Is the Putnam Solution for Var(fg) Inequality Correct?

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SUMMARY

The discussion centers on the Putnam Solution for the inequality involving the variance of the product of two continuous real-valued functions, specifically stating that for functions \(f\) and \(g\) defined on the interval \([0,1]\), the inequality \(\mathrm{Var}(fg) \leq 2 \mathrm{Var}(f) M(g)^2 + 2 \mathrm{Var}(g) M(f)^2\) holds true. The proof utilizes the definitions of variance and maximum value, along with properties of integrals. The solution is attributed to Kiran Kedlaya and associates, and it effectively demonstrates the relationship between the variances and maximum values of the functions involved.

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Here is this week's POTW:

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For any continuous real-valued function $f$ defined on the interval $[0,1]$, let
\begin{gather*}
\mu(f) = \int_0^1 f(x)\,dx, \,
\mathrm{Var}(f) = \int_0^1 (f(x) - \mu(f))^2\,dx, \\
M(f) = \max_{0 \leq x \leq 1} \left| f(x) \right|.
\end{gather*}
Show that if $f$ and $g$ are continuous real-valued functions defined on the interval $[0,1]$, then
\[
\mathrm{Var}(fg) \leq 2 \mathrm{Var}(f) M(g)^2 + 2 \mathrm{Var}(g) M(f)^2.
\]

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No one answered this week's question, which was Problem B-4 in the 2013 Putnam archive. The solution, attributed to Kiran Kedlaya and associates, follows.

[sp]
$\newcommand{\Var}{\mathrm{Var}}$

Write $f_0(x) = f(x)-\mu(f)$ and $g_0(x) = g(x)-\mu(g)$, so that $\int_0^1 f_0(x)^2\,dx = \Var(f)$, $\int_0^1 g_0(x)^2\,dx = \Var(g)$, and $\int_0^1 f_0(x)\,dx = \int_0^1 g_0(x)\,dx = 0$. Now since $|g(x)| \leq M(g)$ for all $x$, $0\leq \int_0^1 f_0(x)^2(M(g)^2-g(x)^2)\,dx = \Var(f) M(g)^2-\int_0^1 f_0(x)^2g(x)^2\,dx$, and similarly $0 \leq \Var(g)M(f)^2-\int_0^1 f(x)^2g_0(x)^2\,dx$. Summing gives
\begin{equation}
\Var(f)M(g)^2+\Var(g)M(f)^2
\geq \int_0^1 (f_0(x)^2g(x)^2+f(x)^2g_0(x)^2)\,dx. \qquad (1)
\end{equation}
Now
\begin{align*}
&\int_0^1 (f_0(x)^2g(x)^2+f(x)^2g_0(x)^2)\,dx-\Var(fg) \\&= \int_0^1 (f_0(x)^2g(x)^2+f(x)^2g_0(x)^2-(f(x)g(x)-\int_0^1 f(y)g(y)\,dy)^2)\,dx;
\end{align*}
substituting $f_0(x)+\mu(f)$ for $f(x)$ everywhere and $g_0(x)+\mu(g)$ for $g(x)$ everywhere, and using the fact that $\int_0^1 f_0(x)\,dx = \int_0^1 g_0(x)\,dx = 0$, we can expand and simplify the right hand side of this equation to obtain
\begin{align*}
&\int_0^1 (f_0(x)^2g(x)^2+f(x)^2g_0(x)^2)\,dx-\Var(fg) \\
&= \int_0^1 f_0(x)^2g_0(x)^2\,dx \\
&-2\mu(f)\mu(g)\int_0^1 f_0(x)g_0(x)\,dx +(\int_0^1 f_0(x)g_0(x)\,dx)^2 \\
&\geq -2\mu(f)\mu(g)\int_0^1 f_0(x)g_0(x)\,dx.
\end{align*}
Because of (1), it thus suffices to show that
\begin{equation}
2\mu(f)\mu(g)\int_0^1 f_0(x)g_0(x)\,dx
\leq \Var(f)M(g)^2+\Var(g)M(f)^2. \qquad (2)
\end{equation}
Now since $(\mu(g) f_0(x)-\mu(f) g_0(x))^2 \geq 0$ for all $x$, we have
\begin{align*}
2\mu(f)\mu(g) \int_0^1 f_0(x)g_0(x)\,dx
& \leq \int_0^1 (\mu(g)^2 f_0(x)^2 + \mu(f)^2 g_0(x)^2) dx \\
& = \Var(f) \mu(g)^2 + \Var(g) \mu(f)^2 \\
& \leq \Var(f) M(g)^2 + \Var(g) M(f)^2,
\end{align*}
establishing (2) and completing the proof.
[/sp]
 

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