Generating multidimensional normal random variables in matlab

the question is about the use of the covariance matrix in the multidimensional normal distribution:

I want to generate multi-dimensional random numbers x in matlab with a given mean mu and covariance matrix Sigma. Assuming Z is a standard normally distributed random number (eg. generated using randn() ), what is a correct code:

x = mu + chol(Sigma) * Z?   

or

x = mu + Sigma^0.5 * Z ?  

I am not sure about the use in the multidimensional normal distribution definition - whether the determinant in the denominator is of the square root of Sigma or the cholesky factor...

Looking forward to any hints. Thanks!