The Jacobian matrix collects all first partial derivatives of a differentiable map. When it is square, its Jacobian determinant gives the signed local volume factor.
The Jacobian matrix contains all first partial derivatives of a coordinate transformation.
To deduce from , the remainder must be small in a topology controlling its spatial derivatives, such as locally. Small displacement alone is insufficient: differs uniformly from the identity by , but has Jacobian determinant at for nonzero . A smooth flow map generated by a smooth vector field has the required derivative control.
The Jacobian matrix and determinant describe respectively the linear derivative and its signed volume factor.
For a smooth map , set . In Einstein summation convention, applying the product rule leaves only the term differentiating : the terms with second derivatives cancel against antisymmetry. The remaining Levi-Civita symbol contraction is , so . Equivalently this vector field is one third of the cofactor matrix transposed, applied to .

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The Jacobian matrix and its determinant play a significant role in multivariable calculus, particularly in the study of transformations and functions of several variables. ### Jacobian Matrix The Jacobian matrix is a matrix of first-order partial derivatives of a vector-valued function.