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The nuclear fuel loading pattern optimization problem belongs to the class of large-scale combinatorial optimization. It is also characterized by multiple objectives and constraints, which makes it impossible to solve explicitly. Stochastic…

Machine Learning · Computer Science 2023-07-18 Paul Seurin , Koroush Shirvan

The identification of causal effects in observational studies typically relies on two standard assumptions: unconfoundedness and overlap. However, both assumptions are often questionable in practice: unconfoundedness is inherently…

Methodology · Statistics 2025-09-17 Han Cui , Xinran Li

We transform the randomness of LLMs into precise assurances using an actuator at the API interface that applies a user-defined risk constraint in finite samples via Conformal Risk Control (CRC). This label-free and model-agnostic actuator…

Methodology · Statistics 2025-09-30 Lingyou Pang , Lei Huang , Jianyu Lin , Tianyu Wang , Alexander Aue , Carey E. Priebe

Measurement of the parity-violating electron scattering asymmetry is an established technique at Jefferson Lab and provides a new opportunity to measure the weak charge distribution and hence pin down the neutron radius in nuclei in a…

Nuclear Experiment · Physics 2015-06-16 C. J. Horowitz , K. S. Kumar , R. Michaels

Measurements of the reactor antineutrino flux and spectrum compared to model predictions have revealed an apparent deficit in the interaction rates of reactor antineutrinos and an unexpected spectral deviation. PROSPECT, the Precision…

Instrumentation and Detectors · Physics 2015-11-03 Karin Gilje

Reliable, real-time state estimation in nuclear reactors is of critical importance for monitoring, control and safety. It further empowers the development of digital twins that are sufficiently accurate for real-world deployment. As nuclear…

Instrumentation and Detectors · Physics 2025-07-29 Stefano Riva , Carolina Introini , Antonio Cammi , J. Nathan Kutz

Advances in Deep Learning bring further investigation into credibility and robustness, especially for safety-critical engineering applications such as the nuclear industry. The key challenges include the availability of data set (often…

Machine Learning · Computer Science 2024-05-29 Yu Chen , Edoardo Patelli , Zhen Yang , Adolphus Lye

Robotic search and rescue (SAR) supports response teams by accelerating disaster assessment and by keeping operators away from hazardous environments. In the event of a chemical, biological, radiological, and nuclear (CBRN) disaster, robots…

Shannon entropy is not the only entropy that is relevant to machine-learning datasets, nor possibly even the most important one. Traditional entropies such as Shannon entropy capture information represented by elements' frequencies but not…

Information Theory · Computer Science 2026-04-01 Phuc Nguyen , Josiah Couch , Rahul Bansal , Alexandra Morgan , Chris Tam , Miao Li , Rima Arnaout , Ramy Arnaout

The study of neutron cross sections for elements used as efficient ``absorbers'' of ultracold neutrons (UCN) is crucial for many precision experiments in nuclear and particle physics, cosmology and gravity. In this context, ``absorption''…

Spectroscopy of laser-produced plasmas offers an avenue for real-time, standoff and non-preparatory sensing of rare-earth elements (REEs) within a mineralogical context with applications spanning exploration geology to ore body mapping to…

Hypothetical short-range interactions could be detected by measuring the wavefunctions of ultracold neutrons (UCNs) on a mirror bounded by the Earth's gravitational field. The Searches require detectors with higher spatial resolution. We…

This paper presents a new approach to classification of high dimensional spectroscopy data and demonstrates that it outperforms other current state-of-the art approaches. The specific task we consider is identifying whether samples contain…

Machine Learning · Computer Science 2020-03-27 James Houston , Frank G. Glavin , Michael G. Madden

A technique for characterizing and correcting the linearity of radiometric instruments is known by the names the "flux-addition method" and the "combinatorial technique". In this paper, we develop a rigorous uncertainty quantification…

Applications · Statistics 2023-02-22 Adam L. Pintar , Zachary H. Levine , Howard W. Yoon , Stephen E. Maxwell

Nuclear magnetic resonance (NMR) spectroscopy provides an experimental readout of local chemical environments, but its use in molecular representation learning has been constrained by heterogeneous data and incomplete atom-level…

Chemical Physics · Physics 2026-05-12 Jiebin Fang , Zidi Yan , Churu Mao , Yongjun Jiang , Xinyi Tang , Lei Miao , Dan Lu , Yun Huang , Wanjing Ding , Zhongjun Ma

Tristructural-isotropic (TRISO) fuel is currently one of the most mature fuel types for candidate advanced reactor types, namely pebble bed reactors (PBRs). In PBRs, TRISO-fueled pebbles can be re-introduced into the core several times…

Instrumentation and Detectors · Physics 2024-05-21 Ming Fang , Angela Di Fulvio

This paper proposes a unified semi-blind detection framework for sourced and unsourced random access (RA), which enables next-generation ultra-reliable low-latency communications (URLLC) with massive devices. Specifically, the active…

Information Theory · Computer Science 2023-03-21 Malong Ke , Zhen Gao , Mingyu Zhou , Dezhi Zheng , Derrick Wing Kwan Ng , H. Vincent Poor

Precision measurements in the neutrino sector are becoming increasingly feasible due to the development of relatively high-rate experimental capabilities. These important developments command renewed attention to the systematic corrections…

Nuclear Experiment · Physics 2007-05-23 W. K. Brooks

SoLid is a short baseline neutrino experiment, which is currently operating a 1.6 tons detector at the SCK$\bullet$CEN BR2 research reactor in Belgium. SoLid will address the study of the so called Reactor Antineutrino Anomaly (RAA), whose…

Instrumentation and Detectors · Physics 2019-10-29 Luis Manzanillas