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In a recent publication (Phys. Rev E 77, 056705 (2008)),we have presented the stochastic Green function (SGF) algorithm, which has the properties of being general and easy to apply to any lattice Hamiltonian of the form H=V-T, where V is diagonal in the chosen occupation number basis and T has only positive matrix elements. We propose here a modified version of the update scheme that keeps the simplicity and generality of the original SGF algorithm, and enhances significantly its efficiency.
We present the Stochastic Green Function (SGF) algorithm designed for bosons on lattices. This new quantum Monte Carlo algorithm is independent of the dimension of the system, works in continuous imaginary time, and is exact (no error beyond statisti
We analyze the operation of a molecular machine driven by the non-adiabatic variation of external parameters. We derive a formula for the integrated flow from one configuration to another, obtain a no-pumping theorem for cyclic processes with thermal
We present efficient algorithms to generate a bit string in which each bit is set with arbitrary probability. By adopting a hybrid algorithm, i.e., a finite-bit density approximation with correction techniques, we achieve 3.8 times faster random bit
A methodical derivation of RKKY interaction in framework of T=0 Green function method is given in great detail. The article is complimentary to standard textbooks on the physics of magnetism and condensed matter physics. It is shown that the methods
We introduce a stochastic sandpile model where finite drive and dissipation are coupled to the activity field. The absorbing phase transition here, as expected, belongs to the directed percolation (DP) universality class. We focus on the small drive