cppdlr: Imaginary time calculations using the discrete Lehmann representationWe introduce cppdlr, a C++ library implementing the discrete Lehmann representation (DLR) of functions in imaginary time and Matsubara frequency, such as Green's functions and self-energies. The DLR…Jason Kaye, Hugo U. R. Strand, Nils Wentzell·Apr 2, 2024SaveLearn
Circle radius distributions determine random close packing densityCircles of a single size can pack together densely in a hexagonal lattice, but adding in size variety disrupts the order of those packings. We conduct simulations which generate dense random packings…David J. Meer, Isabela Galoustian, Julio Gabriel de Falco Manuel et al.·Apr 2, 2024SaveLearn
Predicting the statistical error of analog particle tracing Monte CarloLarge particle systems are often described by high-dimensional (linear) kinetic equations that are simulated using Monte Carlo methods for which the asymptotic convergence rate is independent of the…Vince Maes, Ignace Bossuyt, Hannes Vandecasteele et al.·Mar 30, 2024SaveLearn
A generalized approach for rapid entropy calculation of liquids and solidsWe build a comprehensive methodology for the fast computation of entropy across both solid and liquid phases. The proposed method utilizes a single trajectory of molecular dynamics (MD) to facilitate…Qi-Jun Hong, Zi-Kui Liu·Mar 28, 2024SaveLearn
Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous MaterialsIn the field of nanoconfined fluids, there are striking examples of deformation/transport coupling in which mechanical solicitation of the confining host and dynamics of the confined fluid impact…Alexander Schlaich, Matthieu Vandamme, Marie Plazanet et al.·Mar 28, 2024SaveLearn
twoPhaseInterTrackFoam: an OpenFOAM module for Arbitrary Lagrangian/Eulerian Interface Tracking with Surfactants and Subgrid-Scale ModelingWe provide an implementation of the unstructured Finite-Volume Arbitrary Lagrangian / Eulerian (ALE) Interface-Tracking method for simulating incompressible, immiscible two-phase flows as an OpenFOAM…Moritz Schwarzmeier, Suraj Raju, Željko Tuković et al.·Mar 28, 2024SaveLearn
Convolutional network learning of self-consistent electron density via grid-projected atomic fingerprintsThe self-consistent field (SCF) generation of the three-dimensional (3D) electron density distribution () represents a fundamental aspect of density functional theory (DFT) and related…Ryong-Gyu Lee, Yong-Hoon Kim·Mar 28, 2024SaveLearn
Expanding Density-Correlation Machine Learning Representations for Anisotropic Coarse-Grained ParticlesPhysics-based, atom-centered machine learning (ML) representations have been instrumental to the effective integration of ML within the atomistic simulation community. Many of these representations…Arthur Y. Lin, Kevin K. Huguenin-Dumittan, Yong-Cheol Cho et al.·Mar 27, 2024SaveLearn
Bayesian electron density determination from sparse and noisy single-molecule X-ray scattering imagesSingle molecule X-ray scattering experiments using free electron lasers hold the potential to resolve both single structures and structural ensembles of biomolecules. However, molecular electron…Steffen Schultze, Helmut Grubmüller·Mar 27, 2024SaveLearn
Adaptive Loss Weighting for Machine Learning Interatomic PotentialsTraining machine learning interatomic potentials often requires optimizing a loss function composed of three variables: potential energies, forces, and stress. The contribution of each variable to…Daniel Ocampo, Daniela Posso, Reza Namakian et al.·Mar 26, 2024SaveLearn
Augmented Lagrangian method for coupled-clusterWe propose to improve the convergence properties of the single-reference coupled cluster (CC) method through an augmented Lagrangian formalism. The conventional CC method changes a linear…Fabian M. Faulstich, Yuehaw Khoo, Kangbo Li·Mar 25, 2024SaveLearn
Exact and Efficient Numerical approaches to MIT Bag ModelIn this document, we examine exact and efficient numerical approaches to the MIT Bag Model, a theoretical framework used to describe the properties of bound quarks in Hadrons. We present the exact…Amirhossein Rezaei, Mohammad Parsa Akrami·Mar 23, 2024SaveLearn
Keldysh-Lattice Boltzmann approach to quantum nanofluidicsWe present a mathematical and computational framework to couple the Keldysh non equilibrium quantum transport formalism with a nanoscale lattice Boltzmann method for the computational design of…Sauro Succi, Andrea Montessori·Mar 23, 2024SaveLearn
Multiphysics Numerical Method for Modeling Josephson Traveling-Wave Parametric AmplifiersJosephson traveling-wave parametric amplifiers (JTWPAs) are wideband, ultralow-noise amplifiers used to enable the readout of superconducting qubits. While individual JTWPAs have achieved high…Samuel T. Elkin, Michael Haider, Thomas E. Roth·Mar 22, 2024SaveLearn
Coherent Phonon Control of Ultrafast Magnetization Dynamics in Fe3GeTe2 from Time-Dependent Ab Initio TheoryExploring ultrafast magnetization control in two-dimensional (2D) magnets through optically driven coherent phonons has been well-established. Yet, the microscopic interplay between spin dynamics and…Zhaobo Zhou, Min Li, Thomas Frauenheim et al.·Mar 22, 2024SaveLearn
Incorrect Resonance Escape Probability in Monte Carlo Codes due to the Threshold Approximation of Temperature-Dependent ScatteringMonte Carlo-transport codes are designed to simulate the complex neutron transport physics associated with nuclear systems. These codes are tasked with simulating phenomena such as temperature…Gabriel Lentchner, William Fritsch, Robert Crowder et al.·Mar 21, 2024SaveLearn
Phonon-induced band gap renormalization by dielectric dependent global hybrid density functional tight-bindingAccurate electronic bandstructures of solids are indispensable for a wide variety of applications and should provide a sound prediction of phonon-induced band gap renormalization at finite…Tammo van der Heide, Ben Hourahine, Bálint Aradi et al.·Mar 21, 2024SaveLearn
Thermal Conductivity Calculation using Homogeneous Non-equilibrium Molecular Dynamics Simulation with AllegroIn this study, we derive the heat flux formula for the Allegro model, one of machine-learning interatomic potentials using the equivariant deep neural network, to calculate lattice thermal…Kohei Shimamura, Shinnosuke Hattori, Ken-ichi Nomura et al.·Mar 21, 2024SaveLearn
The hybrid anti-symmetrized coupled channels method (haCC) for the tRecX codeWe present a new implementation of the hybrid antisymmetrized Coupled Channels (haCC) method in the framework of the tRecX [A. Scrinzi, Comp. Phys. Comm., 270:108146, 2022.]. The method represents…Hareesh Chundayil, Vinay P. Majety, Armin Scrinzi·Mar 18, 2024SaveLearn
Identification of mechanisms of magnetic transitions using an efficient method for converging on first order saddle pointsA method for locating first order saddle points on the energy surface of a magnetic system is described and several applications presented where the mechanism of various magnetic transitions is…Hendrik Schrautzer, Moritz Sallermann, Pavel F. Bessarab et al.·Mar 18, 2024SaveLearn
Neural Downscaling for Complex Systems: from Large-scale to Small-scale by Neural OperatorPredicting and understanding the chaotic dynamics in complex systems is essential in various applications. However, conventional approaches, whether full-scale simulations or small-scale omissions,…Pengyu Lai, Jing Wang, Rui Wang et al.·Mar 18, 2024SaveLearn
Neural-network Density Functional Theory Based on Variational Energy MinimizationDeep-learning density functional theory (DFT) shows great promise to significantly accelerate material discovery and potentially revolutionize materials research. However, current research in this…Yang Li, Zechen Tang, Zezhou Chen et al.·Mar 17, 2024SaveLearn
A component-level co-rotational 3D continuum finite element framework for efficient flexible multibody analysisThis paper proposes a systematic and novel component level co-rotational (CR) framework, for upgrading existing 3D continuum finite elements to flexible multibody analysis. Without using any model…Ziyun Kan, Mingdong Chen, Haijun Peng et al.·Mar 17, 2024SaveLearn
Theoretical and numerical comparison between the pseudopotential and the free energy lattice Boltzmann methodsThe pseudopotential and free energy models are two popular extensions of the lattice Boltzmann method for multiphase flows. Until now, they have been developed apart from each other in the…L. E. Czelusniak, I. T. Martins, L. Cabezas-Gómez et al.·Mar 17, 2024SaveLearn
Conversion of weighted macro-particle distributionsThis article introduces a method for adjusting macro-particle weights within a particle distribution while preserving statistical and physical properties. The method allows the weights of the new…Nicolas Pichoff, Samuel Marini·Mar 15, 2024SaveLearn