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Correcting for detector effects in experimental data, particularly through unfolding, is critical for enabling precision measurements in high-energy physics. However, traditional unfolding methods face challenges in scalability,…
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We identify a new, flux-dependent correction to the antineutrino spectrum as produced in nuclear reactors. The abundance of certain nuclides, whose decay chains produce antineutrinos above the threshold for inverse beta decay, has a…
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Bonner Spheres have been used widely for the measurement of neutron spectra with neutron energies ranged from thermal up to at least 20 MeV. A Bonner Sphere neutron spectrometer (BSS) was developed by extending a Berthold LB 6411…
Modern nuclear data evaluation increasingly requires not only accurate scattering calculations, but also efficient methods for uncertainty quantification and parameter optimization, tasks that benefit from differentiable solvers amenable to…
We present the sensitivity of the Theia experiment to low-energy geo- and reactor antineutrinos. For this study, we consider one of the possible proposed designs, a 17.8-ktonne fiducial volume Theia-25 detector filled with water-based…
We study source-free unsupervised domain adaptation (SFUDA) for semantic segmentation, which aims to adapt a source-trained model to the target domain without accessing the source data. Many works have been proposed to address this…
We present a carefully designed, systematic study of the angular resolution dependence of simulations with the Prometheus-Vertex neutrino-hydrodynamics code. Employing a simplified neutrino heating-cooling scheme in the Prometheus…
The Muon optimizer has recently demonstrated remarkable empirical success in training large language models. However, the theoretical understanding of its mechanisms remains limited. Current convergence guarantees for Muon rely heavily on…
The cross section averaged over 235U thermal-neutron induced fission spectrum is a fundamental quantity that can be used in evaluation and validation of nuclear data. Many experiments focused on the determination of Spectrum Averaged Cross…
The design of moderators and cold sources of neutrons is a key point in research-reactor physics, requiring extensive knowledge of the scattering properties of very important light molecular liquids such as methane, hydrogen and their…
We tackle unsupervised anomaly detection (UAD), a problem of detecting data that significantly differ from normal data. UAD is typically solved by using density estimation. Recently, deep neural network (DNN)-based density estimators, such…
We present a novel methodology of augmenting the scattering data measured by small angle neutron scattering via an emerging deep convolutional neural network (CNN) that is widely used in artificial intelligence (AI). Data collection time is…
It is challenging to design an equalizer for the complex time-frequency doubly-selective channel. In this paper, we employ the deep unfolding approach to establish an equalizer for the underwater acoustic (UWA) orthogonal frequency division…