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Segmented antineutrino detectors placed near a compact research reactor provide an excellent opportunity to probe short-baseline neutrino oscillations and precisely measure the reactor antineutrino spectrum. Close proximity to a reactor…

Instrumentation and Detectors · Physics 2015-01-05 T. J. Langford

PROSPECT, the Precision Reactor Oscillation and Spectrum Experiment, will use two segmented detectors positioned 7-20 m from the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory to measure the U-235 antineutrino spectrum…

Instrumentation and Detectors · Physics 2019-08-13 Danielle Norcini

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

The Precision Reactor Oscillation and Spectrum Experiment (PROSPECT) performs a precision measurement of reactor antineutrinos through inverse beta decay at a baseline range of 7-9 m from the core of the High Flux Isotope Reactor (HFIR).…

High Energy Physics - Experiment · Physics 2019-11-05 Olga Kyzylova

The Precision Reactor Oscillation and Spectrum Experiment, PROSPECT, is designed to make a precise measurement of the antineutrino spectrum from a highly-enriched uranium reactor and probe eV-scale sterile neutrinos by searching for…

The Precision Reactor Oscillation and Spectrum Experiment, PROSPECT, is designed to make both a precise measurement of the antineutrino spectrum from a highly-enriched uranium reactor and to probe eV-scale sterile neutrinos by searching for…

PROSPECT is a short-baseline reactor antineutrino experiment designed to search for short-baseline sterile neutrino oscillations and perform a precise measurement of $^{235}$U reactor antineutrino spectrum from the High Flux Isotope Reactor…

High Energy Physics - Experiment · Physics 2019-10-14 P. T. Surukuchi

Machine-learning-based methods can be developed for the reconstruction of clusters in segmented detectors for high energy physics experiments. Convolutional neural networks with autoencoder architecture trained on labeled data from a…

Instrumentation and Detectors · Physics 2025-06-02 Kalina Dimitrova , Venelin Kozhuharov , Ruslan Nastaev , Peicho Petkov

The PROSPECT experiment is designed to perform precise searches for antineutrino disappearance at short distances (7 - 9~m) from compact nuclear reactor cores. This Letter reports results from a new neutrino oscillation analysis performed…

This Letter reports the first scientific results from the observation of antineutrinos emitted by fission products of $^{235}$U at the High Flux Isotope Reactor. PROSPECT, the Precision Reactor Oscillation and Spectrum Experiment, consists…

We propose a genetic algorithm powered evolution (GAPE) method to create deep learning solutions for energy and position estimation for reactor antineutrino interactions in the Precision Reactor Oscillation and Spectrum Experiment…

Active target time projection chambers are important tools in low energy radioactive ion beams or gamma rays related researches. In this work, we present the application of machine learning methods to the analysis of data obtained from an…

Instrumentation and Detectors · Physics 2023-07-11 Huangkai Wu , Youjing Wang , Yumiao Wang , Xiangai Deng , Xiguang Cao , Deqing Fang , Weihu Ma , Hongwei Wang , Wanbing He , Changbo Fu , Yugang Ma

We evaluate machine learning methods for event classification in the Active-Target Time Projection Chamber detector at the National Superconducting Cyclotron Laboratory (NSCL) at Michigan State University. An automated method to single out…

Computer Vision and Pattern Recognition · Computer Science 2019-07-17 Michelle P. Kuchera , Raghuram Ramanujan , Jack Z. Taylor , Ryan R. Strauss , Daniel Bazin , Joshua Bradt , Ruiming Chen

While convolutional neural networks have gained impressive success recently in solving structured prediction problems such as semantic segmentation, it remains a challenge to differentiate individual object instances in the scene. Instance…

Machine Learning · Computer Science 2017-07-14 Mengye Ren , Richard S. Zemel
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