At first I did not make use of the Brownian Bridge technique in Heston QMC, because the variance process is not simulated like a Brownian Motion under the Quadratic Exponential algorithm from Andersen.
It is, however, perfectly possible to use the Brownian Bridge on the asset process. Does it make a difference? In my small test, it does not seem to make a difference. An additional question would be, is it better to take first N for the asset and next N for the variance or vice versa or intertwined? Intertwined would seem the most natural (this is what I used without Brownian Bridge, but for simplicity I did Brownian bridge on first N).
By contrast, Schobel-Zhu QE scheme can make full use of the Brownian Bridge technique, in the asset process as well as in the variance process. Here is a summary of the volatility process under the QE scheme from van Haastrecht:
Another nice property of Schobel-Zhu is that the QE simulation is as fast as Euler, and therefore 2.5x faster than the Heston QE.
I calibrated the model to the same surface, and the QMC price of a ATM call option seems to have a similar accuracy as Heston QMC. But we can see that the Brownian Bridge does increase accuracy in this case. I was surprised that accuracy was not much better than Heston, but maybe it is because I did yet not implement the Martingale correction, while I did so in the Heston case.