Characterization of the Benchmark Binary NLTT 33370

We report the confirmation of the binary nature of the nearby, very low-mass system NLTT 33370 with adaptive optics imaging and present resolved near-infrared photometry and integrated light optical and near-infrared spectroscopy to characterize the system. VLT-NaCo and LBTI-LMIRCam images show significant orbital motion between 2013 February and 2013 April. Optical spectra reveal weak, gravity sensitive alkali lines and strong lithium 6708 Angstrom absorption that indicate the system is younger than field age. VLT-SINFONI near-IR spectra also show weak, gravity sensitive features and spectral morphology that is consistent with other young, very low-mass dwarfs. We combine the constraints from all age diagnostics to estimate a system age of ~30-200 Myr. The 1.2-4.7 micron spectral energy distribution of the components point toward T_eff=3200 +/- 500 K and T_eff=3100 +/- 500 K for NLTT 33370 A and B, respectively. The observed spectra, derived temperatures, and estimated age combine to constrain the component spectral types to the range M6-M8. Evolutionary models predict masses of 113 +/- 8 M_Jup and 106 +/- 7 M_Jup from the estimated luminosities of the components. KPNO-Phoenix spectra allow us to estimate the systemic radial velocity of the binary. The Galactic kinematics of NLTT 33370AB are broadly consistent with other young stars in the Solar neighborhood. However, definitive membership in a young, kinematic group cannot be assigned at this time and further follow-up observations are necessary to fully constrain the system's kinematics. The proximity, age, and late-spectral type of this binary make it very novel and an ideal target for rapid, complete orbit determination. The system is one of only a few model calibration benchmarks at young ages and very low-masses.Comment: 25 pages, 3 tables, 13 figures, accepted for publication in The Astrophysical Journa

Characterization methods dedicated to nanometer-thick hBN layers

Hexagonal boron nitride (hBN) regains interest as a strategic component in graphene engineering and in van der Waals heterostructures built with two dimensional materials. It is crucial then, to handle reliable characterization techniques capable to assess the quality of structural and electronic properties of the hBN material used. We present here characterization procedures based on optical spectroscopies, namely cathodoluminescence and Raman, with the additional support of structural analysis conducted by transmission electron microscopy. We show the capability of optical spectroscopies to investigate and benchmark the optical and structural properties of various hBN thin layers sources

Has U.S. Inflation Really Become Harder to Forecast?

Recently Stock and Watson (2007) showed that since the mid-1980s it has been hard for backward-looking Phillips curve models to improve on simple univariate models in forecasting U.S. inflation. While this indeed is the case when the benchmark is a causal autoregression, little change in forecast accuracy is detected when a noncausal autoregression is taken as the benchmark. In this note, we argue that a noncausal autoregression indeed provides a better characterization of U.S. inflation dynamics than the conventional causal autoregression and it is, therefore, the appropriate univariate benchmark model.Inflation forecast; Noncausal time series; Phillips curve

ShenZhen transportation system (SZTS): a novel big data benchmark suite

Data analytics is at the core of the supply chain for both products and services in modern economies and societies. Big data workloads, however, are placing unprecedented demands on computing technologies, calling for a deep understanding and characterization of these emerging workloads. In this paper, we propose ShenZhen Transportation System (SZTS), a novel big data Hadoop benchmark suite comprised of real-life transportation analysis applications with real-life input data sets from Shenzhen in China. SZTS uniquely focuses on a specific and real-life application domain whereas other existing Hadoop benchmark suites, such as HiBench and CloudRank-D, consist of generic algorithms with synthetic inputs. We perform a cross-layer workload characterization at the microarchitecture level, the operating system (OS) level, and the job level, revealing unique characteristics of SZTS compared to existing Hadoop benchmarks as well as general-purpose multi-core PARSEC benchmarks. We also study the sensitivity of workload behavior with respect to input data size, and we propose a methodology for identifying representative input data sets

Frontiers of the physics of dense plasmas and planetary interiors: experiments, theory, applications

Recent developments of dynamic x-ray characterization experiments of dense matter are reviewed, with particular emphasis on conditions relevant to interiors of terrestrial and gas giant planets. These studies include characterization of compressed states of matter in light elements by x-ray scattering and imaging of shocked iron by radiography. Several applications of this work are examined. These include the structure of massive "Super Earth" terrestrial planets around other stars, the 40 known extrasolar gas giants with measured masses and radii, and Jupiter itself, which serves as the benchmark for giant planets.Comment: Accepted to Physics of Plasmas special issue. Review from HEDP/HEDLA-08, April 12-15, 200

Consumption Externalities and Capital Accumulation in an Overlapping Generations Economy

This paper extends the standard overlapping generations model of capital accumulation by introducing consumption externalities. It is assumed that each generation's felicity depends on the social level of benchmark consumption as well as on its own consumption. Since the benchmark consumption is represented by the average consumption of all agents, the contemporaneous consumption externalities are determined by both intragenerational and intergenerational interactions among the consumers. Given this setting, we show that even in a simple model with a logarithmic utility function, the presence of consumption externalities may significantly affect the dynamic behavior and steady-state characterization of the economy. We also reveal that the same conclusion holds in an endogenous growth model in which production externalities sustain continuing growth.overlapping generations, benchmark consumption, intergenerational externalities, intragenerational externalities

Optimal Competitive Auctions

We study the design of truthful auctions for selling identical items in unlimited supply (e.g., digital goods) to n unit demand buyers. This classic problem stands out from profit-maximizing auction design literature as it requires no probabilistic assumptions on buyers' valuations and employs the framework of competitive analysis. Our objective is to optimize the worst-case performance of an auction, measured by the ratio between a given benchmark and revenue generated by the auction. We establish a sufficient and necessary condition that characterizes competitive ratios for all monotone benchmarks. The characterization identifies the worst-case distribution of instances and reveals intrinsic relations between competitive ratios and benchmarks in the competitive analysis. With the characterization at hand, we show optimal competitive auctions for two natural benchmarks. The most well-studied benchmark $\mathcal{F}^{(2)}(\cdot)$ measures the envy-free optimal revenue where at least two buyers win. Goldberg et al. [13] showed a sequence of lower bounds on the competitive ratio for each number of buyers n. They conjectured that all these bounds are tight. We show that optimal competitive auctions match these bounds. Thus, we confirm the conjecture and settle a central open problem in the design of digital goods auctions. As one more application we examine another economically meaningful benchmark, which measures the optimal revenue across all limited-supply Vickrey auctions. We identify the optimal competitive ratios to be $(\frac{n}{n-1})^{n-1}-1$ for each number of buyers n, that is $e-1$ as $n$ approaches infinity

An Extensible Benchmarking Infrastructure for Motion Planning Algorithms

Sampling-based planning algorithms are the most common probabilistically complete algorithms and are widely used on many robot platforms. Within this class of algorithms, many variants have been proposed over the last 20 years, yet there is still no characterization of which algorithms are well-suited for which classes of problems. This has motivated us to develop a benchmarking infrastructure for motion planning algorithms. It consists of three main components. First, we have created an extensive benchmarking software framework that is included with the Open Motion Planning Library (OMPL), a C++ library that contains implementations of many sampling-based algorithms. Second, we have defined extensible formats for storing benchmark results. The formats are fairly straightforward so that other planning libraries could easily produce compatible output. Finally, we have created an interactive, versatile visualization tool for compact presentation of collected benchmark data. The tool and underlying database facilitate the analysis of performance across benchmark problems and planners.Comment: Submitted to IEEE Robotics & Automation Magazine (Special Issue on Replicable and Measurable Robotics Research), 201