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Light Yield Calibration in MicroBooNE

The MicroBooNE detector is a Liquid Argon Time Projection Chamber (LArTPC) located along the Booster Neutrino Beam (BNB) at Fermilab. Its primary physics goal is to contribute to addressing the elusive short-baseline MiniBooNE low energy excess. MicroBooNE records and utilises both the ionisation charge and scintillation light produced inside the TPC to select and reconstruct neutrino interactions. The scintillation light collected using a plane of PhotoMultiplier Tubes (PMTs) is also used for accurate event timing and cosmic muon rejection with the latter being an important background for detectors, such as MicroBooNE, located on the surface. A good understanding of light modeling and its related systematic uncertainties is crucial to evaluate their impact on physics analyses. The experience acquired from MicroBooNE regarding how the stability of the scintillation light behaves and evolves during the 5 years of the primary physics run will be discussed as well as the calibration method used. This experience will help with understanding the physics of scintillation light in LArTPCs for the future long-running Short-Baseline Neutrino (SBN) and Deep Underground Neutrino Experiment (DUNE) programs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Event Selection in the MicroBooNE Deep Learning Based Low Energy Excess Analysis Using Two-Body Scattering Criteria

The uniquely detailed neutrino event information from liquid argon time projection chambers allows reconstruction of a set of kinematic quantities that over-constrain the expectations for charged current quasielastic scattering (CCQE). MicroBooNE makes use of the CCQE consistency requirements in a deep-learning-based search for the MiniBooNE low energy excess analysis. This requirement rejects backgrounds as well as events with poorly reconstructed neutrino energy due to final state interactions of the outgoing proton. The results presented here demonstrate the quality of the selection of $\nu_e$ and $\nu_µ$ events. We show excellent agreement between the data and the simulation across many data sets. This positions us to be ready to unblind the MicroBooNE low energy excess analysis in the very near future.

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Chimera Events for Performance Studies of the MicroBooNE Deep Learning-based Low Energy Excess Search

MicroBooNE is a short baseline neutrino oscillation experiment based at Fermilab that employs Liquid Argon Time Projection Chamber (LArTPC) technology. One of its target measurements is to investigate the nature of the excess of low energy electron-like events observed by MiniBooNE. This measurement will require an excellent understanding of systematic uncertainties, obtained through testing the performance of reconstruction algorithms on samples with known properties. However, using exclusively Monte Carlo events for this task is limited by how well the discrepancies between simulation and data are understood. An alternative is to test against samples of “chimera” events, which are made up of separate single-particle components from data that are combined to create neutrino-like events. These chimera events can be used to help quantify systematic uncertainties. This note covers the performance and status of creating and using chimera events that match a target neutrino topology in MicroBooNE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Identifying Neutrino Final States and Energies in MicroBooNE with New Deep-Learning Based LArTPC Reconstruction Frameworks

MicroBooNE, a Liquid Argon Time Projection Chamber (LArTPC) located in the $\nu_{\mu}$-dominated Booster Neutrino Beam at Fermilab, has been studying $\nu_{e}$ charged-current (CC) interaction rates to shed light on the MiniBooNE low energy excess. The LArTPC technology employed by MicroBooNE provides the capability to image neutrino interactions with mm-scale precision. Computer vision and other machine learning techniques are promising tools for image processing that could boost efficiencies for selecting $\nu_{e}$-CC and other rare signals, reduce cosmic and beam-induced backgrounds, and improve the reconstruction of neutrino energies. The MicroBooNE experiment has been at the forefront of developing and testing such techniques for use in physics analyses. In this poster we overview deep-learning based reconstruction methods. We will showcase the use of a recurrent neural network to estimate neutrino energies and present a new reconstruction framework that uses convolutional neural networks to locate neutrino interaction vertices, tag pixels with track and shower labels, and perform particle identification on reconstructed clusters. We will present studies characterizing the performance of these new tools and demonstrate their effectiveness through their use in an inclusive $\nu_{e}$-CC event selection.

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Progress Towards an Expanded Search for Neutral-Current Delta Radiative Decays in MicroBooNE

In this note, we present progress toward an expanded search for neutral current Delta radiative decays (NC $\Delta \rightarrow N\gamma$) in MicroBooNE. We present sensitivities for several tests of the MiniBooNE Low Energy Excess (LEE) under NC $\Delta \rightarrow N\gamma$ scaling hypotheses, with significantly enhanced sensitivity relative to previous tests. These selections can also be used for additional single photon searches in the future, including searches which target more specific hadronic final states and particular regions of shower kinematic phase space.

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An Updated Simulation of the Booster Neutrino Beam

For accelerator neutrino experiments, an accurate prediction of the incoming neutrino flux is crucial for reducing uncertainties for all physics measurements. In this exciting period for the Short-Baseline Neutrino program at Fermilab, with far detector (ICARUS) already operating and the near detector (SBND) nearing operation, an updated flux model for the Booster Neutrino Beam (BNB) is presented. The BNB delivers 8 GeV protons to a beryllium target, subsequently producing neutrinos from the decay of the secondary beam of hadrons. A updated Monte-Carlo simulation of beam production in GEANT4 has been created, allowing predictions to be made for detectors with different baselines, offsets and sizes. This new simulation contains new features, such as a full neutrino ancestry to handle hadron production systematics with more precision, with a view to storing all resulting particles - including neutral mesons - from the proton-Beryllium scatter to allow the study of exotic BSM scenarios. Results are presented, with comparisons to the original flux simulated for the MiniBooNE experiment.

Paton, Josephine↗

New MicroBooNE Single Photon Searches: Delta Radiative Decay, Coherent, and Inclusive

The MicroBooNE experiment is a liquid argon time projection chamber (LArTPC) in the Booster Neutrino Beam at Fermilab. The LArTPC technology allows us to distinguish between electron and photon showers, which is crucial for identifying the source of the long-standing anomalous excess reported by MiniBooNE. Initial MicroBooNE results have challenged the electron interpretation, which highlights the importance of further study of the single photon channel. In this talk, we present results from three new and improved searches for single photons, offering a wider probe of the photon channel: an enhanced search for NC Delta radiative single photon production, the world’s first search for neutrino-induced coherent single photon production, and an inclusive search for single photons in a diverse set of topologies.

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Conducting Beyond the Standard Model Searches in the MicroBooNE Detector with Machine Learning

MicroBooNE is one of the three neutrino detectors that comprise the Short Baseline Neutrino program at Fermilab. It utilizes Liquid Argon Time Projection Chamber (LArTPC) technology to probe the anomalous excess of electron-like events seen by its predecessor, MiniBooNE. Additionally, it provides a rich avenue of study for Beyond the Standard Model (BSM) theories. In the GeV energy regime relevant to MicroBooNE's beam neutrino program, many such theories lead to signatures which produce electron-positron (e+e-) final-states in the detector. While photons can pair produce into e+e- pairs with negligible opening angles, BSM theories often predict e+e- pairs with a broader range of opening angles. Thus, developing a tool that can reliably measure the opening angles of e+e- events is crucial for conducting rigorous BSM studies. However, these e+e- pairs result in topologically complex showers instead of clean tracks, making non-machine learning (ML) based methods such as line-fitting unsuitable for this task. This poster discusses the effectiveness of ML, namely a graph neural network called PointNet++, in accomplishing this goal. Our studies show promising results, with a resolution for the opening angle of 5 or less.

Bhelande, Vedang Adutya [Los Alamos]↗

Improving ICARUS Track Reconstruction Algorithms

The ICARUS experiment is part of the Short-Baseline Neutrino (SBN) program at Fermilab. The main goal of the experiment is to investigate the possibility of sterile neutrinos in the O(1 eV) mass region and provide clarification of the anomaly detected from the Liquid Scintillator Neutrino Detector (LSND) and MiniBooNE experiments. The ICARUS-T600 detector is a Liquid Argon Time Projection Chamber (LAr-TPC), that can provide excellent 3D imaging and calorimetric reconstruction of any ionizing particles. This detection technique allows a detailed study of neutrino interactions, spanning a wide energy spectrum (from a few keV to several hundreds of GeV). The detector consists of two identical adjacent modules, filled with a total of 760 tons of ultra-pure liquid argon. Each module houses two LAr-TPCs separated by a common cathode with a maximum drift distance of 1.5 m, equivalent to about 1 ms drift time for the nominal $500$ V/m electric drift field. The anode is made of three parallel wire planes positioned 3 mm apart, where the stainless-steel wires are oriented on each plane at a different angle with respect to the horizontal direction ($+60^\degree$,$-60^\degree$,$0^\degree$). The first two planes (Induction 1 and Induction 2) provide a non-destructive charge measurement, whereas the ionization charge is fully collected by the last collection plane. In total, 53248 wires with a 3 mm pitch and length up to 9 m are installed in the detector. In the first stage of the reconstruction, segments of waveforms corresponding to physical signals (hits) are searched for in the deconvolved wire waveform with a threshold-based hit-finding algorithm. Each hit is then fitted with a Gaussian, whose area is proportional to the number of drift electrons generating the signal. In the second stage of the reconstruction, hits are passed as input to Pandora, a framework software composed of different pattern recognition algorithms, that performs a 3D reconstruction of the full image recorded in the collected event, including the identification of interaction vertices and tracks and showers inside the TPC. These are organized into a hierarchical structure (called slice) of particles generated starting from a primary interaction vertex. In some cases, related to the inefficiencies in the hit detection or excessive deflection of the particle trajectory, Pandora breaks the particle's track into two or more smaller pieces and considers each piece as an independent track. We studied this phenomenon focusing on primary muons from ν_μ CC interactions contained in a single module with a track at least 20 cm long, to exclude delta rays. The study determined that about $7-8\%$ of the muon tracks are broken. Approximately $80\%$ of the times, Pandora assigns all segments of the track to the same slice (intra-slice track split), while in the remaining $20\%$ of the cases, one of the segments is associated with another slice (extra-slice track split). To mitigate this phenomenon, we designed an algorithm that detects and stitches the tracks broken by Pandora for the intra-slice split. In Monte Carlo simulations, the algorithm showed an efficiency exceeding $80\%$ and a purity exceeding $93\%$.

Ricci, Alessandro Maria [Pisa U.; INFN, Pisa] (ORC↗

Shower Reconstruction for Cross-Section Measurements with Photon(s) in the Final State at SBND

The Short-Baseline Near Detector (SBND) is a 112-ton liquid argon time projection chamber operating in the Booster Neutrino Beam at Fermilab as part of the Short-Baseline Neutrino Program. Precise reconstruction of electromagnetic showers from photons and electrons is essential for searches for neutrino oscillations, cross-section measurements, and rare-process studies in liquid argon. In this poster, we present a unified set of SBND analyses enabled by the SPINE (Scalable Particle Imaging with Neural Embeddings) end-to-end machine-learning–based reconstruction framework, highlighting charged-current neutral pion (CC π⁰) production and neutral-current (NC) Δ radiative decay as complementary physics cases. Charged-current π⁰ interactions provide a high-statistics benchmark for validating photon reconstruction, constraining the electromagnetic energy scale, and modeling backgrounds to other cross-section measurements and BSM searches with one or more photons in the final state. We summarize progress toward the ongoing development of a CC π⁰ selection in SBND and, report on the current status of a search for NC resonant Δ production followed by radiative decay (Δ→Nγ) in SBND. This rare process, previously investigated in MicroBooNE, provides a stringent test of photon-only final-state reconstruction and is of interest in the context of the MiniBooNE low-energy excess. Together, these analyses demonstrate how modern machine-learning–based shower reconstruction enables a diverse and scalable physics program at SBND.

Chung, Seokju [Nevis Labs, Columbia U.]↗

Status of 1eNp0π Charged-Current Electron Neutrino Cross Section on Argon in the NuMI Beam at ICARUS

The Short-Baseline Neutrino (SBN) Program is designed to probe short-baseline neutrino anomalies, including the LSND electron neutrino excess and the MiniBooNE low-energy excess. Essential to interpreting these anomalies and to the success of future experiments like DUNE, is the precise measurement of neutrino-argon interaction cross sections. The program utilizes two liquid argon time projection chamber (LArTPC) detectors: the Short-Baseline Near Detector (SBND) located 110 meters downstream from the Booster Neutrino Beam (BNB) target, and the ICARUS detector positioned 600 meters downstream. Additionally, the ICARUS detector lies off-axis to the NuMI beamline, providing a unique, high-statistics flux of electron neutrinos and sensitivity to energies that overlap with the DUNE spectrum. To analyze the data from these detectors, we have begun employing a machine-learning-based reconstruction algorithm referred to as “Scalable Particle Imaging with Neural Embeddings” (SPINE). SPINE has shown improvement in the ability to reconstruct the properties of final state particles in the detector, like the particle ID and momentum, with the potential to enhance the quality of measurements achievable within the SBN Program e.g., the resolution on kinematics used in differential cross section extraction. This poster presents progress toward measuring the electron neutrino argon interaction cross section in the 1eNp0π topology using the NuMI beam, highlighting the impact of SPINE through the ability to select signal events across a wide kinematic range without sacrificing background rejection power.

Carber, Dan [Colorado State U.] (ORCID:00090006451↗

Search for muon neutrino disappearance with multi-topologically splitted Inclusive events at SBN

The Short-Baseline Neutrino (SBN) program at Fermilab searches for signatures of sterile neutrinos with mass-squared splittings at the O(1) eV2 scale, motivated by anomalies previously reported by the LSND and MiniBooNE experiments. We present a search for such signatures using the muon neutrino disappearance channel. This analysis exploits the large statistics of fully inclusive charged-current interactions collected by the SBND and ICARUS detectors to maximize sensitivity. The inclusive samples in both detectors are further subdivided into multiple exclusive topological channels, a strategy designed to enhance sensitivity by isolating differences in interaction-mode composition and reconstructed energy response. This multi-topology approach represents a novel analysis technique within SBN, enabling improved constraints on systematic uncertainties arising from neutrino flux, interaction modeling, and detector response. We will present comparisons of data with detailed predictions incorporating a comprehensive treatment of systematic uncertainties and constraints on the systematics obtained by the multi-topology method.

Yadav, Shweta [Texas U., Arlington]↗

Improving MicroBooNE's Inclusive Single-Photon Search with Low-Energy Hadronic Identification

This analysis aims to further investigate MicroBooNE’s inclusive single-photon search results, which reported a 2.2$\sigma$ excess below 600 MeV in shower energy for events with no reconstructed protons using roughly half of MicroBooNE's dataset. Taken together with MiniBooNE’s long-standing low-energy excess and MicroBooNE’s recent electron-like search results showing no observable excess with respect to Standard Model predictions, this result provides strong impetus for expanded exploration of the single-photon channel in Fermilab’s short-baseline liquid-argon time projection chamber (LArTPC) experiments. By identifying and classifying isolated MeV-scale energy depositions, or blips, in the vicinity of single-photon events selected by the Wire-Cell reconstruction framework, we establish a more comprehensive labeling scheme for nearby hadronic content. In particular, blips found backwards along the shower axis indicate the presence of previously-unidentified final-state protons, while elevated blip counts at wide angles signal the presence of final-state neutrons. By applying this new technique to its full dataset, MicroBooNE will perform a purer and higher-statistics test of the truly isolated nature of its modest photon-like excess, furthering its hunt for the presence of unexpected new physics beyond the Standard Model.

Andrade Aldana, Diego [Los Alamos; IIT, Chicago (m↗

Cross Section Prospects for MicroBooNE

MicroBooNE is a liquid-argon-based neutrino experiment, which began collecting data in Fermilab's Booster neutrino beam in October 2015. The physics goals of the experiment include probing the source of the anomalous excess of electron-like events in MiniBooNE. In addition to this, MicroBooNE is carrying out an extensive neutrino cross section physics program that will allow to investigate current theories on neutrino-nucleus interactions relevant to the neutrino oscillation program and in understanding the role played by nuclear effects in argon. These proceedings summarise the status of MicroBooNE's neutrino cross section analyses.

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Status of the MicroBooNE Low Energy Excess Search

MicroBooNE is a neutrino experiment that utilizes a liquid argon time projection chamber (LArTPC) located on-axis in the Booster Neutrino Beam (BNB) at Fermilab. One of the experiment’s main goals is to search for excess low-energy electromagnetic-like events as seen by the MiniBooNE experiment, located just downstream of MicroBooNE in the BNB. As MicroBooNE nears the completion of its first single-electron-like and single-photon-like searches, these proceedings present the status of MicroBooNE's low-energy excess search as of early summer 2020. In addition to presenting an overview of the approach to these analyses, we showcase results from $\pi^0$ calibrations and $e$/$\gamma$ separation, and sample results from sidebands aimed at validating the analysis' progress outside the low-energy signal region.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Charged-Current Electron Neutrino Measurement with the MicroBooNE Detector

MicroBooNE is the first phase of Fermilab’s Short Baseline Neutrino (SBN) Liquid Argon Time Projection Chamber (LArTPC) programme.This proceeding outlays the first characterisation of electron neutrinos in a muon neutrino beam with the LArTPC detector technology. The Booster Neutrino Beam has an energy peaking around 1GeV and an electron content of approximately 0.5%. The analysis investigates electrons produced in charged-current electron neutrino interactions. The kinematics of the electrons are measured along with comparisons to simulation. Most of the systematic uncertainties are constrained using a data-driven sample of charged-current muon neutrino events. The measurement of electron neutrinos originating from the Booster Neutrino Beam is a crucial component to understand the nature of the observed excess of low energy electromagnetic-like events at MiniBooNE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Improved Limits on Sterile Neutrino Mixing from a Joint Search of the MINOS, MINOS+, Daya Bay, and Bugey-3 Experiments

The Daya Bay, MINOS and MINOS+ experiments have searched for sterile neutrino mixing using electron antineutrino and muon (anti)neutrino disappearance, respectively, within a minimally extended four-neutrino scenario. They have recently combined their results, together with those from the Bugey-3 reactor neutrino experiment, to set the most stringent limits to date on the $\theta_{\mu e}$ mixing angle over five orders of magnitude in the sterile mass-squared difference $|\Delta m^2_{41}|$. The new constraints are significantly more stringent than the previous ones and exclude the sterileneutrino parameter space allowed by the LSND and MiniBooNE observations at 99% C.L.(CL$_{s}$) for $|\Delta m^2_{41}| <$ 1.2 eV$^2$, weakening the interpretation of these observations by the presence of a sterile neutrino. The result of the joint Daya Bay, MINOS, MINOS+ and Bugey-3 search along with a brief overview of the searches done by each experiment is presented.

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The Short Baseline Neutrino Program at Fermilab

The current status of the Short Baseline Neutrino (SBN) project at Fermilab is reviewed. While the installation of SBND is still in progress, ICARUS has taken its first neutrino data on beam:using both the Booster Neutrino Beam (BNB) and the Neutrino at the Main Injector (NuMI) beam.MicroBooNE has presently completed its data taking and is producing the world’s first high statistics results on neutrino Argon interactions, in both inclusive and exclusive channels. In parallel, the unexpected MiniBooNE “low energy excess” is under investigation, to search for sterile neutrinos.The physics potential for sterile neutrino searches at SBN will be outlined, with emphasis on the Neutrino-4 experiment and the possible ICARUS verification of this claim.

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