HL-LHC Computing Review Stage 2, Common Software Projects: Data Science Tools for AnalysisThis paper was prepared by the HEP Software Foundation (HSF) PyHEP Working Group as input to the second phase of the LHCC review of High-Luminosity LHC (HL-LHC) computing, which took place in…Jim Pivarski, Eduardo Rodrigues, Kevin Pedro et al.·Feb 4, 2022SaveLearn
Deep learning study of an electromagnetic calorimeterThe accurate and precise extraction of information from a modern particle physics detector, such as an electromagnetic calorimeter, may be complicated and challenging. In order to overcome the…Elihu Sela, Shan Huang, David Horn·Feb 3, 2022SaveLearn
Unifying Pairwise Interactions in Complex DynamicsScientists have developed hundreds of techniques to measure the interactions between pairs of processes in complex systems. But these computational methods, from correlation coefficients to causal…Oliver M. Cliff, Annie G. Bryant, Joseph T. Lizier et al.·Jan 28, 2022SaveLearn
Accelerating Laue Depth Reconstruction Algorithm with CUDAThe Laue diffraction microscopy experiment uses the polychromatic Laue micro-diffraction technique to examine the structure of materials with sub-micron spatial resolution in all three dimensions.…Ke Yue, Schwarz Nicholas, Tischler Jonathan Z·Jan 20, 2022SaveLearn
RAMANMETRIX: a delightful way to analyze Raman spectraAlthough Raman spectroscopy is widely used for the investigation of biomedical samples and has a high potential for use in clinical applications, it is not common in clinical routines. One of the…Darina Storozhuk, Oleg Ryabchykov, Juergen Popp et al.·Jan 19, 2022SaveLearn
Comparison of Bayesian and particle swarm algorithms for hyperparameter optimisation in machine learning applications in high energy physicsWhen using machine learning (ML) techniques, users typically need to choose a plethora of algorithm-specific parameters, referred to as hyperparameters. In this paper, we compare the performance of…Laurits Tani, Christian Veelken·Jan 18, 2022SaveLearn
The matrix optimum filter for Low Temperature Detectors dead-time reductionExperiments aiming at high sensitivities usually demand for a very high statistics in order to reach more precise measurements. However, for those exploiting Low Temperature Detectors (LTDs), a high…Matteo Borghesi, Marco Faverzani, Cecilia Ferrari et al.·Jan 14, 2022SaveLearn
Determining liquid crystal properties with ordinal networks and machine learningMachine learning methods are becoming increasingly important for the development of materials science. In spite of this, the use of image analysis in the development of these systems is still recent…Arthur A. B. Pessa, Rafael S. Zola, Matjaz Perc et al.·Jan 14, 2022SaveLearn
Rapid and facile reconstruction of time-resolved fluorescence data with exponentially modified GaussiansAnalyte response is convoluted with instrument response in time resolved fluorescence data. Decoding the desired analyte information from the measurement usually requires iterative numerical…Darien J. Morrow, Xuedan Ma·Jan 10, 2022SaveLearn
Systematic treatment of hypernuclear data and application to the hypertritonA database is under construction to provide a complete collection of published basic properties of hypernuclei such as Λ binding energies, lifetimes, or excitation energies. From these values,…P. Eckert, P. Achenbach, M. Aragones Fontbote et al.·Jan 7, 2022SaveLearn
Wavescan: Multiresolution Time-Frequency Transform of Gravitational-Wave DataIdentifying transient signals embedded in non-stationary noise requires analyzing the time-dependent spectral components of the observed time series. The time-frequency distribution of the signal…Sergey Klimenko·Jan 4, 2022SaveLearn
Quantitative assessment of fitting errors associated with streak camera noise in Thomson scattering data analysisThomson scattering measurements in High Energy Density experiments are often recorded using optical streak cameras. In the low-signal regime, noise introduced by the streak camera can become an…G. F. Swadling, C. Bruulsema, W. Rozmus et al.·Dec 22, 2021SaveLearn
Classification of diffraction patterns using a convolutional neural network in single particle imaging experiments performed at X-ray free-electron lasersSingle particle imaging (SPI) at X-ray free electron lasers (XFELs) is particularly well suited to determine the 3D structure of particles in their native environment. For a successful…Dameli Assalauova, Alexandr Ignatenko, Fabian Isensee et al.·Dec 16, 2021SaveLearn
Estimating nonlinear stability from time series dataBasin stability (BS) is a measure of nonlinear stability in multi-stable dynamical systems. BS has previously been estimated using Monte-Carlo simulations, which requires the explicit knowledge of a…Adrian van Kan, Jannes Jegminat, Jonathan Donges·Dec 3, 2021SaveLearn
The Linear Template FitThe estimation of parameters from data is a common problem in many areas of the physical sciences, and frequently used algorithms rely on sets of simulated data which are fit to data. In this…Daniel Britzger·Dec 2, 2021SaveLearn
Inferring a property of a large system from a small number of samplesInferring the value of a property of a large stochastic system is a difficult task when the number of samples is insufficient to reliably estimate the probability distribution. The Bayesian estimator…Damián G. Hernández, Inés Samengo·Dec 1, 2021SaveLearn
Quantifying Non-Stationarity with Information TheoryWe introduce an index based on information theory to quantify the stationarity of a stochastic process.The index compares on the one hand the information contained in the increment at the time scale…Carlos Granero-Belinchon, Stéphane G. Roux, Nicolas B. Garnier·Dec 1, 2021SaveLearn
Detecting frequency modulation in stochastic time series dataWe propose a new statistical test to identify non-stationary frequency-modulated stochastic processes from time series data. Our method uses the instantaneous phase as a discriminatory statistics…Adrian L. Hauber, Christian Sigloch, Jens Timmer·Nov 29, 2021SaveLearn
Bias and synergy in the self-consistent approach of data analysis of ion beam techniquesUsing multiple ion beam analysis measurements, or techniques, combined with self-consistent data processing, generally allows extracting more (or more accurate) information from the measurements than…Tiago F. Silva, Cleber L. Rodrigues, Manfredo H. Tabacniks et al.·Nov 26, 2021SaveLearn
Detecting structured sources in noisy images via Minkowski mapsAstronomy, biophysics, and material science often depend on the possibility to extract information out of faint spatial signals. Here we present a morphometric analysis technique to quantify the…Michael Andreas Klatt, Klaus Mecke·Nov 26, 2021SaveLearn
Particle Graph Autoencoders and Differentiable, Learned Energy Mover's DistanceAutoencoders have useful applications in high energy physics in anomaly detection, particularly for jets - collimated showers of particles produced in collisions such as those at the CERN Large…Steven Tsan, Raghav Kansal, Anthony Aportela et al.·Nov 24, 2021SaveLearn
Explaining machine-learned particle-flow reconstructionThe particle-flow (PF) algorithm is used in general-purpose particle detectors to reconstruct a comprehensive particle-level view of the collision by combining information from different…Farouk Mokhtar, Raghav Kansal, Daniel Diaz et al.·Nov 24, 2021SaveLearn
Correlations between Panoramic Imagery and Gamma-Ray Background in an Urban AreaWhen searching for radiological sources in an urban area, a vehicle-borne detector system will often measure complex, varying backgrounds primarily from natural gamma-ray sources. Much work has been…M. S. Bandstra, B. J. Quiter, M. Salathe et al.·Nov 19, 2021SaveLearn
Phase reconstruction from oscillatory data with iterated Hilbert transform embeddings -- benefits and limitationsIn the data analysis of oscillatory systems, methods based on phase reconstruction are widely used to characterize phase-locking properties and inferring the phase dynamics. The main component in…Erik Gengel, Arkady Pikovsky·Nov 19, 2021SaveLearn
Improved algorithms for determination of particle directions with Timepix3Timepix3 pixel detectors have demonstrated great potential for tracking applications. With 256× 256 pixels, 55 μm pitch and improved resolution in time (1.56 ns) and energy (2 keV at…Petr Mánek, Benedikt Bergmann, Petr Burian et al.·Oct 31, 2021SaveLearn