稀疏部分跟踪

摘要：

矩阵和更一般的多维数组，形成计算研究的支柱。在本文中，我们证明了通过在稀疏阵列上执行部分跟踪/张量收缩来提高计算效率。稀疏数组实际上是3个密集数组（密集形状，索引数组和数据数组）。这些组成数组的密集数组操作被用来确定所产生的部分跟踪。由于计算阵列被用于各种不同的研究，这些方法具有广泛的适用性。

英文摘要：

Matrices and more generally multidimensional arrays, form the backbone of computational studies. In this paper we demonstrate increases in computational efficiency by performing partial-tracing/tensor-contractions on sparse-arrays. It was shown that sparse-arrays are really 3 dense-arrays (dense-shape, index-array, and data-array). Dense-array manipulations of these constituent arrays are used to determine the resulting partial-trace. Because computational arrays are used in a verity of different studies, these methods are broadly applicable.

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