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1. Improving neutrino energy estimation of charged-current interaction events with recurrent neural networks in MicroBooNE

   https://doi.org/10.1103/PhysRevD.110.092010  

   Abratenko, P; Alterkait, O; Andrade_Aldana, D; Arellano, L; Asaadi, J; Ashkenazi, A; Balasubramanian, S; Baller, B; Barnard, A; Barr, G; et al (November 2024, Physical Review D)

   We present a deep learning-based method for estimating the neutrino energy of charged-current neutrino-argon interactions. We employ a recurrent neural network (RNN) architecture for neutrino energy estimation in the MicroBooNE experiment, utilizing liquid argon time projection chamber (LArTPC) detector technology. Traditional energy estimation approaches in LArTPCs, which largely rely on reconstructing and summing visible energies, often experience sizable biases and resolution smearing because of the complex nature of neutrino interactions and the detector response. The estimation of neutrino energy can be improved after considering the kinematics information of reconstructed final-state particles. Utilizing kinematic information of reconstructed particles, the deep learning-based approach shows improved resolution and reduced bias for the muon neutrino Monte Carlo simulation sample compared to the traditional approach. In order to address the common concern about the effectiveness of this method on experimental data, the RNN-based energy estimator is further examined and validated with dedicated data-simulation consistency tests using MicroBooNE data. We also assess its potential impact on a neutrino oscillation study after accounting for all statistical and systematic uncertainties and show that it enhances physics sensitivity. This method has good potential to improve the performance of other physics analyses. Published by the American Physical Society2024 

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2. First study of neutrino angle reconstruction using quasielasticlike interactions in MicroBooNE

   https://doi.org/10.1103/f8nt-ygng  

   Abratenko, P; Andrade_Aldana, D; Arellano, L; Asaadi, J; Ashkenazi, A; Balasubramanian, S; Baller, B; Barnard, A; Barr, G; Barrow, D; et al (June 2025, Physical Review D)

   We investigate the expected precision of the reconstructed neutrino direction using a ${\nu }_{\mu }$-argon quasielasticlike event topology with one muon and one proton in the final state and the reconstruction capabilities of the MicroBooNE liquid argon time projection chamber. This direction is of importance in the context of DUNE sub-GeV atmospheric oscillation studies. MicroBooNE allows for a data-driven quantification of this resolution by investigating the deviation of the reconstructed muon-proton system orientation with respect to the well-known direction of neutrinos originating from the Booster Neutrino Beam with an exposure of $1.3\times {10}^{21}$protons on target. Using simulation studies, we derive the expected sub-GeV DUNE atmospheric-neutrino reconstructed simulated spectrum by developing a reweighting scheme as a function of the true neutrino energy. We further report flux-integrated single- and double-differential cross section measurements of charged-current ${\nu }_{\mu }$quasielasticlike scattering on argon as a function of the muon-proton system angle using the full MicroBooNE data sets. We also demonstrate the sensitivity of these results to nuclear effects and final state hadronic reinteraction modeling. 

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3. Searches for Neutrinos from Large High Altitude Air Shower Observatory Ultra-high-energy γ-Ray Sources Using the IceCube Neutrino Observatory

   https://doi.org/10.3847/2041-8213/acb933  

   Abbasi, R.; Ackermann, M.; Adams, J.; Aggarwal, N.; Aguilar, J. A.; Ahlers, M.; Alameddine, J. M.; Alves, A. A.; Amin, N. M.; Andeen, K.; et al (March 2023, The Astrophysical Journal Letters)

   Abstract Galactic PeV cosmic-ray accelerators (PeVatrons) are Galactic sources theorized to accelerate cosmic rays up to PeV in energy. The accelerated cosmic rays are expected to interact hadronically with nearby ambient gas or the interstellar medium, resulting in γ -rays and neutrinos. Recently, the Large High Altitude Air Shower Observatory (LHAASO) identified 12 γ -ray sources with emissions above 100 TeV, making them candidates for PeVatrons. While at these high energies the Klein–Nishina effect exponentially suppresses leptonic emission from Galactic sources, evidence for neutrino emission would unequivocally confirm hadronic acceleration. Here, we present the results of a search for neutrinos from these γ -ray sources and stacking searches testing for excess neutrino emission from all 12 sources as well as their subcatalogs of supernova remnants and pulsar wind nebulae with 11 yr of track events from the IceCube Neutrino Observatory. No significant emissions were found. Based on the resulting limits, we place constraints on the fraction of γ -ray flux originating from the hadronic processes in the Crab Nebula and LHAASO J2226+6057. 

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4. Spin-flavor precession of Dirac neutrinos in dense matter and its potential in core-collapse supernovae

   https://doi.org/10.1103/PhysRevD.108.103046  

   Sasaki, Hirokazu; Takiwaki, Tomoya; Balantekin, A. Baha (November 2023, Physical Review D)

   We calculate the spin-flavor precession (SFP) of Dirac neutrinos induced by strong magnetic fields and finite neutrino magnetic moments in dense matter. As found in the case of Majorana neutrinos, the SFP of Dirac neutrinos is enhanced by the large magnetic field potential and suppressed by large matter potentials composed of the baryon density and the electron fraction. The SFP is possible irrespective of the large baryon density when the electron fraction is close to 1/3. The diagonal neutrino magnetic moments that are prohibited for Majorana neutrinos enable the spin precession of Dirac neutrinos without any flavor mixing. With supernova hydrodynamics simulation data, we discuss the possibility of the SFP of both Dirac and Majorana neutrinos in core-collapse supernovae. The SFP of Dirac neutrinos occurs at a radius where the electron fraction is 1/3. The required magnetic field of the proto-neutron star for the SFP is a few 10^{14} G at any explosion time. For the Majorana neutrinos, the required magnetic field fluctuates from 10^{13} G to 10^{15} G. Such a fluctuation of the magnetic field is more sensitive to the numerical scheme of the neutrino transport in the supernova simulation. 

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5. Retrieval of energy spectra for all flavours of neutrinos from core-collapse supernova with multiple detectors

   https://doi.org/10.1093/mnras/staa3287  

   Nagakura, Hiroki (November 2020, Monthly Notices of the Royal Astronomical Society)

   null (Ed.)

   ABSTRACT We present a new method by which to retrieve energy spectrum for all falvours of neutrinos from core-collapse supernova (CCSN). In the retrieval process, we do not assume any analytic formulas to express the energy spectrum of neutrinos but rather take a direct way of spectrum reconstruction from the observed data; the singular value decomposition algorithm with a newly developed adaptive energy-gridding technique is adopted. We employ three independent reaction channels having different flavour sensitivity to neutrinos. Two reaction channels, inverse beta decay on proton and elastic scattering on electrons, from a water Cherenkov detector such as Super-Kamiokande (SK) and Hyper-Kamiokande (HK), and a charged current reaction channel with Argon from the Deep Underground Neutrino Experiment (DUNE) are adopted. Given neutrino oscillation models, we iteratively search the neutrino energy spectra at the CCSN source until they provide the consistent event counts in the three reaction channels. We test the capability of our method by demonstrating the spectrum retrieval to a theoretical neutrino data computed by our recent three-dimensional CCSN simulation. Although the energy spectrum with either electron-type or electron-type antineutrinos at the CCSN source has relatively large error compared to that of other species, the joint analysis with HK + DUNE or SK + DUNE will provide precise energy spectrum of all flavours of neutrinos at the source. Finally, we discuss perspectives for improvements of our method by using neutrino data of other detectors. 

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