added gwda tutorial

tuturials/gw_tutorials.tex

@@ -212,7 +212,7 @@ $\sigma^2$ is the variance of the noise.
 
 \subsubsection{Problems}
 \begin{enumerate}
-\item You are given a time-series data $d(t)$. This contains a simulated gravitational-wave signal from a black hole binary buried in zero-mean, Gaussian white noise $n(t)$ with standard deviation $\sigma = 10^{-21}$. i.e., $d(t) = n(t) + h(t)$, where $h(t)$ is the leading order PN waveform from a binary with (unknown masses) $m_1$ and $m_2$. Detect the location of the signal in the data and values of $m_1$ and $m_2$ by maximising the correlation of the waveform templates with the data.: 
+\item You are \href{http://gitlab.icts.res.in/ajith/gwcourse2023/blob/master/tuturials/fake_gw_data.dat.gz}{given} a time-series data $d(t)$. This contains a simulated gravitational-wave signal from a black hole binary buried in zero-mean, Gaussian white noise $n(t)$ with standard deviation $\sigma = 10^{-21}$. i.e., $d(t) = n(t) + h(t)$, where $h(t)$ is the leading order PN waveform from a binary with (unknown masses) $m_1$ and $m_2$. Detect the location of the signal in the data and values of $m_1$ and $m_2$ by maximising the correlation of the waveform templates with the data.: 
 \begin{equation}
 R_\mathrm{max} = \mathrm{max}~_{m_1, m_2,\tau}~ R(\tau),
 \end{equation}