The exterior derivative and the mean value equality in $\mathbb{R}^n$
This work provides a theoretical foundation and computational tool for analysis and vector calculus, with potential applications in numerical methods, but it is incremental as it revisits and extends classical results.
The paper tackles the problem of generalizing the exterior derivative and Mean Value Theorem to higher dimensions for differential forms, resulting in a formulation of Stokes' theorem that relaxes smoothness requirements and a practical algorithm for computation without mesh discretization.
This survey revisits classical results in vector calculus and analysis by exploring a generalised perspective on the exterior derivative, interpreting it as a measure of "infinitesimal flux". This viewpoint leads to a higher-dimensional analogue of the Mean Value Theorem, valid for differential $k$-forms, and provides a natural formulation of Stokes' theorem that mirrors the exact hypotheses of the Fundamental Theorem of Calculus -- without requiring full $C^1$ smoothness of the differential form. As a numerical application, we propose an algorithm for exterior differentiation in $\mathbb{R}^n$ that relies solely on black-box access to the differential form, offering a practical tool for computation without the need for mesh discretization or explicit symbolic expressions.