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Gregorio Landi; Giovanni E. Landi
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The construction of a well tuned probability distributions is illustrated in synthetic way, these probability distributions produce faithful realizations of the impact point distributions for particles in silicon strip detector. Their use for track fitting shows a drastic improvements of a factor two, for the low noise case, and a factor three, for the high noise case, respect to the standard approach. The tracks are well reconstructed even in presence of hits with large errors, with a...
Topics: Physics, Data Analysis, Statistics and Probability, Instrumentation and Detectors
Source: http://arxiv.org/abs/1404.1968
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L. A. MartinMontoya; N. M. ArandaCamacho; C. J. Quimbay
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We study longrange correlations and trends in time series extracted from the data of seismic events occurred from 1973 to 2011 in a rectangular region that contains mainly all the continental part of Colombia. The longrange correlations are detected by the calculation of the Hurst exponents for the time series of interevent intervals, separation distances, depth differences and magnitude differences. By using a modification of the classical $R/S$ method that has been developed to detect...
Topics: Physics, Data Analysis, Statistics and Probability, Geophysics
Source: http://arxiv.org/abs/1404.3376
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Experimental and empirical data are often analyzed on loglog plots in order to find some scaling argument for the observed/examined phenomenon at hands, in particular for ranksize rule research, but also in critical phenomena in thermodynamics, and in fractal geometry. The fit to a straight line on such plots is not always satisfactory. Deviations occur at low, intermediate and high regimes along the log($x$)axis. Several improvements of the mere power law fit are discussed, in particular...
Topics: Physics, Data Analysis, Statistics and Probability
Source: http://arxiv.org/abs/1404.3605
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YoungHo Eom; HangHyun Jo
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Many complex networks in natural and social phenomena have often been characterized by heavytailed degree distributions. However, due to rapidly growing size of network data and concerns on privacy issues about using these data, it becomes more difficult to analyze complete data sets. Thus, it is crucial to devise effective and efficient estimation methods for heavy tails of degree distributions in largescale networks only using local information of a small fraction of sampled nodes. Here we...
Topics: Physics, Data Analysis, Statistics and Probability, Physics and Society, Computing Research...
Source: http://arxiv.org/abs/1411.6871
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Pouya Esmailian; Seyed Ebrahim Abtahi; Mahdi Jalili
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A class of networks are those with both positive and negative links.In this manuscript, we studied the interplay between positive and negative ties on mesoscopic level of these networks, i.e., their community structure.A community is considered as a tightly interconnected group of actors; therefore, it does not borrow any assumption from balance theory and merely uses the wellknown assumption in the community detection literature.We found that if one detects the communities based on only...
Topics: Physics, Data Analysis, Statistics and Probability, Physics and Society, Computing Research...
Source: http://arxiv.org/abs/1411.6057
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Andrea Cairoli; Adrian Baule
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Many transport processes in nature exhibit anomalous diffusive properties with nontrivial scaling of the mean square displacement, e.g., diffusion of cells or of biomolecules inside the cell nucleus, where typically a crossover between different scaling regimes appears over time. Here, we investigate a class of anomalous diffusion processes that is able to capture such complex dynamics by virtue of a general waiting time distribution. We obtain a complete characterization of such generalized...
Topics: Biological Physics, Physics, Data Analysis, Statistics and Probability, Statistical Mechanics,...
Source: http://arxiv.org/abs/1411.7005
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Giulio Cimini; Tiziano Squartini; Diego Garlaschelli; Andrea Gabrielli
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We address a fundamental problem that is systematically encountered when modeling complex systems: the limitedness of the information available. In the case of economic and financial networks, privacy issues severely limit the information that can be accessed and, as a consequence, the possibility of correctly estimating the resilience of these systems to events such as financial shocks, crises and cascade failures. Here we present an innovative method to reconstruct the structure of such...
Topics: Physics, Data Analysis, Statistics and Probability, Physics and Society, Computing Research...
Source: http://arxiv.org/abs/1411.7613
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Cameron Smith; Raymond S. Puzio; Aviv Bergman
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The relationship between network topology and system dynamics has significant implications for unifying our understanding of the interplay among metabolic, generegulatory, and ecosystem network architecures. Here we analyze the stability and robustness of a large class of dynamics on such networks. We determine the probability distribution of robustness as a function of network topology and show that robustness is classified by the number of links between modules of the network. We also...
Topics: Physics, Nonlinear Sciences, Data Analysis, Statistics and Probability, Quantitative Biology,...
Source: http://arxiv.org/abs/1412.0709
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Irina Stolbova; Scott Backhaus; Michael Chertkov
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We analyze the dynamics of a distribution circuit loaded with many induction motor and subjected to sudden changes in voltage at the beginning of the circuit. As opposed to earlier work \cite{13DCB}, the motors are disordered, i.e. the mechanical torque applied to the motors varies in a random manner along the circuit. In spite of the disorder, many of the qualitative features of a homogenous circuit persist, e.g. longrange motormotor interactions mediated by circuit voltage and electrical...
Topics: Physics, Data Analysis, Statistics and Probability, Systems and Control, Physics and Society,...
Source: http://arxiv.org/abs/1412.2721
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We have recently proposed a new informationbased approach to model selection, the Frequentist Information Criterion (FIC), that reconciles informationbased and frequentist inference. The purpose of this current paper is to provide a simple example of the application of this criterion and a demonstration of the natural emergence of model complexities with both AIClike ($N^0$) and BIClike ($\log N$) scaling with observation number $N$. The application developed is deliberately simplified to...
Topics: Data Analysis, Statistics and Probability, Physics, Statistics, Learning, Machine Learning,...
Source: http://arxiv.org/abs/1506.06129
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Kyle Cranmer; Sven Kreiss; David LopezVal; Tilman Plehn
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We develop a technique to present Higgs coupling measurements, which decouple the poorly defined theoretical uncertainties associated to inclusive and exclusive cross section predictions. The technique simplifies the combination of multiple measurements and can be used in a more general setting. We illustrate the approach with toy LHC Higgs coupling measurements and a collection of new physics models.
Topics: Physics, Data Analysis, Statistics and Probability, High Energy Physics  Phenomenology
Source: http://arxiv.org/abs/1401.0080
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Gelu M. Nita; Gregory D. Fleishman; Dale E. Gary; William Marin; Kristine Boone
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Spectra derived from fast Fourier transform (FFT) analysis of timedomain data intrinsically contain statistical fluctuations whose distribution depends on the number of accumulated spectra contributing to a measurement. The tail of this distribution, which is essential for separation of the true signal from the statistical fluctuations, deviates noticeably from the normal distribution for a finite number of the accumulations. In this paper we develop a theory to properly account for the...
Topics: Physics, Data Analysis, Statistics and Probability, Applications, Astrophysics, Statistics,...
Source: http://arxiv.org/abs/1406.2280
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Till Moritz Karbach; Gerhard Raven; Manuel Schiller
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In neutral meson mixing, a certain class of convolution integrals is required whose solution involves the error function $\mathrm{erf}(z)$ of a complex argument $z$. We show the the general shape of the analytic solution of these integrals, and give expressions which allow the normalisation of these expressions for use in probability density functions. Furthermore, we derive expressions which allow a (decay time) acceptance to be included in these integrals, or allow the calculation of moments....
Topics: Physics, Data Analysis, Statistics and Probability
Source: http://arxiv.org/abs/1407.0748
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Y. X. Huang; Francois G. Schmitt; Q. Zhou; X. Qiu; X. D. Shang; Z. M. Lu; and Y. L. Liu
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In this paper, we introduce a new way to estimate the scaling parameter of a selfsimilar process by considering the maximum probability density function (pdf) of tis increments. We prove this for $H$selfsimilar processes in general and experimentally investigate it for turbulent velocity and temperature increments. We consider turbulent velocity database from an experimental homogeneous and nearly isotropic turbulent channel flow, and temperature data set obtained near the sidewall of a...
Topics: Fluid Dynamics, Physics, Data Analysis, Statistics and Probability
Source: http://arxiv.org/abs/1401.4207
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Mindaugas Bloznelis; Friedrich Götze
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In an affiliation network vertices are linked to attributes and two vertices are declared adjacent whenever they share a common attribute. For example, two customers of an internet shop are called adjacent if they have purchased the same or similar items. Assuming that each newly arrived customer is linked preferentially to already popular items we obtain a preferred attachment model of an evolving affiliation network. We show that the network has a scalefree property and establish the...
Topics: Physics, Probability, Mathematics, Data Analysis, Statistics and Probability, Physics and Society
Source: http://arxiv.org/abs/1401.7560
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Skyler J. Cranmer; Elizabeth J. Menninga; Peter J. Mucha
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The study of complex social and political phenomena with the perspective and methods of network science has proven fruitful in a variety of areas, including applications in political science and more narrowly the field of international relations. We propose a new line of research in the study of international conflict by showing that the multiplex fractionalization of the international system (which we label Kantian fractionalization) is a powerful predictor of the propensity for violent...
Topics: Physics, Data Analysis, Statistics and Probability, Physics and Society, Computing Research...
Source: http://arxiv.org/abs/1402.0126
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Santanu Das; Tarun Souradeep
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Markov Chain Monte Carlo (MCMC) sampler is widely used for cosmological parameter estimation from CMB and other data. However, due to the intrinsic serial nature of the MCMC sampler, convergence is often very slow. Here we present a fast and independently written Monte Carlo method for cosmological parameter estimation named as Slick Cosmological Parameter Estimator (SCoPE), that employs delayed rejection to increase the acceptance rate of a chain, and prefetching that helps an individual...
Topics: Physics, Data Analysis, Statistics and Probability, Astrophysics, General Relativity and Quantum...
Source: http://arxiv.org/abs/1403.1271
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José M. Miotto; Eduardo G. Altmann
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It is part of our daily socialmedia experience that seemingly ordinary items (videos, news, publications, etc.) unexpectedly gain an enormous amount of attention. Here we investigate how unexpected these events are. We propose a method that, given some information on the items, quantifies the predictability of events, i.e., the potential of identifying in advance the most successful items defined as the upper bound for the quality of any prediction based on the same information. Applying this...
Topics: Physics, Data Analysis, Statistics and Probability, Physics and Society, Computing Research...
Source: http://arxiv.org/abs/1403.3616
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Ken Yamamoto; Yoshihiro Yamazaki
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This paper proposes a numerical model of the network of twoChinesecharacter compound words (twocharacter network, for short). In this network, a Chinese character is a node and a twoChinesecharacter compound word links two nodes. The basic framework of the model is that an important character gets many edges. As the importance of a character, we use the frequency of each character appearing in publications. The direction of edge is given according to a random number assigned to nodes. The...
Topics: Physics, Data Analysis, Statistics and Probability, Physics and Society, Computing Research...
Source: http://arxiv.org/abs/1405.2167
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Pau Rabassa; Christian Beck
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We perform a statistical analysis of measured time series of sea levels at various coastal locations in the UK, measured at time differences of 15 minutes over the past 20 years. When the astronomical tide and other deterministic components are subtracted, a stochastic signal remains which is welldescribed by a superstatistical model. We do various tests on the measured time series, and compare the data of 5 different UK locations. Overall it appears that $\chi^2$superstatistics is best...
Topics: Physics, Data Analysis, Statistics and Probability, Statistical Mechanics, Condensed Matter
Source: http://arxiv.org/abs/1405.6007
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Y. Y. Kagan; D. D Jackson
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In our paper published earlier we discussed forecasts of earthquake focal mechanism and ways to test the forecast efficiency. Several verification methods were proposed, but they were based on adhoc, empirical assumptions, thus their performance is questionable. In this work we apply a conventional likelihood method to measure a skill of forecast. The advantage of such an approach is that earthquake rate prediction can in principle be adequately combined with focal mechanism forecast, if both...
Topics: Physics, Data Analysis, Statistics and Probability, Geophysics
Source: http://arxiv.org/abs/1405.5934
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Ladislav Kristoufek
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Bitcoin has emerged as a fascinating phenomenon of the financial markets. Without any central authority issuing the currency, it has been associated with controversy ever since its popularity and public interest reached high levels. Here, we contribute to the discussion by examining potential drivers of Bitcoin prices ranging from fundamental to speculative and technical sources as well as a potential influence of the Chinese market. The evolution of the relationships is examined in both time...
Topics: Physics, Data Analysis, Statistics and Probability, Quantitative Finance, Computational Finance,...
Source: http://arxiv.org/abs/1406.0268
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Two measurements are employed to quantitatively investigate the scaling properties of the spatial distribution of urban facilities, the K function by number counting and the variancemean relationship with the method of expanding bins. The K function and the variancemean relationship are both power functions. It means that the spatial distribution of urban facilities are scaling invariant. Further analysis of more data (which includes 8 types of facilities in 37 major Chinese cities) shows...
Topics: Physics, Data Analysis, Statistics and Probability, Physics and Society
Source: http://arxiv.org/abs/1406.0691
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Yingying Xu; Yoshiyuki Kabashima; Lenka Zdeborova
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The 1bit compressed sensing framework enables the recovery of a sparse vector x from the sign information of each entry of its linear transformation. Discarding the amplitude information can significantly reduce the amount of data, which is highly beneficial in practical applications. In this paper, we present a Bayesian approach to signal reconstruction for 1bit compressed sensing, and analyze its typical performance using statistical mechanics. Utilizing the replica method, we show that the...
Topics: Physics, Data Analysis, Statistics and Probability, Mathematics, Computing Research Repository,...
Source: http://arxiv.org/abs/1406.3782
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Xiaodong Luo; Rolf J. Lorentzen; Andreas S. Stordal; Geir Nævdal
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In this work the authors study the multiphase flow softsensing problem based on a previously established framework. There are three functional modules in this framework, namely, a transient well flow model that describes the response of certain physical variables in a well, for instance, temperature, velocity and pressure, to the flow rates entering and leaving the well zones; a Markov jump process that is designed to capture the potential abrupt changes in the flow rates; and an estimation...
Topics: Physics, Data Analysis, Statistics and Probability, Computation, Statistics, Mathematics,...
Source: http://arxiv.org/abs/1406.4306
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Nishant Kumar; Stefan Luding
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Soft, disordered, microstructured materials are ubiquitous in nature and industry, and are different from ordinary fluids or solids, with unusual, interesting static and flow properties. The transition from fluid to solid at the socalled jamming density features a multitude of complex mechanisms, but there is no unified theoretical framework that explains them all. In this study, a simple yet quantitative and predictive model is presented, which allows for a variable, changing jamming...
Topics: Physics, Data Analysis, Statistics and Probability, Soft Condensed Matter, Condensed Matter
Source: http://arxiv.org/abs/1407.6167
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Cunlai Pu; Siyuan Li; Jian Yang
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Random walk is one of the basic mechanisms found in many network applications. We study the epidemic spreading dynamics driven by biased random walks on complex networks. In our epidemic model, each time infected nodes constantly spread some infected packets by biased random walks to their neighbor nodes causing the infection of the susceptible nodes that receive the packets. An infected node get recovered from infection with a fixed probability. Simulation and analytical results on model and...
Topics: Physics, Data Analysis, Statistics and Probability, Physics and Society, Computing Research...
Source: http://arxiv.org/abs/1408.0063
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Jean Golay; Mikhail Kanevski
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The size of datasets has been increasing rapidly both in terms of number of variables and number of events. As a result, the empty space phenomenon and the curse of dimensionality complicate the extraction of useful information. But, in general, data lie on nonlinear manifolds of much lower dimension than that of the spaces in which they are embedded. In many pattern recognition tasks, learning these manifolds is a key issue and it requires the knowledge of their true intrinsic dimension. This...
Topics: Physics, Data Analysis, Statistics and Probability
Source: http://arxiv.org/abs/1408.0369
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Javier BorgeHolthoefer; Nicola Perra; Bruno Gonçalves; Sandra GonzálezBailón; Alex Arenas; Yamir Moreno; Alessandro Vespignani
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Data from social media are providing unprecedented opportunities to investigate the processes that rule the dynamics of collective social phenomena. Here, we consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social...
Topics: Nonlinear Sciences, Social and Information Networks, Physics and Society, Data Analysis, Statistics...
Source: http://arxiv.org/abs/1507.06106
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Masafumi Hino; Yosuke Irie; Masato Hisakado; Taiki Takahashi; Shintaro Mori
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We propose a method of detecting a phase transition in a generalized P\'olya urn in an information cascade experiment. The method is based on the asymptotic behavior of the correlation $C(t)$ between the first subject's choice and the $t+1$th subject's choice, the limit value of which, $c\equiv \lim_{t\to \infty}C(t)$, is the order parameter of the phase transition. To verify the method, we perform a voting experiment using twochoice questions. An urn X is chosen at random from two urns A and...
Topics: Methodology, Data Analysis, Statistics and Probability, Statistical Mechanics, Physics, Condensed...
Source: http://arxiv.org/abs/1507.07269
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Weiran Huang; Liang Li; Wei Chen
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Public opinion polling is usually done by random sampling from the entire population, treating individual opinions as independent. In the real world, individuals' opinions are often correlated, e.g., among friends in a social network. In this paper, we explore the idea of partitioned sampling, which partitions individuals with high opinion similarities into groups and then samples every group separately to obtain an accurate estimate of the population opinion. We rigorously formulate the above...
Topics: Physics and Society, Social and Information Networks, Computing Research Repository, Data Analysis,...
Source: http://arxiv.org/abs/1510.05217
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Yin Xian; Loren Nolte; Stacy Tantum; Xuejun Liao; Yuan Zhang
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Since the spectrogram does not preserve phase information contained in the original data, any algorithm based on the spectrogram is not likely to be optimum for detection. In this paper, we present the Short Time Fourier Transform detector to detect marine mammals in the timefrequency plane. The detector uses phase information for detection. We evaluate this detector by comparing it to the existing spectrogram based detectors for different SNRs and various environments including a known ocean,...
Topics: Instrumentation and Detectors, Data Analysis, Statistics and Probability, Physics
Source: http://arxiv.org/abs/1510.05520
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F. Thiel; I. M. Sokolov; E. B. Postnikov
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We consider the OrnsteinUhlenbeck process with a broad initial probability distribution (Levy distribution), which exhibits socalled nonspectral modes. The relaxation of such modes differs from those determined from the parameters of the corresponding FokkerPlanck equation. The first nonspectral mode is shown to govern the relaxation process and allows for estimation of the initial distribution's Levy index. A method based on continuous wavelet transformation is proposed to extract both...
Topics: Data Analysis, Statistics and Probability, Statistical Mechanics, Condensed Matter, Physics
Source: http://arxiv.org/abs/1602.04319
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Nikolai Gagunashvili
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The unfolding problem formulation for correcting experimental data distortions due to finite resolution and limited detector acceptance is discussed. A novel validation of the problem solution is proposed. Attention is drawn to fact that different unfolded distributions may satisfy the validation criteria, in which case a conservative approach using entropy is suggested. The importance of analysis of residuals is demonstrated.
Topics: Data Analysis, Statistics and Probability, Nuclear Experiment, Instrumentation and Methods for...
Source: http://arxiv.org/abs/1602.05834
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Eulalie Joelle Ngamga; Stephan Bialonski; Norbert Marwan; Jürgen Kurths; Christian Geier; Klaus Lehnertz
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We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of preseizure states in multiday, multichannel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high...
Topics: Data Analysis, Statistics and Probability, Medical Physics, Chaotic Dynamics, Nonlinear Sciences,...
Source: http://arxiv.org/abs/1602.07974
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Xiaoyuan Huang; YueLin Sming Tsai; Qiang Yuan
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With the large progress in searches for dark matter (DM) particles with indirect and direct methods, we develop a numerical tool that enables fast calculations of the likelihoods of specified DM particle models given a number of observational data, such as charged cosmic rays from spaceborne experiments (e.g., PAMELA, AMS02), gammarays from the Fermi space telescope, and underground direct detection experiments. The purpose of this tool  LikeDM, likelihood calculator for dark matter...
Topics: Computational Physics, Data Analysis, Statistics and Probability, High Energy Physics ...
Source: http://arxiv.org/abs/1603.07119
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Sean E. Lake; E. L. Wright
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In this paper we provide formulae that can be used to determine the uncertainty contributed to a measurement by a $K$correction and, thus, valuable information about which flux measurement will provide the most accurate $K$corrected luminosity. All of this is done at the level of a Gaussian approximation of the statistics involved, that is, where the galaxies in question can be characterized by a mean spectral energy distribution (SED) and a covariance function (spectral 2point function)....
Topics: Data Analysis, Statistics and Probability, Astrophysics, Astrophysics of Galaxies, Instrumentation...
Source: http://arxiv.org/abs/1603.07299
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Hari Nortunen; Mikko Kaasalainen
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We model the shape and spin characteristics of an object population when there are not enough data to model its single members. The data are random projection areas of the members. We construct a mapping $f(x)\rightarrow C(y)$, $x\in\mathbb{R}^2$, $y\in\mathbb{R}$, where $f(x)$ is the distribution function of the shape elongation and spin vector obliquity, and $C(y)$ is the cumulative distribution function of an observable $y$ describing the variation of the observed projection areas of one...
Topics: Data Analysis, Statistics and Probability, Physics
Source: http://arxiv.org/abs/1606.00692
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Ruth GarcíaGavilanes; Milena Tsvetkova; Taha Yasseri
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The Internet not only has changed the dynamics of our collective attention, but also through the transactional log of online activities, provides us with the opportunity to study attention dynamics at scale. In this paper, we particularly study attention to aircraft incidents and accidents using Wikipedia transactional data in two different language editions, English and Spanish. We study both the editorial activities on and the viewership of the articles about airline crashes. We analyse how...
Topics: Physics and Society, Computers and Society, Data Analysis, Statistics and Probability, Physics,...
Source: http://arxiv.org/abs/1606.08829
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Francesco Alderisio; Maria Lombardi; Gianfranco Fiore; Mario di Bernardo
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Movement coordination in human ensembles has been studied little in the current literature. In the existing experimental works, situations where all subjects are connected with each other through direct visual and auditory coupling, and social interaction affects their coordination, have been investigated. Here, we study coordination in human ensembles via a novel computerbased setup that enables individuals to coordinate each other's motion from a distance so as to minimize the influence of...
Topics: Data Analysis, Statistics and Probability, HumanComputer Interaction, Physics, Neurons and...
Source: http://arxiv.org/abs/1608.04652
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In this paper we consider a class of probability distributions on the sixvertex model from statistical mechanics, which originate from the higher spin vertex models of https://arxiv.org/abs/1601.05770. We define operators, inspired by the Macdonald difference operators, which extract various correlation functions, measuring the probability of observing different arrow configurations. The development of our operators is largely based on the properties of a remarkable family of symmetric...
Topics: Data Analysis, Statistics and Probability, Statistical Mechanics, Condensed Matter, Physics,...
Source: http://arxiv.org/abs/1610.06893
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Many uncertainty propagation software exist, written in different programming languages, but not all of them are able to handle functional correlation between quantities. In this paper we review one strategy to deal with uncertainty propagation of quantities that are functionally correlated, and introduce a new software offering this feature: the Julia package Measurements.jl. It supports real and complex numbers with uncertainty, arbitraryprecision calculations, mathematical and linear...
Topics: Data Analysis, Statistics and Probability, Physics
Source: http://arxiv.org/abs/1610.08716
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Gerardo Adesso; Marco Cianciaruso; Thomas R. Bromley
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In this didactic article we explore the concept of quantum correlations beyond entanglement. We begin by introducing and motivating the classically correlated states and then showing how to quantify the quantum correlations using an entropic approach, arriving at a well known measure called the quantum discord. Quantum correlations and discord are then operationally linked with the task of local broadcasting. We conclude by providing some alternative perspectives on quantum correlations and how...
Topics: Quantum Physics, Data Analysis, Statistics and Probability, Statistical Mechanics, Condensed...
Source: http://arxiv.org/abs/1611.01959
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John Harlim; Tyrus Berry
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While the formulation of most data assimilation schemes assumes an unbiased observation model error, in real applications, model error with nontrivial biases is unavoidable. A practical example is the error in the radiative transfer model (which is used to assimilate satellite measurements) in the presence of clouds. As a consequence, many (in fact 99\%) of the cloudy observed measurements are not being used although they may contain useful information. This paper presents a novel nonparametric...
Topics: Data Analysis, Statistics and Probability, Methodology, Physics, Statistics
Source: http://arxiv.org/abs/1611.05405
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Sandip De; Felix Musil; Teresa Ingram; Carsten Baldauf; Michele Ceriotti
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Highthroughput computational materials design promises to greatly accelerate the process of discovering new materials and compounds, and of optimizing their properties. The large databases of structures and properties that result from computational searches, as well as the agglomeration of data of heterogeneous provenance leads to considerable challenges when it comes to navigating the database, representing its structure at a glance, understanding structureproperty relations, eliminating...
Topics: Data Analysis, Statistics and Probability, Condensed Matter, Physics, Biological Physics, Chemical...
Source: http://arxiv.org/abs/1611.06246
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H. Esat Kondakci; Ayman F. Abouraddy; Bahaa E. A. Saleh
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Propagation of coherent light through a disordered network is accompanied by randomization and possible conversion into thermal light. Here, we show that network topology plays a decisive role in determining the statistics of the emerging field if the underlying lattice satisfies chiral symmetry. By examining onedimensional arrays of randomly coupled waveguides arranged on linear and ring topologies, we are led to a remarkable prediction: the field circularity and the photon statistics in ring...
Topics: Data Analysis, Statistics and Probability, Optics, Quantum Physics, Physics
Source: http://arxiv.org/abs/1611.06662
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Andrey Y. Lokhov; Marc Vuffray; Sidhant Misra; Michael Chertkov
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Reconstruction of structure and parameters of a graphical model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine learning. The focus of the research community shifted towards developing universal reconstruction algorithms which are both computationally efficient and require the minimal amount of expensive data. We introduce a new method, Interaction Screening, which...
Topics: Data Analysis, Statistics and Probability, Machine Learning, Statistical Mechanics, Condensed...
Source: http://arxiv.org/abs/1612.05024
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by
Liang Sun; Rafael Aoude; Alberto Correa Dos Reis; Michael David Sokoloff
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The functionality of GooFit, a GPUfriendly framework for doing maximumlikelihood fits, has been extended to extract modelindependent Swave amplitudes in threebody decays such as $D^+ \to h^+h^+h^$. A full amplitude analysis is done where the magnitudes and phases of the Swave amplitudes are anchored at a finite number of $m^2(h^+h^)$ control points, and a cubic spline is used to interpolate between these points. The amplitudes for Pwave and Dwave intermediate states are modeled as...
Topics: Physics, Data Analysis, Statistics and Probability, High Energy Physics  Experiment
Source: http://arxiv.org/abs/1703.03284
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5.0



by
Joseph Lemley; Filip Jagodzinski; Razvan Andonie
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We present the first algorithm for finding holes in high dimensional data that runs in polynomial time with respect to the number of dimensions. Previous algorithms are exponential. Finding large empty rectangles or boxes in a set of points in 2D and 3D space has been well studied. Efficient algorithms exist to identify the empty regions in these lowdimensional spaces. Unfortunately such efficiency is lacking in higher dimensions where the problem has been shown to be NPcomplete when the...
Topics: Computational Geometry, Physics, Data Analysis, Statistics and Probability, Computing Research...
Source: http://arxiv.org/abs/1704.00683
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3.0



by
Yingying Xu; Erik Aurell; Jukka Corander; Yoshiyuki Kabashima
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We consider the statistical properties of interaction parameter estimates obtained by the direct coupling analysis (DCA) approach to learning interactions from large data sets. Assuming that the data are generated from a random background distribution, we determine the distribution of inferred interactions. Two inference methods are considered: the L2 regularized naive meanfield inference procedure (regularized least squares, RLS), and the pseudolikelihood maximization (plmDCA). For RLS we...
Topics: Physics, Data Analysis, Statistics and Probability, Disordered Systems and Neural Networks,...
Source: http://arxiv.org/abs/1704.01459