where o(x) computes the microscopic contribution of a property for a conformation. Generating i.i.d. samples from the Boltzmann distribution is challenging. However, if a surrogate model p(x) overlaps with µ(x), unbiased Boltzmann-distributed samples can be generated by reweighting the surrogate distribution . This reweighing or resampling, can be achieved with various algorithms, but the simplest one is known as importance sampling, in which samples from p(x) are assigned statistical weight w = e -u(x) /p(x).