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New generations of neutron scattering sources and instrumentation are providing challenges in data handling for user software. Time-of-Flight instruments used at pulsed sources typically produce hundreds or thousands of channels of data for…

Graphics · Computer Science 2007-05-23 T. G. Worlton , A. Chatterjee , J. P. Hammonds , P. F. Peterson , D. J. Mikkelson , R. L. Mikkelson

Non-contextual word embedding models have been shown to inherit human-like stereotypical biases of gender, race and religion from the training corpora. To counter this issue, a large body of research has emerged which aims to mitigate these…

Computation and Language · Computer Science 2020-10-27 Vaibhav Kumar , Tenzin Singhay Bhotia , Vaibhav Kumar

The Fisher information matrix (FIM) is a foundational concept in statistical signal processing. The FIM depends on the probability distribution, assumed to belong to a smooth parametric family. Traditional approaches to estimating the FIM…

Computation · Statistics 2015-06-22 Visar Berisha , Alfred O. Hero

Time series forecasting is important in many fields that require accurate predictions for decision-making. Patching techniques, commonly used and effective in time series modeling, help capture temporal dependencies by dividing the data…

Machine Learning · Computer Science 2026-02-03 Xiangfei Qiu , Xvyuan Liu , Tianen Shen , Xingjian Wu , Hanyin Cheng , Bin Yang , Jilin Hu

The analysis of signal-to-interference ratios (SIRs) in wireless networks is instrumental to derive important performance metrics, including reliability, throughput, and delay. While a host of results on SIR distributions are now available,…

Information Theory · Computer Science 2020-03-10 Martin Haenggi

We propose a new class of physics-informed neural networks, called physics-informed Variational Autoencoder (PI-VAE), to solve stochastic differential equations (SDEs) or inverse problems involving SDEs. In these problems the governing…

Machine Learning · Statistics 2022-11-09 Weiheng Zhong , Hadi Meidani

Quantifying inherent neutron sources in matter, particularly $(\alpha, n)$ reactions and spontaneous fission, is important in nuclear engineering and other fields. The SOURCES code is a common tool for calculating the yield and spectrum of…

Nuclear Theory · Physics 2025-10-28 Sigtryggur Hauksson , Ilaria Casalbore , Daniele Tomatis , Nunzio Burgio

Atom probe tomography (APT) helps elucidate the link between the nanoscale chemical variations and physical properties, but it has limited structural resolution. Field ion microscopy (FIM), a predecessor technique to APT, is capable of…

Scanning transmission electron microscopy (STEM) plays a critical role in modern materials science, enabling direct imaging of atomic structures and their evolution under external interferences. However, interpreting time-resolved STEM data…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Hao Wang , Hongkui Zheng , Kai He , Abolfazl Razi

The recently developed algorithm FIRE performs the reduction of Feynman integrals to master integrals. It is based on a number of strategies, such as applying the Laporta algorithm, the s-bases algorithm, region-bases and integrating…

High Energy Physics - Phenomenology · Physics 2008-11-26 A. V. Smirnov

Fitting the multi-wavelength spectral energy distributions (SEDs) of galaxies is a widely used technique to extract information about the physical properties of galaxies. However, a major difficulty lies in the numerous uncertainties…

Astrophysics of Galaxies · Physics 2020-06-17 Yunkun Han , Zhanwen Han , Lulu Fan

In electronic structure calculations, various material properties can be obtained by means of computing the total energy of a system as well as derivatives of the total energy w.r.t. atomic positions. The derivatives, also known as…

Computational Physics · Physics 2021-01-07 Robert Cimrman , Matyáš Novák , Radek Kolman , Miroslav Tůma , Jiří Vackář

We implement the Fourier shape parametrization within the point-coupling covariant density functional theory to construct the collective space, potential energy surface (PES), and mass tensor, which serve as inputs for the time-dependent…

Nuclear Theory · Physics 2025-03-13 Zeyu Li , Yang Su , Lile Liu , Yongjing Chen , Zhipan Li

Wire-arc directed energy deposition (DED) has emerged as a promising additive manufacturing (AM) technology for large-scale structural engineering applications. However, the complex thermal dynamics inherent to the process present…

Computational Engineering, Finance, and Science · Computer Science 2025-07-15 Michael Ryan , Mohammad Hassan Baqershahi , Hessamoddin Moshayedi , Elyas Ghafoori

Neutron/gamma discrimination has been intensively researched in recent years, due to its unique scientific value and widespread applications. With the advancement of detection materials and algorithms, nowadays we can achieve fairly good…

Instrumentation and Detectors · Physics 2025-05-28 Pengcheng Ai , Hongtao Qin , Xiangming Sun , Kaiwen Shang

Understanding how well future cosmological experiments can reconstruct the mechanism that generated primordial inhomogeneities is key to assessing the extent to which cosmology can inform fundamental physics. In this work, we apply a…

Cosmology and Nongalactic Astrophysics · Physics 2026-02-23 Michał Piotrak , Thomas Colas , Ana Alonso-Serrano , Alessio Serafini

We present a new algorithm called 'Fast Integrated Spectra Analyzer" (FISA) that permits fast and reasonably accurate age and reddening determinations for small angular diameter open clusters by using their integrated spectra in the…

Instrumentation and Methods for Astrophysics · Physics 2015-06-04 Alejandro Benítez-Llambay , Juan J. Clariá , Andrés E. Piatti

We present a Fisher-information (FI) framework for photon-efficient fluorescence lifetime imaging microscopy (FLIM) that treats temporal sampling as a controllable design variable under a fixed photon (dose) budget. Starting from a Poisson…

Instrumentation and Detectors · Physics 2026-01-05 J. Sumaya-Martinez , E. Torres-Garcia

An innovative physics-guided learning algorithm for predicting the mechanical response of materials and structures is proposed in this paper. The key concept of the proposed study is based on the fact that physics models are governed by…

Computational Engineering, Finance, and Science · Computer Science 2020-04-22 Houpu Yao , Yi Gao , Yongming Liu

The integration of Fourier transform and deep learning opens new avenues for time series forecasting. We reconsider the Fourier transform from a basis functions perspective. Specifically, the real and imaginary parts of the frequency…

Machine Learning · Computer Science 2025-08-05 Runze Yang , Longbing Cao , Xin You , Kun Fang , Jianxun Li , Jie Yang