Are these functions necessarily linearly independent?

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SUMMARY

The discussion centers on the linear independence of differentiable functions $x_1, x_2, \dots, x_n$ defined by a system of first-order linear differential equations with positive coefficients $a_{ij}$. It is established that if each function approaches zero as $t$ approaches infinity, then the functions are necessarily linearly independent. This conclusion is derived from the properties of the solutions to such differential equations, particularly in the context of the 1995 William Lowell Putnam Mathematical Competition.

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  • Knowledge of linear independence in the context of function spaces
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  • Basic concepts from real analysis and differential equations
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This discussion is beneficial for mathematicians, students preparing for mathematical competitions, and anyone interested in advanced topics in differential equations and linear algebra.

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Here is this week's POTW:

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Let $x_1, x_2,\dots,x_n$ be differentiable (real-valued) functions of a single variable $t$ which satisfy
\begin{align*}
\d{x_1}{t}&=a_{11}x_1+a_{12}x_2+\cdots+a_{1n}x_n \\
\d{x_2}{t}&=a_{21}x_1+a_{22}x_2+\cdots+a_{2n}x_n \\
\vdots \\
\d{x_n}{t}&=a_{n1}x_1+a_{n2}x_2+\cdots+a_{nn}x_n
\end{align*}
for some constants $a_{ij}>0$. Suppose that for all $i, \; x_i(t)\to 0$ as $t\to\infty$. Are the functions $x_1,x_2,\dots,x_n$ necessarily linearly independent?

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Re: Problem Of The Week # 216 - May 17, 2016

This was Problem A-5 in the 1995 William Lowell Putnam Mathematical Competition.

No one answered this week's POTW. The solution, attributed to Kiran Kedlaya and his associates, follows:

It is known that the set of solutions of a system of
linear first-order differential equations with constant coefficients
is $n$-dimensional, with basis vectors of the form $f_{i}(t)
\vec{v}_{i}$ (i.e.\ a function times a constant vector), where the
$\vec{v}_{i}$ are linearly independent. In
particular, our solution $\vec{x}(t)$ can be written as $\sum_{i=1}^{n}
c_{i}f_{i}(t) \vec{v}_{1}$.

Choose a vector $\vec{w}$ orthogonal to $\vec{v}_{2}, \dots,
\vec{v}_{n}$ but not to $\vec{v}_1$. Since $\vec{x}(t) \to 0$ as $t
\to \infty$, the same is true of $\vec{w} \cdot \vec{x}$; but that is
simply $(\vec{w} \cdot \vec{v}_{1}) c_{1} f_{1}(t)$. In other words,
if $c_{i} \neq 0$, then $f_{i}(t)$ must also go to 0.

However, it is easy to exhibit a solution which does not go to 0. The
sum of the eigenvalues of the matrix $A = (a_{ij})$, also known as the
trace of $A$, being the sum of the diagonal entries of $A$, is
nonnegative, so $A$ has an eigenvalue $\lambda$ with nonnegative real
part, and a corresponding eigenvector $\vec{v}$. Then $e^{\lambda t}
\vec{v}$ is a solution that does not go to 0. (If $\lambda$ is not
real, add this solution to its complex conjugate to get a real
solution, which still doesn't go to 0.)

Hence one of the $c_{i}$, say $c_{1}$, is zero, in which case
$\vec{x}(t) \cdot \vec{w} = 0$ for all $t$.
 

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