Topological Data Analysis Detects Percolation Thresholds in Arctic Melt-Pond EvolutionDuring the summer melt period, ponds form on the surface of Arctic sea ice as it melts, with important consequences for ice evolution and marine ecology. Due to the ice-albedo feedback, these melt…Wilfred Offord, Michael Coughlan, Ian J. Hewitt et al.·Dec 15, 2022SaveLearn
Parameterizing Network Graph Heterogeneity using a Modified Weibull DistributionWe present a simple method to quantitatively capture the heterogeneity in the degree distribution of a network graph using a single parameter σ. Using an exponential transformation of the…Sinan A. Ozbay, Maximilian M. Nguyen·Dec 14, 2022SaveLearn
Quantifying Tipping Risks in Power Grids and beyondCritical transitions, ubiquitous in nature and technology, necessitate anticipation to avert adverse outcomes. While many studies focus on bifurcation-induced tipping, where a control parameter…Martin Heßler, Oliver Kamps·Dec 13, 2022SaveLearn
MFV approach to robust estimate of neutron lifetimeAiming at evaluating the lifetime of the neutron, we introduce a novel statistical method to analyse the updated compilation of precise measurements including the 2022 dataset of Particle Data Group…Jiang Zhang, Sen Zhang, Zhen-Rong Zhang et al.·Dec 8, 2022SaveLearn
A Workflow Management System GuideA workflow describes the entirety of processing steps in an analysis, such as employed in many fields of physics. Workflow management makes the dependencies between individual steps of a workflow and…Caspar Schmitt, Boyang Yu, Thomas Kuhr·Dec 2, 2022SaveLearn
Data-Driven Prognosis of Failure Detection and Prediction of Lithium-ion BatteriesBattery prognostics and health management predictive models are essential components of safety and reliability protocols in battery management system frameworks. Overall, developing a robust and…Hamed Sadegh Kouhestani, Lin Liu, Ruimin Wang et al.·Dec 2, 2022SaveLearn
Using uncertainty-aware machine learning models to study aerosol-cloud interactionsAerosol-cloud interactions (ACI) include various effects that result from aerosols entering a cloud, and affecting cloud properties. In general, an increase in aerosol concentration results in…Maëlys Solal, Andrew Jesson, Yarin Gal et al.·Nov 30, 2022SaveLearn
ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision datasetThe flavour-tagging algorithms developed by the ATLAS Collaboration and used to analyse its dataset of s = 13 TeV pp collisions from Run 2 of the Large Hadron Collider are presented. These…ATLAS Collaboration·Nov 24, 2022SaveLearn
Hunting for bumps in the marginsData driven modelling is vital to many analyses at collider experiments, however the derived inference of physical properties becomes subject to details of the model fitting procedure. This work…David Yallup, Will Handley·Nov 18, 2022SaveLearn
Using scaling-region distributions to select embedding parametersReconstructing state-space dynamics from scalar data using time-delay embedding requires choosing values for the delay τ and the dimension m. Both parameters are critical to the success of the…Varad Deshmukh, Robert Meikle, Elizabeth Bradley et al.·Nov 16, 2022SaveLearn
Dimensional homogeneity constrained gene expression programming for discovering governing equationsData-driven discovery of governing equations is of great significance for helping us understand intrinsic mechanisms and build physical models. Recently, numerous highly innovative algorithms have…Wenjun Ma, Jun Zhang, Kaikai Feng et al.·Nov 16, 2022SaveLearn
Automated Learning: An Implementation of The A* Search Algorithm over The Random Base FunctionsThis letter explains an algorithm for finding a set of base functions. The method aims to capture the leading behavior of the dataset in terms of a few base functions. Implementation of the A-star…Nima Tatari·Nov 9, 2022SaveLearn
Artificial intelligence for improved fitting of trajectories of elementary particles in inhomogeneous dense materials immersed in a magnetic fieldIn this article, we use artificial intelligence algorithms to show how to enhance the resolution of the elementary particle track fitting in inhomogeneous dense detectors, such as plastic…Saúl Alonso-Monsalve, Davide Sgalaberna, Xingyu Zhao et al.·Nov 9, 2022SaveLearn
Study of nonlinear optical diffraction patterns using machine learning models based on ResNet 152 architectureAs the advancements in the field of artificial intelligence and nonlinear optics continues new methods can be used to better describe and determine nonlinear optical phenomena. In this research we…Behnam Pishnamazi, Ehsan Koushki·Nov 9, 2022SaveLearn
Retention Time Prediction for Chromatographic Enantioseparation by Quantile Geometry-enhanced Graph Neural NetworkA new research framework is proposed to incorporate machine learning techniques into the field of experimental chemistry to facilitate chromatographic enantioseparation. A documentary dataset of…Hao Xu, Jinglong Lin, Dongxiao Zhang et al.·Nov 7, 2022SaveLearn
Rational Tracer: a Tool for Faster Rational Function ReconstructionRational Tracer (Ratracer) is a tool to simplify complicated arithmetic expressions using modular arithmetics and rational function reconstruction, with the main idea of separating the construction…Vitaly Magerya·Nov 7, 2022SaveLearn
Genuine multifractality in time series is due to temporal correlationsBased on the mathematical arguments formulated within the Multifractal Detrended Fluctuation Analysis (MFDFA) approach it is shown that in the uncorrelated time series from the Gaussian basin of…Jarosław Kwapień, Pawel Blasiak, Stanisław Drożdż et al.·Nov 1, 2022SaveLearn
A robust estimator of mutual information for deep learning interpretabilityWe develop the use of mutual information (MI), a well-established metric in information theory, to interpret the inner workings of deep learning models. To accurately estimate MI from a finite number…Davide Piras, Hiranya V. Peiris, Andrew Pontzen et al.·Oct 31, 2022SaveLearn
The Hurricane Track Fit Consensus Model for Improving Hurricane ForecastingWe present a new method for creating a model consensus to improve real-time hurricane track prediction. The method is based on the statistical fitting of historic numerical model track forecasts to…Nathan Ginis, Timothy Marchok·Oct 28, 2022SaveLearn
DUNE Offline Computing Conceptual Design ReportThis document describes the conceptual design for the Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE). The goals of the experiment include 1) studying neutrino…The DUNE collaboration·Oct 28, 2022SaveLearn
Sequential hypothesis testing for Axion HaloscopesThe goal of this paper is to introduce a novel likelihood-based inferential framework for axion haloscopes which is valid under the commonly applied "rescanning" protocol. The proposed method enjoys…Andrea Gallo Rosso, Sara Algeri, Jan Conrad·Oct 28, 2022SaveLearn
Locating the eigenshield of a network via perturbation theoryThe functions of complex networks are usually determined by a small set of vital nodes. Finding the best set of vital nodes (eigenshield nodes) is critical to the network's robustness against rumor…Ming-Yang Zhou, Manuel Sebastian Mariani, Hao Liao et al.·Oct 28, 2022SaveLearn
Inference in conditioned dynamics through causality restorationComputing observables from conditioned dynamics is typically computationally hard, because, although obtaining independent samples efficiently from the unconditioned dynamics is usually feasible,…Alfredo Braunstein, Giovanni Catania, Luca Dall'Asta et al.·Oct 18, 2022SaveLearn
Testing the data framework for an AI algorithm in preparation for high data rate X-ray facilitiesThe advent of next-generation X-ray free electron lasers will be capable of delivering X-rays at a repetition rate approaching 1 MHz continuously. This will require the development of data systems to…Hongwei Chen, Sathya R. Chitturi, Rajan Plumley et al.·Oct 18, 2022SaveLearn
A noise-robust Multivariate Multiscale Permutation Entropy for two-phase flow characterisationUsing a graph-based approach, we propose a multiscale permutation entropy to explore the complexity of multivariate time series over multiple time scales. This multivariate multiscale permutation…John Stewart Fabila-Carrasco, Chao Tan, Javier Escudero·Oct 14, 2022SaveLearn