Article
Multidisciplinary Sciences
Jan Kessler, Francesco Calcavecchia, Thomas D. Kuehne
Summary: Inspired by the universal approximation theorem and the widespread adoption of artificial neural network techniques, feed-forward neural networks are proposed as a general purpose trial wave function for quantum Monte Carlo simulations of continuous many-body systems. The accuracy of the trial wave functions was demonstrated by studying an exactly solvable model system of two trapped interacting particles and the hydrogen dimer. The whole many-body wave function can be represented by a neural network for simple model systems, while the antisymmetry condition of non-trivial fermionic systems is incorporated by means of a Slater determinant.
ADVANCED THEORY AND SIMULATIONS
(2021)
Article
Chemistry, Physical
Tina N. Mihm, William Z. Van Benschoten, James J. Shepherd
Summary: A new approach using low-cost calculations was developed to find a twist angle that matches the coupled cluster doubles energy in a finite unit cell. The method was shown to have comparable accuracy with exact methods beyond coupled cluster doubles theory. Additionally, for small system sizes, the same twist angle can be found by comparing energies directly, suggesting a potential route towards twist angle selection.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Multidisciplinary Sciences
Yifan Wang, Jake Kalscheur, Ya-Qiong Su, Emiel J. M. Hensen, Dionisios G. Vlachos
Summary: Understanding the evolution of the catalyst's structure under working conditions is challenging. The study introduces a multiscale modeling framework and machine learning to investigate the structures and nucleation of CeO2-supported Pd clusters and single atoms at different catalyst loadings, temperatures, and exposures to CO. Experimental data lacks simultaneous temporal and spatial resolution, hindering accurate structure determination.
NATURE COMMUNICATIONS
(2021)
Article
Chemistry, Physical
Grzegorz Ziolkowski, Dariusz Chrobak, Grazyna Chelkowska, Ondrej Zivotsky, Artur Chrobak
Summary: The paper discusses Monte Carlo magnetic simulations for fractal-like nano and mesoscopic grains, showing that the size effects depend on the chosen value of magnetic anisotropy. For fractals with ultra-high coercivity, decreasing their size leads to deterioration of coercivity, especially for high surface to volume ratio, while soft magnetic fractals exhibit the opposite effect with the appearance of coercive field and significantly higher energy product than conventional rare earths' free permanent magnets.
Article
Physics, Particles & Fields
Stefano Carrazza, Juan Cruz-Martinez, Marco Rossi, Marco Zaro
Summary: MadFlow is a general-purpose framework for MC event simulation in particle physics, optimized for hardware accelerators like GPUs. It automates the generation and deployment of components for MC simulation using MadGraph5_aMC@NLO framework, with the ability to export code in GPU format. The simulation can be performed on systems with different hardware acceleration capabilities, providing an asynchronous unweighted events procedure to store simulation results. Despite automating only the Leading Order, the framework offers all necessary ingredients for building complex Monte Carlo simulators in a modern, extensible, and maintainable manner.
EUROPEAN PHYSICAL JOURNAL C
(2021)
Article
Mathematics
Yangjun Wu, Xiansong Xu, Dario Poletti, Yi Fan, Chu Guo, Honghui Shang
Summary: In this paper, a single-layer fully connected neural network called tanh-FCN is proposed as a tool to solve ab initio quantum chemistry problems, adapted from the restricted Boltzmann machine (RBM). The network represents real electronic wave functions using real numbers, achieving comparable precision to RBM for various molecules. Additionally, the authors show that knowledge of the Hartree-Fock reference state can be utilized to accelerate the convergence of the variational Monte Carlo algorithm and improve the energy precision.
Article
Astronomy & Astrophysics
Shiyan Zhong, Shuo Li, Peter Berczik, Rainer Spurzem
Summary: We study the tidal disruption of stars in dense nuclear star clusters containing supermassive central black holes (SMBH) using high-accuracy direct N-body simulation. Tidal disruption events (TDEs) are used to probe the properties of SMBHs, their accretion disks, and the surrounding nuclear stellar cluster. We compare the rates of full tidal disruption events (FTDEs) with partial tidal disruption events (PTDEs). Two novel effects, variation of the leftover star's mass and radius, and variation of its orbital energy, are observed in the simulation. The number of FTDEs is reduced by 28% after incorporating these effects, mainly due to ejection of leftover stars from PTDEs. The number of PTDEs is 75% higher than the simple estimation, primarily due to multiple PTDEs produced by leftover stars in the diffusive regime. The peak mass fallback rate for PTDEs and FTDEs is computed, with 58% of PTDEs exceeding the Eddington limit and the number of super-Eddington PTDEs being 2.3 times the number of super-Eddington FTDEs.
ASTROPHYSICAL JOURNAL
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Paula Ibanez, Amaia Villa-Abaunza, Marie Vidal, Pedro Guerra, Sergio Graullera, Carlos Illana, Jose Manuel Udias
Summary: This study presents the implementation of two different dose calculation algorithms based on MC phase-space information on a GPU to calculate dose distributions for the INTRABEAM device quickly and accurately within seconds. The performance study showed that the HMC algorithm is more efficient than the WC-MC algorithm in GPU implementation, achieving dose calculation with noise below 5% in a very short time.
Article
Mechanics
Pipat Harata, Prathan Srivilai
Summary: We calculate the grand canonical partition function of a serial metallic island system using the imaginary-time path integral formalism. All electronic excitations in the lead and island electrodes are described using Grassmann numbers, and the Coulomb charging energy is represented in terms of phase fields. By using the large channel approximation, we determine the explicit phase dependence of the tunneling action. The partition function is represented as a path integral over phase fields, with a path probability given in an analytically known effective action functional. Additionally, we propose a method to calculate the average electron number and construct the quantum stability diagram of the serial island system using winding numbers.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Chemistry, Physical
Dilimulati Aierken, Michael Bachmann
Summary: We systematically investigate the effect of bending stiffness on the ground-state conformations of semiflexible polymers. The formation of different conformations depends strongly on the strength of the bending restraint, as observed through detailed analysis of contact and distance maps.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Materials Science, Multidisciplinary
Massimo Boninsegni
Summary: The bound state of a He-3 atom at the interface between crystalline and superfluid phases of He-4 is investigated using first principle Quantum Monte Carlo simulations. The results show that the He-3 atom is sharply localized in a quasi-2D layer of He-4, located in the intermediate region between the solid and liquid states. The localization and quantum-mechanical exchanges of the He-3 atom are influenced by the attractive strength of the substrate.
RESULTS IN PHYSICS
(2022)
Article
Computer Science, Artificial Intelligence
Kunlun Han, Tianwei Huang, Linfei Yin
Summary: In doubly-fed induction generator-based wind turbines (DFIG-WTs), the rotor-side controller (RSC) with optimized parameters improves wind energy utilization efficiency. However, conventional intelligent optimization algorithms face challenges in quickly finding the controller parameters due to long optimization times and inadequate exploration and development capabilities. To address this issue, a quantum-inspired parallel multi-layer Monte Carlo algorithm accelerated by transfer learning is proposed. This algorithm significantly shortens the optimization time and enhances the reliability and stability of the optimized controller.
APPLIED SOFT COMPUTING
(2023)
Article
Materials Science, Multidisciplinary
M. D. Burke, Maxence Grandadam, J. P. F. LeBlanc
Summary: We introduce a method to speed up the numerical evaluation of spatial integrals of Feynman diagrams on the real frequency axis. This is achieved by using a renormalized perturbation expansion with a constant but complex renormalization shift. The complex shift acts as a regularization parameter for the numerical integration of sharp functions, resulting in an exponential speed up of stochastic numerical integration. We provide proof of concept calculations for the difficult limit of the half-filled two-dimensional Hubbard model on a square lattice.
Article
Chemistry, Physical
Oliver A. Bramley, Timothy J. H. Hele, Dmitrii Shalashilin
Summary: Zombie states are a formalism that describes coupled coherent fermionic states in a computationally tractable manner. This study extends the previous work on Zombie states and develops efficient algorithms for evaluating operators and addressing normalization. It also presents techniques for improving accuracy and calculating low-lying excited states.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Mechanics
M. Beljin-Cavic, I Loncarevic, Lj Budinski-Petkovic, Z. M. Jaksic, S. B. Vrhovac
Summary: This study uses Monte Carlo simulations to investigate the random sequential adsorption of mixtures of objects with varying shapes on a three-dimensional cubic lattice. The research focuses on the influence of geometrical properties of the shapes on the jamming coverage and temporal evolution of density. The results show that the coverage approaches the jamming limit exponentially and the relaxation time is determined by the number of orientations the objects can take on the lattice. The jamming coverage of a mixture can be greater than or in between the jamming coverages of the single-component shapes, depending on the local geometry.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Physics, Fluids & Plasmas
R. J. Magyar, L. Shulenburger, A. D. Baczewski
CONTRIBUTIONS TO PLASMA PHYSICS
(2016)
Article
Chemistry, Physical
M. Chandler Bennett, Cody A. Melton, Abdulgani Annaberdiyev, Guangming Wang, Luke Shulenburger, Lubos Mitas
JOURNAL OF CHEMICAL PHYSICS
(2017)
Article
Geosciences, Multidisciplinary
Seth Root, Joshua P. Townsend, Erik Davies, Raymond W. Lemke, David E. Bliss, Dayne E. Fratanduono, Richard G. Kraus, Marius Millot, Dylan K. Spaulding, Luke Shulenburger, Sarah T. Stewart, Stein B. Jacobsen
GEOPHYSICAL RESEARCH LETTERS
(2018)
Article
Physics, Condensed Matter
Jeongnim Kim, Andrew T. Baczewski, Todd D. Beaudet, Anouar Benali, M. Chandler Bennett, Mark A. Berrill, Nick S. Blunt, Edgar Josue, Landinez Borda, Michele Casula, David M. Ceperley, Simone Chiesa, Bryan K. Clark, Raymond C. Clay, Kris T. Delaney, Mark Dewing, Kenneth P. Esler, Hongxia Hao, Olle Heinonen, Paul R. C. Kent, Jaron T. Krogel, Ilkka Kylanpaa, Ying Wai Li, M. Graham Lopez, Ye Luo, Fionn D. Malone, Richard M. Martin, Amrita Mathuriya, Jeremy McMinis, Cody A. Melton, Lubos Mitas, Miguel A. Morales, Eric Neuscamman, William D. Parker, Sergio D. Pineda Flores, Nichols A. Romero, Brenda M. Rubenstein, Jacqueline A. R. Shea, Hyeondeok Shin, Luke Shulenburger, Andreas F. Tillack, Joshua P. Townsend, Norm M. Tubman, Brett Van der Goetz, Jordan E. Vincent, D. ChangMo Yang, Yubo Yang, Shuai Zhang, Luning Zhao
JOURNAL OF PHYSICS-CONDENSED MATTER
(2018)
Article
Chemistry, Physical
M. Chandler Bennett, Guangming Wang, Abdulgani Annaberdiyev, Cody A. Melton, Luke Shulenburger, Lubos Mitas
JOURNAL OF CHEMICAL PHYSICS
(2018)
Article
Chemistry, Physical
Ye Luo, Kenneth P. Esler, Paul R. C. Kent, Luke Shulenburger
JOURNAL OF CHEMICAL PHYSICS
(2018)
Article
Chemistry, Physical
Abdulgani Annaberdiyev, Guangming Wang, Cody A. Melton, M. Chandler Bennett, Luke Shulenburger, Lubos Mitas
JOURNAL OF CHEMICAL PHYSICS
(2018)
Article
Chemistry, Physical
Guangming Wang, Abdulgani Annaberdiyev, Cody A. Melton, M. Chandler Bennett, Luke Shulenburger, Lubos Mitas
JOURNAL OF CHEMICAL PHYSICS
(2019)
Article
Multidisciplinary Sciences
Yingwei Fei, Christopher T. Seagle, Joshua P. Townsend, Chad A. McCoy, Asmaa Boujibar, Peter Driscoll, Luke Shulenburger, Michael D. Furnish
Summary: The research reports high melting temperatures of MgSiO3 at 500 GPa, providing important data for understanding the thermal evolution of the interiors of Earth and super-Earths.
NATURE COMMUNICATIONS
(2021)
Editorial Material
Chemistry, Physical
Miguel A. Morales-Silva, Kenneth D. Jordan, Luke Shulenburger, Lucas K. Wagner
Summary: Stochastic methods in electronic structure have seen rapid growth in recent years, with applications to both molecules and solids, accurately describing systems with strong electron correlation. This growth is driven by favorable scaling with the number of electrons and better parallelization over large numbers of CPU cores or GPUs.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Physics, Fluids & Plasmas
D. A. Yager-Elorriaga, F. W. Doss, G. A. Shipley, P. F. Knapp, D. E. Ruiz, A. J. Porwitzky, J. R. Fein, E. C. Merritt, M. R. Martin, C. E. Myers, C. A. Jennings, I. C. Smith, D. J. Marshall, C. R. Aragon, L. Shulenburger, T. R. Mattsson, D. B. Sinars
Summary: The Decel platform at Sandia National Laboratories investigates the Richtmyer-Meshkov instability (RMI) in converging geometry under high energy density conditions. The platform has been improved to enhance stability and data acquisition, allowing for the study of RMI in different stages of evolution. Experimental results demonstrate the effectiveness of the platform and its utility for benchmarking simulations.
PHYSICS OF PLASMAS
(2022)
Article
Chemistry, Physical
Anouar Benali, Kevin Gasperich, Kenneth D. Jordan, Thomas Applencourt, Ye Luo, M. Chandler Bennett, Jaron T. Krogel, Luke Shulenburger, Paul R. C. Kent, Pierre-Francois Loos, Anthony Scemama, Michel Caffarel
JOURNAL OF CHEMICAL PHYSICS
(2020)
Article
Materials Science, Multidisciplinary
Philippe F. Weck, Kyle R. Cochrane, Seth Root, J. Matthew D. Lane, Luke Shulenburger, John H. Carpenter, Travis Sjostrom, Thomas R. Mattsson, Tracy J. Vogler
Proceedings Paper
Computer Science, Hardware & Architecture
Amrita Mathuriya, Ye Luo, Anouar Benali, Luke Shulenburger, Jeongnim Kim
2017 31ST IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM (IPDPS)
(2017)
Article
Materials Science, Multidisciplinary
R. Nazarov, L. Shulenburger, M. Morales, Randolph Q. Hood
