Explicit Renormalization Group for D=2 random bond Ising model with long-range correlated disorder

We investigate the explicit renormalization group for fermionic field theoretic representation of two-dimensional random bond Ising model with long-range correlated disorder. We show that a new fixed point appears by introducing a long-range correlated disorder. Such as the one has been observed in previous works for the bosonic ($\phi^4$) description. We have calculated the correlation length exponent and the anomalous scaling dimension of fermionic fields at this fixed point. Our results are in agreement with the extended Harris criterion derived by Weinrib and Halperin.Comment: 5 page

Deconfined criticality, runaway flow in the two-component scalar electrodynamics and weak first-order superfluid-solid transitions

We perform a comparative Monte Carlo study of the easy-plane deconfined critical point (DCP) action and its short-range counterpart to reveal close similarities between the two models for intermediate and strong coupling regimes. For weak coupling, the structure of the phase diagram depends on the interaction range: while the short-range model features a tricritical point and a continuous U(1)xU(1) transition,the long-range DCP action is characterized by the runaway renormalization flow of coupling into a first (I) order phase transition. We develop a "numerical flowgram" method for high precision studies of the runaway effect, weakly I-order transitions, and polycritical points. We prove that the easy-plane DCP action is the field theory of a weakly I-order phase transition between the valence bond solid and the easy-plane antiferromagnet (or superfluid, in particle language) for any value of the weak coupling strength. Our analysis also solves the long standing problem of what is the ultimate fate of the runaway flow to strong coupling in the theory of scalar electrodynamics in three dimensions with U(1)xU(1) symmetry of quartic interactionsComment: 25 pages, 18 figures, Mottness and quantum criticality conference (to appear in Annals of physics

Late stage, non-equilibrium dynamics in the dipolar Ising model

Magnetic domain structures are a fascinating area of study with interest deriving both from technological applications and fundamental scientific questions. The nature of the striped magnetic phases observed in ultra-thin films is one such intriguing system. The non-equilibrium dynamics of such systems as they evolve toward equilibrium has only recently become an area of interest and previous work on model systems showed evidence of complex, slow dynamics with glass-like properties as the stripes order mesoscopically. To aid in the characterization of the observed phases and the nature of the transitions observed in model systems we have developed an efficient method for identifying clusters or domains in the spin system, where the clusters are based on the stripe orientation. Thus we are able to track the growth and decay of such clusters of stripes in a Monte Carlo simulation and observe directly the nature of the slow dynamics. We have applied this method to consider the growth and decay of ordered domains after a quench from a saturated magnetic state to temperatures near and well below the critical temperature in the two dimensional dipolar Ising model. We discuss our method of identifying stripe domains or clusters of stripes within this model and present the results of our investigations.Comment: 17 pages, 12 figures, submitted to JMM

Universal finite-size scaling analysis of Ising models with long-range interactions at the upper critical dimensionality: Isotropic case

We investigate a two-dimensional Ising model with long-range interactions that emerge from a generalization of the magnetic dipolar interaction in spin systems with in-plane spin orientation. This interaction is, in general, anisotropic whereby in the present work we focus on the isotropic case for which the model is found to be at its upper critical dimensionality. To investigate the critical behavior the temperature and field dependence of several quantities are studied by means of Monte Carlo simulations. On the basis of the Privman-Fisher hypothesis and results of the renormalization group the numerical data are analyzed in the framework of a finite-size scaling analysis and compared to finite-size scaling functions derived from a Ginzburg-Landau-Wilson model in zero mode (mean-field) approximation. The obtained excellent agreement suggests that at least in the present case the concept of universal finite-size scaling functions can be extended to the upper critical dimensionality.Comment: revtex4, 10 pages, 5 figures, 1 tabl

Landau-Ginzburg Description of Boundary Critical Phenomena in Two Dimensions

The Virasoro minimal models with boundary are described in the Landau-Ginzburg theory by introducing a boundary potential, function of the boundary field value. The ground state field configurations become non-trivial and are found to obey the soliton equations. The conformal invariant boundary conditions are characterized by the reparametrization-invariant data of the boundary potential, that are the number and degeneracies of the stationary points. The boundary renormalization group flows are obtained by varying the boundary potential while keeping the bulk critical: they satisfy new selection rules and correspond to real deformations of the Arnold simple singularities of A_k type. The description of conformal boundary conditions in terms of boundary potential and associated ground state solitons is extended to the N=2 supersymmetric case, finding agreement with the analysis of A-type boundaries by Hori, Iqbal and Vafa.Comment: 42 pages, 13 figure

Spin glass transition in a magnetic field: a renormalization group study

We study the transition of short range Ising spin glasses in a magnetic field, within a general replica symmetric field theory, which contains three masses and eight cubic couplings, that is defined in terms of the fields representing the replicon, anomalous and longitudinal modes. We discuss the symmetry of the theory in the limit of replica number n to 0, and consider the regular case where the longitudinal and anomalous masses remain degenerate. The spin glass transitions in zero and non-zero field are analyzed in a common framework. The mean field treatment shows the usual results, that is a transition in zero field, where all the modes become critical, and a transition in non-zero field, at the de Almeida-Thouless (AT) line, with only the replicon mode critical. Renormalization group methods are used to study the critical behavior, to order epsilon = 6-d. In the general theory we find a stable fixed-point associated to the spin glass transition in zero field. This fixed-point becomes unstable in the presence of a small magnetic field, and we calculate crossover exponents, which we relate to zero-field critical exponents. In a finite magnetic field, we find no physical stable fixed-point to describe the AT transition, in agreement with previous results of other authors.Comment: 36 pages with 4 tables. To be published in Phys. Rev.

Self-Averaging, Distribution of Pseudo-Critical Temperatures and Finite Size Scaling in Critical Disordered Systems

The distributions $P(X)$ of singular thermodynamic quantities in an ensemble of quenched random samples of linear size $l$ at the critical point $T_c$ are studied by Monte Carlo in two models. Our results confirm predictions of Aharony and Harris based on Renormalization group considerations. For an Ashkin-Teller model with strong but irrelevant bond randomness we find that the relative squared width, $R_X$, of $P(X)$ is weakly self averaging. $R_X\sim l^{\alpha/\nu}$, where $\alpha$ is the specific heat exponent and $\nu$ is the correlation length exponent of the pure model fixed point governing the transition. For the site dilute Ising model on a cubic lattice, known to be governed by a random fixed point, we find that $R_X$ tends to a universal constant independent of the amount of dilution (no self averaging). However this constant is different for canonical and grand canonical disorder. We study the distribution of the pseudo-critical temperatures $T_c(i,l)$ of the ensemble defined as the temperatures of the maximum susceptibility of each sample. We find that its variance scales as $(\delta T_c(l))^2 \sim l^{-2/\nu}$ and NOT as $\sim l^{-d}. We find that$R_\chi$is reduced by a factor of$\sim 70$with respect to$R_\chi (T_c)$by measuring$\chi$of each sample at$T_c(i,l)$. We analyze correlations between the magnetization at criticality$m_i(T_c,l)$and the pseudo-critical temperature$T_c(i,l)$in terms of a sample independent finite size scaling function of a sample dependent reduced temperature$(T-T_c(i,l))/T_c$. This function is found to be universal and to behave similarly to pure systems.Comment: 31 pages, 17 figures, submitted to Phys. Rev.

Percolation in random environment

We consider bond percolation on the square lattice with perfectly correlated random probabilities. According to scaling considerations, mapping to a random walk problem and the results of Monte Carlo simulations the critical behavior of the system with varying degree of disorder is governed by new, random fixed points with anisotropic scaling properties. For weaker disorder both the magnetization and the anisotropy exponents are non-universal, whereas for strong enough disorder the system scales into an {\it infinite randomness fixed point} in which the critical exponents are exactly known.Comment: 8 pages, 7 figure

Predicting patient death after allogeneic stem cell transplantation for inborn errors using machine learning (PREPAD): a European society for blood and marrow transplantation inborn errors working party study

Allogeneic hematopoietic stem cell transplantation (HSCT) is a curative treatment for many inborn errors of immunity, metabolism, and hematopoiesis. No predictive models are available for these disorders. We created a machine learning model using XGBoost to predict survival after HSCT using European Society for Blood and Marrow Transplant registry data of 10,888 patients who underwent HSCT for inborn errors between 2006 and 2018, and compared it to a simple linear Cox model, an elastic net Cox model, and a random forest model. The XGBoost model had a cross-validated area under the curve value of .73 at 1 year, which was significantly superior to the other models, and it accurately predicted for countries excluded while training. It predicted close to 0% and >30% mortality more often than other models at 1 year, while maintaining good calibration. The 5-year survival was 94.7% in the 25% of patients at lowest risk and 62.3% in the 25% at highest risk. Within disease and donor subgroups, XGBoost outperformed the best univariate predictor. We visualized the effect of the main predictors-diagnosis, performance score, patient age and donor type-using the SHAP ML explainer and developed a stand-alone application, which can predict using the model and visualize predictions. The risk of mortality after HSCT for inborn errors can be accurately predicted using an explainable machine learning model. This exceeds the performance of models described in the literature. Doing so can help detect deviations from expected survival and improve risk stratification in trials.(c) 2023 The American Society for Transplantation and Cellular Therapy. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)Transplantation and immunomodulatio

Short-time dynamics and magnetic critical behavior of two-dimensional random-bond Potts model

The critical behavior in the short-time dynamics for the random-bond Potts ferromagnet in two-dimensions is investigated by short-time dynamic Monte Carlo simulations. The numerical calculations show that this dynamic approach can be applied efficiently to study the scaling characteristic, which is used to estimate the critical exponents theta, beta/nu and z for the quenched disorered systems from the power-law behavior of the kth moments of magnetizations.Comment: 10 pages, 4 figures Soft Condensed Matte