What is the maximum number of positive roots $\sum_{i}^N\frac{a_i}{x+b_i}$ can have where $b_i$'s are all positive? (everything here is a real number. To provide context, I encountered this problem while doing theoretical neuroscience research where I am modeling a biological neuronal network as an artificial neural network.)
$x$ is our variable, $a_i$ is a constant (can be either positive or negative), and $b_i$ is always a positive constant. $a_i$ and $b_i$ have unique values at each $i$.
In other words, how many $x>0$ can satisfy $\sum_{i}^N\frac{a_i}{x+b_i}=0$?
If $a_i$ happens to be all positive or negative, I see that there are no roots at positive $x$. For example, the following shows $y=\frac{1}{x+1}+\frac{1}{x+2}+\frac{1}{x+3}$. You can see that there are poles at -1, -2, and -3 (which are $-b_i$'s), and the roots exist between the poles. Since $b_i$'s are all positive, the roots between the poles need to be all negative.
However, if $a_i$'s are a mix of positives and negatives (and $b_i$'s are still all positive), there can be root(s) outside the poles, making it possible to have a root when $x>0$. For example, $y=\frac{1}{x+1}+\frac{1}{x+2}-\frac{3}{x+3}$ is $0$ at $x>0$ as shown below:
If I zoom in to the positive $x$ part, we see the following:
It overshoots below 0, and then asymptotically approaches 0.
So far, no matter how large my $N$ is, a randomly generated function $\sum_{i}^N\frac{a_i}{x+b_i}$ seemed to have only one root at positive $x$, if there was any, when I swept through $x$ on my computer. However, I still believe the number of positive roots should be dependent on $N$. Any thoughts?