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Register a new userDiffusive thermal dynamics for the spin-S Ising ferromagnet
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We introduce an alternative thermal diffusive dynamics for the spin-S Ising ferromagnet realized by means of a random walker. The latter hops across the sites of the lattice and flips the relevant spins according to a probability depending on both the local magnetic arrangement and the temperature. The random walker, intended to model a diffusing excitation, interacts with the lattice so that it is biased towards those sites where it can achieve an energy gain. In order to adapt our algorithm to systems made up of arbitrary spins, some non trivial generalizations are implied. In particular, we will apply the new dynamics to two-dimensional spin-1/2 and spin-1 systems analyzing their relaxation and critical behavior. Some interesting differences with respect to canonical results are found; moreover, by comparing the outcomes from the examined cases, we will point out their main features, possibly extending the results to spin-S systems.
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We study sample-to-sample fluctuations in a critical two-dimensional Ising model with quenched random ferromagnetic couplings. Using replica calculations in the renormalization group framework we derive explicit expressions for the probability distribution function of the critical internal energy and for the specific heat fluctuations. It is shown that the disorder distribution of internal energies is Gaussian, and the typical sample-to-sample fluctuations as well as the average value scale with the system size $L$ like $sim L lnln(L)$. In contrast, the specific heat is shown to be self-averaging with a distribution function that tends to a $delta$-peak in the thermodynamic limit $L to infty$. While previously a lack of self-averaging was found for the free energy, we here obtain results for quantities that are directly measurable in simulations, and implications for measurements in the actual lattice system are discussed.
We present a numerical analysis of the entropy rate and statistical complexity related to the spin flip dynamics of the 2D Ising Ferromagnet at different temperatures T. We follow an information theoretic approach and test three different entropy estimation algorithms to asses entropy rate and statistical complexity of binary sequences. The latter are obtained by monitoring the orientation of a single spin on a square lattice of side-length L=256 at a given temperature parameter over time. The different entropy estimation procedures are based on the M-block Shannon entropy (a well established method that yields results for benchmarking purposes), non-sequential recursive pair substitution (providing an elaborate and an approximate estimator) and a convenient data compression algorithm contained in the zlib-library (providing an approximate estimator only). We propose an approximate measure of statistical complexity that emphasizes on correlations within the sequence and which is easy to implement, even by means of black-box data compression algorithms. Regarding the 2D Ising Ferromagnet simulated using Metropolis dynamics and for binary sequences of finite length, the proposed approximate complexity measure is peaked close to the critical temperature. For the approximate estimators, a finite-size scaling analysis reveals that the peak approaches the critical temperature as the sequence length increases. Results obtained using different spin-flip dynamics are briefly discussed. The suggested complexity measure can be extended to non-binary sequences in a straightforward manner.
We study low-temperature nucleation in kinetic Ising models by analytical and simulational methods, confirming the general result for the average metastable lifetime, <tau> = A*exp(beta*Gamma) (beta = 1/kT) [E. Jordao Neves and R.H. Schonmann, Commun. Math. Phys. 137, 209 (1991)]. Contrary to common belief, we find that both A and Gamma depend significantly on the stochastic dynamic. In particular, for a ``soft dynamic, in which the effects of the interactions and the applied field factorize in the transition rates, Gamma does NOT simply equal the energy barrier against nucleation, as it does for the standard Glauber dynamic, which does not have this factorization property.
Improved fabrication techniques have enabled the possibility of ballistic transport and unprecedented spin manipulation in ultraclean graphene devices. Spin transport in graphene is typically probed in a nonlocal spin valve and is analyzed using spin diffusion theory, but this theory is not necessarily applicable when charge transport becomes ballistic or when the spin diffusion length is exceptionally long. Here, we study these regimes by performing quantum simulations of graphene nonlocal spin valves. We find that conventional spin diffusion theory fails to capture the crossover to the ballistic regime as well as the limit of long spin diffusion length. We show that the latter can be described by an extension of the current theoretical framework. Finally, by covering the whole range of spin dynamics, our study opens a new perspective to predict and scrutinize spin transport in graphene and other two-dimensional material-based ultraclean devices.
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