High-growth firms: introduction to the special section

High-growth firms (HGFs) have attracted considerable attention recently, as academics and policymakers have increasingly recognized the highly skewed nature of many metrics of firm performance. A small number of HGFs drives a disproportionately large amount of job creation, while the average firm has a limited impact on the economy. This article explores the reasons for this increased interest, summarizes the existing literature, and highlights the methodological considerations that constrain and bias research. This special section draws attention to the importance of HGFs for future industrial performance, explores their unusual growth trajectories and strategies, and highlights the lack of persistence of high growth. Consequently, while HGFs are important for understanding the economy and developing public policy, they are unlikely to be useful vehicles for public policy given the difficulties involved in predicting which firms will grow, the lack of persistence in high growth levels, and the complex and often indirect relationship between firm capability, high growth, and macro-economic performance

Quantum Speedup by Quantum Annealing

We study the glued-trees problem of Childs et. al. in the adiabatic model of quantum computing and provide an annealing schedule to solve an oracular problem exponentially faster than classically possible. The Hamiltonians involved in the quantum annealing do not suffer from the so-called sign problem. Unlike the typical scenario, our schedule is efficient even though the minimum energy gap of the Hamiltonians is exponentially small in the problem size. We discuss generalizations based on initial-state randomization to avoid some slowdowns in adiabatic quantum computing due to small gaps.Comment: 7 page

Anomalous dynamics in two- and three- dimensional Heisenberg-Mattis spin glasses

We investigate the spectral and localization properties of unmagnetized Heisenberg-Mattis spin glasses, in space dimensionalities $d=2$ and 3, at T=0. We use numerical transfer-matrix methods combined with finite-size scaling to calculate Lyapunov exponents, and eigenvalue-counting theorems, coupled with Gaussian elimination algorithms, to evaluate densities of states. In $d=2$ we find that all states are localized, with the localization length diverging as $\omega^{-1}$, as energy $\omega \to 0$. Logarithmic corrections to density of states behave in accordance with theoretical predictions. In $d=3$ the density-of-states dependence on energy is the same as for spin waves in pure antiferromagnets, again in agreement with theoretical predictions, though the corresponding amplitudes differ.Comment: RevTeX4, 9 pages, 9 .eps figure

The Dynamic Exponent of the Two-Dimensional Ising Model and Monte Carlo Computation of the Sub-Dominant Eigenvalue of the Stochastic Matrix

We introduce a novel variance-reducing Monte Carlo algorithm for accurate determination of autocorrelation times. We apply this method to two-dimensional Ising systems with sizes up to $15 \times 15$, using single-spin flip dynamics, random site selection and transition probabilities according to the heat-bath method. From a finite-size scaling analysis of these autocorrelation times, the dynamical critical exponent $z$ is determined as $z=2.1665$ (12)

Semiclassical description of spin ladders

The Heisenberg spin ladder is studied in the semiclassical limit, via a mapping to the nonlinear $\sigma$ model. Different treatments are needed if the inter-chain coupling $K$ is small, intermediate or large. For intermediate coupling a single nonlinear $\sigma$ model is used for the ladder. Its predicts a spin gap for all nonzero values of $K$ if the sum $s+\tilde s$ of the spins of the two chains is an integer, and no gap otherwise. For small $K$, a better treatment proceeds by coupling two nonlinear sigma models, one for each chain. For integer $s=\tilde s$, the saddle-point approximation predicts a sharp drop in the gap as $K$ increases from zero. A Monte-Carlo simulation of a spin 1 ladder is presented which supports the analytical results.Comment: 8 pages, RevTeX 3.0, 4 PostScript figure

Basin-scale variability of microbial methanol uptake in the Atlantic Ocean

© 2018 Author(s). Methanol is a climate-active gas and the most abundant oxygenated volatile organic compound (OVOC) in the atmosphere and seawater. Marine methylotrophs are aerobic bacteria that utilise methanol from seawater as a source of carbon (assimilation) and/or energy (dissimilation). A few spatially limited studies have previously reported methanol oxidation rates in seawater; however, the basin-wide ubiquity of marine microbial methanol utilisation remains unknown. This study uniquely combines seawater 14C labelled methanol tracer studies with 16S rRNA pyrosequencing to investigate variability in microbial methanol dissimilation and known methanol-utilising bacteria throughout a meridional transect of the Atlantic Ocean between 47° N to 39° S. Microbial methanol dissimilation varied between 0.05 and 1.68nmolL-1h-1 in the top 200m of the Atlantic Ocean and showed significant variability between biogeochemical provinces. The highest rates of methanol dissimilation were found in the northern subtropical gyre (average 0.99±0.41nmolL-1h-1), which were up to 8 times greater than other Atlantic regions. Microbial methanol dissimilation rates displayed a significant inverse correlation with heterotrophic bacterial production (determined using 3H-leucine). Despite significant depth stratification of bacterial communities, methanol dissimilation rates showed much greater variability between oceanic provinces compared to depth. There were no significant differences in rates between samples collected under light and dark environmental conditions. The variability in the numbers of SAR11 (16S rRNA gene sequences) were estimated to explain approximately 50% of the changes in microbial methanol dissimilation rates. We estimate that SAR11 cells in the Atlantic Ocean account for between 0.3% and 59% of the rates of methanol dissimilation in Atlantic waters, compared t

The phase diagram of the anisotropic Spin-1 Heisenberg Chain

We applied the Density Matrix Renormalization Group to the XXZ spin-1 quantum chain. In studing this model we aim to clarify controversials about the point where the massive Haldane phase appears.Comment: 2 pages (standart LaTex), 1 figure (PostScript) uuencode

Numerical Studies of the Two Dimensional XY Model with Symmetry Breaking Fields

We present results of numerical studies of the two dimensional XY model with four and eight fold symmetry breaking fields. This model has recently been shown to describe hydrogen induced reconstruction on the W(100) surface. Based on mean-field and renormalization group arguments,we first show how the interplay between the anisotropy fields can give rise to different phase transitions in the model. When the fields are compatible with each other there is a continuous phase transition when the fourth order field is varied from negative to positive values. This transition becomes discontinuous at low temperatures. These two regimes are separated by a multicritical point. In the case of competing four and eight fold fields, the first order transition at low temperatures opens up into two Ising transitions. We then use numerical methods to accurately locate the position of the multicritical point, and to verify the nature of the transitions. The different techniques used include Monte Carlo histogram methods combined with finite size scaling analysis, the real space Monte Carlo Renormalization Group method, and the Monte Carlo Transfer Matrix method. Our numerical results are in good agreement with the theoretical arguments.Comment: 29 pages, HU-TFT-94-36, to appear in Phys. Rev. B, Vol 50, November 1, 1994. A LaTeX file with no figure

Seasonal variability in microbial methanol utilisation in coastal waters of the western English Channel

© The authors 2016. Methanol is ubiquitous in seawater and is the most abundant oxygenated volatile organic compound (OVOC) in the atmosphere, where it influences oxidising capacity and ozone formation. Marine methylotrophic bacteria utilise methanol in seawater as an energy and/or growth substrate. This work represents the first fully resolved seasonal study of marine microbial methanol uptake dynamics. Rates of microbial methanol dissimilation in coastal surface waters of the UK varied between 0.7 and 11.2 nmol l-1 h-1 and reached a maximum in February. Rates of microbial methanol assimilation varied between 0.04 and 2.64 10-2 nmol l-1 h-1 and reached a maximum in August. Temporal variability in microbial methanol uptake rates shows that methanol assimilation and dissimilation display opposing seasonal cycles, although overall