In statistics and physics, multicanonical ensemble (also called multicanonical sampling or flat histogram) is a Markov chain Monte Carlo sampling technique that uses the Metropolis–Hastings algorithm to compute integrals where the integrand has a rough landscape with multiple local minima. It samples states according to the inverse of the density of states,[1] which has to be known a priori or be computed using other techniques like the Wang and Landau algorithm.[2] Multicanonical sampling is an important technique for spin systems like the Ising model or spin glasses.[1][3][4]
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