Application of disturbance management principles in fresh food supply chains

The desire for more robust supply chains has led to a growth in theoretical and practical interest in the application of both preventive and impact reductive disturbance management principles. This application should ultimately lead to less vulnerable and more competitive supply chains. Based on the extant literature we identify fresh food supply chain's contextual factors (products, processes, supply chain networks and supply chain business environment) and their corresponding characteristics, as well as the main disturbance management principles used. To analyse their influence on the selection and application of disturbance management principles in fresh food supply chains we conducted three case studies. In each case we collected data on the relevant contextual factors, disturbance management principles applied and company background. As an underlying methodology, we first conduct within-case analysis and then expand the analyses to a cross-case context. Based on the findings from these case studies, propositions are built concerning the nature of contextual factors and their characteristics, and their influence on the selection and application of disturbance management principles in fresh food supply chains. Our main findings are related to the identification of contextual characteristics of fresh food supply chains that are either critical vulnerability sources, critical enablers or conditionals and as such require, facilitate or condition selection and application of disturbance management principles.

Formation of helical ion chains

We study the nonequilibrium dynamics of the linear to zigzag structural phase transition exhibited by an ion chain confined in a trap with periodic boundary conditions. The transition is driven by reducing the transverse confinement at a finite quench rate, which can be accurately controlled. This results in the formation of zigzag domains oriented along different transverse planes. The twists between different domains can be stabilized by the topology of the trap and under laser cooling the system has a chance to relax to a helical chain with nonzero winding number. Molecular dynamics simulations are used to obtain a large sample of possible trajectories for different quench rates. The scaling of the average winding number with different quench rates is compared to the prediction of the Kibble-Zurek theory, and a good quantitative agreement is found.

Non-Gaussian distribution of collective operators in quantum spin chains

We numerically analyse the behavior of the full distribution of collective observables in quantum spin chains. While most of previous studies of quantum critical phenomena are limited to the first moments, here we demonstrate how quantum fluctuations at criticality lead to highly non-Gaussian distributions. Interestingly, we show that the distributions for different system sizes collapse on thesame curve after scaling for a wide range of transitions: first and second order quantum transitions and transitions of the Berezinskii–Kosterlitz–Thouless type. We propose and analyse the feasibility of an experimental reconstruction of the distribution using light–matter interfaces for atoms in optical lattices or in optical resonators.