In this work the influence of $5|7$ dislocations in multiplayer graphene stacks (up to six layers) is examined. The study is conducted through a recently developed Phase Field Crystal (PFC) model for multilayer systems incorporating out-of-plane deformations and parameterized to match to density functional theory calculations for graphene bilayers and other systems. The specific configuration considered consists of one monolayer containing four $5|7$ dislocations (i.e., two dislocation dipoles) sandwiched in between perfect graphene layers. The study reveals how the strain field from the dislocations in the defected layer leads to out-of-plane deformations that in turn cause deformations of neighboring layers. Quantitative predictions are made for the defect free energy of the multilayer stacks as compared to a defect-free system, which is shown to increase with the number of layers and system size. Furthermore it is predicted that system defect energy saturates by roughly ten sheets in the stack, indicating the range of defect influence across the multilayer. Variations of stress field distribution and layer height profiles in different layer of the stack are also quantitatively identified.
{"title":"Influence of dislocations in multilayer graphene stacks: A phase field crystal study","authors":"K. R. Elder, Zhi-Feng Huang, T. Ala-Nissila","doi":"arxiv-2409.12073","DOIUrl":"https://doi.org/arxiv-2409.12073","url":null,"abstract":"In this work the influence of $5|7$ dislocations in multiplayer graphene\u0000stacks (up to six layers) is examined. The study is conducted through a\u0000recently developed Phase Field Crystal (PFC) model for multilayer systems\u0000incorporating out-of-plane deformations and parameterized to match to density\u0000functional theory calculations for graphene bilayers and other systems. The\u0000specific configuration considered consists of one monolayer containing four\u0000$5|7$ dislocations (i.e., two dislocation dipoles) sandwiched in between\u0000perfect graphene layers. The study reveals how the strain field from the\u0000dislocations in the defected layer leads to out-of-plane deformations that in\u0000turn cause deformations of neighboring layers. Quantitative predictions are\u0000made for the defect free energy of the multilayer stacks as compared to a\u0000defect-free system, which is shown to increase with the number of layers and\u0000system size. Furthermore it is predicted that system defect energy saturates by\u0000roughly ten sheets in the stack, indicating the range of defect influence\u0000across the multilayer. Variations of stress field distribution and layer height\u0000profiles in different layer of the stack are also quantitatively identified.","PeriodicalId":501369,"journal":{"name":"arXiv - PHYS - Computational Physics","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Radhika Achikanath Chirakkara, Christoph Federrath, Amit Seta
We introduce $texttt{A}$strophysical $texttt{H}$ybrid-$texttt{K}$inetic simulations with the $texttt{flASH}$ code ($texttt{AHKASH}$) -- a new Hybrid particle-in-cell (PIC) code developed within the framework of the multi-physics code $texttt{FLASH}$. The new code uses a second-order accurate Boris integrator and a predictor-predictor-corrector algorithm for advancing the Hybrid-kinetic equations, using the constraint transport method to ensure that magnetic fields are divergence-free. The code supports various interpolation schemes between the particles and grid cells, with post-interpolation smoothing to reduce finite particle noise. We further implement a $delta f$ method to study instabilities in weakly collisional plasmas. The new code is tested on standard physical problems such as the motion of charged particles in uniform and spatially varying magnetic fields, the propagation of Alfv'en and whistler waves, and Landau damping of ion acoustic waves. We test different interpolation kernels and demonstrate the necessity of performing post-interpolation smoothing. We couple the $texttt{TurbGen}$ turbulence driving module to the new Hybrid PIC code, allowing us to test the code on the highly complex physical problem of the turbulent dynamo. To investigate steady-state turbulence with a fixed sonic Mach number, it is important to maintain isothermal plasma conditions. Therefore, we introduce a novel cooling method for Hybrid PIC codes and provide tests and calibrations of this method to keep the plasma isothermal. We describe and test the `hybrid precision' method, which significantly reduces (by a factor $sim1.5$) the computational cost, without compromising the accuracy of the numerical solutions. Finally, we test the parallel scalability of the new code, showing excellent scaling up to 10,000~cores.
{"title":"AHKASH: a new Hybrid particle-in-cell code for simulations of astrophysical collisionless plasma","authors":"Radhika Achikanath Chirakkara, Christoph Federrath, Amit Seta","doi":"arxiv-2409.12151","DOIUrl":"https://doi.org/arxiv-2409.12151","url":null,"abstract":"We introduce $texttt{A}$strophysical $texttt{H}$ybrid-$texttt{K}$inetic\u0000simulations with the $texttt{flASH}$ code ($texttt{AHKASH}$) -- a new Hybrid\u0000particle-in-cell (PIC) code developed within the framework of the multi-physics\u0000code $texttt{FLASH}$. The new code uses a second-order accurate Boris\u0000integrator and a predictor-predictor-corrector algorithm for advancing the\u0000Hybrid-kinetic equations, using the constraint transport method to ensure that\u0000magnetic fields are divergence-free. The code supports various interpolation\u0000schemes between the particles and grid cells, with post-interpolation smoothing\u0000to reduce finite particle noise. We further implement a $delta f$ method to\u0000study instabilities in weakly collisional plasmas. The new code is tested on\u0000standard physical problems such as the motion of charged particles in uniform\u0000and spatially varying magnetic fields, the propagation of Alfv'en and whistler\u0000waves, and Landau damping of ion acoustic waves. We test different\u0000interpolation kernels and demonstrate the necessity of performing\u0000post-interpolation smoothing. We couple the $texttt{TurbGen}$ turbulence\u0000driving module to the new Hybrid PIC code, allowing us to test the code on the\u0000highly complex physical problem of the turbulent dynamo. To investigate\u0000steady-state turbulence with a fixed sonic Mach number, it is important to\u0000maintain isothermal plasma conditions. Therefore, we introduce a novel cooling\u0000method for Hybrid PIC codes and provide tests and calibrations of this method\u0000to keep the plasma isothermal. We describe and test the `hybrid precision'\u0000method, which significantly reduces (by a factor $sim1.5$) the computational\u0000cost, without compromising the accuracy of the numerical solutions. Finally, we\u0000test the parallel scalability of the new code, showing excellent scaling up to\u000010,000~cores.","PeriodicalId":501369,"journal":{"name":"arXiv - PHYS - Computational Physics","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ravindra Shinde, Claudia Filippi, Anthony Scemama, William Jalby
The era of exascale computing presents both exciting opportunities and unique challenges for quantum mechanical simulations. While the transition from petaflops to exascale computing has been marked by a steady increase in computational power, the shift towards heterogeneous architectures, particularly the dominant role of graphical processing units (GPUs), demands a fundamental shift in software development strategies. This review examines the changing landscape of hardware and software for exascale computing, highlighting the limitations of traditional algorithms and software implementations in light of the increasing use of heterogeneous architectures in high-end systems. We discuss the challenges of adapting quantum chemistry software to these new architectures, including the fragmentation of the software stack, the need for more efficient algorithms (including reduced precision versions) tailored for GPUs, and the importance of developing standardized libraries and programming models.
{"title":"Exascale Quantum Mechanical Simulations: Navigating the Shifting Sands of Hardware and Software","authors":"Ravindra Shinde, Claudia Filippi, Anthony Scemama, William Jalby","doi":"arxiv-2409.11881","DOIUrl":"https://doi.org/arxiv-2409.11881","url":null,"abstract":"The era of exascale computing presents both exciting opportunities and unique\u0000challenges for quantum mechanical simulations. While the transition from\u0000petaflops to exascale computing has been marked by a steady increase in\u0000computational power, the shift towards heterogeneous architectures,\u0000particularly the dominant role of graphical processing units (GPUs), demands a\u0000fundamental shift in software development strategies. This review examines the\u0000changing landscape of hardware and software for exascale computing,\u0000highlighting the limitations of traditional algorithms and software\u0000implementations in light of the increasing use of heterogeneous architectures\u0000in high-end systems. We discuss the challenges of adapting quantum chemistry\u0000software to these new architectures, including the fragmentation of the\u0000software stack, the need for more efficient algorithms (including reduced\u0000precision versions) tailored for GPUs, and the importance of developing\u0000standardized libraries and programming models.","PeriodicalId":501369,"journal":{"name":"arXiv - PHYS - Computational Physics","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wei Si, Shifeng Li, Pingwen Zhang, An-Chang Shi, Kai Jiang
Interparticle interactions with multiple length scales play a pivotal role in the formation and stability of quasicrystals. Choosing a minimal set of length scales to stabilize a given quasicrystal is a challenging problem. To address this challenge, we propose an intelligent screening method (ISM) to design a Landau theory with a minimal number of length scales -- referred to as the minimal Landau theory -- that includes only the essential length scales necessary to stabilize quasicrystals. Based on a generalized multiple-length-scale Landau theory, ISM first evaluates various spectral configurations of candidate structures under a hard constraint. It then identifies the configuration with the lowest free energy. Using this optimal configuration, ISM calculates phase diagrams to explore the thermodynamic stability of desired quasicrystals. ISM can design a minimal Landau theory capable of stabilizing the desired quasicrystals by incrementally increasing the number of length scales. Our application of ISM has not only confirmed known behaviors in 10- and 12-fold quasicrystals but also led to a significant prediction that quasicrystals with 8-, 14-, 16-, and 18-fold symmetry could be stable within three-length-scale Landau models.
{"title":"Designing a minimal Landau theory to stabilize desired quasicrystals","authors":"Wei Si, Shifeng Li, Pingwen Zhang, An-Chang Shi, Kai Jiang","doi":"arxiv-2409.11830","DOIUrl":"https://doi.org/arxiv-2409.11830","url":null,"abstract":"Interparticle interactions with multiple length scales play a pivotal role in\u0000the formation and stability of quasicrystals. Choosing a minimal set of length\u0000scales to stabilize a given quasicrystal is a challenging problem. To address\u0000this challenge, we propose an intelligent screening method (ISM) to design a\u0000Landau theory with a minimal number of length scales -- referred to as the\u0000minimal Landau theory -- that includes only the essential length scales\u0000necessary to stabilize quasicrystals. Based on a generalized\u0000multiple-length-scale Landau theory, ISM first evaluates various spectral\u0000configurations of candidate structures under a hard constraint. It then\u0000identifies the configuration with the lowest free energy. Using this optimal\u0000configuration, ISM calculates phase diagrams to explore the thermodynamic\u0000stability of desired quasicrystals. ISM can design a minimal Landau theory\u0000capable of stabilizing the desired quasicrystals by incrementally increasing\u0000the number of length scales. Our application of ISM has not only confirmed\u0000known behaviors in 10- and 12-fold quasicrystals but also led to a significant\u0000prediction that quasicrystals with 8-, 14-, 16-, and 18-fold symmetry could be\u0000stable within three-length-scale Landau models.","PeriodicalId":501369,"journal":{"name":"arXiv - PHYS - Computational Physics","volume":"189 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We investigate the growth of two-dimensional (2D) crystals on fluctuating surfaces using a phase field crystal model that is relevant on atomic length and diffusive time scales. Motivated by recent experiments which achieved unprecedented fast growth of large-size high-quality 2D crystals on liquid substrates, we uncover novel effects of liquid surfaces on microstructural ordering. We find that substrate fluctuations generate short-ranged noise that speeds up crystallization and grain growth of the overlayer, surpassing that of free-standing system. Coupling to the liquid substrate fluctuations can also modulate local randomness, leading to intriguing disordered structures with hidden spatial order, i.e., disordered hyperuniformity. These results reveal the physical mechanisms underlying the fast growth of 2D crystals on liquid surfaces and demonstrate a novel strategy for synthesizing disordered hyperuniform thin film structures.
{"title":"Uncovering liquid-substrate fluctuation effects on crystal growth and disordered hyperuniformity of two-dimensional materials","authors":"S. K. Mkhonta, Zhi-Feng Huang, K. R. Elder","doi":"arxiv-2409.12090","DOIUrl":"https://doi.org/arxiv-2409.12090","url":null,"abstract":"We investigate the growth of two-dimensional (2D) crystals on fluctuating\u0000surfaces using a phase field crystal model that is relevant on atomic length\u0000and diffusive time scales. Motivated by recent experiments which achieved\u0000unprecedented fast growth of large-size high-quality 2D crystals on liquid\u0000substrates, we uncover novel effects of liquid surfaces on microstructural\u0000ordering. We find that substrate fluctuations generate short-ranged noise that\u0000speeds up crystallization and grain growth of the overlayer, surpassing that of\u0000free-standing system. Coupling to the liquid substrate fluctuations can also\u0000modulate local randomness, leading to intriguing disordered structures with\u0000hidden spatial order, i.e., disordered hyperuniformity. These results reveal\u0000the physical mechanisms underlying the fast growth of 2D crystals on liquid\u0000surfaces and demonstrate a novel strategy for synthesizing disordered\u0000hyperuniform thin film structures.","PeriodicalId":501369,"journal":{"name":"arXiv - PHYS - Computational Physics","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cynthia Ihuoma Osuala, Tanu Choudhary, Raju K. Biswas, Sudin Ganguly, Chunlei Qu, Santanu K. Maiti
We present a comprehensive study on enhancing the thermoelectric (TE) performance of bilayer graphene (BLG) through irradiation with arbitrarily polarized light, focusing on $AA$- and $AB$-stacked configurations with zigzag edges. Utilizing a combination of tight-binding theory and density functional theory (DFT), we systematically analyze the impact of light irradiation on electronic and phononic transport properties. Light irradiation alters the electronic hopping parameters, creating an asymmetric transmission function, which significantly increases the Seebeck coefficient, thereby boosting the overall {it figure of merit} (FOM). For the phononic contribution, DFT calculations reveal that $AB$-stacked BLG exhibits lower lattice thermal conductivity compared to $AA$-stacked, attributed to enhanced anharmonic scattering and phonon group velocity. The combined analysis shows that FOM exceeds unity in both stacking types, with notable improvements near the irradiation-induced gap. Additionally, we explore the dependence of FOM on the system dimensions and temperature, demonstrating that light-irradiated BLG holds great promise for efficient thermoelectric energy conversion and waste heat recovery. Our results show favorable responses over a wide range of irradiation parameters. These findings provide crucial insights into optimizing BLG for advanced TE applications through light-induced modifications.
{"title":"Thermolectricity in irradiated bilayer graphene flakes","authors":"Cynthia Ihuoma Osuala, Tanu Choudhary, Raju K. Biswas, Sudin Ganguly, Chunlei Qu, Santanu K. Maiti","doi":"arxiv-2409.10380","DOIUrl":"https://doi.org/arxiv-2409.10380","url":null,"abstract":"We present a comprehensive study on enhancing the thermoelectric (TE)\u0000performance of bilayer graphene (BLG) through irradiation with arbitrarily\u0000polarized light, focusing on $AA$- and $AB$-stacked configurations with zigzag\u0000edges. Utilizing a combination of tight-binding theory and density functional\u0000theory (DFT), we systematically analyze the impact of light irradiation on\u0000electronic and phononic transport properties. Light irradiation alters the\u0000electronic hopping parameters, creating an asymmetric transmission function,\u0000which significantly increases the Seebeck coefficient, thereby boosting the\u0000overall {it figure of merit} (FOM). For the phononic contribution, DFT\u0000calculations reveal that $AB$-stacked BLG exhibits lower lattice thermal\u0000conductivity compared to $AA$-stacked, attributed to enhanced anharmonic\u0000scattering and phonon group velocity. The combined analysis shows that FOM\u0000exceeds unity in both stacking types, with notable improvements near the\u0000irradiation-induced gap. Additionally, we explore the dependence of FOM on the\u0000system dimensions and temperature, demonstrating that light-irradiated BLG\u0000holds great promise for efficient thermoelectric energy conversion and waste\u0000heat recovery. Our results show favorable responses over a wide range of\u0000irradiation parameters. These findings provide crucial insights into optimizing\u0000BLG for advanced TE applications through light-induced modifications.","PeriodicalId":501369,"journal":{"name":"arXiv - PHYS - Computational Physics","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jonathan R. Church, Ofir Blumer, Tommer D. Keidar, Leo Ploutno, Shlomi Reuveni, Barak Hirshberg
We present a procedure for enhanced sampling of molecular dynamics simulations through informed stochastic resetting. Many phenomena, such as protein folding and crystal nucleation, occur over time scales that are inaccessible using standard simulation methods. We recently showed that stochastic resetting can accelerate molecular simulations that exhibit broad transition time distributions. However, standard stochastic resetting does not exploit any information about the reaction progress. Here, we demonstrate that an informed resetting protocol leads to greater accelerations than standard stochastic resetting, both for molecular dynamics and Metadynamics simulations. This is achieved by resetting only when a certain condition is met, e.g., when the distance from the target along the reaction coordinate is larger than some threshold. We then employ recently obtained theoretical results to identify the condition that leads to the greatest acceleration and to infer the unbiased mean transition time from accelerated simulations. Our work significantly extends the applicability of stochastic resetting for enhanced sampling of molecular simulations.
{"title":"Accelerating Molecular Dynamics through Informed Resetting","authors":"Jonathan R. Church, Ofir Blumer, Tommer D. Keidar, Leo Ploutno, Shlomi Reuveni, Barak Hirshberg","doi":"arxiv-2409.10115","DOIUrl":"https://doi.org/arxiv-2409.10115","url":null,"abstract":"We present a procedure for enhanced sampling of molecular dynamics\u0000simulations through informed stochastic resetting. Many phenomena, such as\u0000protein folding and crystal nucleation, occur over time scales that are\u0000inaccessible using standard simulation methods. We recently showed that\u0000stochastic resetting can accelerate molecular simulations that exhibit broad\u0000transition time distributions. However, standard stochastic resetting does not\u0000exploit any information about the reaction progress. Here, we demonstrate that\u0000an informed resetting protocol leads to greater accelerations than standard\u0000stochastic resetting, both for molecular dynamics and Metadynamics simulations.\u0000This is achieved by resetting only when a certain condition is met, e.g., when\u0000the distance from the target along the reaction coordinate is larger than some\u0000threshold. We then employ recently obtained theoretical results to identify the\u0000condition that leads to the greatest acceleration and to infer the unbiased\u0000mean transition time from accelerated simulations. Our work significantly\u0000extends the applicability of stochastic resetting for enhanced sampling of\u0000molecular simulations.","PeriodicalId":501369,"journal":{"name":"arXiv - PHYS - Computational Physics","volume":"104 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. -G. Dethero, J. Pratt, D. G. Vlaykov, I. Baraffe, T. Guillet, T. Goffrey, A. Le Saux, A. Morison
Theoretical descriptions of convective overshooting often rely on a one-dimensional parameterization of the flow called the filling factor for convection. Several definitions of the filling factor have been developed, based on: (1) the percentage of the volume, (2) the mass flux, and (3) the convective flux that moves through the boundary. We examine these definitions of the filling factor with the goal of establishing their ability to explain differences between 2D and 3D global simulations of stellar interiors that include fully compressible hydrodynamics and realistic microphysics for stars. We study pairs of identical two- and three-dimensional global simulations of stars produced with MUSIC, a fully compressible, time-implicit hydrodynamics code. We examine (1) a $3 M_odot$ red giant star near the first dredge-up point, (2) a $1 M_odot$ pre-main-sequence star with a large convection zone, (3) the current sun, and (4) a $20 M_odot$ main-sequence star with a large convective core. Our calculations of the filling factor based on the volume percentage and the mass flux indicate asymmetrical convection near the surface for each star with an outer convection zone. However, near the convective boundary, convective flows achieve inward-outward symmetry; for 2D and 3D simulations, these filling factors are indistinguishable. A filling factor based on the convective flux is contaminated by boundary-layer-like flows, making theoretical interpretation difficult. We present two new alternatives to these standard definitions, which compare flows at two different radial points. The first is the penetration parameter of Anders et al. (2022). The second is a new statistic, the plume interaction parameter. We demonstrate that both of these parameters capture systematic differences between 2D and 3D simulations around the convective boundary.
{"title":"The shape of convection in 2D and 3D global simulations of stellar interiors","authors":"M. -G. Dethero, J. Pratt, D. G. Vlaykov, I. Baraffe, T. Guillet, T. Goffrey, A. Le Saux, A. Morison","doi":"arxiv-2409.09815","DOIUrl":"https://doi.org/arxiv-2409.09815","url":null,"abstract":"Theoretical descriptions of convective overshooting often rely on a\u0000one-dimensional parameterization of the flow called the filling factor for\u0000convection. Several definitions of the filling factor have been developed,\u0000based on: (1) the percentage of the volume, (2) the mass flux, and (3) the\u0000convective flux that moves through the boundary. We examine these definitions\u0000of the filling factor with the goal of establishing their ability to explain\u0000differences between 2D and 3D global simulations of stellar interiors that\u0000include fully compressible hydrodynamics and realistic microphysics for stars.\u0000We study pairs of identical two- and three-dimensional global simulations of\u0000stars produced with MUSIC, a fully compressible, time-implicit hydrodynamics\u0000code. We examine (1) a $3 M_odot$ red giant star near the first dredge-up\u0000point, (2) a $1 M_odot$ pre-main-sequence star with a large convection zone,\u0000(3) the current sun, and (4) a $20 M_odot$ main-sequence star with a large\u0000convective core. Our calculations of the filling factor based on the volume\u0000percentage and the mass flux indicate asymmetrical convection near the surface\u0000for each star with an outer convection zone. However, near the convective\u0000boundary, convective flows achieve inward-outward symmetry; for 2D and 3D\u0000simulations, these filling factors are indistinguishable. A filling factor\u0000based on the convective flux is contaminated by boundary-layer-like flows,\u0000making theoretical interpretation difficult. We present two new alternatives to\u0000these standard definitions, which compare flows at two different radial points.\u0000The first is the penetration parameter of Anders et al. (2022). The second is a\u0000new statistic, the plume interaction parameter. We demonstrate that both of\u0000these parameters capture systematic differences between 2D and 3D simulations\u0000around the convective boundary.","PeriodicalId":501369,"journal":{"name":"arXiv - PHYS - Computational Physics","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
First-principles calculation software is of significant importance to material research and development, serving as a fundamental resource for analyzing the microscopic structure and properties of materials. Nevertheless, limitations on the scale of computations and the associated cost restrict the applicability of first-principles calculation within the materials field. The rapid development of heterogeneous computing, particularly General-Purpose Graphics Processing Units (GPGPUs), have heralded new prospects for the enhancement and cost-effectiveness of scientific computing. Utilizing GPGPUs, this paper boost the existing algorithms in Atomic-orbital Based Ab-initio Computation at UStc (ABACUS), a first-principles calculation software grounded on the linear combination of atomic orbitals (LCAO) basis set, with an overarching objective of increasing computation speed. The effectiveness of the computational acceleration has been clearly demonstrated through calculations on twisted bilayer graphene systems, spanning a wide range of scales, with systems as large as 10,444 carbon atoms.
{"title":"GPU acceleration of LCAO basis set first-principle calculations","authors":"Haochong Zhang, Shi Yin, Lixin He","doi":"arxiv-2409.09399","DOIUrl":"https://doi.org/arxiv-2409.09399","url":null,"abstract":"First-principles calculation software is of significant importance to\u0000material research and development, serving as a fundamental resource for\u0000analyzing the microscopic structure and properties of materials. Nevertheless,\u0000limitations on the scale of computations and the associated cost restrict the\u0000applicability of first-principles calculation within the materials field. The\u0000rapid development of heterogeneous computing, particularly General-Purpose\u0000Graphics Processing Units (GPGPUs), have heralded new prospects for the\u0000enhancement and cost-effectiveness of scientific computing. Utilizing GPGPUs,\u0000this paper boost the existing algorithms in Atomic-orbital Based Ab-initio\u0000Computation at UStc (ABACUS), a first-principles calculation software grounded\u0000on the linear combination of atomic orbitals (LCAO) basis set, with an\u0000overarching objective of increasing computation speed. The effectiveness of the\u0000computational acceleration has been clearly demonstrated through calculations\u0000on twisted bilayer graphene systems, spanning a wide range of scales, with\u0000systems as large as 10,444 carbon atoms.","PeriodicalId":501369,"journal":{"name":"arXiv - PHYS - Computational Physics","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PiNNAcLe is an implementation of our adaptive learn-on-the-fly algorithm for running machine-learning potential (MLP)-based molecular dynamics (MD) simulations -- an emerging approach to simulate the large-scale and long-time dynamics of systems where empirical forms of the PES are difficult to obtain. The algorithm aims to solve the challenge of parameterizing MLPs for large-time-scale MD simulations, by validating simulation results at adaptive time intervals. This approach eliminates the need of uncertainty quantification methods for labelling new data, and thus avoids the additional computational cost and arbitrariness thereof. The algorithm is implemented in the NextFlow workflow language (Di Tommaso et al., 2017). Components such as MD simulation and MLP engines are designed in a modular fashion, and the workflows are agnostic to the implementation of such modules. This makes it easy to apply the same algorithm to different references, as well as scaling the workflow to a variety of computational resources. The code is published under BSD 3-Clause License, the source code and documentation are hosted on Github. It currently supports MLP generation with the atomistic machine learning package PiNN (Shao et al., 2020), electronic structure calculations with CP2K (K"uhne et al., 2020) and DFTB+ (Hourahine et al., 2020), and MD simulation with ASE (Larsen et al., 2017).
{"title":"PiNNAcLe: Adaptive Learn-On-The-Fly Algorithm for Machine-Learning Potential","authors":"Yunqi Shao, Chao Zhang","doi":"arxiv-2409.08886","DOIUrl":"https://doi.org/arxiv-2409.08886","url":null,"abstract":"PiNNAcLe is an implementation of our adaptive learn-on-the-fly algorithm for\u0000running machine-learning potential (MLP)-based molecular dynamics (MD)\u0000simulations -- an emerging approach to simulate the large-scale and long-time\u0000dynamics of systems where empirical forms of the PES are difficult to obtain. The algorithm aims to solve the challenge of parameterizing MLPs for\u0000large-time-scale MD simulations, by validating simulation results at adaptive\u0000time intervals. This approach eliminates the need of uncertainty quantification\u0000methods for labelling new data, and thus avoids the additional computational\u0000cost and arbitrariness thereof. The algorithm is implemented in the NextFlow workflow language (Di Tommaso et\u0000al., 2017). Components such as MD simulation and MLP engines are designed in a\u0000modular fashion, and the workflows are agnostic to the implementation of such\u0000modules. This makes it easy to apply the same algorithm to different\u0000references, as well as scaling the workflow to a variety of computational\u0000resources. The code is published under BSD 3-Clause License, the source code and\u0000documentation are hosted on Github. It currently supports MLP generation with\u0000the atomistic machine learning package PiNN (Shao et al., 2020), electronic\u0000structure calculations with CP2K (K\"uhne et al., 2020) and DFTB+ (Hourahine et\u0000al., 2020), and MD simulation with ASE (Larsen et al., 2017).","PeriodicalId":501369,"journal":{"name":"arXiv - PHYS - Computational Physics","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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