We propose a strategy to achieve the fastest convergence in the Wang-Landau algorithm with varying modification factors. With this strategy, the convergence of a simulation is at least as good as the conventional Monte Carlo algorithm, i.e. the stati
stical error vanishes as $1/sqrt{t}$, where $t$ is a normalized time of the simulation. However, we also prove that the error cannot vanish faster than $1/t$. Our findings are consistent with the $1/t$ Wang-Landau algorithm discovered recently, and we argue that one needs external information in the simulation to beat the conventional Monte Carlo algorithm.
In the absence of disorder, the degeneracy of a Landau level (LL) is $N=BA/phi_0$, where $B$ is the magnetic field, $A$ is the area of the sample and $phi_0=h/e$ is the magnetic flux quantum. With disorder, localized states appear at the top and bott
om of the broadened LL, while states in the center of the LL (the critical region) remain delocalized. This well-known phenomenology is sufficient to explain most aspects of the Integer Quantum Hall Effect (IQHE) [1]. One unnoticed issue is where the new states appear as the magnetic field is increased. Here we demonstrate that they appear predominantly inside the critical region. This leads to a certain ``spectral ordering of the localized states that explains the stripes observed in measurements of the local inverse compressibility [2-3], of two-terminal conductance [4], and of Hall and longitudinal resistances [5] without invoking interactions as done in previous work [6-8].
We study the phase diagram of a quasi-two dimensional magnetic system ${rm Rb_2MnF_4}$ with Monte Carlo simulations of a classical Heisenberg spin Hamiltonian which includes the dipolar interactions between ${rm Mn}^{2+}$ spins. Our simulations revea
l an Ising-like antiferromagnetic phase at low magnetic fields and an XY phase at high magnetic fields. The boundary between Ising and XY phases is analyzed with a recently proposed finite size scaling technique and found to be consistent with a bicritical point at T=0. We discuss the computational techniques used to handle the weak dipolar interaction and the difference between our phase diagram and the experimental results.
