Carrier Transport in 2D Hybrid Organic-Inorganic Perovskites: the role of spacer moleculesTwo-dimensional organic-inorganic hybrid perovskites (2D HOIPs) have been widely used for various optoelectronics owing to the excellent photoelectric properties. Recently, a great deal of studies…Caihong Zheng, Fan Zheng·Nov 30, 2023SaveLearn
Penalty and auxiliary wave function methods for electronic Excitation in neural network variational Monte CarloThis study explores the application of neural network variational Monte Carlo (NN-VMC) for the computation of low-lying excited states in molecular systems. Our focus lies on the implementation and…Zixiang Lu, Weizhong Fu·Nov 29, 2023SaveLearn
A computational tool for symbolic derivation of the small angle scattering from complex composite structuresAnalysis of small angle scattering (SAS) data requires intensive modelling to infer and characterize the structures present in a sample. This iterative improvement of models is a time consuming…Tobias William Jensen Jarrett, Carsten Svaneborg·Nov 29, 2023SaveLearn
A multi-physics compiler for generating numerical solvers from differential equationsWe develop a tool that enables domain experts to quickly generate numerical solvers for emerging multi-physics phenomena starting from a high-level description based on ordinary/partial differential…John T. Maxwell, Morad Behandish, Søren Taverniers·Nov 28, 2023SaveLearn
XLB: A differentiable massively parallel lattice Boltzmann library in PythonThe lattice Boltzmann method (LBM) has emerged as a prominent technique for solving fluid dynamics problems due to its algorithmic potential for computational scalability. We introduce XLB library, a…Mohammadmehdi Ataei, Hesam Salehipour·Nov 27, 2023SaveLearn
PF-DMD: Physics-fusion dynamic mode decomposition for accurate and robust forecasting of dynamical systems with imperfect data and physicsThe DMD (Dynamic Mode Decomposition) method has attracted widespread attention as a representative modal-decomposition method and can build a predictive model. However, the DMD may give predicted…Yuhui Yin, Chenhui Kou, Shengkun Jia et al.·Nov 27, 2023SaveLearn
U-DeepONet: U-Net Enhanced Deep Operator Network for Geologic Carbon SequestrationFNO and DeepONet are by far the most popular neural operator learning algorithms. FNO seems to enjoy an edge in popularity due to its ease of use, especially with high dimensional data. However, a…Waleed Diab, Mohammed Al-Kobaisi·Nov 26, 2023SaveLearn
A GPU-based Hydrodynamic Simulator with Boid InteractionsWe present a hydrodynamic simulation system using the GPU compute shaders of DirectX for simulating virtual agent behaviors and navigation inside a smoothed particle hydrodynamical (SPH) fluid…Xi Liu, Gizem Kayar, Ken Perlin·Nov 25, 2023SaveLearn
Leveraging Neural Networks with Attention Mechanism for High-Order Accuracy in Charge Density in Particle-in-Cell SimulationIn this research, we introduce an innovative three-network architecture that comprises an encoder-decoder framework with an attention mechanism. The architecture comprises a 1st-order-pre-trainer, a…Jian-Nan Chen, Jun-Jie Zhang·Nov 25, 2023SaveLearn
Application of Machine Learning Method to Model-Based Library Approach to Critical Dimension Measurement by CD-SEMThe model-based library (MBL) method has already been established for the accurate measurement of critical dimension (CD) of semiconductor linewidth from a critical dimension scanning electron…P. Guo, H. Miao, Y. B. Zou et al.·Nov 25, 2023SaveLearn
Differentiable and accelerated spherical harmonic and Wigner transformsMany areas of science and engineering encounter data defined on spherical manifolds. Modelling and analysis of spherical data often necessitates spherical harmonic transforms, at high degrees, and…Matthew A. Price, Jason D. McEwen·Nov 24, 2023SaveLearn
A symmetric Gauss-Seidel method for the steady-state Boltzmann equationWe introduce numerical solvers for the steady-state Boltzmann equation based on the symmetric Gauss-Seidel (SGS) method. Due to the quadratic collision operator in the Boltzmann equation, the SGS…Tianai Yin, Zhenning Cai, Yanli Wang·Nov 23, 2023SaveLearn
A Posteriori Evaluation of a Physics-Constrained Neural Ordinary Differential Equations Approach Coupled with CFD Solver for Modeling Stiff Chemical KineticsThe high computational cost associated with solving for detailed chemistry poses a significant challenge for predictive computational fluid dynamics (CFD) simulations of turbulent reacting flows.…Tadbhagya Kumar, Anuj Kumar, Pinaki Pal·Nov 22, 2023SaveLearn
An iterative deep learning procedure for determining electron scattering cross-sections from transport coefficientsWe propose improvements to the Artificial Neural Network (ANN) method of determining electron scattering cross-sections from swarm data proposed by coauthors. A limitation inherent to this problem,…Dale L Muccignat, Gregory G Boyle, Nathan A Garland et al.·Nov 22, 2023SaveLearn
Alpha Zero for Physics: Application of Symbolic Regression with Alpha Zero to find the analytical methods in physicsMachine learning with neural networks is now becoming a more and more powerful tool for various tasks, such as natural language processing, image recognition, winning the game, and even for the…Yoshihiro Michishita·Nov 21, 2023SaveLearn
A SPIRED code for the reconstruction of spin distributionIn Nuclear Magnetic Resonance (NMR), it is of crucial importance to have an accurate knowledge of the sample probability distribution corresponding to inhomogeneities of the magnetic fields. An…S. Buchwald, G. Ciaramella, J. Salomon et al.·Nov 20, 2023SaveLearn
Machine learning of (1+1)-dimensional directed percolation based on raw and shuffled configurationsMachine learning (ML) can process large sets of data generated from complex systems, which is ideal for classification tasks as often appeared in critical phenomena. Meanwhile ML techniques have been…Shen Jianmin, Wang Shanshan, Li Wei et al.·Nov 20, 2023SaveLearn
ZZPolyCalc: An open-source code with fragment caching for determination of Zhang-Zhang polynomials of carbon nanostructuresDetermination of topological invariants of graphene flakes, nanotubes, and fullerenes constitutes a challenging task due to its time-intensive nature and exponential scaling. The invariants can be…Rafał Podeszwa, Henryk A. Witek, Chien-Pin Chou·Nov 19, 2023SaveLearn
Atomistic mechanism of friction force independence on the normal load and other friction laws for dynamic structural superlubricityWe explore dynamic structural superlubricity for the case of a relatively large contact area, where the friction force is proportional to the area (exceeding 100\,nm2) experimentally,…Nikolay V. Brilliantov, Alexey A. Tsukanov, Artem K. Grebenko et al.·Nov 18, 2023SaveLearn
Total Skin Electron Therapy Stanford Technique Evolution With Monte Carlo Simulation Toward Personalized Treatments For Cutaneous LymphomaCurrent Total Skin Electron Therapy (TSET) Stanford technique for cutaneous lymphoma, established in the 70's, involves a unique irradiation setup, i.e. patient's position and beam arrangement, for…Tullio Basaglia, Patrizia Boccacci, Stephane Chauvie et al.·Nov 17, 2023SaveLearn
A consistent and conservative diffuse-domain lattice Boltzmann method for multiphase flows in complex geometriesModeling and simulation of multiphase flows in complex geomerties are challenging due to the complexity in describing the interface topology changes among different phases and the difficulty in…Xi Liu, Chengjie Zhan, Yin Chen et al.·Nov 17, 2023SaveLearn
Degeneration of kernel regression with Matern kernels into low-order polynomial regression in high dimensionKernel methods such as kernel ridge regression and Gaussian process regressions with Matern type kernels have been increasingly used, in particular, to fit potential energy surfaces (PES) and density…Sergei Manzhos, Manabu Ihara·Nov 17, 2023SaveLearn
GUGA-based MRCI approach with Core-Valence Separation Approximation (CVS) for the calculation of the Core-Excited States of moleculesWe develop and demonstrate how to use the GUGA-based MRCISD with Core-Valence Separation approximation (CVS) to compute the core-excited states. Firstly, perform a normal SCF or valence MCSCF…Qi Song, Baoyuan Liu, Junfeng Wu et al.·Nov 15, 2023SaveLearn
Bounding free energy difference with flow matchingThis paper introduces a method for computing the Helmholtz free energy using the flow matching technique. Unlike previous work that utilized flow-based models for variational free energy…Lu Zhao, Lei Wang·Nov 14, 2023SaveLearn
Accurate estimates of dynamical statistics using memoryMany chemical reactions and molecular processes occur on timescales that are significantly longer than those accessible by direct simulation. One successful approach to estimating dynamical…Chatipat Lorpaiboon, Spencer C. Guo, John Strahan et al.·Nov 14, 2023SaveLearn