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Thin-film solar cells are predominately designed similar to a stacked structure. Optimizing the layer thicknesses in this stack structure is crucial to extract the best efficiency of the solar cell. The commonplace method used in…

Neural and Evolutionary Computing · Computer Science 2020-04-08 Premkumar Vincent , Gwenaelle Cunha Sergio , Jaewon Jang , In Man Kang , Jaehoon Park , Hyeok Kim , Minho Lee , Jin-Hyuk Bae

We continue our presentation of VINE. We begin with a description of relevant architectural properties of the serial and shared memory parallel computers on which VINE is intended to run, and describe their influences on the design of the…

Astrophysics · Physics 2009-10-02 Andrew F. Nelson , M. Wetzstein , T. Naab , .

Robot grasping is often formulated as a learning problem. With the increasing speed and quality of physics simulations, generating large-scale grasping data sets that feed learning algorithms is becoming more and more popular. An often…

Robotics · Computer Science 2019-12-13 Clemens Eppner , Arsalan Mousavian , Dieter Fox

The field of software verification has produced a wide array of algorithmic techniques that can prove a variety of properties of a given program. It has been demonstrated that the performance of these techniques can vary up to 4 orders of…

Software Engineering · Computer Science 2023-09-07 Will Leeson , Matthew B Dwyer

Quantification and minimization of uncertainty is an important task in the design of electromagnetic devices, which comes with high computational effort. We propose a hybrid approach combining the reliability and accuracy of a Monte Carlo…

Machine Learning · Computer Science 2022-04-12 Mona Fuhrländer , Sebastian Schöps

Aims. We present an innovative artificial neural network (ANN) architecture, called Generative ANN (GANN), that computes the forward model, that is it learns the function that relates the unknown outputs (stellar atmospheric parameters, in…

Instrumentation and Methods for Astrophysics · Physics 2016-10-19 C. Dafonte , D. Fustes , M. Manteiga , D. Garabato , M. A. Alvarez , A. Ulla , C. Allende Prieto

The gamma-ray burst (GRB) rate is essential for revealing the connection between GRBs, supernovae and stellar evolution. Additionally, the GRB rate at high redshift provides a strong probe of star formation history in the early universe.…

High Energy Astrophysical Phenomena · Physics 2016-03-25 Amy Lien , Takanori Sakamoto , Neil Gehrels , David M. Palmer , Scott D. Barthelmy , Carlo Graziani , John K. Cannizzo

The last two decades have seen a major expansion in the availability, size, and precision of time-domain datasets in astronomy. Owing to their unique combination of flexibility, mathematical simplicity and comparative robustness, Gaussian…

Instrumentation and Methods for Astrophysics · Physics 2022-11-11 Suzanne Aigrain , Daniel Foreman-Mackey

Radio occultation events recorded on 28-29 July 2004 by a GPS receiver aboard the GRACE-B satellite are analyzed. The stability of the receiver clock allows for the derivation of excess phase profiles using a zero difference technique,…

Geophysics · Physics 2015-06-26 G. Beyerle , T. Schmidt , G. Michalak , S. Heise , J. Wickert , Ch. Reigber

Purpose: To develop schemes that deliver faithful 2D slices near field heterogeneities of the kind arising from non-ferromagnetic metal implants, with reduced artifacts and shorter scan times. Methods: An excitation scheme relying on…

Medical Physics · Physics 2020-03-24 Gil Farkash , Gilad Liberman , Ricardo P. Martinho , Lucio Frydman

We present a novel approach to estimate the time delay between light curves of multiple images in a gravitationally lensed system, based on Kernel methods in the context of machine learning. We perform various experiments with artificially…

Astrophysics · Physics 2009-11-11 Juan C. Cuevas-Tello , Peter Tino , Somak Raychaudhury

In this work, we propose a graph-adaptive pruning (GAP) method for efficient inference of convolutional neural networks (CNNs). In this method, the network is viewed as a computational graph, in which the vertices denote the computation…

Computer Vision and Pattern Recognition · Computer Science 2018-11-22 Mengdi Wang , Qing Zhang , Jun Yang , Xiaoyuan Cui , Wei Lin

Motivated by the need to study the molecular mechanism underlying Type 1 Diabetes (T1D) with the gene expression data collected from both the patients and healthy controls at multiple time points, we propose an innovative method for jointly…

Methodology · Statistics 2018-12-10 Bochao Jia , Faming Liang , the TEDDY Study Group

We present the open-source Python package, BAGLE (Bayesian Analysis of Gravitational Lensing Events), which enables modeling and joint fitting of photometric and astrometric data sets. We describe the model parameterizations and present the…

Solar and Stellar Astrophysics · Physics 2025-12-04 J. R. Lu , M. Medford , C. Y. Lam , T. D. Bhadra , M. J. Huston , N. S. Abrams , E. Broadberry , J. Chen , S. K. Terry , N. Arredondo , A. Scharf

Stochastic Gradient Descent (SGD) is the key learning algorithm for many machine learning tasks. Because of its computational costs, there is a growing interest in accelerating SGD on HPC resources like GPU clusters. However, the…

Machine Learning · Computer Science 2021-01-20 Peng Jiang , Gagan Agrawal

While the Lomb-Scargle periodogram is foundational to astronomy, it has a significant shortcoming: the variance in the estimated power spectrum does not decrease as more data are acquired. Statisticians have a 60-year history of developing…

Instrumentation and Methods for Astrophysics · Physics 2023-12-18 Sarah E. Dodson-Robinson , Charlotte Haley

Gamma-ray burst (GRBs) are the brightest events in the universe. For decades, astrophysicists have known about their cosmological nature. Every year, space missions such as Fermi and SWIFT detect hundreds of them. In spite of this large…

High Energy Astrophysical Phenomena · Physics 2024-04-10 Keneth Garcia-Cifuentes , Rosa L. Becerra , Fabio De Colle

We study the statistical characteristics of a box-fitting algorithm to analyze stellar photometric time series in the search for periodic transits by extrasolar planets. The algorithm searches for signals characterized by a periodic…

Astrophysics · Physics 2016-08-30 G. Kovács , S. Zucker , T. Mazeh

Genetic Algorithms (GA) are a powerful tool for stochastic optimisation and non-parametric symbolic regression, already widely used in cosmology. They are capable of reconstructing analytical functions directly from data points without…

Cosmology and Nongalactic Astrophysics · Physics 2026-02-16 Matteo Peronaci , Matteo Martinelli , Savvas Nesseris
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