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DUNE requires reconstruction of neutrino energies to measure oscillation parameters. We study the calorimetric method on QE events and use electron data to constrain the reconstruction. In order to study resonant events later, we compare electron and Neutrino scattering in that regime
The Short Baseline Neutrino (SBN) program consists of three liquid argon time projection chamber (LArTPC) experiments: SBND, MicroBooNE and ICARUS, with 110 m, 470 m and 600 m baselines respectively. The detectors are located in the Booster Neutrino Beam (BNB) at Fermilab which has a peak energy around 0.7 GeV and contains predominantly muon neutrinos. The baseline and energy range of the SBN program is conducive to measuring neutrino oscillation parameters under various sterile neutrino hypotheses. Sterile neutrinos have been proposed as a possible solution to the numerous short baseline anomalies. The proposed particles must be sterile in nature such that they do not interact via the weak force, however they may undergo oscillations with the active neutrino flavours. Their existence may consequently be confirmed through measurements of the appearance and disappearance of the active flavours. The analyses presented in this thesis aimed to calculate and understand the sensitivity of the SBN program to measuring the ?µ disappearance parameters under the (3+1) sterile neutrino oscillation hypothesis. The sensitivity of SBN to measuring the ?µ disappearance sterile oscillation parameters, sin2 2?µµ, ?m2 41, was calculated through semi-exclusive joint fits of the ?µ CC 0p and ?µ CC Other reconstructed neutrino energy spectra. The first iteration used truth-level Monte Carlo (MC) events, and determined that the 5s SBN sensitivity is comparable to the 90% MINOS/MINOS+ confidence level and supersedes the 90% MiniBooNE confidence level across entire phase space. Semi-exclusive joint fits of the aforementioned sample spectra were performed between the MC and multiple mock data sets in SBND. This analysis assessed the accuracy with which the near detector can disentangle systematic from physics effects in the oscillation analysis. The result was a 5.49% discrepancy between the ICARUS Monte Carlo and mock data event rates, when the systematic constraints from the near detector fit were extrapolated to the far detector. The second iteration of the SBN sensitivity analysis involved the application of an event selection procedure developed in SBND, following the full reconstruction chain. ?µ CC 0p events were selected from sample of neutrinos with 84.5% efficiency and 84.3% purity. The sterile neutrino sensitivity was determined once more at the near detector with these samples, and was shown to be consistent with the truth-level studies.
Electronic health record (EHR) systems are critical to modern healthcare delivery, yet the dynamic workflows that govern electronic order processing remain underexplored. Inefficiencies in these digital pathways can cause delays in care, repetitive workloads, and even patient harm. This study presents a discrete-event simulation framework used to reconstruct and evaluate EHR-based order workflows in a large integrated healthcare system. Using real-world data extracted from the Veterans Health Administration’s Corporate Data Warehouse, the authors mapped order events to standardized state transitions and modeled their progression across different facilities of varying complexity levels. After being calibrated with empirical distributions of transition times and validated against observed time-in-system metrics, the simulation demonstrates close alignment with historical performance. Scenario analyses reveal that resource capacity constraints significantly amplify the impact of electronic order surges, which are reflected in the disproportionate growth in backlogs and processing delays. Adjustments in transition probabilities further increased recirculation and extended workflow paths. Network-based analysis identified Reserved, InProgress, and Completed as structurally critical states that function as hubs within the process network but the transitions in-between also act as major bottlenecks. These results showcased the effectiveness of simulation-based approaches in monitoring EHR order processing performance and evaluating consequences of workflow changes on healthcare network resources planning. The proposed simulation framework provides a scalable data-driven tool to support operational decision-making and improve the efficiency of electronic order management in complex healthcare environments.
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.
We present a novel method to perform gamma-ray spectroscopy suitable for extreme pileup situations, wherein traditional pulse-height spectroscopy is infeasible or impractical. One example of such application is spectral characterization of intense laser-based radiation sources that employ laser wakefield acceleration, in which a large number of photons can be produced in a well-collimated beam on a picosecond or shorter timescale. The method relies on the angularly-resolved calorimetric measurement of Compton scattering. The probability for a photon to undergo Compton scattering into a given solid angle is a function of its energy and is described by the Klein–Nishina formula. By first Compton scattering the incident beam and then measuring the total energies deposited in multiple detectors placed at various scattering angles, the incident beam energy spectrum can be reconstructed without resolving the individual events in detectors. Here, we compare the performance of an maximum likelihood expectation maximization algorithm with that of an artificial neural network to measure the energy spectrum of a beam of monoenergetic gamma rays from 137Cs decay. We demonstrate that the method can be used to reconstruct the characteristic inverse Compton scattering spectra.
A search for long-lived heavy neutrinos (N) in the decays of B mesons produced in proton-proton collisions at $ \sqrt{s} $ = 13 TeV is presented. The data sample corresponds to an integrated luminosity of 41.6 fb$^{−1}$ collected in 2018 by the CMS experiment at the CERN LHC, using a dedicated data stream that enhances the number of recorded events containing B mesons. The search probes heavy neutrinos with masses in the range 1 < m$_{N}$ < 3 GeV and decay lengths in the range 10$^{−2}$ < cτ$_{N}$ < 10$^{4}$ mm, where τ$_{N}$ is the N proper mean lifetime. Signal events are defined by the signature B → ℓ$_{B}$NX; N → ℓ$^{±}$π$^{∓}$, where the leptons ℓ$_{B}$ and ℓ can be either a muon or an electron, provided that at least one of them is a muon. The hadronic recoil system, X, is treated inclusively and is not reconstructed. No significant excess of events over the standard model background is observed in any of the ℓ$^{±}$π$^{∓}$ invariant mass distributions. Limits at 95% confidence level on the sum of the squares of the mixing amplitudes between heavy and light neutrinos, |V$_{N}$|$^{2}$, and on cτ$_{N}$ are obtained in different mixing scenarios for both Majorana and Dirac-like N particles. The most stringent upper limit |V$_{N}$|$^{2}$ < 2.0 × 10$^{−5}$ is obtained at m$_{N}$ = 1.95 GeV for the Majorana case where N mixes exclusively with muon neutrinos. The limits on |V$_{N}$|$^{2}$ for masses 1 < m$_{N}$ < 1.7 GeV are the most stringent from a collider experiment to date.[graphic not available: see fulltext]
We present a flexible and scalable approach to address the challenges of charged particle track reconstruction in real-time event filters (Level-1 triggers) in collider physics experiments. The method described here is based on a full-mesh architecture for data distribution and relies on the Associative Memory approach to implement a pattern recognition algorithm that quickly identifies and organizes hits associated to trajectories of particles originating from particle collisions. We describe a successful implementation of a demonstration system composed of several innovative hardware and algorithmic elements. The implementation of a full-size system relies on the assumption that an Associative Memory device with the sufficient pattern density becomes available in the future, either through a dedicated ASIC or a modern FPGA. We demonstrate excellent performance in terms of track reconstruction efficiency, purity, momentum resolution, and processing time measured with data from a simulated LHC-like tracking detector.
This thesis covers work performed for the Accelerator Neutrino Neutron Interaction Experiment (ANNIE) between 2015 and 2020. ANNIE is a beamline neutrino experiment located at the Fermi National Accelerator Laboratory in Chicago. Its primary physics goals are the measurement of neutrino interaction cross-sections on oxygen, and a measurement of the multiplicity of final state neutrons from these interactions, both as functions of final state kinematics. In order to achieve these goals ANNIE will be pioneering the use of Large Area Picosecond Photodetectors and the use of gadolinium doping to enhance neutron visibility in a water Cherenkov detector. Over the time period of this thesis the ANNIE detector was constructed, an initial 'Phase I' background run was completed, the detector was decommissioned and then substantially upgraded in preparation for the main 'Phase II' physics run. At the time of writing ANNIE is being re-commissioned, with Phase II data taking anticipated to begin in 2021. During this time I spent 21/2 years on-site contributing to almost all aspects of hardware work, while performing software development for the simulation and analysis frameworks. As my first software task I developed Monte Carlo simulations of the detector response, based on the WCSim framework. While thismore » framework provided a starting point for the tank simulation significant modifications were required to implement the complete ANNIE detector system. This included a rewrite of the geometry, along with modifications to the photosensor definitions, hit collections, digitization, triggering, input and output interfaces, etc. To take advantage of improved modelling of neutrons in Geant4.10 the physics lists were also reimplemented in the new version format. As part of this work I determined performance metrics based on the output files, calculating kinematic acceptance, detector efficiency and expected event rates. My contributions on reconstruction focused primarily on the MRD, for which I implemented two track reconstruction algorithms, specialised for high and low energy muons. The high energy algorithm achieves >90% efficiency for tracks with at least 8 hits, and is robust against dead paddles and unrelated hits. The low energy algorithm performs a search in combination with tank information to provide sensitivity down to a single MRD hit. Early data handling work for the Phase I background run included writing the code for handling TDC hits and performing studies on neutron detection without the requirement of multi-hit coincidence. As the collaboration moved to a new framework for the Phase II analysis I performed a substantial amount of work to develop the codebase, implementing tools to perform tasks such as file IO, data parsing, waveform processing, event building, timestamp alignment, time clustering, hit residual calculation, event visualisation etc. I helped develop the python API for integrating multi-language tools, and ported the framework into a Singularity container to provide a self-contained environment that…« less
Here, we demonstrate three-dimensional track reconstruction of electrons in a low pressure (50 Torr) optical TPC consisting of two glass GEMs with an ITO strip readout in CF 4 and CF 4 /Ar mixtures. The reconstructed tracks show a variety of event topologies, including short tracks from photoelectrons induced by 55 Fe 5.9 keV X-rays and long tracks from gamma ray interactions and beta decays. Algorithms for event identification and track ridge detection are discussed as well as multiple methods for integrating information from the camera image and ITO waveforms with the goal of full 3D reconstruction of the track.
Motivated by the recent XENON 1T results, we explore various new physics models that can be discovered through searches for electron recoils in O(keV)-threshold direct-detection experiments. First, we consider the absorption of axion-like particles, dark photons, and scalars, either as dark matter relics or being produced directly in the Sun. In the latter case, we find that keV mass bosons produced in the Sun provide an adequate fit to the data but are excluded by stellar cooling constraints. We address this tension by introducing a novel Chameleon-like axion model, which can explain the excess while evading the stellar bounds. We find that absorption of bosonic dark matter provides a viable explanation for the excess only if the dark matter is a dark photon or an axion. In the latter case, photophobic axion couplings are necessary to avoid X-ray constraints. Second, we analyze models of dark matter-electron scattering to determine which models might explain the excess. Standard scattering of dark matter with electrons is generically in conflict with data from lower-threshold experiments. Momentum-dependent interactions with a heavy mediator can fit the data with dark matter mass heavier than a GeV but are generically in tension with collider constraints. Next, we consider dark matter consisting of two (or more) states that have a small mass splitting. The exothermic (down)scattering of the heavier state to the lighter state can fit the data for keV mass splittings. Finally, we consider a subcomponent of dark matter that is accelerated by scattering off cosmic rays, finding that dark matter interacting though an O(100 keV)-mass mediator can fit the data. The cross sections required in this scenario are, however, typically challenged by complementary probes of the light mediator. Throughout our study, we implement an unbinned Monte Carlo analysis and use an improved energy reconstruction of the XENON 1T events.
The structure of the proton-unbound nucleus 21 Al has been studied via proton transfer from a 9 Be target to a 20 Mg beam at E/A = 103 MeV. Three resonant states in 21 Al are identified by the invariant-mass reconstruction of 18 Ne + 3p events. The decay-energy spectra for the two subsystems of 21 Al , i.e. 18 Ne+ 1 p and 18 Ne+ 2 p , indicate that the observed resonant state with the lowest energy has decay branches consisting of three sequential steps of one-proton decay. Based on the ab initio and the distorted-wave Born approximation (DWBA) calculations, this resonant state at Ε ⁎ = 6.09(11) MeV likely has a spin-parity of (1/2 + - 7/2 + ). Meanwhile, the possibility that the observed resonant peak represents an admixture of several states cannot be ruled out. The good isospin-symmetry of the low-lying states with d 5/2 , d 3/2 configurations in the 21 Al- 21 O pair and the ab initio calculations indicate weak configuration mixing between the s - and d -orbital components. The systematics of experimental energy differences between the 5/2 + ground state and lowest-lying 3/2 + excited state for isotopes (isotones) of Z(N) = 13 suggest a likely semimagic nature of 21 Al.
Abstract Based on the 13.7 yr Fermi-LAT data, Yeung, Bamba, and Sano (2023, PASJ, 75, 384) claimed detection of two γ-ray sources (namely Src-NE and Src-NW) associated with the supernova remnant (SNR) G298.6−0.0, and interpreted it as an old GeV SNR interacting with molecular clouds (MCs). In this follow-up study, we refine the flux measurements below 2 GeV with Fermi-LAT event types of better angular reconstruction. Then, we report our γ-ray spectral fittings and cosmic-ray phenomenology in a hadronic scenario, considering both the shell and MC regions of SNR G298.6−0.0. We confirm that the γ-ray spectra of both Src-NE and Src-NW exhibit spectral breaks, at $1.50_{-0.50}^{+0.60}$ and $0.68_{-0.11}^{+0.32}\:$GeV, respectively. Src-NW has a harder broad-band photon index than Src-NE, suggesting an appreciable difference between the physical separations of their respective emission sites from SNR G298.6−0.0. The cosmic-ray spectrum responsible for Src-NE starts with a minimum energy $E_\mathrm{CR,min}=1.38_{-0.16}^{+0.47}\:$GeV, and has a proton index $\Gamma _\mathrm{CR}=2.57_{-0.21}^{+0.18}$ below the exponential cutoff energy $E_\mathrm{CR,max}=240_{-150}^{+240}\:$GeV. Accordingly, we argue that Src-NE is dominated by the SNR shell, while only a minor portion of lower-energy emission is contributed by the MCs interacting with the SNR. The cosmic-ray population for Src-NW starts at a higher energy such that the ECR, min ratio of Src-NW to Src-NE is ≳2. The high ECR, min, as well as the high cosmic-ray energy density required (∼26 eV cm−3), supports the interpretation that Src-NW is predominantly the γ-ray emission from the farther MCs being bombarded by protons that had earlier escaped from SNR G298.6−0.0. By comparing the high-energy features of G298.6−0.0 with those of analogical SNRs, especially SNR W 28 and SNR W 44, we further constrain the age of SNR G298.6−0.0 to be 10–30 kyr, under the assumption of a purely hadronic scenario.
18 Mg was observed, for the first time, by the invariant-mass reconstruction of 14 O + 4p events. The ground-state decay energy and width are E T = 4.865(34) MeV and Γ = 115(100) keV, respectively. The observed momentum correlations between the five particles are consistent with two sequential steps of prompt 2p decay passing through the ground state of 16 Ne. The invariant-mass spectrum also provides evidence for an excited state at an excitation energy of 1.84(14) MeV, which is likely the first excited 2 + state. As this energy exceeds that for the 2 + state in 20 Mg, this observation provides an argument for the demise of the N = 8 shell closure in nuclei far from stability. Furthermore, in open systems this classical argument for shell strength is compromised by Thomas-Ehrman shifts.
We measure the tau-to-light-lepton ratio of inclusive B -meson branching fractions R ( X τ / ℓ ) ≡ B ( B → X τ ν ) / B ( B → X ℓ ν ) , where ℓ indicates an electron or muon, and thereby test the universality of charged-current weak interactions. We select events that have one fully reconstructed B meson and a charged lepton candidate from 189 fb − 1 of electron-positron collision data collected with the Belle II detector. We find R ( X τ / ℓ ) = 0.228 ± 0.016 ( stat ) ± 0.036 ( syst ) , in agreement with standard-model expectations. This is the first direct measurement of R ( X τ / ℓ ) . Published by the American Physical Society 2024
The Locally Competitive Algorithm (LCA) uses local competition between non-spiking leaky integrator neurons to infer sparse representations, allowing for potentially real-time execution on massively parallel neuromorphic architectures such as Intel's Loihi processor. Here, we focus on the problem of inferring sparse representations from streaming video using dictionaries of spatiotemporal features optimized in an unsupervised manner for sparse reconstruction. Non-spiking LCA has previously been used to achieve unsupervised learning of spatiotemporal dictionaries composed of convolutional kernels from raw, unlabeled video. We demonstrate how unsupervised dictionary learning with spiking LCA (\hbox{S-LCA}) can be efficiently implemented using accumulator neurons, which combine a conventional leaky-integrate-and-fire (\hbox{LIF}) spike generator with an additional state variable that is used to minimize the difference between the integrated input and the spiking output. We demonstrate dictionary learning across a wide range of dynamical regimes, from graded to intermittent spiking, for inferring sparse representations of both static images drawn from the CIFAR database as well as video frames captured from a DVS camera. On a classification task that requires identification of the suite from a deck of cards being rapidly flipped through as viewed by a DVS camera, we find essentially no degradation in performance as the LCA model used to infer sparse spatiotemporal representations migrates from graded to spiking. We conclude that accumulator neurons are likely to provide a powerful enabling component of future neuromorphic hardware for implementing online unsupervised learning of spatiotemporal dictionaries optimized for sparse reconstruction of streaming video from event based DVS cameras.
The System for on-Axis Neutrino Detection (SAND) is one of the three components of the DUNE Near Detector Complex. Its main goals are monitoring of the beam, precision measurements of neutrino cross-sections and short-baseline neutrino physics. The SAND detector is composed of a 0.6 T superconducting magnet, an electromagnetic calorimeter, a liquid argon active target (GRAIN) and a modular low-density target system. The GRAIN subdetector has been designed to allow the reconstruction of neutrino interactions in Argon using only the scintillation light, by implementing an innovative imaging system. In this poster, the performances of SAND are presented focusing on its capability to reconstruct νμ+Ar→μ−+p events using the information provided by the calorimeter, the tracking system and GRAIN.
MicroBooNE, a liquid argon time projection chamber at Fermilab, is investigating the MiniBooNE anomaly, which consists of an excess of low-energy electromagnetic showers in a neutrino beam. Recent results from MicroBooNE have ruled out a 3+1 sterile neutrino explanation of the anomaly, leaving the single photon-like explanation as the most likely possibility. In this poster, we describe results of a new expanded search for the neutral current Delta radiative decay topology, a rare type of event which is by far the largest expected source of neutrino-induced single photons. Using two different reconstruction paradigms simultaneously, we study in detail events both with and without visible hadronic activity; either category of event could explain the MiniBooNE anomaly, but the two could have very different implications for underlying physics. We find that events with visible protons are excluded as an explanation of the MiniBooNE anomaly, but events without visible protons remain a possible explanation requiring further study.
Paleoclimate data provide important information about the character of natural climate variability. However, records with sufficient length and resolution to resolve high-frequency (decadal-scale) variability across the Holocene are scarce. We present a 10,800-year reconstruction of spring and summer temperature at three-year resolution based on biochemical varves from Lake $\dot{Z}abi$$\acute{n}skie$, Poland. The reconstruction is based on Ca/Ti ratio, which are significantly correlated with instrumental spring and summer temperature spanning 240 years. Major climate events of the Holocene period are represented in the reconstruction, including the Holocene Thermal Maximum, 8.2 ka Event, Medieval Climate Anomaly, and Little Ice Age. A low-frequency 8,000-year decreasing trend in warm-season temperatures is driven by declining summer insolation. Temperature variability is highest during the early Holocene, likely related to warmer and drier conditions. The rate of warming during the past 90 years is extremely unusual, if not unprecedented for the Holocene, based on our reconstruction.