A unified and automated approach to attractor reconstructionWe present a fully automated method for the optimal state space reconstruction from univariate and multivariate time series. The proposed methodology generalizes the time delay embedding procedure by…K. H. Krämer, G. Datseris, J. Kurths et al.·Nov 12, 2020SaveLearn
Application of Adaptive Multilevel Splitting to High-Dimensional Dynamical SystemsStochastic nonlinear dynamical systems can undergo rapid transitions relative to the change in their forcing, for example due to the occurrence of multiple equilibrium solutions for a specific…S. Baars, D. Castellana, F. W. Wubs et al.·Nov 11, 2020SaveLearn
Mode hunting through active informationWe propose a new method to find modes based on active information. We develop an algorithm that, when applied to the whole space, will say whether there are any modes present and where they…Daniel Andrés Díaz-Pachón, Juan Pablo Sáenz, J. Sunil Rao et al.·Nov 10, 2020SaveLearn
Using machine-learning modelling to understand macroscopic dynamics in a system of coupled mapsMachine learning techniques not only offer efficient tools for modelling dynamical systems from data, but can also be employed as frontline investigative instruments for the underlying physics.…Francesco Borra, Marco Baldovin·Nov 8, 2020SaveLearn
Serial Electron Diffraction Data Processing with diffractem and CrystFELSerial electron diffraction (SerialED) is an emerging technique, which applies the snapshot data-collection mode of serial X-ray crystallography to three-dimensional electron diffraction (3D ED),…Robert Bücker, Pascal Hogan-Lamarre, R. J. Dwayne Miller·Nov 5, 2020SaveLearn
Learning to Identify ElectronsWe investigate whether state-of-the-art classification features commonly used to distinguish electrons from jet backgrounds in collider experiments are overlooking valuable information. A deep…Julian Collado, Jessica N. Howard, Taylor Faucett et al.·Nov 3, 2020SaveLearn
Applying clock comparison methods to pulsar timing observationsFrequency metrology outperforms any other branch of metrology in accuracy (parts in 10-16) and small fluctuations (<10-17). In turn, among celestial bodies, the rotation speed of…Siyuan Chen, Francois Vernotte, Enrico Rubiola·Nov 3, 2020SaveLearn
Accuracy and precision of the estimation of the number of missing levels in chaotic spectra using long-range correlationsWe study the accuracy and precision for estimating the fraction of observed levels in quantum chaotic spectra through long-range correlations. We focus on the main statistics where…I. Casal, L. Muñoz, R. A. Molina·Nov 3, 2020SaveLearn
Cluster-based network modeling -- automated robust modeling of complex dynamical systemsWe propose a universal method for data-driven modeling of complex nonlinear dynamics from time-resolved snapshot data without prior knowledge. Complex nonlinear dynamics govern many fields of science…Daniel Fernex, Bernd R. Noack, Richard Semaan·Oct 30, 2020SaveLearn
Denoising scheme based on singular-value decomposition for one-dimensional spectra and its application in precision storage-ring mass spectrometryThis work concerns noise reduction for one-dimensional spectra in the case that the signal is corrupted by an additive white noise. The proposed method starts with mapping the noisy spectrum to a…X. C. Chen, Yu. A. Litvinov, M. Wang et al.·Oct 27, 2020SaveLearn
A Brief Note of Analyzing and Plotting μ Disappearance in SBN Detector under ROOT FrameworkThis is a brief technical note of analyzing the μ disappearance in SBN detector. We here provide a kind of method of plotting the histograms and the heat map plot. We will explore the…Castaly Fan·Oct 26, 2020SaveLearn
Using Deep Learning Techniques to Search for the MiniBooNE Low Energy Excess in MicroBooNE with > 3σ SensitivityThis thesis describes an analysis developed for the MicroBooNE experiment to investigate an anomalous excess of electron-like events observed in the MiniBooNE detector. The hypothesis investigated…Jarrett Moon·Oct 26, 2020SaveLearn
Independent Normalization for γ-ray Strength Functions: The Shape MethodThe Shape method, a novel approach to obtain the functional form of the γ-ray strength function (γSF) in the absence of neutron resonance spacing data, is introduced. When used in…M. Wiedeking, M. Guttormsen, A. C. Larsen et al.·Oct 24, 2020SaveLearn
On the Feynman-alpha Method for Reflected Fissile AssembliesThe Feynman-alpha method is a neutron noise technique that is used to estimate the prompt neutron period of fissile assemblies. The method and quantity are of widespread interest including in…Michael Y. Hua, Jesson D. Hutchinson, George E. McKenzie et al.·Oct 22, 2020SaveLearn
Towards Bayesian Data CompressionIn order to handle large data sets omnipresent in modern science, efficient compression algorithms are necessary. Here, a Bayesian data compression (BDC) algorithm that adapts to the specific…Johannes Harth-Kitzerow, Reimar Leike, Philipp Arras et al.·Oct 20, 2020SaveLearn
Asymptotics for the fastest among n stochastics particles: role of an extended initial distribution and an additional drift componentWe derive asymptotic formulas for the mean exit time τN of the fastest among N identical independently distributed Brownian particles to an absorbing boundary for various initial…Suney Toste, David Holcman·Oct 16, 2020SaveLearn
Nonparametric, data-based kernel interpolation for particle-tracking simulations and kernel density estimationTraditional interpolation techniques for particle tracking include binning and convolutional formulas that use pre-determined (i.e., closed-form, parameteric) kernels. In many instances, the…David A Benson, Diogo Bolster, Stephen Pankavich et al.·Oct 13, 2020SaveLearn
Rossi-alpha Uncertainty Quantification by Analytic, Bootstrap, and Sample Methods to Inform Fitting Best PracticesThe prompt neutron period (the negative reciprocal of the prompt neutron decay constant) can be estimated using the Rossi-alpha technique that is predicated on fitting Rossi-alpha histograms and of…M. Y. Hua, C. A. Bravo, R. M. Marchie et al.·Oct 13, 2020SaveLearn
A Comparative Analysis on LaueUtil and PRECOGNITION Software Packages as Tools in Treating the Small Molecule Time-Resolved Laue Diffraction Measurements at High Flux X-ray facilitiesInvestigating metal organic systems with time-resolved photocrystallography poses a unique challenge while interpreting the time dependent photodifference maps. In these difference Fourier maps, the…J. J. Velazquez-Garcia, J. Wong, K. Basuroy et al.·Oct 12, 2020SaveLearn
Full Automation for Rapid Modulator Characterization and Accurate Analysis Using SciPyModulator testing involved complex biasing conditions, hardware connections and data analysis. Also, any optical signal distortion due to the grating coupler effect could potentially induce…T. L. Yap, A. Sasidhara, N. X. Ang et al.·Oct 11, 2020SaveLearn
Data assimilation for chaotic dynamicsChaos is ubiquitous in physical systems. The associated sensitivity to initial conditions is a significant obstacle in forecasting the weather and other geophysical fluid flows. Data assimilation is…Alberto Carrassi, Marc Bocquet, Jonathan Demaeyer et al.·Oct 10, 2020SaveLearn
A surrogate-based optimal likelihood function for the Bayesian calibration of catalytic recombination in atmospheric entry protection materialsThis work deals with the inference of catalytic recombination parameters from plasma wind tunnel experiments for reusable thermal protection materials. One of the critical factors affecting the…Anabel del Val, Olivier P. Le Maître, Olivier Chazot et al.·Oct 9, 2020SaveLearn
The spectrum decorrelation assumption for the cross-spectrum methodThis paper presents a very simple method ensuring the independence of consecutive spectra of the phase or frequency noise of an oscillator. This condition is essential for using cross-spectrum…François Vernotte, Antoine Baudiquez, Enrico Rubiola·Oct 9, 2020SaveLearn
MatDRAM: A pure-MATLAB Delayed-Rejection Adaptive Metropolis-Hastings Markov Chain Monte Carlo SamplerMarkov Chain Monte Carlo (MCMC) algorithms are widely used for stochastic optimization, sampling, and integration of mathematical objective functions, in particular, in the context of Bayesian…Shashank Kumbhare, Amir Shahmoradi·Oct 8, 2020SaveLearn
Pulse Shape Discrimination in CUPID-Mo using Principal Component AnalysisCUPID-Mo is a cryogenic detector array designed to search for neutrinoless double-beta decay (0ββ) of 100Mo. It uses 20 scintillating 100Mo-enriched Li2MoO4 bolometers…R. Huang, E. Armengaud, C. Augier et al.·Oct 8, 2020SaveLearn