Real Analysis 2

Partial Derivatives & Consequences

Partial derivatives, sufficient conditions for differentiability, mixed partials, Mean Value Theorem, and Directional Derivatives.

Partial Derivatives

Let \(f: \Omega \subset \mathbb{R}^n \to \mathbb{R}\), where \(a \in \Omega\) (open).

Definition: Partial Derivative

\(f\) is said to be differentiable in the \(j\)-th variable at \(x=a\) if

\[ \lim_{t \to 0} \frac{f(a+te_j) - f(a)}{t} \text{ exists.} \]

(where \((a_1, \dots, a_j+t, \dots, a_n) = a + te_j\)).

It is called the partial derivative of \(f\) at \(x=a\), denoted as \(D_j f(a)\):

\[ D_j f(a) := \lim_{t \to 0} \frac{f(a+te_j) - f(a)}{t} \]
Remark

If \(g(t) = f(a+te_j)\) (\(t \in \mathbb{R}\)), then \(g(0) = f(a)\). And \(\frac{g(t)-g(0)}{t-0} = \frac{f(a+te_j)-f(a)}{t}\).

Suppose \(f\) admits a maximum or minimum at an interior point \(a\) of \(A\), where \(f: A \to \mathbb{R}\). If the \(j\)-th partial derivative of \(f\) exists at \(x=a\), then it must be zero.

Proposition

If \(f\) is differentiable at \(x=a\), then for \(1 \le j \le n\), \(D_j f(a)\) exists.


Proof: We have \(\lim_{h \to 0} \frac{|f(a+h) - f(a) - Df(a)(h)|}{|h|} = 0\).

Substitute \(h = te_j\). As \(t \to 0\), \(h \to 0\).

\[ \lim_{t \to 0} \frac{|f(a+te_j) - f(a) - Df(a)(te_j)|}{|t|} = 0 \] \[ \implies \lim_{t \to 0} \left| \frac{f(a+te_j) - f(a) - tDf(a)(e_j)}{t} \right| = 0 \] \[ \implies \lim_{t \to 0} \left| \frac{f(a+te_j) - f(a)}{t} - Df(a)(e_j) \right| = 0 \]

Thus, \(\lim_{t \to 0} \frac{f(a+te_j) - f(a)}{t} = Df(a)(e_j)\). Hence, \(D_j f(a) = Df(a)(e_j)\) (Partial derivative w.r.t \(j\)-th coord). ∎

Remark

\(f'(a) = [Df(a)(e_1) \dots Df(a)(e_n)]\).

The converse is not true in general. The existence of partial derivatives does not guarantee total differentiability.

Sufficient Condition
Claim: Sufficient Condition for Differentiability

Suppose \(f: \Omega \subset \mathbb{R}^n \to \mathbb{R}\). Then \(f\) is differentiable at \(x=a\) if all partial derivatives of \(f\) exist at \(x=a\) and are also continuous at \(a\).

Then \(f\) is diff at \(x=a\) and \(Df(a)(h) = \sum_{j=1}^{n} h_j D_j f(a)\), where \(h = \sum_{j=1}^{n} h_j e_j = (h_1, \dots, h_n)^T\).


Proof: Let \(a = \sum_{j=1}^{n} a_j e_j\), \(h = \sum_{j=1}^{n} h_j e_j\).

We decompose the difference \(f(a+h) - f(a)\) by adding and subtracting intermediate points:

\begin{align*} f(a+h) - f(a) &= f(a_1+h_1, \dots, a_n+h_n) - f(a_1, \dots, a_n) \\ &= [f(a_1+h_1, \dots, a_n+h_n) - f(a_1+h_1, \dots, a_{n-1}+h_{n-1}, a_n)] \\ &\quad + \dots + [f(a_1+h_1, a_2, \dots, a_n) - f(a_1, \dots, a_n)] \end{align*}

By Mean Value Theorem (MVT) in one variable for each term:

\[ = D_n f(c_n)h_n + D_{n-1} f(c_{n-1})h_{n-1} + \dots + D_1 f(c_1)h_1 \]

where \(c_j\) lies on the line segment. Observe that \(c_j \to a\) as \(h \to 0\) for \(1 \le j \le n\).

By continuity of \(D_j f\) at \(x=a\) (\(1 \le j \le n\)), \(D_j f(c_j) \to D_j f(a)\).

\[ \left| f(a+h) - f(a) - \sum_{j=1}^{n} h_j D_j f(a) \right| = \left| \sum_{j=1}^{n} h_j D_j f(c_j) - \sum_{j=1}^{n} h_j D_j f(a) \right| \] \[ \le \sum_{j=1}^{n} \frac{|h_j|}{|h|} |D_j f(c_j) - D_j f(a)| \le \sum_{j=1}^{n} |D_j f(c_j) - D_j f(a)| \to 0 \text{ as } h \to 0 \]

Since \(\frac{|h_j|}{|h|} \le 1\), the limit goes to 0, establishing differentiability. ∎

Continuous Differentiability and Mixed Partials

\(f: \Omega \subset \mathbb{R}^n \to \mathbb{R}^m\) is continuously differentiable (or \(C^1\)) at \(a \iff f\) is diff at \(a\) and \(f'(a) = (D_1 f(a), \dots, D_n f(a))\) is continuous.

We will also denote \(D_i f(a) = \frac{\partial f}{\partial x_i}(a)\).

Definition: \(k\)-times continuously differentiable

\(f: \mathbb{R}^n \to \mathbb{R}\) is said to be \(k\)-times continuously differentiable (\(C^k\)) if all partial derivatives of \(f\) up to (including) order \(k\) exist and are continuous in \(\Omega\).

Theorem: Equality of Mixed Partials (Clairaut's Theorem)

Let \(f: \Omega \subset \mathbb{R}^2 \to \mathbb{R}\). If \(f\) is continuously differentiable twice in \(\Omega\), then \(D_1 D_2 f(a,b) = D_2 D_1 f(a,b)\) for all \((a,b) \in \Omega\).


Proof: Consider a rectangle defined by \((a,b), (a+h,b), (a,b+k), (a+h, b+k)\).

Let \(\Phi(s) = f(s, b+k) - f(s,b)\) for \(s \in [a, a+h]\).
Let \(\Psi(t) = f(a+h, t) - f(a,t)\) for \(t \in [b, b+k]\).

Observe that \(\Phi(a+h) - \Phi(a) = \Psi(b+k) - \Psi(b) = f(a+h, b+k) - f(a+h, b) - f(a, b+k) + f(a, b)\).

\(\Phi\) is continuous in \([a, a+h]\) and differentiable in \((a, a+h)\). \(\Psi\) is continuous in \([b, b+k]\) and differentiable in \((b, b+k)\).

By MVT, \(\exists s_0 \in (a, a+h)\) such that \(\Phi(a+h) - \Phi(a) = h \cdot \Phi'(s_0)\).
And \(\exists t_1 \in (b, b+k)\) such that \(\Psi(b+k) - \Psi(b) = k \cdot \Psi'(t_1)\).

Now, \([D_1 f(s_0, b+k) - D_1 f(s_0, b)] \cdot h = [D_2 f(a+h, t_1) - D_2 f(a, t_1)] \cdot k\).

Applying MVT again to \(D_1 f\) and \(D_2 f\), \(\exists t_0 \in (b, b+k)\) & \(s_1 \in (a, a+h)\) such that:

\[ [D_2 D_1 f(s_0, t_0) \cdot k] \cdot h = [D_1 D_2 f(s_1, t_1) \cdot h] \cdot k \]

For \(h, k \neq 0\), \(D_2 D_1 f(s_0, t_0) = D_1 D_2 f(s_1, t_1)\).

Taking limit as \((h,k) \to (0,0)\), we get \((s_0, t_0) \to (a,b)\) and \((s_1, t_1) \to (a,b)\).
Using the hypothesis that \(f\) is twice continuously differentiable, we conclude \(D_2 D_1 f(a,b) = D_1 D_2 f(a,b)\). ∎

Consequences of Chain Rule
Theorem: Mean Value Theorem (MVT)

Suppose \(f: \Omega \to \mathbb{R}\) is a differentiable function and \(a,b \in \Omega\) such that the line segment \(a+t(b-a)\), \(0 \le t \le 1\) with the end points \(a\) & \(b\) lies in \(\Omega\).

Then \(\exists c\) on this line segment such that \(f(b) - f(a) = Df(c)(b-a)\).


Proof: Let \(\phi(t) = f(a+t(b-a))\) for \(t \in [0,1]\).

The map \(t \mapsto a+t(b-a)\) is differentiable on \((0,1)\) & continuous on \([0,1]\). \(f\) is differentiable on \(\Omega\). So \(\phi\) is continuous on \([0,1]\) & differentiable on \((0,1)\).

By 1D MVT, \(\exists t_0 \in (0,1)\) such that \(\phi'(t_0) = \phi(1) - \phi(0) = f(b) - f(a)\).

We have \(\phi'(t) = Df(a+t(b-a)) \cdot D(a+t(b-a))|_{t=t_0} = Df(c) \cdot (b-a)\) where \(c = a+t_0(b-a)\).

So \(f(b) - f(a) = Df(c)(b-a)\). ∎

Directional Derivatives

\(D_j f(a) = Df(a)(e_j)\), when derivative of \(f\) exists at \(x=a\).
\(\phi(t) = f(a+te_j)\) is diff at \(t=0\), when \(D_j f(a)\) exists.
\(\frac{d}{dt}|_{t=0} \phi(t) = Df(a)(e_j)\).

Definition: Directional Derivative

Let \(f: \Omega \to \mathbb{R}\), \(a \in \Omega\), \(0 \neq v \in \mathbb{R}^n\). Define the directional derivative of \(f\) at \(a\) w.r.t \(v\) as:

\[ D_v f(a) := \lim_{t \to 0} \frac{f(a+tv) - f(a)}{t} = \left. \frac{d}{dt} \right|_{t=0} f(a+tv) \]

if it exists. If \(Df(a)\) exists, \(D_v f(a)\) exists and equals \(Df(a)(v)\).

Consequences
  1. Suppose \(f: \Omega \to \mathbb{R}\) is diff at \(x=a\). Then \(D_v f(a)\) exists & is equal to \(Df(a)(v)\).
  2. Suppose \(f\) is Ctsly diff and say \(\exists\) diff fun \(g: \mathbb{R} \to \mathbb{R}\) st \(g(f(x)) = x \forall x \in \Omega\).
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