Subject 01
Topology & Differential Calculus in ℝⁿ
The metric structure of finite-dimensional spaces and the differential calculus of vector-valued maps, carried to submanifolds and constrained extrema.
A
Norms, Compactness & Derivatives
Equivalence of Norms in Finite Dimensions
Prove that all norms on a finite-dimensional space are equivalent, and derive the Heine–Borel theorem together with the Bolzano–Weierstrass property for closed bounded subsets of ℝⁿ.
Fréchet vs. Gâteaux Derivatives
Compare the full (Fréchet) derivative with directional (Gâteaux) differentiability; compute the Jacobi matrix and prove that continuous partials suffice for class C¹.
Mean Value Inequality for Vector Maps
Establish the operator-norm mean value bound ‖f(x) − f(y)‖ ≤ sup‖Df‖·‖x − y‖ and extend differentiation to higher multilinear maps.
B
Higher Derivatives, Submanifolds & Constrained Extrema
Schwarz Symmetry & the Taylor Formula
Prove equality of mixed partials under continuity hypotheses, interpret the Hessian as a quadratic form, and state the second-order Taylor expansion in several variables.
Inverse & Implicit Function Theorems
Prove both theorems via the contraction mapping principle and derive their equivalence through block-manipulation of the Jacobi matrix.
Sard's Theorem
Show that the set of critical values of a sufficiently smooth map has measure zero, the cornerstone of transversality arguments.
Submanifolds of ℝⁿ
Characterize submanifolds as level sets of submersions; construct tangent and normal spaces and develop Lagrange multipliers together with the KKT conditions for inequality constraints.