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Quantum Monte Carlo Study of Frustrated Spin Chain under External Field

HY Yu

Published Jan 1, 2010• 0 citations
OpenAlex

Abstract

In this paper a stochastic series expansion quantum Monte Carlo algorithm is used to study a frustrated spin chain with diagonal next-nearest-neighbor interactions. The detailed balance conditions are carefully analyzed to improve the efficiency of simulation process. As an application of this algothrim, the total magnetization, the static structure factor and spin-stiffness are calculated for a certain set of system parameters as a function of external field strength.

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In this paper a stochastic series expansion quantum Monte Carlo algorithm is used to study a frustrated spin chain with diagonal next-nearest-neighbor interactions. The detailed balance conditions are carefully analyzed to improve the efficiency of simulation process. As an application of this algothrim, the total magnetization, the static structure factor and spin-stiffness are calculated for a certain set of system parameters as a function of external field strength.
Working within the stochastic series expansion framework, we introduce and characterize a plaquette-based quantum cluster algorithm for quantum Monte Carlo simulations of transverse field Ising models with frustrated Ising exchange interactions. As a demonstration of the capabilities of this algorithm, we show that a relatively small ferromagnetic next-nearest-neighbor coupling drives the transverse field Ising antiferromagnet on the triangular lattice from an antiferromagnetic three-sublattice ordered state at low temperature to a ferrimagnetic three-sublattice ordered state.
Motivated by recent experiments on quasi-one-dimensional spin-frustrated quantum spin systems, we study the dynamic properties of exactly solvable quantum spin models with spin frustration. The ground-state dynamic structure factor, static structure factor (important for the neutron scattering), inhomogeneous static magnetic susceptibility, etc., are calculated. The results differ strongly from the behavior of similar characteristics of a standard Heisenberg quantum spin chain. We believe that the obtained behavior of the mentioned characteristics is generic for quantum spin chains with nearest- and next-nearest-neighbor interactions.
Using the density matrix renormalization group technique, we investigate the quantum phase diagram of a ferromagnetic frustrated two-leg spin-1/2 ladder with diagonal and in-chain next-nearest-neighbor (NNN) interactions. By analyzing the correlation function and four-site entropy, we obtain the quantum phase diagram of the system. We find that the system possesses a tetramer phase, a ferromagnetic phase and states I and II. Spin arrangements for states I and II are also determined. In addition, the influence of the in-chain NNN interaction J 2 on the phase transitions of the anti-ferromagnetic case is studied. We show the phase diagram and find that the stagger dimer phase exists only in a narrow parameter region. Meanwhile, the existence of the controversial columnar dimer phase at J 2 = 0 is carefully analyzed.
We introduce the concept of directed loops in stochastic series expansion and path-integral quantum Monte Carlo methods. Using the detailed balance rules for directed loops, we show that it is possible to smoothly connect generally applicable simulation schemes (in which it is necessary to include backtracking processes in the loop construction) to more restricted loop algorithms that can be constructed only for a limited range of Hamiltonians (where backtracking can be avoided). The "algorithmic discontinuities" between general and special points (or regions) in parameter space can hence be eliminated. As a specific example, we consider the anisotropic S=1/2 Heisenberg antiferromagnet in an external magnetic field. We show that directed-loop simulations are very efficient for the full range of magnetic fields (zero to the saturation point) and anisotropies. In particular, for weak fields and anisotropies, the autocorrelations are significantly reduced relative to those of previous approaches. The back-tracking probability vanishes continuously as the isotropic Heisenberg point is approached. For the XY model, we show that back tracking can be avoided for all fields extending up to the saturation field. The method is hence particularly efficient in this case. We use directed-loop simulations to study the magnetization process in the two-dimensional Heisenberg model at very low temperatures. For LxL lattices with L up to 64, we utilize the step structure in the magnetization curve to extract gaps between different spin sectors. Finite-size scaling of the gaps gives an accurate estimate of the transverse susceptibility in the thermodynamic limit: chi( perpendicular )=0.0659+/-0.0002.
We apply the transfer-matrix density matrix renormalization group (DMRG) approach to frustrated quantum spin chains, down to T=0.025KT\phantom{\rule{0ex}{0ex}}=\phantom{\rule{0ex}{0ex}}0.025\mathrm{K}T=0.025K in the thermodynamic limit. The incommensurability problem of exact diagonalization and the negative sign problem of quantum Monte Carlo vanish completely. For illustration, we give results for chains with next-nearest-neighbor frustration and for the delta chain, which has been a testbed for many thermodynamic methods. The DMRG approach proves to be an extremely powerful method for the old problem of the thermodynamics of frustrated systems.