Although Monte Carlo calculations using Importance Sampling have matured into the most widely employed method for determining first principle results in QCD, they spectacularly fail for theories with a sign problem or for which certain rare configurations play an important role. Non-Markovian Random walks, based upon iterative refinements of the density-of-states, overcome such overlap problems. I will review the Linear Logarithmic Relaxation (LLR) method and, in particular, focus onto ergodicity and exponential error suppression. Applications include the high-state Potts model, SU(2) and SU(3) Yang-Mills theories as well as a quantum field theory with a strong sign problem: QCD at finite densities of heavy quarks
1 + 11 pages, 6 figures. Invited talk presented by B. Lucini at the conference "XIIIth Quark Confine...
QCD at finite densities of heavy quarks is investigated using the density-of-states method. The phas...
We put the Density-of-States (DoS) approach to Monte-Carlo (MC) simulations under a stress test by a...
During the last 40 years, Monte Carlo calculations based upon Importance Sampling have matured into ...
During the last 40 years, Monte Carlo calculations based upon Importance Sampling have matured into ...
The density-of-states method (Phys.Rev.Lett. 109 (2012) 111601) features an exponential error suppre...
The LLR method is a novel algorithm that enables us to evaluate the density of states in lattice gau...
International audienceWhile importance sampling Monte Carlo algorithms have proved to be a crucial t...
The Logarithmic Linear Relaxation (LLR) algorithm is an efficient method for computing densities of ...
We develop a first-principle generalized density-of-states method for numerically studying quantum f...
We apply the linear logarithmic relaxation (LLR) method, which generalizes the Wang-Landau algorithm...
10 pages, 6 figures, talk at at DISCRETE2014, King's College London, December 2014Finite density qua...
In Wang–Landau type algorithms, Monte-Carlo updates are performed with respect to the density of sta...
We extend the density-of-states approach to gauge systems (LLR method) to QCD at finite temperature ...
International audienceThe study of QFTs at finite density is hindered by the presence of the so-call...
1 + 11 pages, 6 figures. Invited talk presented by B. Lucini at the conference "XIIIth Quark Confine...
QCD at finite densities of heavy quarks is investigated using the density-of-states method. The phas...
We put the Density-of-States (DoS) approach to Monte-Carlo (MC) simulations under a stress test by a...
During the last 40 years, Monte Carlo calculations based upon Importance Sampling have matured into ...
During the last 40 years, Monte Carlo calculations based upon Importance Sampling have matured into ...
The density-of-states method (Phys.Rev.Lett. 109 (2012) 111601) features an exponential error suppre...
The LLR method is a novel algorithm that enables us to evaluate the density of states in lattice gau...
International audienceWhile importance sampling Monte Carlo algorithms have proved to be a crucial t...
The Logarithmic Linear Relaxation (LLR) algorithm is an efficient method for computing densities of ...
We develop a first-principle generalized density-of-states method for numerically studying quantum f...
We apply the linear logarithmic relaxation (LLR) method, which generalizes the Wang-Landau algorithm...
10 pages, 6 figures, talk at at DISCRETE2014, King's College London, December 2014Finite density qua...
In Wang–Landau type algorithms, Monte-Carlo updates are performed with respect to the density of sta...
We extend the density-of-states approach to gauge systems (LLR method) to QCD at finite temperature ...
International audienceThe study of QFTs at finite density is hindered by the presence of the so-call...
1 + 11 pages, 6 figures. Invited talk presented by B. Lucini at the conference "XIIIth Quark Confine...
QCD at finite densities of heavy quarks is investigated using the density-of-states method. The phas...
We put the Density-of-States (DoS) approach to Monte-Carlo (MC) simulations under a stress test by a...