How to Tell if a System of Differential Equations Is Homogeneous
Imagine you’re walking into the land of differential equations, and someone hands you this pair of mysterious creatures:
dx/dt = 8*sin(t)*x + ln(t)*y
dy/dt = 4*t^2*y + 2*e^t*x
You’re told they form a system — two variables, x and y, both evolving with time t.
But the question is: are they homogeneous or not?
Setting the Scene
In the world of linear systems, every creature (each differential equation) can be described in one neat matrix sentence:
where
- X is a column matrix whose entries are the evolving quantities x and y,
- A(t) is the system’s personality matrix, telling how x and y interact, and
- b(t) is an external forcing term — like an outside influence that pushes the system whether or not x or y are there. Note that b(t) is a column matrix as well.
The Heart of the Definition
Now, here’s the key idea — the moral of the story:
If the system has no external push — that is, if b(t) = 0 everywhere — the system is called homogeneous.
But if there is such a push, some f(t), g(t), or any term that doesn’t multiply x or y, then the system becomes non-homogeneous.
It’s like the difference between a boat drifting because of its own currents (homogeneous), versus being tugged by an outside rope (non-homogeneous).
Applying the Rule
Look again at your system.
Every term on the right-hand side — (8sin(t)x), (ln(t)y), (4t^2y), (2e^t*x) — is attached to either x or y.
No lonely term like “+sin(t)” or “+e^t” appears by itself.
That means there’s no external forcing vector b(t).
So, in matrix form:
X' = [ [8*sin(t), ln(t)],
[2*e^t, 4*t^2] ] * X
and b(t) = 0.
The Verdict
Since b(t) is zero, your system is homogeneous.
A Broader Intuition — The Lotka–Volterra Example
Now, let’s step out of pure symbols and into the real world for a moment.
Imagine an ecosystem — a small island where rabbits and foxes live together. The rabbits (x) multiply when food is plenty, and the foxes (y) thrive when there are enough rabbits to hunt. Their story unfolds through this pair of equations:
dx/dt = a*x - b*x*y
dy/dt = d*x*y - g*y
Here, the first equation says the rabbit population grows on its own (the ax part) but drops when foxes catch them (the -bxy part). The second says the fox population depends on how many rabbits are around (the dxy part) but declines naturally when food is scarce (the -gy part).
Everything that happens here comes from inside the system — from the way rabbits and foxes affect each other. There’s no outside interference, no extra food shipments, no hunters arriving. It’s a perfectly homogeneous world — a closed system driven entirely by its own internal interactions. But now imagine that, every spring, humans drop extra food for the rabbits. That small seasonal help can be written as an extra term added to the first equation:
dx/dt = a*x - b*x*y + f(t)
That new friend, f(t), is an external push — a source of energy or resources coming from the outside. And just like that, the peaceful island is no longer isolated. The system has become non-homogeneous, because the change in x now depends not just on the rabbits and foxes, but also on what’s happening beyond their little world.