matplotlib/matplotlib: REL: v3.3.3

Caswell, Thomas A; Droettboom, Michael; Lee, Antony; Hunter, John; Andrade, Elliott Sales de; Firing, Eric; Hoffmann, Tim; Klymak, Jody M.; Stansby, David; Varoquaux, Nelle; Nielsen, Jens Hedegaard; Root, Benjamin; May, Ryan; Elson, Phil; Seppänen, Janne; Dale, Darren; Lee, Jae‐Joon; McDougall, Damon; Straw, Andrew; Hobson, Paul; Gohlke, Christoph; Yu, Tony S; Ma, Eric; Vincent, Adrien F.; Silvester, Steven; Moad, Charlie; hannah,; Kniazev, Nikita; Ernest, Elan; Ivanov, Paul

doi:10.5281/zenodo.4268928

Cited by 13 publications

(7 citation statements)

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“…Computations were performed with the SpECTRE code [11] on the Minerva cluster at the Max Planck Institute for Gravitational Physics. The figures in this article were produced with dgpy [40], matplotlib [41,42], TikZ [43] and ParaView [44].…”

Section: Acknowledgmentsmentioning

confidence: 99%

Unified discontinuous Galerkin scheme for a large class of elliptic equations

Fischer,

Pfeiffer

2021

Preprint

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We present a discontinuous Galerkin internal-penalty scheme that is applicable to a large class of linear and non-linear elliptic partial differential equations. The scheme constitutes the foundation of the elliptic solver for the SpECTRE numerical relativity code. As such it can accommodate (but is not limited to) elliptic problems in linear elasticity, general relativity and hydrodynamics, including problems formulated on a curved manifold. We provide practical instructions that make the scheme functional in a production code, such as instructions for imposing a range of boundary conditions, for implementing the scheme on curved and non-conforming meshes and for ensuring the scheme is compact and symmetric so it may be solved more efficiently. We report on the accuracy of the scheme for a suite of numerical test problems.

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Section: Acknowledgmentsmentioning

confidence: 99%

Unified discontinuous Galerkin scheme for a large class of elliptic equations

Fischer,

Pfeiffer

2021

Preprint

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“…Software: Astropy version 4.2 (Robitaille et al 2013;Price-Whelan et al 2018), Matplotlib version 3.3.3 (Hunter 2007Caswell et al 2020), NumPy version 1.19.5 (Harris et al 2020), SciPy version 1.6.0 (Virtanen et al 2020a,b)…”

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confidence: 99%

Magnetic Activity of F-, G-, and K-type Stars in the LAMOST–Kepler Field

Zhang

et al. 2020

ApJS

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Monitoring chromospheric and photospheric indexes of magnetic activity can provide valuable information, especially the interaction between different parts of the atmosphere and their response to magnetic fields. We extract chromospheric indexes, S and + R HK , for 59,816 stars from LAMOST spectra in the LAMOST-Kepler program, and photospheric index, R eff , for 5575 stars from Kepler light curves. The log R eff shows positive correlation with log + R HK . We estimate the power-law indexes between R eff and + R HK for F-, G-, and K-type stars, respectively. We also confirm the dependence of both chromospheric and photospheric activity on stellar rotation. Ca II H and K emissions and photospheric variations generally decrease with increasing rotation periods for stars with rotation periods exceeding a few days. The power-law indexes in exponential decay regimes show different characteristics in the two activity-rotation relations. The updated largest sample including the activity proxies and reported rotation periods provides more information to understand the magnetic activity for cool stars.

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“…Charm++ [38] was developed by the Parallel Programming Laboratory in the Department of Computer Science at the University of Illinois at Urbana-Champaign. The figures in this article were produced with dgpy [70], matplotlib [71,72], TikZ [73] and ParaView…”

Section: Acknowledgmentsmentioning

confidence: 99%

A scalable elliptic solver with task-based parallelism for the SpECTRE numerical relativity code

Vu,

Pfeiffer,

Bonilla

et al. 2021

Preprint

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Elliptic partial differential equations must be solved numerically for many problems in numerical relativity, such as initial data for every simulation of merging black holes and neutron stars. Existing elliptic solvers can take multiple days to solve these problems at high resolution and when matter is involved, because they are either hard to parallelize or require a large amount of computational resources. Here we present a new solver for linear and non-linear elliptic problems that is designed to scale with resolution and to parallelize on computing clusters. To achieve this we employ a discontinuous Galerkin discretization, an iterative multigrid-Schwarz preconditioned Newton-Krylov algorithm, and a task-based parallelism paradigm. To accelerate convergence of the elliptic solver we have developed novel subdomain-preconditioning techniques. We find that our multigrid-Schwarz preconditioned elliptic solves achieve iteration counts that are independent of resolution, and our task-based parallel programs scale over 200 million degrees of freedom to at least a few thousand cores. Our new code solves a classic black-hole binary initial-data problem faster than the spectral code SpEC when distributed to only eight cores, and in a fraction of the time on more cores. It is publicly accessible in the next-generation SpECTRE numerical relativity code. Our results pave the way for highly-parallel elliptic solves in numerical relativity and beyond.

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matplotlib/matplotlib: REL: v3.3.3

Cited by 13 publications

References 0 publications

Unified discontinuous Galerkin scheme for a large class of elliptic equations

Unified discontinuous Galerkin scheme for a large class of elliptic equations

Magnetic Activity of F-, G-, and K-type Stars in the LAMOST–Kepler Field

A scalable elliptic solver with task-based parallelism for the SpECTRE numerical relativity code

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