Efficient and Extensible Policy Mining for Relationship-Based Access Control

Relationship-based access control (ReBAC) is a flexible and expressive framework that allows policies to be expressed in terms of chains of relationship between entities as well as attributes of entities. ReBAC policy mining algorithms have a potential to significantly reduce the cost of migration from legacy access control systems to ReBAC, by partially automating the development of a ReBAC policy. Existing ReBAC policy mining algorithms support a policy language with a limited set of operators; this limits their applicability. This paper presents a ReBAC policy mining algorithm designed to be both (1) easily extensible (to support additional policy language features) and (2) scalable. The algorithm is based on Bui et al.'s evolutionary algorithm for ReBAC policy mining algorithm. First, we simplify their algorithm, in order to make it easier to extend and provide a methodology that extends it to handle new policy language features. However, extending the policy language increases the search space of candidate policies explored by the evolutionary algorithm, thus causes longer running time and/or worse results. To address the problem, we enhance the algorithm with a feature selection phase. The enhancement utilizes a neural network to identify useful features. We use the result of feature selection to reduce the evolutionary algorithm's search space. The new algorithm is easy to extend and, as shown by our experiments, is more efficient and produces better policies

Finite-Size Bosonization and Self-Consistent Harmonic Approximation

The self-consistent harmonic approximation is extended in order to account for the existence of Klein factors in bosonized Hamiltonians. This is important for the study of finite systems where Klein factors cannot be ignored a priori. As a test we apply the method to interacting spinless fermions with modulated hopping. We calculate the finite-size corrections to the energy gap and the Drude weight and compare our results with the exact solution for special values of the model parameters

Twitter-based analysis of the dynamics of collective attention to political parties

Large-scale data from social media have a significant potential to describe complex phenomena in real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the elections outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media.Comment: 16 pages, 7 figures, 3 tables. Published in PLoS ON

Detection of B-mode Polarization in the Cosmic Microwave Background with Data from the South Pole Telescope

Gravitational lensing of the cosmic microwave background generates a curl pattern in the observed polarization. This "B-mode" signal provides a measure of the projected mass distribution over the entire observable Universe and also acts as a contaminant for the measurement of primordial gravity-wave signals. In this Letter we present the first detection of gravitational lensing B modes, using first-season data from the polarization-sensitive receiver on the South Pole Telescope (SPTpol). We construct a template for the lensing B-mode signal by combining E-mode polarization measured by SPTpol with estimates of the lensing potential from a Herschel-SPIRE map of the cosmic infrared background. We compare this template to the B modes measured directly by SPTpol, finding a non-zero correlation at 7.7 sigma significance. The correlation has an amplitude and scale-dependence consistent with theoretical expectations, is robust with respect to analysis choices, and constitutes the first measurement of a powerful cosmological observable.Comment: Two additional null tests, matches version published in PR

A Measurement of the Cosmic Microwave Background Gravitational Lensing Potential from 100 Square Degrees of SPTpol Data

We present a measurement of the cosmic microwave background (CMB) gravitational lensing potential using data from the first two seasons of observations with SPTpol, the polarization-sensitive receiver currently installed on the South Pole Telescope (SPT). The observations used in this work cover 100 deg$^2$ of sky with arcminute resolution at 150 GHz. Using a quadratic estimator, we make maps of the CMB lensing potential from combinations of CMB temperature and polarization maps. We combine these lensing potential maps to form a minimum-variance (MV) map. The lensing potential is measured with a signal-to-noise ratio of greater than one for angular multipoles between $100< L <250$. This is the highest signal-to-noise mass map made from the CMB to date and will be powerful in cross-correlation with other tracers of large-scale structure. We calculate the power spectrum of the lensing potential for each estimator, and we report the value of the MV power spectrum between $100< L <2000$ as our primary result. We constrain the ratio of the spectrum to a fiducial $\Lambda$CDM model to be $A_{\rm MV}=0.92 \pm 0.14 {\rm\, (Stat.)} \pm 0.08 {\rm\, (Sys.)}$. Restricting ourselves to polarized data only, we find $A_{\rm POL}=0.92 \pm 0.24 {\rm\, (Stat.)} \pm 0.11 {\rm\, (Sys.)}$. This measurement rejects the hypothesis of no lensing at $5.9 \sigma$ using polarization data alone, and at $14 \sigma$ using both temperature and polarization data.Comment: 16 pages, 8 figure

Measurements of Sub-degree B-mode Polarization in the Cosmic Microwave Background from 100 Square Degrees of SPTpol Data

We present a measurement of the $B$-mode polarization power spectrum (the $BB$ spectrum) from 100 $\mathrm{deg}^2$ of sky observed with SPTpol, a polarization-sensitive receiver currently installed on the South Pole Telescope. The observations used in this work were taken during 2012 and early 2013 and include data in spectral bands centered at 95 and 150 GHz. We report the $BB$ spectrum in five bins in multipole space, spanning the range $300 \le \ell \le 2300$, and for three spectral combinations: 95 GHz $\times$ 95 GHz, 95 GHz $\times$ 150 GHz, and 150 GHz $\times$ 150 GHz. We subtract small ($< 0.5 \sigma$ in units of statistical uncertainty) biases from these spectra and account for the uncertainty in those biases. The resulting power spectra are inconsistent with zero power but consistent with predictions for the $BB$ spectrum arising from the gravitational lensing of $E$-mode polarization. If we assume no other source of $BB$ power besides lensed $B$ modes, we determine a preference for lensed $B$ modes of $4.9 \sigma$. After marginalizing over tensor power and foregrounds, namely polarized emission from galactic dust and extragalactic sources, this significance is $4.3 \sigma$. Fitting for a single parameter, $A_\mathrm{lens}$, that multiplies the predicted lensed $B$-mode spectrum, and marginalizing over tensor power and foregrounds, we find $A_\mathrm{lens} = 1.08 \pm 0.26$, indicating that our measured spectra are consistent with the signal expected from gravitational lensing. The data presented here provide the best measurement to date of the $B$-mode power spectrum on these angular scales.Comment: 21 pages, 4 figure

Mass Calibration and Cosmological Analysis of the SPT-SZ Galaxy Cluster Sample Using Velocity Dispersion σv\sigma_v and X-ray YXY_\textrm{X} Measurements

We present a velocity dispersion-based mass calibration of the South Pole Telescope Sunyaev-Zel'dovich effect survey (SPT-SZ) galaxy cluster sample. Using a homogeneously selected sample of 100 cluster candidates from 720 deg2 of the survey along with 63 velocity dispersion ($\sigma_v$) and 16 X-ray Yx measurements of sample clusters, we simultaneously calibrate the mass-observable relation and constrain cosmological parameters. The calibrations using $\sigma_v$ and Yx are consistent at the $0.6\sigma$ level, with the $\sigma_v$ calibration preferring ~16% higher masses. We use the full cluster dataset to measure $\sigma_8(\Omega_ m/0.27)^{0.3}=0.809\pm0.036$. The SPT cluster abundance is lower than preferred by either the WMAP9 or Planck+WMAP9 polarization (WP) data, but assuming the sum of the neutrino masses is $\sum m_\nu=0.06$ eV, we find the datasets to be consistent at the 1.0$\sigma$ level for WMAP9 and 1.5$\sigma$ for Planck+WP. Allowing for larger $\sum m_\nu$ further reconciles the results. When we combine the cluster and Planck+WP datasets with BAO and SNIa, the preferred cluster masses are $1.9\sigma$ higher than the Yx calibration and $0.8\sigma$ higher than the $\sigma_v$ calibration. Given the scale of these shifts (~44% and ~23% in mass, respectively), we execute a goodness of fit test; it reveals no tension, indicating that the best-fit model provides an adequate description of the data. Using the multi-probe dataset, we measure $\Omega_ m=0.299\pm0.009$ and $\sigma_8=0.829\pm0.011$. Within a $\nu$CDM model we find $\sum m_\nu = 0.148\pm0.081$ eV. We present a consistency test of the cosmic growth rate. Allowing both the growth index $\gamma$ and the dark energy equation of state parameter $w$ to vary, we find $\gamma=0.73\pm0.28$ and $w=-1.007\pm0.065$, demonstrating that the expansion and the growth histories are consistent with a LCDM model ($\gamma=0.55; \,w=-1$).Comment: Accepted by ApJ (v2 is accepted version); 17 pages, 6 figure