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What is the gradient of a scalar function of a symmetric matrix ?

Numerical Analysis 2022-08-17 v2 Numerical Analysis

Abstract

Perusal of research articles that deal with the topic of matrix calculus reveal two different approaches to calculation of the gradient of a real-valued function of a symmetric matrix leading to two different results. In the mechanics and physics communities, the gradient is calculated using the definition of a \frechet derivative, irrespective of whether the argument is symmetric or not. However, members of the statistics, economics, and electrical engineering communities use another notion of the gradient that explicitly takes into account the symmetry of the matrix, and this "symmetric gradient" GsG_s is reported to be related to the gradient GG computed from the \frechet derivative with respect to a general matrix as Gs=G+GTGIG_s = G + G^T - G \circ I, where \circ denotes the elementwise Hadamard product of the two matrices. We demonstrate that this relation is incorrect, and reconcile both these viewpoints by proving that Gs=sym(G)G_s = \mathrm{sym}(G).

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Cite

@article{arxiv.1911.06491,
  title  = {What is the gradient of a scalar function of a symmetric matrix ?},
  author = {Shriram Srinivasan and Nishant Panda},
  journal= {arXiv preprint arXiv:1911.06491},
  year   = {2022}
}

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11 pages