\section{RESULTS AND ANALYSIS}
\subsection{GMA PROPERTIES}
We derived the following cloud properties using the python packages CPROPS and cpropstoo created by \citet{Rosolowsky_2006}. Using moment methods, we derived size, line width, and flux directly from the PPV cubes' emission spectras and then calculated radius, FWHM line width, and CO luminosity from those quantities, respectively. From the CO luminosity and the empirical X-factor relationship \cite{Bolatto_2013}, we found the luminous mass of $H_2$.

To begin our analysis, we recreated the Larson's Laws plots, originally found in \citet{Larson_1981} and subsequently in \citet{Solomon_1987} and \citet{Fukui_2010} for GMCs in the Milky Way Galaxy and  Local Group of galaxies, respectively, to test their scaling relationships for our M100 data. We identified the nuclear, arm and inter-arm GMAs manually using their positions in Fig.~\ref{xypos} and considered each population separately.

In Fig.~\ref{mvir_mlum}, we plotted the luminous masses, $M_{\mathrm{lum}}$, derived from the luminosity of CO, against the virial masses, $M_{\mathrm{vir}}$, inferred from the FWHM line width and cloud radius \citep{Rosolowsky_2006}. The scaling line is the expected one to one ratio for clouds in virial equilibrium. Fig.~\ref{mvir_mlum} shows that the luminous masses are generally higher than the virial masses and that the nuclear clouds are, on average, the most massive, followed by arm and then inter-arm clouds. These results are confirmed in the first two columns of Table \ref{means}, which present the geometric mean of luminous mass, $\overline{M}_\mathrm{lum}$, and the corresponding standard error, $SE(M_\mathrm{lum})$.

