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Gu, W. Q.

Publications and source records attributed to Gu, W. Q..

10 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Measurement of Electron Antineutrino Oscillation Amplitude and Frequency via Neutron Capture on Hydrogen at Daya Bay

This Letter reports the first measurement of the oscillation amplitude and frequency of reactor antineutrinos at Daya Bay via neutron capture on hydrogen using 1958 days of data. With over 3.6 million signal candidates, an optimized candidate selection, improved treatment of backgrounds and efficiencies, refined energy calibration, and an energy response model for the capture-on-hydrogen sensitive region, the relative ν ¯ e rates and energy spectra variation among the near and far detectors gives sin 2 2 θ 13 = 0.075 9 − 0.0049 + 0.0050 and Δ m 32 2 = ( 2.7 2 − 0.15 + 0.14 ) × 10 − 3 eV 2 assuming the normal neutrino mass ordering, and Δ m 32 2 = ( − 2.8 3 − 0.14 + 0.15 ) × 10 − 3 eV 2 for the inverted neutrino mass ordering. This estimate of sin 2 2 θ 13 is consistent with and essentially independent from the one obtained using the capture-on-gadolinium sample at Daya Bay. The combination of these two results yields sin 2 2 θ 13 = 0.0833 ± 0.0022 , which represents an 8% relative improvement in precision regarding the Daya Bay full 3158-day capture-on-gadolinium result. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Search for a Sub-eV Sterile Neutrino Using Daya Bay’s Full Dataset

This Letter presents results of a search for the mixing of a sub-eV sterile neutrino with three active neutrinos based on the full data sample of the Daya Bay Reactor Neutrino Experiment, collected during 3158 days of detector operation, which contains 5.55 × 106 reactor $\overline{v}$ e candidates identified as inverse beta-decay interactions followed by neutron capture on gadolinium. The analysis benefits from a doubling of the statistics of our previous result and from improvements of several important systematic uncertainties. No significant oscillation due to mixing of a sub-eV sterile neutrino with active neutrinos was found. Exclusion limits are set by both Feldman-Cousins and CLs methods. Light sterile neutrino mixing with sin 2⁡ 2⁢θ 14 ≳ 0.01 can be excluded at 95% confidence level in the region of 0.01 eV 2 ≲ |Δ⁢$m$$^{2}_{41}$| ≲ 0.1 eV 2 . This result represents the world-leading constraints in the region of 2 × 10 –4 eV 2 ≲ |Δ⁢$m$$^{2}_{41}$| ≲ 0.2 eV 2 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

First measurement of the yield of 8 He isotopes produced in liquid scintillator by cosmic-ray muons at Daya Bay

Here, Daya Bay presents the first measurement of cosmogenic 8 He isotope production in liquid scintillator, using an innovative method for identifying cascade decays of 8 He and its child isotope, 8 Li. We also measure the production yield of 9 Li isotopes using well-established methodology. The results, in units of 10 –8 μ –1 ⁢g –1 cm 2 , are 0.307 ± 0.042, 0.341 ± 0.040, and 0.546 ± 0.076 for 8 He, and 6.73 ± 0.73, 6.75 ± 0.70, and 13.74 ± 0.82 for 9 Li at average muon energies of 63.9 GeV, 64.7 GeV, and 143.0 GeV, respectively. The measured production rate of 8 He isotopes is more than an order of magnitude lower than any other measurement of cosmogenic isotope production. It replaces the results of previous attempts to determine the ratio of 8 He to 9 Li production that yielded a wide range of limits from 0% to 30%. The results provide future liquid-scintillator-based experiments with improved ability to predict cosmogenic backgrounds.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Charged-current non-standard neutrino interactions at Daya Bay

The full data set of the Daya Bay reactor neutrino experiment is used to probe the effect of the charged current non-standard interactions (CC-NSI) on neutrino oscillation experiments. Two different approaches are applied and constraints on the corresponding CC-NSI parameters are obtained with the neutrino flux taken from the Huber-Mueller model with a 5% uncertainty. For the quantum mechanics-based approach (QM-NSI), the constraints on the CC-NSI parameters $ϵ_{eα}$ and $ϵ^s_{eα}$ are extracted with and without the assumption that the effects of the new physics are the same in the production and detection processes, respectively. The approach based on the weak effective field theory (WEFT-NSI) deals with four types of CC-NSI represented by the parameters [ε X ] eα . For both approaches, the results for the CC-NSI parameters are shown for cases with various fixed values of the CC-NSI and the Dirac CP-violating phases, and when they are allowed to vary freely. We find that constraints on the QM-NSI parameters $ϵ_{eα}$ and $ϵ^s_{eα}$ from the Daya Bay experiment alone can reach the order O(0.01) for the former and O(0.1) for the latter, while for WEFT-NSI parameters [ε X ] eα , we obtain O(0.1) for both cases.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Joint Determination of Reactor Antineutrino Spectra from U 235 and Pu 239 Fission by Daya Bay and PROSPECT

A joint determination of the reactor antineutrino spectra resulting from the fission of 235U and 239Pu has been carried out by the Daya Bay and PROSPECT collaborations. This Letter reports the level of consistency of 235U spectrum measurements from the two experiments and presents new results from a joint analysis of both data sets. The measurements are found to be consistent. The combined analysis reduces the degeneracy between the dominant 235U and 239Pu isotopes and improves the uncertainty of the 235U spectral shape to about 3%. The 235U and 239Pu antineutrino energy spectra are unfolded from the jointly deconvolved reactor spectra using the Wiener-SVD unfolding method, providing a data-based reference for other reactor antineutrino experiments and other applications. This is the first measurement of the 235U and 239Pu spectra based on the combination of experiments at low- and highly enriched uranium reactors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Antineutrino energy spectrum unfolding based on the Daya Bay measurement and its applications

The prediction of reactor antineutrino spectra will play a crucial role as reactor experiments enter the precision era. The positron energy spectrum of 3.5 million antineutrino inverse beta decay reactions observed by the Daya Bay experiment, in combination with the fission rates of fissile isotopes in the reactor, is used to extract the positron energy spectra resulting from the fission of specific isotopes. This information can be used to produce a precise, data-based prediction of the antineutrino energy spectrum in other reactor antineutrino experiments with different fission fractions than Daya Bay. The positron energy spectra are unfolded to obtain the antineutrino energy spectra by removing the contribution from detector response with the Wiener-SVD unfolding method. Consistent results are obtained with other unfolding methods. A technique to construct a data-based prediction of the reactor antineutrino energy spectrum is proposed and investigated. Given the reactor fission fractions, the technique can predict the energy spectrum to a 2% precision. In addition, we illustrate how to perform a rigorous comparison between the unfolded antineutrino spectrum and a theoretical model prediction that avoids the input model bias of the unfolding method.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Augmented signal processing in Liquid Argon Time Projection Chambers with a deep neural network

The Liquid Argon Time Projection Chamber (LArTPC) is an advanced neutrino detector technology widely used in recent and upcoming accelerator neutrino experiments. It features a low energy threshold and high spatial resolution that allow for comprehensive reconstruction of event topologies. In current-generation LArTPCs, the recorded data consist of digitized waveforms on wires produced by induced signal on wires of drifting ionization electrons, which can also be viewed as two-dimensional (2D) (time versus wire) projection images of charged-particle trajectories. For such an imaging detector, one critical step is the signal processing that reconstructs the original charge projections from the recorded 2D images. For the first time, we introduce a deep neural network in LArTPC signal processing to improve the signal region of interest detection. By combining domain knowledge (e.g., matching information from multiple wire planes) and deep learning, this method shows significant improvements over traditional methods. This work details the method, software tools, and performance evaluated with realistic detector simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗