Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “PARTICLE IDENTIFICATION”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Improving the NOvA 3-Flavour Neutrino Oscillation Analysis

NOvA is a long-baseline neutrino experiment studying neutrino oscillations, a quantum mechanical interference phenomena where the observed neutrino flavour differs from that measured earlier, stemming from neutrino mass and flavour states mixing. NOvA consists of two functionally identical tracking calorimeter detectors deployed in the Fermilab NuMI beam. Both detectors are placed 14.6 mrad off the beam axis to achieve a narrow energy peak at 1.8 GeV at an oscillation maximum. The NOvA 3-flavour oscillation analysis measures the neutrino oscillation parameters sin2θ23 and ∆m232 as well as sets limit to δCP , the octant of θ23 and the sign of ∆m32. The event selection for 3-flavour neutrino oscillation analysis ensures the maximum quantity of signal is made available and a minimal amount of background is present. The current disappearance analysis selection has an efficiency of 80% for selecting νμ CC events, and with some improvements additional events could be recovered into the analysis to improve the sensitivity to the aforementioned oscillation parameters. In an effort to recover the currently rejected signal event to the analysis, these events were trained in a classification neural network. The aim of the network was to divide the data into signal (νμ CC events) and background (NC and νe CC events). The highest performing network gave an additional figure of merit gain of 2.34 increasing the sensitivity by 4.3% in effective POT equal to 33 days of additional data taking. This was compared to changing the current particle identification event selection cuts, the best result out of the tested cut combinations gave an additional FOM of 3.36 equal to 3.7% increase in effective POT equivalent to 28 days of data taking.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Construction of a Cosmic Ray Telescope for the hpDIRC Radiators at the Electron Ion Collider

Nuclear physics pertains to the understanding of the structure and dynamics of the nuclei of atoms, accounting for almost all of the visible matter in the universe. The future Electron-Ion Collider (EIC) will play a crucial role in discovering new laws of Nuclear physics. A pivotal aspect of the EIC is exceptional particle identification (PID). Identifying charged hadrons in their final state can be done with special types of Cherenkov Detectors. One type of detector utilizes the Detection of Internally Reflected Cherenkov radiation (DIRC) phenomena. Able to provide precise PID separation up to relatively high momenta, DIRC radiators, made of synthetic fused silica, produce Cherenkov radiation when hit by high energy electromagnetically charged particles. In this thesis we present details of the construction of a cosmic ray telescope (CRT) to utilize high energy muons from cosmic rays to test DIRC radiators. These types of radiators will be used for the high-performance DIRC (hpDIRC) to be used in the ePIC detector in the future EIC. We go into detail on the DIRC process and the individual pieces of hardware required to make the CRT. Lots of labor was used for certain parts of the CRT, specifically the construction of a dark box for the DIRC radiators. The CRT construction and implementation of all of its components are planned to be completed before 2025.

Shankman, Nathan↗
DOE OSTI2017

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identifi-cation or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.

Acciarri, R↗
DOE OSTI2024

STOPGAP—A time-of-flight extension for the Belle II TOP barrel PID system

The Belle II barrel region is instrumented with the Time of Propagation (TOP) particle identification system. Due to its mechanical design, the individual TOP modules do not overlap, leaving a gap of around 2 cm between them in the azimuthal direction. This leads to a 6%–9% drop in acceptance, depending on the track’s momentum. We propose a solution to remedy these gaps by instrumenting them with fast silicon detectors to directly measure the time-of-flight of traversing particles. We present here a simulation study discussing the performance requirements and the possible sensor technologies, and we demonstrate that such a project could be realized with novel, fast monolithic CMOS sensors, or alternatively AC-LGAD sensors, both of which are expected to reach MIP timing resolutions of down to 50 ps or better.

Hartbrich, Oskar↗
DOE OSTI2020

Self-absorption and Phonon Pulse Shape Discrimination in Scintillating Bolometers

In this work, we show that self-absorption of photons in scintillating bolometers can differentiate phonon pulse shapes between α (or nuclear recoil) and β/γ signals. This enables phonon pulse shape discrimination for particle identification. We establish a detector signal model that includes self-absorption and compare the simulated phonon pulse shapes with previously reported experimental results. The model predicts increase in pulse shape difference at higher self-absorption. Based on this result, we propose a new design of scintillating bolometers using 4π light reflectors for maximized self-absorption and only a single phonon readout, instead of light detectors that are typically employed for particle discrimination in scintillating bolometers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Gluonic Excitations in Mesons

This award provided support for the Massachusetts Institute of Technology (MIT) to work on the GlueX experiment at Jefferson Lab (JLab). The MIT-GlueX group played a leading role in the development of an upgraded particle-identification system and in employing data-driven methods for calibrating GlueX data. In addition, our group focused on advancing the usage of machine learning algorithms and other state-of-the-art data science tools within the domain of nuclear physics research.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Investigation of fast timing capabilities of silicon sensors for the CMS high granularity calorimeter at HL-LHC

The High Granularity Calorimeter (HGCAL) is the technology choice of the CMS collaboration for the endcap calorimetry upgrade planned to cope with the harsh radiation and unprecedented in-time event pileup projected at the High Luminosity-LHC era. In this context, profiting from fast-timing information with a resolution of a few tens of picoseconds embedded in the calorimeter would represent a unique capability for resolving information from individual collisions at the HL-LHC. This will enhance the reconstruction and physics capabilities of the CMS detector in terms of pileup mitigation and particle identification. The HGCAL is realized as a sampling calorimeter that uses silicon sensors as its active elements. Prototype sensors were tested with high-energy electron beams at the CERN SPS, and at the FNAL FTBF test beam facilities. We present the motivation for this studies including the concept and use of fast-timing in the HGCAL, and the measured intrinsic timing capabilities of silicon sensors for electromagnetic showers and minimum-ionizing particles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Machine learning-based jet and event classification at the Electron-Ion Collider with applications to hadron structure and spin physics

We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at relatively low EIC energies, focusing on (i) identifying the flavor of the jet and (ii) identifying the underlying hard process of the event. We propose applications of our machine learning-based jet identification in the key research areas at the future EIC and current Relativistic Heavy Ion Collider program, including enhancing constraints on (transverse momentum dependent) parton distribution functions, improving experimental access to transverse spin asymmetries, studying photon structure, and quantifying the modification of hadrons and jets in the cold nuclear matter environment in electron-nucleus collisions. We establish first benchmarks and contrast the estimated performance of flavor tagging at the EIC with that at the Large Hadron Collider. We perform studies relevant to aspects of detector design including particle identification, charge information, and minimum transverse momentum capabilities. Additionally, we study the impact of using full event information instead of using only information associated with the identified jet. These methods can be deployed either on suitably accurate Monte Carlo event generators, or, for several applications, directly on experimental data. We provide an outlook for ultimately connecting these machine learning-based methods with first principles calculations in quantum chromodynamics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Low Energy Neutron-induced Charged-particle (Z) (LENZ) instrument development with a focus on pulse shape discrimination for low-energy charged particles

To study neutron-induced charged-particle reactions with high precision, the Low Energy Neutron-induced Charged-particle (Z) instrument (LENZ) was developed at the Los Alamos Neutron Science Center. For the interest of measuring (n,p) and (n, α) reactions simultaneously, Pulse Shape Discrimination methods were investigated to identify different charged particles in the energy range of 3 - 20 MeV and improve signal-to-background ratios using Double-sided Silicon Strip Detectors and waveform digitizers. The risetime and pulse shape properties of detected charged particles were characterized for various silicon detector’s thickness with different orientations. During the post-processing of waveforms, we implemented different digital filters for effective particle identifications and improved energy- and timing- resolutions. We validated the optimized digital filters and pulse shape analyses, via measurements with 228 Th and 229 Th calibration sources, proton-induced reactions on a 7 LiF target, and neutron-induced reactions on CH 2 , Ta 2 O 5 , 58 Ni, and 6 LiF/ 59 Ni targets at the time-of-flight facility, LANSCE. In conclusion, the summary of effective thresholds and Figure of Merits on separating different charged particles is reported.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

DEATH-STAR: Silicon and photovoltaic fission fragment detector arrays for light-ion induced fission correlation studies

Here, the Direct Excitation Angular Tracking pHotovoltaic-Silicon Telescope ARray (DEATH-STAR) combines a series of 12 silicon detectors in a ΔE–E configuration for charged particle identification with a large-area array of 56 photovoltaic (solar) cells for detection of fission fragments. The combination of many scattering angles and fission fragment detectors allows for an angular-resolved tool to study reaction cross sections using the surrogate method, anisotropic fission distributions, and angular momentum transfers through stripping, transfer, inelastic scattering, and other direct nuclear reactions. The unique photovoltaic detectors efficiently detect fission fragments while being insensitive to light ions and have a timing resolution of 15.63±0.37 ns. Alpha particles are detected with a resolution of 35.5 keV 1σ at 7.9 MeV. Measured fission fragment angular distributions are also presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Modelling detector-specific reconstruction uncertainties in LAr-TPC

The Short-Baseline Neutrino (SBN) program features three Liquid Argon Time Projection Chamber (LAr-TPC) detectors positioned along the Booster Neutrino Beam (BNB) axis: the Short Baseline Neutrino Near Detector, MicroBooNE, and the ICARUS T600. As the largest operational LAr-TPC, ICARUS T600 serves as the far detector, located 600 m from the BNB target. While its primary goal is to record neutrino events, it also detects other ionizing events, including cosmic rays. This work focuses on analyzing and modeling detector-specific reconstruction uncertainties in LAr-TPC. These inefficiencies, identified during the Pattern Recognition phase handled by the PANDORA algorithm, impact subsequent Particle Fits and Offline Analysis. Specifically, inaccuracies in track reconstruction can lead to significant physical consequences, such as erroneous particle energy estimates and poor Particle Identification (PID), reducing the efficiency of neutrino event characterization. A key issue addressed is split tracks, caused by missing hits or incomplete track stitching by PANDORA. The aim of this internship is to characterize, model, and quantify the impact of split tracks on track reconstruction.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

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. Therefore, 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.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Parity Violating Deep Inelastic Electron Scattering from the Deuteron at 6 GeV

An experiment that measured the parity violating (PV) asymmetry A d in e- 2 H deep inelastic scattering (DIS) at Q 2 ~ 1.10 and 1.90 (GeV/c) 2 and x B ~ 0.3 was completed in experimental Hall A at the Thomas Jefferson National Accelerator Facility. The asymmetry can be used to extract the neutral weak coupling combination (2C 2u -C 2d ), providing a factor of five to six improvement over the current world data. To achieve this precision, asymmetries of the 10 -4 level needed to be measured at event rates up to 500 kHz with high electron detection efficiency and high pion background rejection capability. A specialized scaler-based counting data acquisition system (DAQ) with hardware-based particle identification was successfully implemented. The statistical quality of the asymmetry measurement agreed with the Gaussian distribution to over five orders of magnitudes and the experimental goal of 3-4% statistical uncertainty was achieved. The design and performance of the new DAQ system is presented with the preliminary asymmetry results given in the end.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Measurement Of The Total Cross-Section Of Muon Neutrino Charged-Current Coherent Pion Production in NOvA Near Detector

Charged Current (CC) coherent neutrino-nucleus pion production is characterized by small momentum transferred to the nucleus, which is left in its ground state. Despite the relatively large uncertainties on the production cross-section, coherent production of mesons by neutrinos represents an important process, as it can shed light on the structure of the weak current and can also constitute a potential source of background for modern neutrino oscillation experiments and searches for Beyond Standard Model (BSM) physics. This Ph.D. thesis presents a new measurement of CC coherent pion production in the NOvA near detector at the Fermi National Accelerator Laboratory (Fermilab). The analysis is based on the use of both particle identification and kinematic selection criteria based on Convolutional Neural Networks (CNN) to achieve a selection purity of 60%. Given the energy range 1-5 GeV accessible with the available NOvA exposure in the NuMI beam, the results will also be relevant for f uture neutrino experiments like the Deep Underground Neutrino Experiment (DUNE).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

LArIAT In 10 Minutes [Slides]

The LArIAT (Liquid Argon In A Test Beam) experiment at Fermilab's Test Beam Facility exposes a Liquid Argon Time Projection Chamber (LArTPC) to a charged particle test beam in order to calibrate and characterize LArTPCs response. This is a perfect environment in that particle species and momentum can be preselected while event reconstruction tools, particle identification algorithms, and new detector technologies can be tested. The LArIAT exploration of LArTPC capabilities will provide critical input to existing liquid argon neutrino experiments and will help to improve future precision neutrino oscillation measurements such as the Deep Underground Neutrino Experiment (DUNE). The work presented here will give an overview of the experiment and highlight recent results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Precipitation hydrometeor type relative to the mesoscale airflow in mature oceanic deep convection of the Madden-Julian Oscillation

We present that composite analysis of mature near-equatorial oceanic mesoscale convective systems (MCSs) during the active stage of the Madden-Julian Oscillation (MJO) shows where different hydrometeor types occur relative to convective updraft and stratiform midlevel inflow layers. The National Center for Atmospheric Research (NCAR) S-PolKa radar observed these MCSs during the Dynamics of the Madden-Julian Oscillation/Atmospheric Radiation Measurement-MJO Investigation Experiment (DYNAMO/AMIE). NCAR's particle identification algorithm (PID) is applied to S-PolKa's polarimetric data to identify the dominant hydrometeor type in each radar sample volume. Combining S-PolKa's Doppler velocity data with the PID demonstrates that hydrometeors have a systematic relationship to the airflow within mature MCSs. In the convective region, moderate rain occurs within the updraft core; the heaviest rain occurs just downwind of the core; wet aggregates occur immediately below the melting layer; narrow zones containing graupel/rimed aggregates occur just downstream of the updraft core at midlevels; dry aggregates dominate above the melting level; and smaller ice particles occur along the edges of the convective zone. In the stratiform region, rain intensity decreases toward the anvil; melting aggregates occur in horizontally extensive but vertically thin regions at the melting layer; intermittent pockets of graupel/rimed aggregates occur atop the melting layer; dry aggregates and small ice particles occur sequentially above the melting level; and horizontally oriented ice crystals occur between -10°C and -20°C in turbulent air above the descending midlevel inflow, suggesting enhanced depositional growth of dendrites. Finally, the organization of hydrometeors within the midlevel inflow layer is insensitive to the presence or absence of a leading convective line.

58 GEOSCIENCES↗
DOE OSTI2026

Event Reconstruction for Water-based Liquid Scintillator Detectors

Water Cherenkov and liquid scintillator detectors represent two complementary approaches in neutrino physics. Water Cherenkov detectors provide particle track direction and particle identification (PID) through Cherenkov ring topology, while liquid scintillator detectors offer higher light yield and lower energy thresholds. Water-based liquid scintillator (WbLS) is designed to combine the advantages of both technologies. However, the simultaneous detection of Cherenkov and scintillation light by photosensors introduces significant challenges for event reconstruction. This poster presents event reconstruction studies for WbLS detectors. A likelihood-based reconstruction framework, fiTQun, has been successfully used in Super-Kamiokande to reconstruct water Cherenkov events in cylindrical detectors. We extend and improve this framework to demonstrate event reconstruction in WbLS detectors, enabling the concurrent reconstruction of particle energy, PID, vertex, and direction. The results demonstrate competitive performance in energy resolution, PID separation, and vertex and direction reconstruction, highlighting the strong potential of WbLS for next-generation neutrino experiments.

Xie, Zhenxiong [Minnesota U.] (ORCID:0009000301442↗
DOE OSTI2022

Status of the DUNE experiment

The Deep Underground Neutrino Experiment aims at an unprecedentedly precise neutrino CPviolation phase measurement with a broad-band muon neutrino and antineutrino beam, a 1,300 km baseline, an order of 10skt fiducial mass detector with high particle identification efficiency and low external background.Additionally, the orders of systematic uncertainty should be constrained to 2% for the signal and5% for the background. This uncertainty constraint requires an unprecedented level of robustnessand redundancy in the near detector measurement. In this presentation, the near detector designand the far detector prototyping status are shown. The long-baseline sensitivity and differentphysics potentials are described.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗