Study made of large amplitude fuel sloshing

Study of resonant oscillations of an ideal fluid in a cylindrical tank is used to obtain a better understanding of fuel sloshing in large liquid booster. More realistic structural design criteria may be formulated when the dynamic response of the liquid in a cylindrical tank can be predicted analytically

Polaronic signature in the metallic phase of La0.7Ca0.3MnO3 films detected by scanning tunneling spectroscopy

In this work we map tunnel conductance curves with nanometric spatial resolution, tracking polaronic quasiparticle excitations when cooling across the insulator-to-metal transition in La0.7Ca0.3MnO3 films. In the insulating phase the spectral signature of polarons, a depletion of conductance at low bias flanked by peaks, is detected all over the scanned surface. These features are still observed at the transition and persist on cooling into the metallic phase. Polaron-binding energy maps reveal that polarons are not confined to regions embedded in a highly-conducting matrix but are present over the whole field of view both above and below the transition temperature.Comment: 10 pages, 4 figure

Controlling Fast Chaos in Delay Dynamical Systems

We introduce a novel approach for controlling fast chaos in time-delay dynamical systems and use it to control a chaotic photonic device with a characteristic time scale of ~12 ns. Our approach is a prescription for how to implement existing chaos control algorithms in a way that exploits the system's inherent time-delay and allows control even in the presence of substantial control-loop latency (the finite time it takes signals to propagate through the components in the controller). This research paves the way for applications exploiting fast control of chaos, such as chaos-based communication schemes and stabilizing the behavior of ultrafast lasers.Comment: 4 pages, 4 figures, to be published in Physical Review Letter

Local quasiparticle density of states of superconducting SmFeAsO1−x1-xFxx single crystals: Evidence for spin-mediated pairing

We probe the local quasiparticles density-of-states in micron-sized SmFeAsO$_{1-x}$F$_{x}$ single-crystals by means of Scanning Tunnelling Spectroscopy. Spectral features resemble those of cuprates, particularly a dip-hump-like structure developed at energies larger than the gap that can be ascribed to the coupling of quasiparticles to a collective mode, quite likely a resonant spin mode. The energy of the collective mode revealed in our study decreases when the pairing strength increases. Our findings support spin-fluctuation-mediated pairing in pnictides.Comment: 11 pages, 4 figure

A Comparison of Autonomic Decision Making Techniques

Autonomic computing systems are capable of adapting their behavior and resources thousands of times a second to automatically decide the best way to accomplish a given goal despite changing environmental conditions and demands. Different decision mechanisms are considered in the literature, but in the vast majority of the cases a single technique is applied to a given instance of the problem. This paper proposes a comparison of some state of the art approaches for decision making, applied to a self-optimizing autonomic system that allocates resources to a software application, which provides direct performance feedback at runtime. The Application Heartbeats framework is used to provide the sensor data (feedback), and a variety of decision mechanisms, from heuristics to control-theory and machine learning, are investigated. The results obtained with these solutions are compared by means of case studies using standard benchmarks

SEEC: A Framework for Self-aware Computing

As the complexity of computing systems increases, application programmers must be experts in their application domain and have the systems knowledge required to address the problems that arise from parallelism, power, energy, and reliability concerns. One approach to relieving this burden is to make use of self-aware computing systems, which automatically adjust their behavior to help applications achieve their goals. This paper presents the SEEC framework, a unified computational model designed to enable self-aware computing in both applications and system software. In the SEEC model, applications specify goals, system software specifies possible actions, and the SEEC framework is responsible for deciding how to use the available actions to meet the application-specified goals. The SEEC framework is built around a general and extensible control system which provides predictable behavior and allows SEEC to make decisions that achieve goals while optimizing resource utilization. To demonstrate the applicability of the SEEC framework, this paper presents fivedifferent self-aware systems built using SEEC. Case studies demonstrate how these systems can control the performance of the PARSEC benchmarks, optimize performance per Watt for a video encoder, and respond to unexpected changes in the underlying environment. In general these studies demonstrate that systems built using the SEEC framework are goal-oriented, predictable, adaptive, and extensible

A generalized software framework for accurate and efficient management of performance goals

A number of techniques have been proposed to provide runtime performance guarantees while minimizing power consumption. One drawback of existing approaches is that they work only on a fixed set of components (or actuators) that must be specified at design time. If new components become available, these management systems must be redesigned and reimplemented. In this paper, we propose PTRADE, a novel performance management framework that is general with respect to the components it manages. PTRADE can be deployed to work on a new system with different components without redesign and reimplementation. PTRADE's generality is demonstrated through the management of performance goals for a variety of benchmarks on two different Linux/x86 systems and a simulated 128-core system, each with different components governing power and performance tradeoffs. Our experimental results show that PTRADE provides generality while meeting performance goals with low error and close to optimal power consumption.United States. Defense Advanced Research Projects Agency. The Ubiquitous High Performance Computing Progra

A coordinated optical and X-ray spectroscopic campaign on HD179949: searching for planet-induced chromospheric and coronal activity

HD179949 is an F8V star, orbited by a close-in giant planet with a period of ~3 days. Previous studies suggested that the planet enhances the magnetic activity of the parent star, producing a chromospheric hot spot which rotates in phase with the planet orbit. However, this phenomenon is intermittent since it was observed in several but not all seasons. A long-term monitoring of the magnetic activity of HD179949 is required to study the amplitude and time scales of star-planet interactions. In 2009 we performed a simultaneous optical and X-ray spectroscopic campaign to monitor the magnetic activity of HD179949 during ~5 orbital periods and ~2 stellar rotations. We analyzed the CaII H&K lines as a proxy for chromospheric activity, and we studied the X-ray emission in search of flux modulations and to determine basic properties of the coronal plasma. A detailed analysis of the flux in the cores of the CaII H&K lines and a similar study of the X-ray photometry shows evidence of source variability, including one flare. The analysis of the the time series of chromospheric data indicates a modulation with a ~11 days period, compatible with the stellar rotation period at high latitudes. Instead, the X-ray light curve suggests a signal with a period of ~4 days, consistent with the presence of two active regions on opposite hemispheres. The observed variability can be explained, most likely, as due to rotational modulation and to intrinsic evolution of chromospheric and coronal activity. There is no clear signature related to the orbital motion of the planet, but the possibility that just a fraction of the chromospheric and coronal variability is modulated with the orbital period of the planet, or the stellar-planet beat period, cannot be excluded. We conclude that any effect due to the presence of the planet is difficult to disentangle

SEEC: A Framework for Self-aware Management of Multicore Resources

This paper presents SEEC, a self-aware programming model, designed to reduce programming effort in modern multicore systems. In the SEEC model, application programmers specify application goals and progress, while systems programmers separately specify actions system software and hardware can take to affect an application (e.g. resource allocation). The SEEC runtime monitors applications and dynamically selects actions to meet application goals optimally (e.g. meeting performance while minimizing power consumption). The SEEC runtime optimizes system behavior for the application rather than requiring the application programmer to optimize for the system. This paper presents a detailed discussion of the SEEC model and runtime as well as several case studies demonstrating their benefits. SEEC is shown to optimize performance per Watt for a video encoder, find optimal resource allocation for an application with complex resource usage, and maintain the goals of multiple applications in the face of environmental fluctuations

Methods for Estimating Fluxes and Absorptions of Faint X-ray Sources

X-ray sources with very few counts can be identified with low-noise X-ray detectors such as ACIS onboard the Chandra X-ray Observatory. These sources are often too faint for parametric spectral modeling using well-established methods such as fitting with XSPEC. We discuss the estimation of apparent and intrinsic broad-band X-ray fluxes and soft X-ray absorption from gas along the line of sight to these sources, using nonparametric methods. Apparent flux is estimated from the ratio of the source count rate to the instrumental effective area averaged over the chosen band. Absorption, intrinsic flux, and errors on these quantities are estimated from comparison of source photometric quantities with those of high S/N spectra that were simulated using spectral models characteristic of the class of astrophysical sources under study. The concept of this method is similar to the long-standing use of color-magnitude diagrams in optical and infrared astronomy, with X-ray median energy replacing color index and X-ray source counts replacing magnitude. Our nonparametric method is tested against the apparent spectra of 2000 faint sources in the Chandra observation of the rich young stellar cluster in the M17 HII region. We show that the intrinsic X-ray properties can be determined with little bias and reasonable accuracy using these observable photometric quantities without employing often uncertain and time-consuming methods of non-linear parametric spectral modeling. Our method is calibrated for thermal spectra characteristic of stars in young stellar clusters, but recalibration should be possible for some other classes of faint X-ray sources such as extragalactic AGN.Comment: Accepted for publication in The Astrophysical Journal. 39 pages, 15 figure