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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.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Electromagnetic physics models for parallel computing architectures

The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part of the GeantV project. Finally, the results of preliminary performance evaluation and physics validation are presented as well.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Application and performance of an ML-EM algorithm in NEXT

The goal of the NEXT experiment is the observation of neutrinoless double beta decay in (136)Xe using a gaseous xenon TPC with electroluminescent amplification and specialized photodetector arrays for calorimetry and tracking. The NEXT Collaboration is exploring a number of reconstruction algorithms to exploit the full potential of the detector. This paper describes one of them: the Maximum Likelihood Expectation Maximization (ML-EM) method, a generic iterative algorithm to find maximum-likelihood estimates of parameters that has been applied to solve many different types of complex inverse problems. In particular, we discuss a bi-dimensional version of the method in which the photosensor signals integrated over time are used to reconstruct a transverse projection of the event. First results show that, when applied to detector simulation data, the algorithm achieves nearly optimal energy resolution (better than 0.5% FWHM at the Q value of (136)Xe) for events distributed over the full active volume of the TPC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Augmented signal processing in Liquid Argon Time Projection Chambers with a deep neural network

The Liquid Argon Time Projection Chamber (LArTPC) is an advanced neutrino detector technology widely used in recent and upcoming accelerator neutrino experiments. It features a low energy threshold and high spatial resolution that allow for comprehensive reconstruction of event topologies. In current-generation LArTPCs, the recorded data consist of digitized waveforms on wires produced by induced signal on wires of drifting ionization electrons, which can also be viewed as two-dimensional (2D) (time versus wire) projection images of charged-particle trajectories. For such an imaging detector, one critical step is the signal processing that reconstructs the original charge projections from the recorded 2D images. For the first time, we introduce a deep neural network in LArTPC signal processing to improve the signal region of interest detection. By combining domain knowledge (e.g., matching information from multiple wire planes) and deep learning, this method shows significant improvements over traditional methods. This work details the method, software tools, and performance evaluated with realistic detector simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Pile-up mitigation using attention

Abstract Particle production from secondary proton-proton collisions, commonly referred to as pile-up, impair the sensitivity of both new physics searches and precision measurements at large hadron collider (LHC) experiments. We propose a novel algorithm, Puma , for modeling pile-up with the help of deep neural networks based on sparse transformers. These attention mechanisms were developed for natural language processing but have become popular in other applications. In a realistic detector simulation, our method outperforms classical benchmark algorithms for pile-up mitigation in key observables. It provides a perspective for mitigating the effects of pile-up in the high luminosity era of the LHC, where up to 200 proton-proton collisions are expected to occur simultaneously.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Proposal for a dedicated search for millicharged and fractionally charged particles at LANL

In this paper, we propose an experiment, LANSCE-mQ, aiming to detect fractionally charged and millicharged particles (mCPs) using an 800 MeV proton beam fixed target at the Los Alamos Neutron Science Center (LANSCE) facility at Los Alamos National Laboratory. This search can shed new light on numerous fundamental questions, including charge quantization, the predictions of string theories and grand unification theories, the gauge symmetry of the Standard Model, dark sector models, and the tests of cosmic reheating. We propose to install two-layer scintillation detectors made of plastic (such as EJ-200) or CeBr 3 to search for mCPs. Dedicated geant4 detector simulations and in situ measurements have been conducted to obtain a preliminary determination of the background rate. The dominant backgrounds are beam-induced neutrons and coincident dark current signals from the photomultiplier tubes, while beam-induced high-energy photons ( γ ’s) and cosmic muons are subdominant. We determined that LANSCE-mQ, the dedicated mCP experiment, has the leading mCP sensitivity for mass between ∼ 1 and 300 MeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Method to simultaneously facilitate all jet physics tasks

Machine learning has become an essential tool in jet physics. Due to their complex, high-dimensional nature, jets can be explored holistically by neural networks in ways that are not possible manually. However, innovations in all areas of jet physics are proceeding in parallel. We show that specially constructed machine learning models trained for a specific jet classification task can improve the accuracy, precision, or speed of all other jet physics tasks. This is demonstrated by training on a particular multiclass generation and classification task and then using the learned representation for different generation and classification tasks, for datasets with a different (full) detector simulation, for jets from a different collision system ($pp$ versus $ep$), for generative models, for likelihood ratio estimation, and for anomaly detection. We consider our omnilearn approach thus as a jet-physics foundation model. It is made publicly available for use in any area where state-of-the-art precision is required for analyses involving jets and their substructure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Luminosity determination in pp collisions at $\sqrt{s} = 7$ TeV using the ATLAS detector at the LHC

Measurements of luminosity obtained using the ATLAS detector during early running of the Large Hadron Collider (LHC) at √s = 7 TeV are presented. The luminosity is independently determined using several detectors and multiple algorithms, each having different acceptances, systematic uncertainties and sensitivity to background. The ratios of the luminosities obtained from these methods are monitored as a function of time and of μ, the average number of inelastic interactions per bunch crossing. Residual time- and μ-dependence between the methods is less than 2% for 0 < μ < 2.5. Absolute luminosity calibrations, performed using beam separation scans, have a common systematic uncertainty of ±11%, dominated by the measurement of the LHC beam currents. After calibration, the luminosities obtained from the different methods differ by at most ±2%. The visible cross sections measured using the beam scans are compared to predictions obtained with the PYTHIA and PHOJET event generators and the ATLAS detector simulation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

A measurement of the calorimeter response to single hadrons and determination of the jet energy scale uncertainty using LHC Run-1 pp-collision data with the ATLAS detector

A measurement of the calorimeter response to isolated charged hadrons in the ATLAS detector at the LHC is presented. This measurement is performed with 3.2 nb –1 of proton–proton collision data at √s = 7 TeV from 2010 and 0.1 nb –1 of data at √s = 8 TeV from 2012. A number of aspects of the calorimeter response to isolated hadrons are explored. After accounting for energy deposited by neutral particles, there is a 5% discrepancy in the modelling, using various sets of Geant4 hadronic physics models, of the calorimeter response to isolated charged hadrons in the central calorimeter region. The description of the response to anti-protons at low momenta is found to be improved with respect to previous analyses. The electromagnetic and hadronic calorimeters are also examined separately, and the detector simulation is found to describe the response in the hadronic calorimeter well. The jet energy scale uncertainty and correlations in scale between jets of different momenta and pseudorapidity are derived based on these studies. The uncertainty is 2–5% for jets with transverse momenta above 2 TeV, where this method provides the jet energy scale uncertainty for ATLAS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Foundations of automatic feature extraction at LHC–point clouds and graphs

Abstract Deep learning algorithms will play a key role in the upcoming runs of the Large Hadron Collider (LHC), helping bolster various fronts ranging from fast and accurate detector simulations to physics analysis probing possible deviations from the Standard Model. The game-changing feature of these new algorithms is the ability to extract relevant information from high-dimensional input spaces, often regarded as “replacing the expert” in designing physics-intuitive variables. While this may seem true at first glance, it is far from reality. Existing research shows that physics-inspired feature extractors have many advantages beyond improving the qualitative understanding of the extracted features. In this review, we systematically explore automatic feature extraction from a phenomenological viewpoint and the motivation for physics-inspired architectures. We also discuss how prior knowledge from physics results in the naturalness of the point cloud representation and discuss graph-based applications to LHC phenomenology.

Bhardwaj, Akanksha↗
DOE OSTI2016

Conceptual design studies for a CEPC detector

The physics potential of the Circular Electron Positron Collider (CEPC) can be significantly strengthened by two detectors with complementary designs. A promising detector approach based on the Silicon Detector (SiD) designed for the International Linear Collider (ILC) is presented. Several simplifications of this detector for the lower energies expected at the CEPC are proposed. A number of cost optimizations of this detector are illustrated using full detector simulations. We show that the proposed changes will enable one to reach the physics goals at the CEPC.

CEPC↗
DOE OSTI2012

Oklahoma Center for High Energy Physics (OCHEP)

The DOE EPSCoR implementation grant, with the support from the State of Oklahoma and from the three universities, Oklahoma State University, University of Oklahoma and Langston University, resulted in establishing of the Oklahoma Center for High Energy Physics (OCHEP) in 2004. Currently, OCHEP continues to flourish as a vibrant hub for research in experimental and theoretical particle physics and an educational center in the State of Oklahoma. All goals of the original proposal were successfully accomplished. These include foun- dation of a new experimental particle physics group at OSU, the establishment of a Tier 2 computing facility for the Large Hadron Collider (LHC) and Tevatron data analysis at OU and organization of a vital particle physics research center in Oklahoma based on resources of the three universities. OSU has hired two tenure-track faculty members with initial support from the grant funds. Now both positions are supported through OSU budget. This new HEP Experimental Group at OSU has established itself as a full member of the Fermilab D0 Collaboration and LHC ATLAS Experiment and has secured external funds from the DOE and the NSF. These funds currently support 2 graduate students, 1 postdoctoral fellow, and 1 part-time engineer. The grant initiated creation of a Tier 2 computing facility at OU as part of the Southwest Tier 2 facility, and a permanent Research Scientist was hired at OU to maintain and run the facility. Permanent support for this position has now been provided through the OU university budget. OCHEP represents a successful model of cooperation of several universities, providing the establishment of critical mass of manpower, computing and hardware resources. This led to increasing Oklahoma's impact in all areas of HEP, theory, experiment, and computation. The Center personnel are involved in cutting edge research in experimental, theoretical, and computational aspects of High Energy Physics with the research areas ranging from the search for new phenomena at the Fermilab Tevatron and the CERN Large Hadron Collider to theoretical modeling, computer simulation, detector development and testing, and physics analysis. OCHEP faculty members participating on the D0 collaboration at the Fermilab Tevatron and on the ATLAS collaboration at the CERN LHC have made major impact on the Standard Model (SM) Higgs boson search, top quark studies, B physics studies, and measurements of Quantum Chromodynamics (QCD) phenomena. The OCHEP Grid computing facility consists of a large computer cluster which is playing a major role in data analysis and Monte Carlo productions for both the D0 and ATLAS experiments. Theoretical efforts are devoted to new ideas in Higgs bosons physics, extra dimensions, neutrino masses and oscillations, Grand Unified Theories, supersymmetric models, dark matter, and nonperturbative quantum field theory. Theory members are making major contributions to the understanding of phenomena being explored at the Tevatron and the LHC. They have proposed new models for Higgs bosons, and have suggested new signals for extra dimensions, and for the search of supersymmetric particles. During the seven year period when OCHEP was partially funded through the DOE EPSCoR implementation grant, OCHEP members published over 500 refereed journal articles and made over 200 invited presentations at major conferences. The Center is also involved in education and outreach activities by offering summer research programs for high school teachers and college students, and organizing summer workshops for high school teachers, sometimes coordinating with the Quarknet programs at OSU and OU. The details of the Center can be found in http://ochep.phy.okstate.edu.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2012

Particle Physics at the University of Pittsburgh Summary Report for Proposal Period FY'09-11

Presented is the final summary report for grant DOE-FG02-91ER40646. The HEP group at the University consists of three tasks: B,D and L. Task B supports Pitt's CDF group at the energy frontier which includes Joe Boudreau and Paul Shepard. Work of the group includes Hao Song's thesis on the measurement of the B_c lifetime using exclusive J/psi+pion decays, and an update of the previous B_c semi-leptonic analyses under the supervision of Paul Shepard. Task D supports Pitt's neutrino group at the intensity frontier which includes PIs Dytman, Naples and Paolone. The group also includes postdoctoral research associate Danko, and thesis students Isvan (MINOS), Eberly (Minerva ), Ren (Minerva )and Hansen (T2K). This report summarizes their progress on ongoing experiments which are designed to make significant contributions to a detailed understanding of the neutrino mixing matrix. Task L supports Pitt's ATLAS group at the energy frontier and includes investigators Vladimir Savinov, James Mueller and Joe Boudreau. This group contributed both to hardware (calorimeter electronics, Savinov) and to software (Simulation, Detector Description, and Visualization: Boudreau and Mueller; MC generators: Savinov) and a summary of their progress is presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Improving Fission Products at CARIBU: Near Field Detection (Q3/FY23 Quarterly Progress Report)

We have worked on addressing the referees’ comments and are about to resubmit the article describing the results of our mass (of the isomer and ground state) measurement of 128 Sb to Phys. Rev. Letters. We have also been working with our summer student Asha (Seaborg Institute student from Notre Dame University) on setting her up to rerun all beta detector simulations for 111 Ag. With her successful contribution of the simulation work we expect to have the simulated efficiency results by the end of the summer.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Towards Three-Dimensional Neutron Imaging with Light-field Technology

A broad range of applications in nuclear safeguards and security can benefit from compact, fast neutron imagers with large angular acceptance. However, accurate 3D multi-vertex reconstruction in a monolithic detector remains a significant barrier to realization. Current approaches, such as the centroiding approach and the use of shadow masks, have not yet resulted in a successful demonstration in a light-starved environment. This project explored the use of cutting-edge technology—a light field camera—which inherently preserves both the spatial and directional information of incident light. Such technology can, in principle, resolve multi-vertex events and offer accurate position reconstruction in 3D with relatively simple readout electronics. Since the project's inception in May 2023, we have built an experimental setup to calibrate and characterize a commercial light-field camera (Lytro Illum). We assessed its 3D event reconstruction capability in a relatively low-light intensity environment by analyzing the cross-correlation of a series of 2D images of a characterized tunable light source taken at various distances. A sub-cm resolution, lower than typical neutron interaction separations in a compact scintillator volume, was observed with the LED light source, suggesting the promising capability of its nominal optics design to provide the adequate resolution required for a compact monolithic neutron directional detector. However, using a light-field-based readout for a neutron camera requires incorporating an ultra-low-noise light sensor, which is beyond the scope of this project. We also initiated the development of a 3D light-field-based reconstruction algorithm tailored to sparse scenes, as expected from particle interactions in a scintillator medium. Additionally, we demonstrated the capability of the algorithm to replicate the ground truth. Finally, we began the development of a neutron directional detector simulation to determine the performance criteria for light-field-based reconstruction that allows for good neutron directional reconstruction. This Feasibility Study has led to a successful follow-up project under the DNN R&D innovation portfolio starting May 2024.

42 ENGINEERING↗
DOE OSTI2024

Searching for Strongly Coupled Dark Sectors with Unsupervised and Generative Learning

Recipient of the URA Early Career Award for groundbreaking searches for dark matter arising from strongly coupled dark sectors with the CMS detector, pioneering work in ML-based model-independent anomaly detection for collider and astrophysics experiments, and leadership in the development of new AI/ML techniques to improve event reconstruction and detector simulation in particle physics, as well as novel strategies to accelerate AI inference and throughput with heterogeneous computing using coprocessors as a service.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Region of Interest Filter in DUNE DAQ

The Deep Underground Neutrino Experiment (DUNE) is the next generation neutrino experiment currently under construction. It consists of a broadband neutrino beam at Fermilab, a high precision near detector, and the largest liquid argon time projection chamber far detector ever designed at the Sanford Underground Research Facility (SURF). The Region of Interest (ROI) filter is designed for DUNE’s online Data Acquisition (DAQ) system to address data rate constraints and enable low energy physics in the <10 MeV range. The filter employs zero suppression on the detector signal, and by tuning the readout window and threshold the data rates can be reduced by >90%. Performance of the ROI is analyzed in LArsoft on MARLEY generated low energy MC events propagated through the detector simulation. Notably, the optimized ROI filter enables a lower trigger threshold for readout at ~5-10 MeV, allowing DUNE to explore low-energy physics, specifically focusing on solar boron 8 neutrinos which are relevant in this energy range. This advancement enhances DUNE's scientific capabilities, opening avenues for detailed analyses of previously inaccessible low-energy neutrino interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗