arXiv subjects

D. Marsden

Publications and source records attributed to D. Marsden.

At least 55 records · Page 3Linked to original sources

arXiv2022

Search for an Excess of Electron Neutrino Interactions in MicroBooNE Using Multiple Final State Topologies

We present a measurement of electron neutrino interactions from the Fermilab Booster Neutrino Beam using the MicroBooNE liquid argon time projection chamber to address the nature of the excess of low energy interactions observed by the MiniBooNE collaboration. Three independent electron neutrino searches are performed across multiple single electron final states, including an exclusive search for two-body scattering events with a single proton, a semi-inclusive search for pion-less events, and a fully inclusive search for events containing all hadronic final states. With differing signal topologies, statistics, backgrounds, reconstruction algorithms, and analysis approaches, the results are found to be consistent with the nominal electron neutrino rate expectations from the Booster Neutrino Beam and no excess of electron neutrino events is observed.

hep-ex↗

arXiv2022

First Measurement of Energy-Dependent Inclusive Muon Neutrino Charged-Current Cross Sections on Argon with the MicroBooNE Detector

We report a measurement of the energy-dependent total charged-current cross section $σ\left(E_ν\right)$ for inclusive muon neutrinos scattering on argon, as well as measurements of flux-averaged differential cross sections as a function of muon energy and hadronic energy transfer ($ν$). Data corresponding to 5.3$\times$10$^{19}$ protons on target of exposure were collected using the MicroBooNE liquid argon time projection chamber located in the Fermilab Booster Neutrino Beam with a mean neutrino energy of approximately 0.8 GeV. The mapping between the true neutrino energy $E_ν$ and reconstructed neutrino energy $E^{rec}_ν$ and between the energy transfer $ν$ and reconstructed hadronic energy $E^{rec}_{had}$ are validated by comparing the data and Monte Carlo (MC) predictions. In particular, the modeling of the missing hadronic energy and its associated uncertainties are verified by a new method that compares the $E^{rec}_{had}$ distributions between data and an MC prediction after constraining the reconstructed muon kinematic distributions, energy and polar angle, to those of data. The success of this validation gives confidence that the missing energy in the MicroBooNE detector is well-modeled and underpins first-time measurements of both the total cross section $σ\left(E_ν\right)$ and the differential cross section $dσ/dν$ on argon.

hep-ex↗

arXiv2022

Electromagnetic Shower Reconstruction and Energy Validation with Michel Electrons and $π^0$ Samples for the Deep-Learning-Based Analyses in MicroBooNE

This article presents the reconstruction of the electromagnetic activity from electrons and photons (showers) used in the MicroBooNE deep learning-based low energy electron search. The reconstruction algorithm uses a combination of traditional and deep learning-based techniques to estimate shower energies. We validate these predictions using two $ν_μ$-sourced data samples: charged/neutral current interactions with final state neutral pions and charged current interactions in which the muon stops and decays within the detector producing a Michel electron. Both the neutral pion sample and Michel electron sample demonstrate agreement between data and simulation. Further, the absolute shower energy scale is shown to be consistent with the relevant physical constant of each sample: the neutral pion mass peak and the Michel energy cutoff.

hep-ex↗

arXiv2022

Search for an anomalous excess of charged-current $ν_e$ interactions without pions in the final state with the MicroBooNE experiment

This article presents a measurement of $ν_e$ interactions without pions in the final state using the MicroBooNE experiment and an investigation into the excess of low-energy electromagnetic events observed by the MiniBooNE collaboration. The measurement is performed in exclusive channels with (1$e$N$p$0$π$) and without (1$e$0$p$0$π$) visible final-state protons using 6.86$\times 10^{20}$ protons on target of data collected from the Booster Neutrino Beam at Fermilab. Events are reconstructed with the Pandora pattern recognition toolkit and selected using additional topological information from the MicroBooNE liquid argon time projection chamber. Using a goodness-of-fit test the data are found to be consistent with the predicted number of events with nominal flux and interaction models with a $p$-value of 0.098 in the two channels combined. A model based on the low-energy excess observed in MiniBooNE is introduced to quantify the strength of a possible $ν_e$ excess. The analysis suggests that if an excess is present, it is not consistent with a simple scaling of the $ν_e$ contribution to the flux. Combined, the 1$e$N$p$0$π$ and 1$e$0$p$0$π$ channels do not give a conclusive indication about the tested model, but separately they both disfavor the low-energy excess model at $>$90% CL. The observation in the most sensitive 1$e$N$p$0$π$ channel is below the prediction and consistent with no excess. In the less sensitive 1$e$0$p$0$π$ channel the observation at low energy is above the prediction, while overall there is agreement over the full energy spectrum.

hep-ex↗

arXiv2022

First Measurement of Inclusive Electron-Neutrino and Antineutrino Charged Current Differential Cross Sections in Charged Lepton Energy on Argon in MicroBooNE

We present the first measurement of the single-differential $ν_e + \barν_e$ charged-current inclusive cross sections on argon in electron or positron energy and in electron or positron scattering cosine over the full angular range. Data were collected using the MicroBooNE liquid argon time projection chamber located off-axis from the Fermilab Neutrinos at the Main Injector beam over an exposure of $2.0\times10^{20}$ protons on target. The signal definition includes a 60 MeV threshold on the $ν_e$ or $\barν_e$ energy and a 120 MeV threshold on the electron or positron energy. The measured total and differential cross sections are found to be in agreement with the GENIE, NuWro, and GiBUU neutrino generators.

hep-ex↗

arXiv2022

Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data

The MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and development of this novel detector technology. Accurate and precise measurements of calorimetry are essential to the event reconstruction and are achieved by leveraging the TPC to measure deposited energy per unit length along the particle trajectory, with mm resolution. We describe the non-uniform calorimetric reconstruction performance in the detector, showing dependence on the angle of the particle trajectory. Such non-uniform reconstruction directly affects the performance of the particle identification algorithms which infer particle type from calorimetric measurements. This work presents a new particle identification method which accounts for and effectively addresses such non-uniformity. The newly developed method shows improved performance compared to previous algorithms, illustrated by a 94% proton selection efficiency and a 10% muon mis-identification rate, with a fairly loose selection of tracks performed on beam data. The performance is further demonstrated by identifying exclusive final states in $ν_μ CC$ interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS, and DUNE.

physics.ins-det↗

arXiv2021

Wire-Cell 3D Pattern Recognition Techniques for Neutrino Event Reconstruction in Large LArTPCs: Algorithm Description and Quantitative Evaluation with MicroBooNE Simulation

Wire-Cell is a 3D event reconstruction package for liquid argon time projection chambers. Through geometry, time, and drifted charge from multiple readout wire planes, 3D space points with associated charge are reconstructed prior to the pattern recognition stage. Pattern recognition techniques, including track trajectory and $dQ/dx$ (ionization charge per unit length) fitting, 3D neutrino vertex fitting, track and shower separation, particle-level clustering, and particle identification are then applied on these 3D space points as well as the original 2D projection measurements. A deep neural network is developed to enhance the reconstruction of the neutrino interaction vertex. Compared to traditional algorithms, the deep neural network boosts the vertex efficiency by a relative 30\% for charged-current $ν_e$ interactions. This pattern recognition achieves 80-90\% reconstruction efficiencies for primary leptons, after a 65.8\% (72.9\%) vertex efficiency for charged-current $ν_e$ ($ν_μ$) interactions. Based on the resulting reconstructed particles and their kinematics, we also achieve 15-20\% energy reconstruction resolutions for charged-current neutrino interactions.

physics.ins-det↗

arXiv2021

Neutrino Event Selection in the MicroBooNE Liquid Argon Time Projection Chamber using Wire-Cell 3-D Imaging, Clustering, and Charge-Light Matching

An accurate and efficient event reconstruction is required to realize the full scientific capability of liquid argon time projection chambers (LArTPCs). The current and future neutrino experiments that rely on massive LArTPCs create a need for new ideas and reconstruction approaches. Wire-Cell, proposed in recent years, is a novel tomographic event reconstruction method for LArTPCs. The Wire-Cell 3D imaging approach capitalizes on charge, sparsity, time, and geometry information to reconstruct a topology-agnostic 3D image of the ionization electrons prior to pattern recognition. A second novel method, the many-to-many charge-light matching, then pairs the TPC charge activity to the detected scintillation light signal, thus enabling a powerful rejection of cosmic-ray muons in the MicroBooNE detector. A robust processing of the scintillation light signal and an appropriate clustering of the reconstructed 3D image are fundamental to this technique. In this paper, we describe the principles and algorithms of these techniques and their successful application in the MicroBooNE experiment. A quantitative evaluation of the performance of these techniques is presented. Using these techniques, a 95% efficient pre-selection of neutrino charged-current events is achieved with a 30-fold reduction of non-beam-coincident cosmic-ray muons, and about 80\% of the selected neutrino charged-current events are reconstructed with at least 70% completeness and 80% purity.

physics.ins-det↗

arXiv2021

Search for a Higgs portal scalar decaying to electron-positron pairs in the MicroBooNE detector

We present a search for the decays of a neutral scalar boson produced by kaons decaying at rest, in the context of the Higgs portal model, using the MicroBooNE detector. We analyze data triggered in time with the Fermilab NuMI neutrino beam spill, with an exposure of $1.93\times10^{20}$ protons on target. We look for monoenergetic scalars that come from the direction of the NuMI hadron absorber, at a distance of 100 m from the detector, and decay to electron-positron pairs. We observe one candidate event, with a Standard Model background prediction of $1.9\pm0.8$. We set an upper limit on the scalar-Higgs mixing angle of $θ<(3.3-4.6)\times10^{-4}$ at the 95% confidence level for scalar boson masses in the range $(100-200)$ MeV$/c^2$. We exclude at the 95% confidence level the remaining model parameters required to explain the central value of a possible excess of $K^0_L\rightarrowπ^0ν\barν$ decays reported by the KOTO collaboration. We also provide a model-independent limit on a new boson $X$ produced in $K\rightarrowπX$ decays and decaying to $e^+e^-$.

hep-ex↗

arXiv2021

High-performance Generic Neutrino Detection in a LArTPC near the Earth's Surface with the MicroBooNE Detector

Large Liquid Argon Time Projection Chambers (LArTPCs) are being increasingly adopted in neutrino oscillation experiments because of their superb imaging capabilities through the combination of both tracking and calorimetry in a fully active volume. Active LArTPC neutrino detectors at or near the Earth's surface, such as the MicroBooNE experiment, present a unique analysis challenge because of the large flux of cosmic-ray muons and the slow drift of ionization electrons. We present a novel Wire-Cell-based high-performance generic neutrino-detection technique implemented in MicroBooNE. The cosmic-ray background is reduced by a factor of 1.4$\times10^{5}$ resulting in a 9.7\% cosmic contamination in the selected neutrino candidate events, for visible energies greater than 200~MeV, while the neutrino signal efficiency is retained at 88.4\% for $ν_μ$ charged-current interactions in the fiducial volume in the same energy region. This significantly improved performance compared to existing reconstruction algorithms, marks a major milestone toward reaching the scientific goals of LArTPC neutrino oscillation experiments operating near the Earth's surface.

hep-ex↗

arXiv2021

Measurement of the Longitudinal Diffusion of Ionization Electrons in the MicroBooNE Detector

Accurate knowledge of electron transport properties is vital to understanding the information provided by liquid argon time projection chambers (LArTPCs). Ionization electron drift-lifetime, local electric field distortions caused by positive ion accumulation, and electron diffusion can all significantly impact the measured signal waveforms. This paper presents a measurement of the effective longitudinal electron diffusion coefficient, $D_L$, in MicroBooNE at the nominal electric field strength of 273.9 V/cm. Historically, this measurement has been made in LArTPC prototype detectors. This represents the first measurement in a large-scale (85 tonne active volume) LArTPC operating in a neutrino beam. This is the largest dataset ever used for this measurement. Using a sample of $\sim$70,000 through-going cosmic ray muon tracks tagged with MicroBooNE's cosmic ray tagger system, we measure $D_L = 3.74^{+0.28}_{-0.29}$ cm$^2$/s.

physics.ins-det↗

arXiv2021

Semantic Segmentation with a Sparse Convolutional Neural Network for Event Reconstruction in MicroBooNE

We present the performance of a semantic segmentation network, SparseSSNet, that provides pixel-level classification of MicroBooNE data. The MicroBooNE experiment employs a liquid argon time projection chamber for the study of neutrino properties and interactions. SparseSSNet is a submanifold sparse convolutional neural network, which provides the initial machine learning based algorithm utilized in one of MicroBooNE's $ν_e$-appearance oscillation analyses. The network is trained to categorize pixels into five classes, which are re-classified into two classes more relevant to the current analysis. The output of SparseSSNet is a key input in further analysis steps. This technique, used for the first time in liquid argon time projection chambers data and is an improvement compared to a previously used convolutional neural network, both in accuracy and computing resource utilization. The accuracy achieved on the test sample is $\geq 99\%$. For full neutrino interaction simulations, the time for processing one image is $\approx$ 0.5 sec, the memory usage is at 1 GB level, which allows utilization of most typical CPU worker machine.

physics.ins-det↗

arXiv2021

A Convolutional Neural Network for Multiple Particle Identification in the MicroBooNE Liquid Argon Time Projection Chamber

We present the multiple particle identification (MPID) network, a convolutional neural network (CNN) for multiple object classification, developed by MicroBooNE. MPID provides the probabilities of $e^-$, $γ$, $μ^-$, $π^\pm$, and protons in a single liquid argon time projection chamber (LArTPC) readout plane. The network extends the single particle identification network previously developed by MicroBooNE. MPID takes as input an image either cropped around a reconstructed interaction vertex or containing only activity connected to a reconstructed vertex, therefore relieving the tool from inefficiencies in vertex finding and particle clustering. The network serves as an important component in MicroBooNE's deep learning based $ν_e$ search analysis. In this paper, we present the network's design, training, and performance on simulation and data from the MicroBooNE detector.

hep-ex↗

arXiv2021

The Continuous Readout Stream of the MicroBooNE Liquid Argon Time Projection Chamber for Detection of Supernova Burst Neutrinos

The MicroBooNE continuous readout stream is a parallel readout of the MicroBooNE liquid argon time projection chamber (LArTPC) which enables detection of non-beam events such as those from a supernova neutrino burst. The low energies of the supernova neutrinos and the intense cosmic-ray background flux due to the near-surface detector location makes triggering on these events very challenging. Instead, MicroBooNE relies on a delayed trigger generated by SNEWS (the Supernova Early Warning System) for detecting supernova neutrinos. The continuous readout of the LArTPC generates large data volumes, and requires the use of real-time compression algorithms (zero suppression and Huffman compression) implemented in an FPGA (field-programmable gate array) in the readout electronics. We present the results of the optimization of the data reduction algorithms, and their operational performance. To demonstrate the capability of the continuous stream to detect low-energy electrons, a sample of Michel electrons from stopping cosmic-ray muons is reconstructed and compared to a similar sample from the lossless triggered readout stream.

physics.ins-det↗

arXiv2021

Measurement of the Flux-Averaged Inclusive Charged-Current Electron Neutrino and Antineutrino Cross Section on Argon using the NuMI Beam and the MicroBooNE Detector

We present a measurement of the combined $ν_e$ + $\barν_e$ flux-averaged charged-current inclusive cross section on argon using data from the MicroBooNE liquid argon time projection chamber (LArTPC) at Fermilab. Using the off-axis flux from the NuMI beam, MicroBooNE has reconstructed 214 candidate $ν_e$ + $\barν_e$ interactions with an estimated exposure of 2.4$\times10^{20}$ protons on target. Given the estimated purity of 38.6\%, this implies the observation of 80 $ν_e$ + $\barν_e$ events in argon, the largest such sample to date. The analysis includes the first demonstration of a fully automated application of a dE/dx-based particle discrimination technique of electron and photon induced showers in a LArTPC neutrino detector. We measure the $ν_e + \barν_e$ flux-averaged charged-current total cross section to be ${6.84\pm\!1.51~\textrm{(stat.)}\pm\!2.33~\textrm{(sys.)}\!\times\!10^{-39}~\textrm{cm}^{2}/~\textrm{nucleon}}$, for neutrino energies above 250 MeV and an average neutrino flux energy of 905 MeV when this threshold is applied. The measurement is sensitive to neutrino events where the final state electron momentum is above 48 MeV/c, includes the entire angular phase space of the electron, and is in agreement with the theoretical predictions from \texttt{GENIE} and \texttt{NuWro}. This measurement is also the first demonstration of electron neutrino reconstruction in a surface LArTPC in the presence of cosmic ray backgrounds, which will be a crucial task for surface experiments like those that comprise the Short-Baseline Neutrino (SBN) Program at Fermilab.

hep-ex↗

arXiv2020

Measurement of Space Charge Effects in the MicroBooNE LArTPC Using Cosmic Muons

Large liquid argon time projection chambers (LArTPCs), especially those operating near the surface, are susceptible to space charge effects. In the context of LArTPCs, the space charge effect is the build-up of slow-moving positive ions in the detector primarily due to ionization from cosmic rays, leading to a distortion of the electric field within the detector. This effect leads to a displacement in the reconstructed position of signal ionization electrons in LArTPC detectors ("spatial distortions"), as well as to variations in the amount of electron-ion recombination experienced by ionization throughout the volume of the TPC. We present techniques that can be used to measure and correct for space charge effects in large LArTPCs by making use of cosmic muons, including the use of track pairs to unambiguously pin down spatial distortions in three dimensions. The performance of these calibration techniques are studied using both Monte Carlo simulation and MicroBooNE data, utilizing a UV laser system as a means to estimate the systematic bias associated with the calibration methodology.

physics.ins-det↗

arXiv2020

Measurement of Differential Cross Sections for $ν_μ$-Ar Charged-Current Interactions with Protons and no Pions in the Final State with the MicroBooNE Detector

We present an analysis of MicroBooNE data with a signature of one muon, no pions, and at least one proton above a momentum threshold of 300 MeV/c (CC0$π$Np). This is the first differential cross section measurement of this topology in neutrino-argon interactions. We achieve a significantly lower proton momentum threshold than previous carbon and scintillator-based experiments. Using data collected from a total of approximately $1.6 \times 10^{20}$ protons-on-target, we measure the muon neutrino cross section for the CC0$π$Np interaction channel in argon at MicroBooNE in the Booster Neutrino Beam which has a mean energy of around 800 MeV. We present the results from a data sample with estimated efficiency of 29\% and purity of 76\% as differential cross sections in five reconstructed variables: the muon momentum and polar angle, the leading proton momentum and polar angle, and the muon-proton opening angle. We include smearing matrices that can be used to "forward-fold" theoretical predictions for comparison with these data. We compare the measured differential cross sections to a number of recent theory predictions demonstrating largely good agreement with this first-ever data set on argon.

hep-ex↗

arXiv2019

Demonstration of nonstoquastic Hamiltonian in coupled superconducting flux qubits

Quantum annealing (QA) is a heuristic algorithm for finding low-energy configurations of a system, with applications in optimization, machine learning, and quantum simulation. Up to now, all implementations of QA have been limited to qubits coupled via a single degree of freedom. This gives rise to a stoquastic Hamiltonian that has no sign problem in quantum Monte Carlo (QMC) simulations. In this paper, we report implementation and measurements of two superconducting flux qubits coupled via two canonically conjugate degrees of freedom (charge and flux) to achieve a nonstoquastic Hamiltonian. Such coupling can enhance performance of QA processors, extend the range of quantum simulations. We perform microwave spectroscopy to extract circuit parameters and show that the charge coupling manifests itself as a YY interaction in the computational basis. We observe destructive interference in quantum coherent oscillations between the computational basis states of the two-qubit system. Finally, we show that the extracted Hamiltonian is nonstoquastic over a wide range of parameters.

quant-ph↗