Identifying extra high frequency gravitational waves generated from oscillons with cuspy potentials using deep neural networksDuring oscillations of cosmology inflation around the minimum of a cuspy potential after inflation, the existence of extra high frequency gravitational waves (HFGWs) (GHz) has been proven effectively…Li Li Wang, Jin Li, Nan Yang et al.·Oct 17, 2019SaveLearn
Iterative procedure for network inferenceWhen a network is reconstructed from data, two types of errors can occur: false positive and false negative errors about the presence or absence of links. In this paper, the vertex degree…Gloria Cecchini, Bjoern Schelter·Oct 15, 2019SaveLearn
Parametrizing the Detector Response with Neural NetworksIn high energy physics, characterizing the response of a detector to radiation is one of the most important and basic experimental tasks. In many cases, this task is accomplished by parameterizing…Sanha Cheong, Aviv Cukierman, Benjamin Nachman et al.·Oct 9, 2019SaveLearn
Characterizing stochastic time series with ordinal networksApproaches for mapping time series to networks have become essential tools for dealing with the increasing challenges of characterizing data from complex systems. Among the different algorithms, the…Arthur A. B. Pessa, Haroldo V. Ribeiro·Oct 3, 2019SaveLearn
Generic predictions of output probability based on complexities of inputs and outputsFor a broad class of input-output maps, arguments based on the coding theorem from algorithmic information theory (AIT) predict that simple (low Kolmogorov complexity) outputs are exponentially more…Kamaludin Dingle, Guillermo Valle Pérez, Ard A. Louis·Oct 2, 2019SaveLearn
On the Estimation of Mutual InformationIn this paper we focus on the estimation of mutual information from finite samples (X×Y). The main concern with estimations of mutual information is their robustness under…Nicholas Carrara, Jesse Ernst·Oct 1, 2019SaveLearn
Maximal Relevance and Optimal Learning MachinesWe show that the mutual information between the representation of a learning machine and the hidden features that it extracts from data is bounded from below by the relevance, which is the entropy of…O Duranthon, M Marsili, R Xie·Sep 27, 2019SaveLearn
Superstatistical approach to air pollution statisticsAir pollution by Nitrogen Oxides (NOx) is a major concern in large cities as it has severe adverse health effects. However, the statistical properties of air pollutants are not fully understood.…Griffin Williams, Benjamin Schäfer, Christian Beck·Sep 23, 2019SaveLearn
Border effect corrections for diagonal line based recurrence quantification analysis measuresRecurrence Quantification Analysis (RQA) defines a number of quantifiers, which base upon diagonal line structures in the recurrence plot (RP). Due to the finite size of an RP, these lines can be cut…Hauke Kraemer, Norbert Marwan·Sep 19, 2019SaveLearn
An open-source, end-to-end workflow for multidimensional photoemission spectroscopyCharacterization of the electronic band structure of solid state materials is routinely performed using photoemission spectroscopy. Recent advancements in short-wavelength light sources and electron…Rui Patrick Xian, Yves Acremann, Steinn Ymir Agustsson et al.·Sep 17, 2019SaveLearn
libGroomRL: Reinforcement Learning for JetsIn these proceedings, we present a library allowing for straightforward calls in C++ to jet grooming algorithms trained with deep reinforcement learning. The RL agent is trained with a reward…Stefano Carrazza, Frédéric A. Dreyer·Sep 15, 2019SaveLearn
Shadowing the rotating annulus. Part II: Gradient descent in the perfect model scenarioShadowing trajectories are model trajectories consistent with a sequence of observations of a system, given a distribution of observational noise. The existence of such trajectories is a desirable…Roland M. B. Young, Roman Binter, Falk Niehörster et al.·Sep 11, 2019SaveLearn
A new Monte Carlo-based fitting methodWe present a new fitting technique based on the parametric bootstrap method, which relies on the idea to produce artificial measurements using the estimated probability distribution of the…Paolo Pedroni, Stefano Sconfietti·Sep 9, 2019SaveLearn
Gaussian processes for data fulfilling linear differential equationsA method to reconstruct fields, source strengths and physical parameters based on Gaussian process regression is presented for the case where data are known to fulfill a given linear differential…Christopher G. Albert·Sep 8, 2019SaveLearn
Transforming Gaussian correlations. Applications to generating long-range power-law correlated time series with arbitrary distributionThe observable outputs of many complex dynamical systems consist in time series exhibiting autocorrelation functions of great diversity of behaviors, including long-range power-law autocorrelation…Pedro Carpena, Pedro A. Bernaola-Galván, Manuel Gómez-Extremera et al.·Sep 4, 2019SaveLearn
Shadowing the rotating annulus. Part I: Measuring candidate trajectory shadowing timesAn intuitively necessary requirement of models used to provide forecasts of a system's future is the existence of shadowing trajectories that are consistent with past observations of the system:…Roland M. B. Young, Roman Binter, Falk Niehörster·Sep 4, 2019SaveLearn
Learning Physics from Data: a Thermodynamic InterpretationExperimental data bases are typically very large and high dimensional. To learn from them requires to recognize important features (a pattern), often present at scales different to that of the…Francisco Chinesta, Elias Cueto, Miroslav Grmela et al.·Sep 3, 2019SaveLearn
A Comparison of Adaptive and Template Matching Techniques for Radio-Isotope IdentificationWe compare and contrast the effectiveness of a set of adaptive and non-adaptive algorithms for isotope identification based on gamma-ray spectra. One dimensional energy spectra are simulated for a…Emma J. Hague, Mark Kamuda, William P. Ford et al.·Aug 26, 2019SaveLearn
Unfolding as Quantum AnnealingHigh-energy physics is replete with hard computational problems and it is one of the areas where quantum computing could be used to speed up calculations. We present an implementation of…Kyle Cormier, Riccardo Di Sipio, Peter Wittek·Aug 22, 2019SaveLearn
Deconvolution of 3-D Gaussian kernelsUlmer and Kaissl formulas for the deconvolution of one-dimensional Gaussian kernels are generalized to the three-dimensional case. The generalization is based on the use of the scalar version of the…Z. K. Silagadze·Aug 20, 2019SaveLearn
GPS Fit Method for Paths of Non Drunken Sailors and its Connection to EntropyEstimating the altimeters a cyclist has climbed from noisy GPS data is a challenging problem. In this article a method is proposed that assumes that a person locally takes the shortest path. This…Fetze Pijlman·Aug 15, 2019SaveLearn
Rare-Event Properties of the Nagel-Schreckenberg ModelWe have studied the distribution of traffic flow q for the Nagel-Schreckenberg model by computer simulations. We applied a large-deviation approach, which allowed us to obtain the distribution…Wiebke Staffeldt, Alexander K. Hartmann·Aug 13, 2019SaveLearn
Time window to constrain the corner value of the global seismic-moment distributionIt is well accepted that, at the global scale, the Gutenberg-Richter (GR) law describing the distribution of earthquake magnitude or seismic moment has to be modified at the tail to properly account…Alvaro Corral, Isabel Serra·Aug 7, 2019SaveLearn
A simple decomposition of European temperature variability capturing the variance from days to a decadeWe analyze European temperature variability from station data with the method of detrended fluctuation analysis. This method is known to give a scaling exponent indicating long range correlations in…Philipp G Meyer, Holger Kantz·Aug 6, 2019SaveLearn
The distinct flavors of Zipf's law in the rank-size and in the size-distribution representations, and its maximum-likelihood fittingIn the last years, researchers have realized the difficulties of fitting power-law distributions properly. These difficulties are higher in Zipf's systems, due to the discreteness of the variables…Alvaro Corral, Isabel Serra, Ramon Ferrer-i-Cancho·Aug 4, 2019SaveLearn