A component parameter can be assigned a random value with a Gaussian or uniform distribution. To do so, specify a pseudo-random function with the desired statistical parameters in the parameter value field. For instance, you can write in the parameter value field the following expression:
where “Mean” and “Sigma” are defined in the symbol table. In this way, the parameter will assume a random value with Gaussian distribution with the specified Mean and the Sigma values during the simulation:
which returns a pseudo-random value according to a uniform distribution in the range [min,max] where min and max are defined in the symbol table.
The random value is computed at the start of the simulation. If the value is outside the valid range of the parameter, OptSim re-computes it up to 10 times. After ten tries, OptSim will issue an error.
The use of a pseudo-random function in parameter value can also be combined with a scan over random parameter seed as discussed earlier. For example, for a specific value of Mean and Sigma defined in the symbol table, you can set the parameter to the following expression: Mean+rnd_gauss(0.0, Sigma). A scan over global seed will cause this parameter value to assume different Gaussian random variables during each run.
At the end of the simulation, you can see the random values used in each run by clicking Logging on the OptSim menu bar, and then selecting Open Simulation Log File.
On a related note, the pseudo-random data source model has settings to have sequence and polynomial be randomly (or deterministically) selected, and to have the starting point and bit edge randomly (or deterministically) chosen. The latter helps with decorrelation between data channels in multi-channel systems. The all-order PMD model provides a local setting for the seed, which can be scanned for Monte Carlo simulations. Some optical source models allow you to specify deterministic or random
for the starting laser phase.