Comparative Monte Carlo Efficiency by Monte Carlo Analysis

We propose a modified power method for computing the subdominant eigenvalue $\lambda_2$ of a matrix or continuous operator. Here we focus on defining simple Monte Carlo methods for its application. The methods presented use random walkers of mixed signs to represent the subdominant eigenfuction. Accordingly, the methods must cancel these signs properly in order to sample this eigenfunction faithfully. We present a simple procedure to solve this sign problem and then test our Monte Carlo methods by computing the $\lambda_2$ of various Markov chain transition matrices. We first computed ${\lambda_2}$ for several one and two dimensional Ising models, which have a discrete phase space, and compared the relative efficiencies of the Metropolis and heat-bath algorithms as a function of temperature and applied magnetic field. Next, we computed $\lambda_2$ for a model of an interacting gas trapped by a harmonic potential, which has a mutidimensional continuous phase space, and studied the efficiency of the Metropolis algorithm as a function of temperature and the maximum allowable step size $\Delta$. Based on the $\lambda_2$ criterion, we found for the Ising models that small lattices appear to give an adequate picture of comparative efficiency and that the heat-bath algorithm is more efficient than the Metropolis algorithm only at low temperatures where both algorithms are inefficient. For the harmonic trap problem, we found that the traditional rule-of-thumb of adjusting $\Delta$ so the Metropolis acceptance rate is around 50% range is often sub-optimal. In general, as a function of temperature or $\Delta$, $\lambda_2$ for this model displayed trends defining optimal efficiency that the acceptance ratio does not. The cases studied also suggested that Monte Carlo simulations for a continuum model are likely more efficient than those for a discretized version of the model.Comment: 23 pages, 8 figure

The impact of ERP systems on firm and business process performance

Purpose - The purpose of this article is to provide further insights into the adoption of enterprise resource planning (ERP) systems and the impacts on organisational performance. It aims at challenging existing claims of ERP vendors with regard to the benefits of their products and at providing evidence of the benefits of bundling ERPS with supply chain management systems. Design/methodology/approach - A survey was conducted to collect data on several aspects of organisational performance in companies that adopted ERPS and/or SCMS and the respective control groups. Financial key performance indicators were used to measure overall firm performance and the supply-chain operations reference model to operationalise performance at the business process (supply chain) level. Findings - The key results contradict the claims of ERPS vendors insofar as no significant performance differences were found between ERPS adopters and non-adopters, either at the business process level, or at the overall firm level. While it could be confirmed that the longer the experience of firms with ERPS, the higher their overall performance, no evidence was found of a similar effect on business process (supply chain) performance. Only those ERPS adopters that also adopted SCMS achieved significantly higher performance at the business process level. Originality/value - Despite the small size of the SCMS user sample, the results do provide some important insights into the relationships between ERPS, SCMS and performance which might encourage both researchers and practitioners in that field to critically reflect on the "optimal" mix of modules and software packages within increasingly diverse forms of enterprise systems. © Emerald Group Publishing Limited

Interpreting the extended emission around three nearby debris disc host stars

Cool debris discs are a relic of the planetesimal formation process around their host star, analogous to the solar system's Edgeworth-Kuiper belt. As such, they can be used as a proxy to probe the origin and formation of planetary systems like our own. The Herschel Open Time Key Programmes "DUst around NEarby Stars" (DUNES) and "Disc Emission via a Bias-free Reconnaissance in the Infrared/Submillimetre" (DEBRIS) observed many nearby, sun-like stars at far-infrared wavelengths seeking to detect and characterize the emission from their circumstellar dust. Excess emission attributable to the presence of dust was identified from around $\sim$ 20% of stars. Herschel's high angular resolution ($\sim$ 7" FWHM at 100 $\mu$m) provided the capacity for resolving debris belts around nearby stars with radial extents comparable to the solar system (50 to 100 au). As part of the DUNES and DEBRIS surveys, we obtained observations of three debris disc stars, HIP 22263 (HD 30495), HIP 62207 (HD 110897), and HIP 72848 (HD 131511), at far-infrared wavelengths with the Herschel PACS instrument. Combining these new images and photometry with ancilliary data from the literature, we undertook simultaneous multi-wavelength modelling of the discs' radial profiles and spectral energy distributions using three different methodologies: single annulus, modified black body, and a radiative transfer code. We present the first far-infrared spatially resolved images of these discs and new single-component debris disc models. We characterize the capacity of the models to reproduce the disc parameters based on marginally resolved emission through analysis of two sets of simulated systems (based on the HIP 22263 and HIP 62207 data) with the noise levels typical of the Herschel images. We find that the input parameter values are recovered well at noise levels attained in the observations presented here.Comment: 13 pages, 5 figures, 5 tables, accepted for publication in A&

A return to strong radio flaring by Circinus X-1 observed with the Karoo Array Telescope test array KAT-7

Circinus X-1 is a bright and highly variable X-ray binary which displays strong and rapid evolution in all wavebands. Radio flaring, associated with the production of a relativistic jet, occurs periodically on a ~17-day timescale. A longer-term envelope modulates the peak radio fluxes in flares, ranging from peaks in excess of a Jansky in the 1970s to an historic low of milliJanskys during the years 1994 to 2007. Here we report first observations of this source with the MeerKAT test array, KAT-7, part of the pathfinder development for the African dish component of the Square Kilometre Array (SKA), demonstrating successful scientific operation for variable and transient sources with the test array. The KAT-7 observations at 1.9 GHz during the period 13 December 2011 to 16 January 2012 reveal in temporal detail the return to the Jansky-level events observed in the 1970s. We compare these data to contemporaneous single-dish measurements at 4.8 and 8.5 GHz with the HartRAO 26-m telescope and X-ray monitoring from MAXI. We discuss whether the overall modulation and recent dramatic brightening is likely to be due to an increase in the power of the jet due to changes in accretion rate or changing Doppler boosting associated with a varying angle to the line of sight.Comment: 7 pages, 5 figures, accepted for publication in MNRAS 14 May 201

Influence of vegetation on the ITCZ and South Asian monsoon in HadCM3

The role of extra-tropical vegetation on the large-scale tropical circulation is examined in the version 3 Hadley Centre Climate Model (HadCM3). Alternative representations of present day vegetation from observations and a dynamic vegetation model were used as the land-cover component for a number of HadCM3 experiments under a nominal present day climate state, and are shown to induce perturbations to the simulated global dynamics. This results in a shift in the location of the Inter Tropical Convergence Zone (ITCZ) and changes in the South Asian monsoon circulation. This has a significant impact on the Indian land precipitation compared to the standard configuration of HadCM3. This large-scale forcing is consistent with documented mechanisms relating to temperature and snow perturbations in the Northern Hemisphere extra-tropics. This analysis demonstrates that uncertainties in the representation of present day vegetation cover can result in significant perturbations to the simulated climate. The role of the Northern Hemisphere extra-tropics is further demonstrated with a fourth representation of vegetation cover produced by imposing simulated changes in Northern Hemisphere extra-tropical vegetation from the end of the 21st century on the present day climate. This experiment shows that through similar processes extra-tropical vegetation changes in the future contribute to a strengthening of the South Asian monsoon in this model, with a particular influence on the monsoon onset. These findings provide renewed motivation to give careful consideration to the role of global scale vegetation feedbacks when looking at climate change and its impact on the tropics and South Asian monsoon in the latest generation of Earth System models

Monte Carlo Determination of Multiple Extremal Eigenpairs

We present a Monte Carlo algorithm that allows the simultaneous determination of a few extremal eigenpairs of a very large matrix without the need to compute the inner product of two vectors or store all the components of any one vector. The new algorithm, a Monte Carlo implementation of a deterministic one we recently benchmarked, is an extension of the power method. In the implementation presented, we used a basic Monte Carlo splitting and termination method called the comb, incorporated the weight cancellation method of Arnow {\it et al.}, and exploited a new sampling method, the sewing method, that does a large state space sampling as a succession of small state space samplings. We illustrate the effectiveness of the algorithm by its determination of the two largest eigenvalues of the transfer matrices for variously-sized two-dimensional, zero field Ising models. While very likely useful for other transfer matrix problems, the algorithm is however quite general and should find application to a larger variety of problems requiring a few dominant eigenvalues of a matrix.Comment: 22 pages, no figure

Correcting a bias in a climate model with an augmented emulator

This is the final version. Available from Copernicus Publications via the DOI in this record. A key challenge in developing flagship climate model configurations is the process of setting uncertain input parameters at values that lead to credible climate simulations. Setting these parameters traditionally relies heavily on insights from those involved in parameterisation of the underlying climate processes. Given the many degrees of freedom and computational expense involved in evaluating such a selection, this can be imperfect leaving open questions about whether any subsequent simulated biases result from mis-set parameters or wider structural model errors (such as missing or partially parameterised processes). Here, we present a complementary approach to identifying plausible climate model parameters, with a method of bias correcting subcomponents of a climate model using a Gaussian process emulator that allows credible values of model input parameters to be found even in the presence of a significant model bias. A previous study (McNeall et al., 2016) found that a climate model had to be run using land surface input parameter values from very different, almost non-overlapping, parts of parameter space to satisfactorily simulate the Amazon and other forests respectively. As the forest fraction of modelled non-Amazon forests was broadly correct at the default parameter settings and the Amazon too low, that study suggested that the problem most likely lay in the model's treatment of non-plant processes in the Amazon region. This might be due to modelling errors such as missing deep rooting in the Amazon in the land surface component of the climate model, to a warm-dry bias in the Amazon climate of the model or a combination of both. In this study, we bias correct the climate of the Amazon in the climate model from McNeall et al. (2016) using an "augmented" Gaussian process emulator, where temperature and precipitation, variables usually regarded as model outputs, are treated as model inputs alongside land surface input parameters. A sensitivity analysis finds that the forest fraction is nearly as sensitive to climate variables as it is to changes in its land surface parameter values. Bias correcting the climate in the Amazon region using the emulator corrects the forest fraction to tolerable levels in the Amazon at many candidates for land surface input parameter values, including the default ones, and increases the valid input space shared with the other forests. We need not invoke a structural model error in the land surface model, beyond having too dry and hot a climate in the Amazon region. The augmented emulator allows bias correction of an ensemble of climate model runs and reduces the risk of choosing poor parameter values because of an error in a subcomponent of the model. We discuss the potential of the augmented emulator to act as a translational layer between model subcomponents, simplifying the process of model tuning when there are compensating errors and helping model developers discover and prioritise model errors to target.Alan Turing Institut

Corporate volunteering climate: mobilizing employee passion for societal causes and inspiring future charitable action

As a society, we grapple with a host of national and global social issues — ranging from hunger and poverty to education to financial stability. Today’s corporations are playing an increasing role in efforts to address such concerns, predominantly through corporate volunteering. Yet, because research on corporate volunteering has been primarily focused on the individual volunteer experience, we still know relatively little about how corporate volunteering can help address grand challenges. In this study, we introduce the concept of corporate volunteering climate in order to examine the broader, more system-level functioning of corporate volunteering in workplaces. Drawing on the sensemaking process, we theorize about how a corporate volunteering climate develops — to what extent is it driven by company-level policies versus employee convictions for a cause? We also explore the potential influence of corporate volunteering climate for volunteers and non-volunteers, both in terms of the workplace (through employee affective commitment) and in terms of the broader community (through employee intentions to volunteer, both in corporate opportunities and on personal time). The results of a study conducted with United Way Worldwide suggest that corporate volunteering climate not only arises through either employees’ belief in the cause or corporate policies, but also that these forces act as substitutes for one another. Moreover, by fostering a sense of collective pride among employees, this climate is related to affective commitment, as well as both corporate and personal volunteering intentions

The strong coupling constant from lattice QCD with N_f=2 dynamical quarks

We compute $\Lambda_{\bar{MS}}$ for two flavors of light dynamical quarks using non-perturbatively $O(a)$ improved Wilson fermions. We improve on a recent calculation by employing Pad\'e-improved two-loop and three-loop perturbation theory to convert the lattice numbers to the $\bar{MS}$ scheme.Comment: Contribution to Lattice 2001 (matrix elements), typo correcte