Importance sampling algorithms

Oct-Tree Importance sampling algorithms are more practical for routine analysis (Lomax et al. 2000). 

Develop an importance sampling algorithm that samples the Maxwell-Boltzmann distribution of velocities of simple particles. 

In the NVT ensemble one cannot compute the chemical potential or entropy of the system two properties which are of critical importance for interfacial systems. The choice of an ensemble also determines the sampling algorithm used to generate molecular configurations from random moves of the molecules. 

Again, in practical applications it is important to combine the raw branching algorithm defined above with importance sampling. Mathematically, this works in precisely the same way as in Section III in that one reformulates the same algorithm in terms of the similarity transform 6 with Mg = uT chosen to be an accurate, approximate dominant eigenstate [see Eq. 

The basic importance-sampling MC algorithm is the Metropolis method... 

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