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In a MC scheme, it is often not very efficient to generate the whole length chain from scratch in each MC cycle. This can be problematic especially the chain is very long: a growing is more likely to be rejected as the total bead that needs to be regrown increases. Instead, we only regrow a portion of chain in a MC cycle
by randomly choosing a number of beads that need to be regrown from 1 up to a maximum value (determined by REGROWTH). In this case the values of W(new) and W(old) will be restricted to the portions of regrowing beads. In fact, both CHOICE and REGROWTH play a combining role to determine the efficiency of the overall MC scheme.
If the value of CHOICE is large and REGROWTH is small then it is more likely to successfully complete a chain regrowing process (Note: this is different from accepting the newly grown chain, of which the acceptance criteria is NOT depended on values of CHOICE and REGROWTH). However, if CHOICE is set too large, longer computational time will be taken to complete a growing process. Similarly, if REGROWTH is very small this decreases the computational time to complete a growing process, but at the expense of having
to do a lot more MC cycles in order to get a decent statistics. This is because there would be not much change in overall chain structure as a simulation progress since the portion that needs to be regrown in a given MC cycle is always very small.
It is not a trivial task to determine the optimum values for CHOICE and REGROWTH. Furthermore, different temperatures may have different sets of optimum value. However, as a hand-waving guide, the value of CHOICE=5 and REGROWTH=about a third (1/3) of total chain length is about right for most cases. For very low temperature, you may need to increase the value of CHOICE
and/or decrease the value of REGROWTH
There is a variety of ways to regrow a portion of a chain: it can be regrown from either ends, or a portion of beads can be removed from one end and regrow at the other end. In this way, beads at the inner parts of the chain will also eventually be sampled.
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