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AbstractIn recent years substantial efforts have been expended in extending thermodynamics to single quantum systems. Quantum effects have emerged as a resource that can improve the performance of heat machines. However in the fully quantum regime their implementation still remains a challenge. Here, we report an experimental realization of a quantum absorption refrigerator in a system of three trapped ions, with three of its normal modes of motion coupled by a trilinear Hamiltonian such that heat transfer between two modes refrigerates the third. We investigate the dynamics and steady-state properties of the refrigerator and compare its cooling capability when only thermal states are involved to the case when squeezing is employed as a quantum resource. We also study the performance of such a refrigerator in the single shot regime made possible by coherence and demonstrate cooling below both the steady-state energy and a benchmark set by classical thermodynamics.

The study aims to estimate the influence of machine scale size on the behavior of plasma with extrinsic seeded impurities in the scrape-off layer (SOL) and divertor. This is performed through the comparison of plasma boundary simulations using the SOLPS-ITER code including drifts and currents of nitrogen (N) and neon (Ne) injection in ITER and ASDEX Upgrade (AUG) geometries. Trends are examined between the two seeding species in each individual device and by a comparison of the differences between the two machines. In the modeling results, the radiated power peak is located near the X-point in the inner divertor for the AUG cases and in the vicinity of the strike points in both divertors in ITER. The simulations also find less Ne impurity ions in the divertor volume than N and more significant Ne radiation inside the separatrix for AUG, consistent with published experimental findings. In ITER, both species radiate mostly from the divertor, in agreement with the existing SOLPS-4.3 simulation database obtained without drifts and with a less sophisticated treatment of parallel impurity transport. Drifts are important players in determining the plasma background for AUG and are comparatively less important in ITER. In both devices, the spatial distribution of the impurity ion density is complex, with their parallel flow patterns correlating with the thermal and friction force balance. Within this isolated modeling study, the principal reasons for different behavior between N and Ne on AUG and ITER appear to be the combination of a stronger drift effect and reduced screening of recycled fuel and impurity from divertor to private flux region on AUG leading to a more extended, colder plasma than in ITER. The increased temperature in the confined region just inside the separatrix on ITER also means that impurity ions reaching this zone are fully ionized and do not contribute significantly to the radiation loss there. On the basis of this study, both N and Ne are found to be acceptable low Z radiators on ITER.

The photoionization of two representative mono-terpenes (R-limonene and R-carvone) has been investigated using low energy synchrotron radiation in the region from the threshold for ionization of these molecules up to 11 eV. Data from threshold photoelectron spectra are interpreted with the aid of Outer Valence Green's Function (OVGF) calculations to identify the character of the outermost orbitals and improved ionization potentials are deduced. Fragmentation of the parent ions is studied using threshold photoelectron-photoion coincidence (TPEPICO) time-of-flight (TOF) mass spectrometry and breakdown diagrams identifying the major products in this near-threshold region are presented.

In this paper, a two-tiered Wireless Sensor Network (WSN) where nodes are divided into clusters and nodes forward data to base stations through cluster heads is considered. To maximize the network lifetime, two energy efficient approaches are investigated. We first propose an approach that optimally locates the base stations within the network so that the distance between each cluster head and its closest base station is decreased. Then, a routing technique is developed to arrange the communication between cluster heads toward the base stations in order to guaranty that the gathered information effectively and efficiently reach the application. The overall dynamic framework that combines the above two schemes is described and evaluated. The experimental performance evaluation demonstrates the efficacy of topology control as a vital process to maximize the network lifetime of WSNs.

We present a simple mathematical model of glassy dynamics seen as a random walk in a directed, weighted network of minima taken as a representation of the energy landscape. Our approach gives a broader perspective to previous studies focusing on particular examples of energy landscapes obtained by sampling energy minima and saddles of small systems. We point out how the relation between the energies of the minima and their number of neighbors should be studied in connection with the network's global topology, and show how the tools developed in complex network theory can be put to use in this context.

In this paper, we provide an overview of the MANGO project and its goal. The MANGO project aims at addressing power, performance and predictability (the PPP space) in future High-Performance Computing systems. It starts from the fundamental intuition that effective techniques for all three goals ultimately rely on customization to adapt the computing resources to reach the desired Quality of Service (QoS). From this starting point, MANGO will explore different but interrelated mechanisms at various architectural levels, as well as at the level of the system software. In particular, to explore a new positioning across the PPP space, MANGO will investigate system-wide, holistic, proactive thermal and power management aimed at extreme-scale energy efficiency. The MANGO project starts in October 2015 and is funded by the European Commission under the Horizon 2020 FET-HPC program. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 671668.