Multiple Ionization under Strong XUV to X-ray Radiation

We review the main aspects of multiple photoionization processes in atoms exposed to intense, short wavelength radiation. The main focus is the theoretical framework for the description of such processes as well as the conditions under which direct multiphoton multiple ionization processes can dominate over the sequential ones. We discuss in detail the mechanisms available in different wavelength ranges from the infrared to the hard X-rays. The effect of field fluctuations, present at this stage in all SASE free-electron-laser (FEL) facilities, as well as the effect of the interaction volume integration, are also discussed

Effects of relative phase and interactions on atom-laser outcoupling from a double-well Bose-Einstein condensate: Markovian and non-Markovian dynamics

We investigate aspects of the dynamics of a continuous atom-laser scheme based on the merging of independently formed atomic condensates. Our theoretical analysis covers the Markovian as well as the non-Markovian operational regimes, and is based on a semiclassical (mean-field) two-mode model. The role of the relative phase between the two condensates and the effect of interatomic interactions on the evolution of the trapped populations and the distribution of outcoupled atoms are discussed.Comment: to appear in J. Phys.

Route to Direct Multiphoton Multiple Ionization

We address the concept of direct multiphoton multiple ionization in atoms exposed to intense, short wavelength radiation and explore the conditions under which such processes dominate over the sequential. Their contribution is shown to be quite robust, even under intensity fluctuations and interaction volume integration, and reasonable agreement with experimental data is also found.Comment: Close to the version to be published in Phys. Rev. A. Additional supplementary material can be found ther

Effective forecasting for supply-chain planning: an empirical evaluation and strategies for improvement

Demand forecasting is a crucial aspect of the planning process in supply-chain companies. The most common approach to forecasting demand in these companies involves the use of a simple univariate statistical method to produce a forecast and the subsequent judgmental adjustment of this by the company's demand planners to take into account market intelligence relating to any exceptional circumstances expected over the planning horizon. Based on four company case studies, which included collecting more than 12,000 forecasts and outcomes, this paper examines: i) the extent to which the judgmental adjustments led to improvements in accuracy, ii) the extent to which the adjustments were biased and inefficient, iii) the circumstances where adjustments were detrimental or beneficial, and iv) methods that could lead to greater levels of accuracy. It was found that the judgmentally adjusted forecasts were both biased and inefficient. In particular, market intelligence that was expected to have a positive impact on demand was used far less effectively than intelligence suggesting a negative impact. The paper goes on to propose a set of improvements that could be applied to the forecasting processes in the companies and to the forecasting software that is used in these processes