct 31, 2023SaveLearn
Efficient Generation of Multimodal Fluid Simulation DataIn this work, we introduce an efficient generation procedure to produce synthetic multi-modal datasets of fluid simulations. The procedure can reproduce the dynamics of fluid flows and allows for…Daniele Baieri, Donato Crisostomi, Stefano Esposito et al.·Oct 30, 2023SaveLearn
Direct stellarator coil design using global optimization: application to a comprehensive exploration of quasi-axisymmetric devicesMany stellarator coil design problems are plagued by multiple minima, where the locally optimal coil sets can sometimes vary substantially in performance. As a result, solving a coil design problem a…Andrew Giuliani·Oct 29, 2023SaveLearn
A thousand fermions in a 3D harmonic trap via Monte Carlo simulationsBy use of a special wave function derived from similarly transformed propagators, this work shows that the energy of a thousand spin-balanced fermions in a three-dimensional harmonic potential can be…Siu A. Chin·Oct 28, 2023SaveLearn
Anatomy of Path Integral Monte Carlo: algebraic derivation of the harmonic oscillator's universal discrete imaginary-time propagator and its sequential optimizationThe direct integration of the harmonic oscillator path integral obscures the fundamental structure of its discrete, imaginary time propagator (density matrix). This work, by first proving an operator…Siu A. Chin·Oct 28, 2023SaveLearn
Data-driven learning of the generalized Langevin equation with state-dependent memoryWe present a data-driven method to learn stochastic reduced models of complex systems that retain a state-dependent memory beyond the standard generalized Langevin equation (GLE) with a homogeneous…Pei Ge, Zhongqiang Zhang, Huan Lei·Oct 28, 2023SaveLearn
Event generation and consistency tests with sliced Wasserstein distance in high-energy physicsIn the field of modern high-energy physics research, there is a growing emphasis on utilizing deep learning techniques to optimize event simulation, thereby expanding the statistical sample size for…Chu-Cheng Pan, Xiang Dong, Yu-Chang Sun et al.·Oct 27, 2023SaveLearn
Towards chemical accuracy using a multi-mesh adaptive finite element method in all-electron density functional theoryChemical accuracy serves as an important metric for assessing the effectiveness of the numerical method in Kohn--Sham density functional theory. It is found that to achieve chemical accuracy, not…Yang Kuang, Yedan Shen, Guanghui Hu·Oct 24, 2023SaveLearn
Unrealistic assumptions may lead to unrealistic simulation results: Droplet nuclei are neglected in a COVID-19 transmission simulation (Comments)Bale et al. [1] perform a numerical study of droplet/aerosol transport in the air to assess the probability of airborne transmission of COVID-19 from an infected person to a nearby healthy person. In…Masato Ida·Oct 23, 2023SaveLearn
Characteristic boundary conditions for magnetohydrodynamic equationsIn the present study, a characteristic-based boundary condition scheme is developed for the compressible magnetohydrodynamic (MHD) equations in the general curvilinear coordinate system, which is an…P. Makaremi-Esfarjani, A. Najafi-Yazdi·Oct 20, 2023SaveLearn