Strong disorder renormalization group on fractal lattices: Heisenberg models and magnetoresistive effects in tight binding models

We use a numerical implementation of the strong disorder renormalization group (RG) method to study the low-energy fixed points of random Heisenberg and tight-binding models on different types of fractal lattices. For the Heisenberg model new types of infinite disorder and strong disorder fixed points are found. For the tight-binding model we add an orbital magnetic field and use both diagonal and off-diagonal disorder. For this model besides the gap spectra we study also the fraction of frozen sites, the correlation function, the persistent current and the two-terminal current. The lattices with an even number of sites around each elementary plaquette show a dominant $\phi_0=h/e$ periodicity. The lattices with an odd number of sites around each elementary plaquette show a dominant $\phi_0/2$ periodicity at vanishing diagonal disorder, with a positive weak localization-like magnetoconductance at infinite disorder fixed points. The magnetoconductance with both diagonal and off-diagonal disorder depends on the symmetry of the distribution of on-site energies.Comment: 19 pages, 20 figure

Getting a handle on lipid droplets: Insights into ER-lipid droplet tethering.

Lipid droplets (LDs) are hubs for lipid metabolism that form membrane contact sites with multiple organelles. In this issue, Hariri et al. (2019. J. Cell Biol. https://doi.org/10.1083/jcb.201808119) reveal the functions of Mdm1-mediated endoplasmic reticulum (ER)-LD tethering in yeast and Datta et al. (2019. J. Cell Biol. https://doi.org/10.1083/jcb.201808133) identify a role for the Mdm1 orthologue, Snx14, as an ER-LD tether that regulates lipid metabolism in human cells

W-graph ideals

We introduce a concept of a W-graph ideal in a Coxeter group. The main goal of this paper is to describe how to construct a W-graph from a given W-graph ideal. The principal application of this idea is in type A, where it provides an algorithm for the construction of W-graphs for Specht modules.Comment: 25 page

Interfering directed paths and the sign phase transition

We revisit the question of the "sign phase transition" for interfering directed paths with real amplitudes in a random medium. The sign of the total amplitude of the paths to a given point may be viewed as an Ising order parameter, so we suggest that a coarse-grained theory for system is a dynamic Ising model coupled to a Kardar-Parisi-Zhang (KPZ) model. It appears that when the KPZ model is in its strong-coupling ("pinned") phase, the Ising model does not have a stable ferromagnetic phase, so there is no sign phase transition. We investigate this numerically for the case of {\ss}1+1 dimensions, demonstrating the instability of the Ising ordered phase there.Comment: 4 pages, 4 figure

Interacting partially directed self avoiding walk. From phase transition to the geometry of the collapsed phase

In this paper, we investigate a model for a $1+1$ dimensional self-interacting and partially directed self-avoiding walk, usually referred to by the acronym IPDSAW. The interaction intensity and the free energy of the system are denoted by $\beta$ and $f$, respectively. The IPDSAW is known to undergo a collapse transition at $\beta_c$. We provide the precise asymptotic of the free energy close to criticality, that is we show that $f(\beta_c-\epsilon)\sim \gamma \epsilon^{3/2}$ where $\gamma$ is computed explicitly and interpreted in terms of an associated continuous model. We also establish some path properties of the random walk inside the collapsed phase $(\beta>\beta_c)$. We prove that the geometric conformation adopted by the polymer is made of a succession of long vertical stretches that attract each other to form a unique macroscopic bead, we identify the horizontal extension of the random walk inside the collapsed phase and we establish the convergence of the rescaled envelope of the macroscopic bead towards a deterministic Wulff shape.Comment: Accepted for publication in the Annals of Probabilit