An X-ray Spectroscopic Study of the Hot Interstellar Medium Toward the Galactic Bulge

We present a detailed spectroscopic study of the hot gas toward the Galactic bulge along the 4U 1820-303 sight line by a combination analysis of emission and absorption spectra. In addition to the absorption lines of OVII Kalpha, OVII Kbeta, OVIII Kalpha and NeIX Kalpha by Chandra LTGS as shown by previous works, Suzaku detected clearly the emission lines of OVII, OVIII, NeIX and NeX from the vicinity. We used simplified plasma models with constant temperature and density. Evaluation of the background and foreground emission was performed carefully, including stellar X-ray contribution based on the recent X-ray observational results and stellar distribution simulator. If we assume that one plasma component exists in front of 4U1820-303 and the other one at the back, the obtained temperatures are T= 1.7 +/- 0.2 MK for the front-side plasma and T=3.9(+0.4-0.3) MK for the backside. This scheme is consistent with a hot and thick ISM disk as suggested by the extragalactic source observations and an X-ray bulge around the Galactic center.Comment: 14 pages, 15 figures, accepted to be published in PASJ (Replace figure files to fix latex problem

Learning Models over Relational Data using Sparse Tensors and Functional Dependencies

Integrated solutions for analytics over relational databases are of great practical importance as they avoid the costly repeated loop data scientists have to deal with on a daily basis: select features from data residing in relational databases using feature extraction queries involving joins, projections, and aggregations; export the training dataset defined by such queries; convert this dataset into the format of an external learning tool; and train the desired model using this tool. These integrated solutions are also a fertile ground of theoretically fundamental and challenging problems at the intersection of relational and statistical data models. This article introduces a unified framework for training and evaluating a class of statistical learning models over relational databases. This class includes ridge linear regression, polynomial regression, factorization machines, and principal component analysis. We show that, by synergizing key tools from database theory such as schema information, query structure, functional dependencies, recent advances in query evaluation algorithms, and from linear algebra such as tensor and matrix operations, one can formulate relational analytics problems and design efficient (query and data) structure-aware algorithms to solve them. This theoretical development informed the design and implementation of the AC/DC system for structure-aware learning. We benchmark the performance of AC/DC against R, MADlib, libFM, and TensorFlow. For typical retail forecasting and advertisement planning applications, AC/DC can learn polynomial regression models and factorization machines with at least the same accuracy as its competitors and up to three orders of magnitude faster than its competitors whenever they do not run out of memory, exceed 24-hour timeout, or encounter internal design limitations.Comment: 61 pages, 9 figures, 2 table

Landau-Zener-Stuckelberg interference in a multi-anticrossing system

We propose a universal analytical method to study the dynamics of a multi-anticrossing system subject to driving by one single large-amplitude triangle pulse, within its time scales smaller than the dephasing time. Our approach can explain the main features of the Landau-Zener-Stuckelberg interference patterns recently observed in a tripartite system [Nature Communications 1:51 (2010)]. In particular, we focus on the effects of the size of anticrossings on interference and compare the calculated interference patterns with numerical simulations. In addition, Fourier transform of the patterns can extract information on the energy level spectrum.Comment: 6 pages, 5 figure

Efficiency optimization in a correlation ratchet with asymmetric unbiased fluctuations

The efficiency of a Brownian particle moving in periodic potential in the presence of asymmetric unbiased fluctuations is investigated. We found that there is a regime where the efficiency can be a peaked function of temperature, which proves that thermal fluctuations facilitate the efficiency of energy transformation, contradicting the earlier findings (H. kamegawa et al. Phys. Rev. Lett. 80 (1998) 5251). It is also found that the mutual interplay between asymmetry of fluctuation and asymmetry of the potential may induce optimized efficiency at finite temperature. The ratchet is not most efficiency when it gives maximum current.Comment: 10 pages, 7 figure

Effects of losses in the hybrid atom-light interferometer

Enhanced Raman scattering can be obtained by injecting a seeded light field which is correlated with the initially prepared collective atomic excitation. This Raman amplification process can be used to realize atom-light hybrid interferometer. We numerically calculate the phase sensitivities and the signal-to-noise ratios of this interferometer with the method of homodyne detection and intensity detection, and give their differences between this two methods. In the presence of loss of light field and atomic decoherence the measure precision will be reduced which can be explained by the break of the intermode decorrelation conditions of output modesComment: 9 pages, 7 figure

SELINDA: a secure, scalable and light-weight data collection protocol for smart grids

Security in the smart grid is a challenge as an increasing number of sensors and measurement devices are connected to the power grid. General purpose security protocols are not suitable for providing data security to devices with limited memory, computational power and network connectivity. In this paper, we develop a secure and light-weight scalable security protocol that allows a power system operator (PO) to collect data from measurement devices (MDs) using data collectors (DCs). The security protocol trades off between computations and device memory requirements and provides flexible association between DC and MDs. These features allow data to be securely transferred from MDs to PO via mobile or untrustworthy DCs. We analyze the complexity and security of the protocol and validate its performance using experiments. Our results confirm that our proposed protocol collects data in a secure, fast and efficient manner. © 2013 IEEE.published_or_final_versio