DefineThey sum to , with and . Interchanging two slots of a tensor still produces a tensor, so these are a symmetric second-rank tensor and an antisymmetric second-rank tensor, not merely symmetric and antisymmetric arrays in a selected frame.
For uniqueness, if , then . The common difference is both symmetric and antisymmetric, so each of its components equals its own negative and vanishes over . Thus the decomposition is unique. These are the symmetric and antisymmetric parts of a matrix, with their tensor transformation law preserved.
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