Persistence of Kardar-Parisi-Zhang Interfaces

The probabilities $P_\pm(t_0,t)$ that a growing Kardar-Parisi-Zhang interface remains above or below the mean height in the time interval $(t_0, t)$ are shown numerically to decay as $P_\pm \sim (t_0/t)^{\theta_\pm}$ with $\theta_+ = 1.18 \pm 0.08$ and $\theta_- = 1.64 \pm 0.08$. Bounds on $\theta_\pm$ are derived from the height autocorrelation function under the assumption of Gaussian statistics. The autocorrelation exponent $\bar \lambda$ for a $d$--dimensional interface with roughness and dynamic exponents $\beta$ and $z$ is conjectured to be $\bar \lambda = \beta + d/z$. For a recently proposed discretization of the KPZ equation we find oscillatory persistence probabilities, indicating hidden temporal correlations.Comment: 4 pages, 3 figures, uses revtex and psfi

Strong coupling probe for the Kardar-Parisi-Zhang equation

We present an exact solution of the {\it deterministic} Kardar-Parisi-Zhang (KPZ) equation under the influence of a local driving force $f$. For substrate dimension $d \le 2$ we recover the well-known result that for arbitrarily small $f>0$, the interface develops a non-zero velocity $v(f)$. Novel behaviour is found in the strong-coupling regime for $d > 2$, in which $f$ must exceed a critical force $f_c$ in order to drive the interface with constant velocity. We find $v(f) \sim (f-f_c)^{\alpha (d)}$ for $f \searrow f_{c}$. In particular, the exponent $\alpha (d) = 2/(d-2)$ for $2<d<4$, but saturates at $\alpha(d)=1$ for $d>4$, indicating that for this simple problem, there exists a finite upper critical dimension $d_u=4$. For $d>2$ the surface distortion caused by the applied force scales logarithmically with distance within a critical radius $R_{c} \sim (f-f_{c})^{-\nu(d)}$, where $\nu(d) = \alpha (d)/2$. Connections between these results, and the critical properties of the weak/strong-coupling transition in the noisy KPZ equation are pursued.Comment: 18 pages, RevTex, to appear in J. Phys. I Franc

Conserved Growth on Vicinal Surfaces

A crystal surface which is miscut with respect to a high symmetry plane exhibits steps with a characteristic distance. It is argued that the continuum description of growth on such a surface, when desorption can be neglected, is given by the anisotropic version of the conserved KPZ equation (T. Sun, H. Guo, and M. Grant, Phys. Rev. A 40, 6763 (1989)) with non-conserved noise. A one--loop dynamical renormalization group calculation yields the values of the dynamical exponent and the roughness exponent which are shown to be the same as in the isotropic case. The results presented here should apply in particular to growth under conditions which are typical for molecular beam epitaxy.Comment: 10 pages, uses revte

A SYSTEMATIC EXPLORATION OF INSULIN-DEPENDENT PROTEIN NETWORKS BY QUANTITATIVE MASS SPECTROMETRY

The highly conserved peptide hormone insulin functions as a central regulator of metabolic homeostasis in the human body. So far, several large-scale-omics studies based on proteomics approaches have been performed to investigate intracellular insulin signaling, including glucose uptake, gene regulation, and differentiation. These studies uncovered a plethora of insulin-dependent effectors and revealed complex mechanisms of how these signaling molecules interact. However, detailed functions of large numbers of signaling molecules remained entirely unclear. It became further evident that interactions between signaling pathways are much more complex than initially assumed. This thesis aims to generate large-scale insulin-dependent protein-protein interactomes and phosphoproteomes to decipher the complex mechanisms of insulin signaling pathways in brown adipocytes. For the global protein-protein interactome analysis, nearly 100 proteins were selected which either have known functions in insulin signaling pathways or show insulin-dependent phosphorylation. Bait expression experiments in brown adipocytes were performed for the selected candidates by transient transfection of FLAG-tagged expression constructs and enrichment of bait-specific protein interactors. After immuno-precipitation and highresolution mass spectrometric analysis, samples were analyzed by comprehensive statistical and bioinformatics methods. In a semi-automated workflow, 4,197 binary interactions with 95 baits were identified, and a total of 3,815 interactors showed dynamic interaction behavior in response to insulin. The study uncovered various insulin-dependent interactions, and the enrichment of different protein motifs after insulin stimulation demonstrated a dynamic remodeling of protein interaction communities. In addition, an insulin-dependent phosphoproteomics screen in brown adipocytes discovered 2,334 differentially regulated phosphorylation sites, including sites on 46 bait and 319 prey proteins. A comparative analysis of interaction and phosphorylation kinetics revealed 2,010 interaction-phosphosite pairs with either positively or negatively correlating dynamics indicating activating or inhibiting effects of phosphorylation on protein-protein interactions after insulin stimulation. The correlation of insulin-dependent interactions and phosphorylation kinetics allowed the placement of previously unknown proteins within the insulin signaling pathway. iv For example, several bait proteins were strongly associated with cytoskeletal remodeling and vesicle translocation, including RAI14, SHC3, NCK1, and SH3BP4. Other overrepresented pathways included candidates involved in fatty acid metabolism (CERS1), mRNA translocation, and translation (ZC3H11A). Overall, the workflow presented here can be used to analyze any cellular system after stimulation and therefore provides an unbiased platform to study protein-protein interactions. The data collected in this thesis serves as a repository for exploring insulin-dependent dynamics in brown adipocytes and functionally characterizes several proteins so far not known to be involved in insulin signaling

Island Distance in One-Dimensional Epitaxial Growth

The typical island distance $\ell$ in submonlayer epitaxial growth depends on the growth conditions via an exponent $\gamma$. This exponent is known to depend on the substrate dimensionality, the dimension of the islands, and the size $i^*$ of the critical nucleus for island formation. In this paper we study the dependence of $\gamma$ on $i^*$ in one--dimensional epitaxial growth. We derive that $\gamma = i^*/(2i^* + 3)$ for $i^*\geq 2$ and confirm this result by computer simulations.Comment: 5 pages, 3 figures, uses revtex, psfig, 'Note added in proof' appende

Damping of Oscillations in Layer-by-Layer Growth

We present a theory for the damping of layer-by-layer growth oscillations in molecular beam epitaxy. The surface becomes rough on distances larger than a layer coherence length which is substantially larger than the diffusion length. The damping time can be calculated by a comparison of the competing roughening and smoothening mechanisms. The dependence on the growth conditions, temperature and deposition rate, is characterized by a power law. The theoretical results are confirmed by computer simulations.Comment: 19 pages, RevTex, 5 Postscript figures, needs psfig.st

Evaporation and Step Edge Diffusion in MBE

Using kinetic Monte-Carlo simulations of a Solid-on-Solid model we investigate the influence of step edge diffusion (SED) and evaporation on Molecular Beam Epitaxy (MBE). Based on these investigations we propose two strategies to optimize MBE-growth. The strategies are applicable in different growth regimes: during layer-by-layer growth one can reduce the desorption rate using a pulsed flux. In three-dimensional (3D) growth the SED can help to grow large, smooth structures. For this purpose the flux has to be reduced with time according to a power law.Comment: 5 pages, 2 figures, latex2e (packages: elsevier,psfig,latexsym

Persistence exponents for fluctuating interfaces

Numerical and analytic results for the exponent \theta describing the decay of the first return probability of an interface to its initial height are obtained for a large class of linear Langevin equations. The models are parametrized by the dynamic roughness exponent \beta, with 0 < \beta < 1; for \beta = 1/2 the time evolution is Markovian. Using simulations of solid-on-solid models, of the discretized continuum equations as well as of the associated zero-dimensional stationary Gaussian process, we address two problems: The return of an initially flat interface, and the return to an initial state with fully developed steady state roughness. The two problems are shown to be governed by different exponents. For the steady state case we point out the equivalence to fractional Brownian motion, which has a return exponent \theta_S = 1 - \beta. The exponent \theta_0 for the flat initial condition appears to be nontrivial. We prove that \theta_0 \to \infty for \beta \to 0, \theta_0 \geq \theta_S for \beta 1/2, and calculate \theta_{0,S} perturbatively to first order in an expansion around the Markovian case \beta = 1/2. Using the exact result \theta_S = 1 - \beta, accurate upper and lower bounds on \theta_0 can be derived which show, in particular, that \theta_0 \geq (1 - \beta)^2/\beta for small \beta.Comment: 12 pages, REVTEX, 6 Postscript figures, needs multicol.sty and epsf.st

Spatial distribution of persistent sites

We study the distribution of persistent sites (sites unvisited by particles $A$) in one dimensional $A+A\to\emptyset$ reaction-diffusion model. We define the {\it empty intervals} as the separations between adjacent persistent sites, and study their size distribution $n(k,t)$ as a function of interval length $k$ and time $t$. The decay of persistence is the process of irreversible coalescence of these empty intervals, which we study analytically under the Independent Interval Approximation (IIA). Physical considerations suggest that the asymptotic solution is given by the dynamic scaling form $n(k,t)=s^{-2}f(k/s)$ with the average interval size $s\sim t^{1/2}$. We show under the IIA that the scaling function $f(x)\sim x^{-\tau}$ as $x\to 0$ and decays exponentially at large $x$. The exponent $\tau$ is related to the persistence exponent $\theta$ through the scaling relation $\tau=2(1-\theta)$. We compare these predictions with the results of numerical simulations. We determine the two-point correlation function $C(r,t)$ under the IIA. We find that for $r\ll s$, $C(r,t)\sim r^{-\alpha}$ where $\alpha=2-\tau$, in agreement with our earlier numerical results.Comment: 15 pages in RevTeX, 5 postscript figure