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The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry
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有效的代任意高阶方法:低阶和高阶之间的自适应性桥梁.

Lorenzo Micalizzi1, Davide Torlo2, Walter Boscheri3

  • 1Institute of Mathematics, University of Zurich, Winterthurerstrasse 190, Zurich, 8057 Switzerland.

Communications on applied mathematics and computation
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概括

我们为高效的p-自适应高阶方法引入了一种新的方法. 这种方法提高了准确性匹配,并使计算流体动力学的自然p适应性成为可能,提高了效率.

关键词:
随意衍生品 (ADER) 是一种自主衍生品.随意的高层秩序.推迟纠正 (DeC) 是指推迟的纠正.保持积极性的积极性p-适应性 适应性 适应性

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科学领域:

  • 计算流体动力学的流体动力学.
  • 数字分析 数字分析
  • 科学计算科学计算

背景情况:

  • 高阶数值方法对于准确地解决复杂的偏微分方程 (PDEs) 是至关重要的.
  • 现有的代方案往往需要仔细调整,以平衡准确性和计算成本.
  • p-适应性,局部调整多项式顺序,提供了效率的潜力,但可能具有挑战性.

研究的目的:

  • 为高效的p-自适应任意高阶方法开发一个新的范式.
  • 修改现有的代方案以自然结合p-适应性.
  • 为了提高计算效率和稳定性在解决过度波 PDEs.

主要方法:

  • 修改任意的高阶代方案,使代精度与离散精度相匹配.
  • 重构任意衍生 (ADER) 方法作为延期校正 (DeC) 方案.
  • 集成一个局部后期限制器,以保持p适应性和结构保存.

主要成果:

  • 修改后的方法通过在代中对准准确度来实现计算优势.
  • 自然的p适应性是通过根据定义条件停止代来实现的.
  • 这种方法可以很容易地集成到现有实现中,而不会影响并行性.

结论:

  • 拟议的框架为任意的高阶方法提供了更有效的表述.
  • 该方法在可压缩气体动态基准上证明了稳定性和计算效率.
  • 这项工作有助于为PDEs设计先进的,自适应的数值解决器.