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The increased interest in more exclusive fission observables has demanded more detailed models. We present here a new computational model, FREYA, that aims to meet this need by producing large samples of complete fission events from which…

Nuclear Theory · Physics 2009-08-20 J. Randrup , R. Vogt

A rapidly converging 4-dimensional Fourier shape parametrization is used to model the fission process of heavy nuclei. Potential energy landscapes are computed within the macroscopic-microscopic approach, on top of which the…

The nuclear fission process that occurs in the core of nuclear reactors results in unstable, neutron rich fission products that subsequently beta decay and emit electron anti-neutrinos. These reactor neutrinos have served neutrino physics…

Instrumentation and Detectors · Physics 2015-12-09 D. M. Asner , K. Burns , L. W. Campbell , B. Greenfield , M. S. Kos , J. L. Orrell , M. Schram , B. VanDevender , 1 L. S. Wood , D. W. Wootan

We present a coupled Quasi-particle Random Phase Approximation and Hauser-Feshbach (QRPA+HF) model for calculating delayed particle emission. This approach uses microscopic nuclear structure information which starts with Gamow-Teller…

Nuclear Theory · Physics 2017-01-04 Matthew Mumpower , Toshihiko Kawano , Peter Moller

In this article, a new category of soft-input soft-output (SISO) minimum-mean square error (MMSE) finite-impulse response (FIR) decision feedback equalizers (DFEs) with iteration-wise static filters (i.e. iteration variant) is investigated.…

Signal Processing · Electrical Eng. & Systems 2020-01-29 Serdar Şahin , Antonio Maria Cipriano , Charly Poulliat , Marie-Laure Boucheret

Long-term time series forecasting is a long-standing challenge in various applications. A central issue in time series forecasting is that methods should expressively capture long-term dependency. Furthermore, time series forecasting…

Machine Learning · Computer Science 2024-11-06 Xingyu Zhang , Siyu Zhao , Zeen Song , Huijie Guo , Jianqi Zhang , Changwen Zheng , Wenwen Qiang

When training data are fragmented across batches or federated-learned across different geographic locations, trained models manifest performance degradation. That degradation partly owes to covariate shift induced by data having been…

Machine Learning · Computer Science 2025-10-07 Behraj Khan , Tahir Qasim Syed

We present an introduction to some concepts of Bayesian data analysis in the context of atomic physics. Starting from basic rules of probability, we present the Bayes' theorem and its applications. In particular we discuss about how to…

Data Analysis, Statistics and Probability · Physics 2024-01-30 Martino Trassinelli

Information geometry is a study of applying differential geometry methods to challenging statistical problems, such as uncertainty quantification. In this work, we use information geometry to study how measurement uncertainties in…

Nuclear Theory · Physics 2025-09-15 M. Imbrišak , A. E. Lovell , M. R. Mumpower

The protoplanetary discs of T Tauri and Herbig Ae/Be stars have been studied by using geometric disc models to fit their spectral energy distribution (SED). The simulations provide means to reproduce the signatures of different…

Astrophysics · Physics 2009-11-13 A. Hetem , J. Gregorio-Hetem

The FPGA/NIOS FIR filter based on linear prediction (LP) to suppress radio frequency interference (RFI) has been installed in several radio stations in the Auger Engineering Radio Array (AERA) experiment. AERA observes coherent radio…

Instrumentation and Detectors · Physics 2019-08-14 Zbigniew Szadkowski , D. Głas , C. Timmermans , T. Wijnen

We present version 3 of Kira, a Feynman integral reduction program for high-precision calculations in quantum field theory and gravitational-wave physics. Building on previous versions, Kira 3 introduces optimized seeding and equation…

High Energy Physics - Phenomenology · Physics 2025-05-27 Fabian Lange , Johann Usovitsch , Zihao Wu

GELATIO is a new software framework for advanced data analysis and digital signal processing developed for the GERDA neutrinoless double beta decay experiment. The framework is tailored to handle the full analysis flow of signals recorded…

Data Analysis, Statistics and Probability · Physics 2011-09-07 M. Agostini , L. Pandola , P. Zavarise , O. Volynets

A common assumption in signal processing is that underlying data numerically conforms to a Gaussian distribution. It is commonly utilized in signal processing to describe unknown additive noise in a system and is often justified by citing…

Signal Processing · Electrical Eng. & Systems 2025-10-14 Jennie Couchman , Phillip Stanley-Marbell

Fourier-transform infrared spectroscopy (FTIR) is a versatile technique for characterizing the chemical composition of the various uncertainties, including baseline shift and multiplicative error. This study aims at analyzing the effect of…

Signal Processing · Electrical Eng. & Systems 2019-08-30 Hongzhen Tian , Andi Wang , Jialei Chen , Xuzhou Jiang , Jianjun Shi , Chuck Zhang , Yajun Mei , Ben Wang

Real-image super-resolution (Real-ISR) seeks to recover HR images from LR inputs with mixed, unknown degradations. While diffusion models surpass GANs in perceptual quality, they under-reconstruct high-frequency (HF) details due to a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Seungho Choi , Jeahun Sung , Jihyong Oh

Beta-delayed neutron emission is important for nuclear structure and astrophysics as well as for reactor applications. Significant advances in nuclear experimental techniques in the past two decades have led to a wealth of new measurements…

In this work, we present FRIGID, a framework with a novel diffusion language model that generates molecular structures conditioned on mass spectra via intermediate fingerprint representations and determined chemical formulae, training at…

We present a method for computing uncertainties in spectral models, i.e. level populations, line emissivities, and emission line ratios, based upon the propagation of uncertainties originating from atomic data. We provide analytic…

Instrumentation and Methods for Astrophysics · Physics 2015-06-12 Manuel A. Bautista , Vanessa Fivet , Pascal Quinet , Jay Dunn , Theodore R. Gull. Timothy R. Kallman , Claudio Mendoza

Fission fragment yield evaluations are one of the important nuclear data studies. Fission accompanies various physical observables such as prompt fission neutron, prompt fission gamma, and delayed-neutrons. When evaluating fission fragment…

Nuclear Theory · Physics 2024-04-30 Futoshi Minato , Osamu Iwamoto