Quantum-classical interactions through the path integral

I consider the case of two interacting scalar fields, \phi and \psi, and use the path integral formalism in order to treat the first classically and the second quantum-mechanically. I derive the Feynman rules and the resulting equation of motion for the classical field, which should be an improvement of the usual semi-classical procedure. As an application I use this method in order to enforce Gauss's law as a classical equation in a non-abelian gauge theory. I argue that the theory is renormalizable and equivalent to the usual Yang-Mills as far as the gauge field terms are concerned. There are additional terms in the effective action that depend on the Lagrange multiplier field \lambda that is used to enforce the constraint. These terms and their relation to the confining properties of the theory are discussed.Comment: 16 pages, LaTeX, 1 fig, final version to appear in PR

Evaluating Asymmetric Multicore Systems-on-Chip using Iso-Metrics

The end of Dennard scaling has pushed power consumption into a first order concern for current systems, on par with performance. As a result, near-threshold voltage computing (NTVC) has been proposed as a potential means to tackle the limited cooling capacity of CMOS technology. Hardware operating in NTV consumes significantly less power, at the cost of lower frequency, and thus reduced performance, as well as increased error rates. In this paper, we investigate if a low-power systems-on-chip, consisting of ARM's asymmetric big.LITTLE technology, can be an alternative to conventional high performance multicore processors in terms of power/energy in an unreliable scenario. For our study, we use the Conjugate Gradient solver, an algorithm representative of the computations performed by a large range of scientific and engineering codes.Comment: Presented at HiPEAC EEHCO '15, 6 page

Forecasting Industry-Level CPI and PPI Inflation: Does Exchange Rate Pass-Through Matter?

In this paper, we examine whether industry-level forecasts of CPI and PPI inflation can be improved using the ``exchange rate pass-through" effect, that is, when one accounts for the variability of the exchange rate and import prices. An exchange rate depreciation leading to a higher level of pass-through to import prices implies greater expenditure switching, which should be manifested, possibly with a lag, in both producer and consumer prices. We build a forecasting model based on a two or three equation system involving CPI and PPI inflation where the effects of the exchange rate and import prices are taken into account. This setup also incorporates their dynamics, lagged correlations and appropriate restrictions suggested by the theory. We compare the performance of this model with a variety of unrestricted univariate and multivariate time series models, as well as with a model that, in addition, includes standard control variables for inflation, like interest rates and unemployment. Our results indicate that improvements on the forecast accuracy can be effected when one takes into account the possible pass-through effects of exchange rates and import prices on CPI and PPI inflation.Forecasting, Vector Autoregression, Non-linear Models, Inflation, Exchange Rates, Pass-Through Effect

Retirement and Household Expenditure in Turbulent Times

We examine the impact of own and spousal retirement on household expenditure during a period of financial deterioration. We use detailed household data covering the period 2009-2016 in Greece, during which the country experienced a severe financial crisis that affected retirees in ways that were not anticipated. Similar to Moreau and Stancanelli (2015) our empirical strategy allows for the household expenditure to depend on both own and spousal retirement status. We employ an instrumental variable identification strategy by exploiting variation coming from the early retirement age threshold. Our Two-Stage Least Squares estimates show that, even after controlling for income, total expenditure drops significantly when the husband retires and as he becomes older. The reduction is stronger in 2010, when the first wave of austerity plans, including measures affecting pensioners were announced, and after 2014 when horizontal pension cuts were implemented. Expenditure does not change significantly when the wife retires neither the older she gets. A drop-in expenditure for clothing, transport, housing and communication drives the overall reduction in expenditure. Overall, our results can have significant policy implications in the design of structural pension reforms in a period of financial hardship

Improving forecasting performance by window and model averaging

This study presents extensive results on the benefits of rolling window and model averaging. Building on the recent work on rolling window averaging by Pesaran et al (2010, 2009) and on exchange rate forecasting by Molodtsova and Papell (2009), we explore whether rolling window averaging can be considered beneficial on a priori grounds. We investigate whether rolling window averaging can improve the performance of model averaging, especially when ‘simpler’ models are used. The analysis provides strong support for rolling window averaging, outperforming the best window forecasts more than 50% of the time across all rolling windows. Furthermore, rolling window averaging smoothes out the forecast path, improves robustness, and minimizes the pitfalls associated with potential structural breaks.Exchange rate forecasting, inflation forecasting, output growth forecasting, rolling window, model averaging, short horizon, robustness.

Realized Volatility and Asymmetries in the A.S.E. Returns

Using a newly developed dataset of daily, value-weighted market returns we construct and analyze the monthly realized volatility of the Athens Stock Exchange (A.S.E.) from 1985 to 2003. Our analysis focuses on the distributional and time series properties of the realized volatility series and on assessing the connection between realized volatility and returns. In particular, we find strong evidence on the existence of a volatility feedback effect and the leverage effect, and on the existence of asymmetries between lagged returns and volatility. Furthermore, we examine the cross-sectional distribution of unconditional loadings on the realized risk factor(s) for different sets of characteristics-sorted common stock portfolios. We find that realized risk is a significantly priced factor in A.S.E. and its high explanatory power for the cross- section of portfolio average returns is independent of any return variation related to the market (CAPM) or size and book-to-market (Fama- French) factors. We discuss our findings in the context of the recent literature on realized volatility and feedback effects, as well as the literature on the pricing power of realized risk.realized volatility, leverage effect, volatility feedback effect, asset pricing, A.S.E.

X-Ray Spectra of Z Sources

A simple, physically consistent model has been proposed that seeks to explain in a unified way the X-ray spectra and rapid X-ray variability of the so-called Z sources and other accreting neutron stars in low-mass systems. Here we summarize the results of detailed numerical calculations of the X-ray spectra of the Z sources predicted by this model. Our computations show that in the Z sources, photons are produced primarily by electron cyclotron emission in the neutron star magnetosphere. Comptonization of these photons by the hot central corona and radial inflow produces X-ray spectra, color-color tracks, and countrate variations like those observed in the Z sources.Comment: 6 pages, 2 Postscript figures in 4 files, uses aas2pp4.sty, submitted to ApJ (Letters) 1995 May 3

Edge-as-a-Service: Towards Distributed Cloud Architectures

We present an Edge-as-a-Service (EaaS) platform for realising distributed cloud architectures and integrating the edge of the network in the computing ecosystem. The EaaS platform is underpinned by (i) a lightweight discovery protocol that identifies edge nodes and make them publicly accessible in a computing environment, and (ii) a scalable resource provisioning mechanism for offloading workloads from the cloud on to the edge for servicing multiple user requests. We validate the feasibility of EaaS on an online game use-case to highlight the improvement in the QoS of the application hosted on our cloud-edge platform. On this platform we demonstrate (i) low overheads of less than 6%, (ii) reduced data traffic to the cloud by up to 95% and (iii) minimised application latency between 40%-60%.Comment: 10 pages; presented at the EdgeComp Symposium 2017; will appear in Proceedings of the International Conference on Parallel Computing, 201

ENORM: A Framework For Edge NOde Resource Management

Current computing techniques using the cloud as a centralised server will become untenable as billions of devices get connected to the Internet. This raises the need for fog computing, which leverages computing at the edge of the network on nodes, such as routers, base stations and switches, along with the cloud. However, to realise fog computing the challenge of managing edge nodes will need to be addressed. This paper is motivated to address the resource management challenge. We develop the first framework to manage edge nodes, namely the Edge NOde Resource Management (ENORM) framework. Mechanisms for provisioning and auto-scaling edge node resources are proposed. The feasibility of the framework is demonstrated on a PokeMon Go-like online game use-case. The benefits of using ENORM are observed by reduced application latency between 20% - 80% and reduced data transfer and communication frequency between the edge node and the cloud by up to 95\%. These results highlight the potential of fog computing for improving the quality of service and experience.Comment: 14 pages; accepted to IEEE Transactions on Services Computing on 12 September 201