Multicanonical ensemble

<p>In <a href="/facts/Statistics/DNPsKGYU">statistics</a> and <a href="/facts/Physics/a7aH2y08">physics</a>, multicanonical ensemble (also called multicanonical sampling or flat histogram) is a <a href="/facts/Markov_chain_Monte_Carlo/eTjk3WQy">Markov chain Monte Carlo</a> sampling technique that uses the <a href="/facts/Metropolis%E2%80%93Hastings_algorithm/8K7bz3LN">Metropolis–Hastings algorithm</a> to compute <a href="/facts/Integral/V7lyV997">integrals</a> where the integrand has a rough landscape with multiple <a href="/facts/Local_minimum/ADlgnyzV">local minima</a>. It samples states according to the inverse of the <a href="/facts/Density_of_states/bwVTyhTf">density of states</a>, which has to be known a priori or be computed using other techniques like the <a href="/facts/Wang_and_Landau_algorithm/QfXQn5HN">Wang and Landau algorithm</a>. Multicanonical sampling is an important technique for <a href="/facts/Spin_(physics)/4Jvp7e8P">spin</a> systems like the <a href="/facts/Ising_model/lvBpj2h1">Ising model</a> or <a href="/facts/Spin_glass/v2Cxng9Y">spin glasses</a>.
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Multicanonical ensemble open-in-new

Multicanonical ensemble