Progress so far:
In a previous task, I determined a polynomial interpolation using a system of linear equations.
The data points to be used were $(0, f(0)), (\frac{1}{6}, f(\frac{1}{6})), (\frac{1}{4}, f(\frac{1}{4}))$
The linear equation used was of the form:
\begin{pmatrix}0^2&0^1&0^0\\ \:\frac{1}{6}^2&\frac{1}{6}^1&\frac{1}{6}^0\\ \:\frac{1}{4}^2&\frac{1}{4}^1&\frac{1}{4}^0\end{pmatrix}\begin{pmatrix}a_2\\ \:a_1\\ \:a_0\end{pmatrix}=\begin{pmatrix}0\\ \frac{1}{\sqrt{3}}\\ 1\end{pmatrix}
and the polynomial of the form
$$ p_2(x) = a_0 + a_1 x + a_2 x^2$$ was determined to have the coefficients
$a_0 = 0, a_1 = -8 + \frac{18}{\sqrt{3}}, a_2 = 48 - \frac{72}{\sqrt{3}}$
I am not aware of how I would use a system of linear equations to determine $Q(x)$. Is it perhaps possible to derive the coefficients from $p_2$? Or is there some other method of interpolation I should pursue?
Instead of working with $Q(x)$ $$Q(x) = b_0 + b_1 x + \frac{b_2}{x-\frac{1}{2}}$$ work with $\Phi(x)$ an $\Psi(x)$ $$\Phi(x)=\left(x-\frac 12\right) Q(x)=\left(b_2-\frac{b_0}{2}\right)+x \left(b_0-\frac{b_1}{2}\right)+b_1 x^2=\alpha+\beta x+\gamma x^2$$
$$\Psi(x)=\left(x-\frac 12\right) F(x)=\left(x-\frac 12\right) \tan(\pi x)$$ $\Psi(x)$ is a very nice function for the range of interest.
Compute $\alpha,\beta ,\gamma$ and go back to $b_0,b_1,b_2$.