In contrast to Tutorial 1, the second tutorial will focus on techniques that aim to avoid the bias of a specific set of chosen collective variables. Such techniques are useful when it is not clear, as is often the case, what variables should be targeted owing to the complexity of the structures, themselves, or to the nature of underlying potential free energy landscape. Methods in this category include the replica-exchange Monte Carlo approach, temperature accelerated dynamics, parallel replica dynamics, and the transition path sampling and related approaches, and techniques in this category will be the focus of this tutorial. As in the first tutorial, I will discuss the basic strategies of approaches of this type, their advantages, and their limitations in specific applications.
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