Search NASA⌕ Search

SEARCH · Search NASA

Results for “Detector simulation”

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 1,513 records · Page 84

Pulsed-Neutron Experiments at the Inherently Safe Subcritical Assembly

The pulsed neutron technique is a powerful, dynamic method to assay the reactivity of a multiplying system. This work presents the novel application of the pulsed neutron technique to the Inherently Safe Subcritical Assembly, an experimental configuration accepted by the International Criticality Safety Benchmark Evaluation Project Handbook. The experiments were replicated with COG11.3, a continuous-energy Monte Carlo code. The pulsed neutron data were analyzed using the Sjöstrand and Gozani area-ratio methods and by extracting the prompt neutron decay constant. Subsequent static k-eigenvalue and 𝛼-eigenvalue simulations were also performed for the same configurations. Neutron detector dead-time effects from the experiments were corrected using the Backwards Extrapolation Method and shown to have a negligible impact on the estimated reactivities. The results highlight that capturing time-dependent effects like delayed neutron precursor buildup are essential to accurately reproduce experimental results. They also highlight the importance of shielding the detectors from generator source neutrons in deeply subcritical configurations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Lessons Learned from Radiative Transfer Simulations of the Venus Atmosphere

The Venus atmosphere is extremely complex, and because of this the spectrum of Earths sister planet is likewise intricate and a challenge to model accurately. However, accurate modeling of Venus spectrum opens up multiple opportunities to better understand the planet next door, and even for understanding Venus-like planets beyond our solar system. Near-infrared (1-2.5 um, NIR) spectral windows observable on the Venus nigthside present the opportunity to probe beneath the Venusian cloud deck and measure thermal emission from the surface and lower atmosphere remotely from Earth or from orbit. These nigthside spectral windows were discovered by Allen and Crawford (1984) and have since been used measure trace gas abundances in the Venus lower atmosphere (less than 45 km), map surface emissivity varisions, and measure properties of the lower cloud deck. These windows sample radiation from below the cloud base at roughly 45 km, and pressures in this region range from roughly Earthlike (approx. 1 bar) up to 90 bars at the surface. Temperatures in this region are high: they range from about 400 K at the base of the cloud deck up to about 740 K at the surface. This high temperature and pressure presents several challenges to modelers attempting radiative transfer simulations of this region of the atmosphere, which we will review. Venus is also important to spectrally model to predict the remote observables of Venus-like exoplanets in anticipation of data from future observatories. Venus-like planets are likely one of the most common types of terrestrial planets and so simulations of them are valuable for planning observatory and detector properties of future telescopes being designed, as well as predicting the types of observations required to characterize them.

Arney, G.↗

HPC s Pivot to Data

Computer centers such as NERSC and OLCF have traditionally focused on delivering computational capability that enables breakthrough innovation in a wide range of science domains. Accessing that computational power has required services and tools to move the data from input and output to computation and storage. A ''pivot to data'' is occurring in HPC. Data transfer tools and services that were previously peripheral are becoming integral to scientific workflows. Emerging requirements from high-bandwidth detectors, high-throughput screening techniques, highly concur- rent simulations, increased focus on uncertainty quantification, and an emerging open-data policy posture toward published research are among the data-drivers shaping the networks, file systems, databases, and overall compute and data environment. In this paper we explain the pivot to data in HPC through user requirements and the changing resources provided by HPC with particular focus on data movement. For WAN data transfers we present the results of a study of network performance between centers.

97 MATHEMATICS AND COMPUTING↗

Neutron structure with (un)polarized deuterons and forward spectator tagging at the Electron-Ion Collider

An Electron-Ion Collider (EIC) would enable novel measurements of neutron structure through deep-inelastic electron-deuteron scattering with coincidence tagging of the forward-moving spectator proton. The free neutron structure functions can be obtained by extrapolating the measured recoil momentum distributions to the on-shell point. Such measurements provide essential information for the flavor separation of the nucleon parton densities, the nucleon spin decomposition, and precision studies of QCD evolution in the flavor-singlet and nonsinglet sectors. The EMC effect in light nuclei can be elucidated by measuring the recoil momentum dependence of the nuclear modification. A Jefferson Lab LDRD project has supported a study of neutron structure measurements with spectator tagging at an EIC, with Monte Carlo simulation of the physical processes and the accelerator and detector requirements. We present results of a model-independent extraction of the free neutron structure function $F_2^n$, as well as the spin structure function $g_1^n$, through on-shell extrapolation in the spectator momentum.

Park, Kijun↗

Energy reconstruction in a highly granularity semi-digital hadronic calorimeter

A semi-digital hadronic calorimeter using Glass Resistive Plate Chambers (GRPCs) is one of the calorimeters candidates proposed for particle physics experiments at the future electrons collider. It is a high granular calorimeter which is required for application of the particle flow algorithm in order to improve the jet energy resolution as one of the goals of this experiments. We discussed the energy reconstruction, based on digital and semi-Digital methods, to study the effect on the improvement of the single particle energy resolution and the linearity of the detector response. This study was performed with the GEANT4 simulation. Results on the energy resolution and linearity, for negative pions over an energy range from 1 to 100 GeV are presented and compared with different energy reconstruction methods including Artificial Neural Networks. (authors)

43 PARTICLE ACCELERATORS↗

Searches for New Physics With Muon Conversion at Fermilab and Triboson Production at the LHC

We report on several efforts to search for physics beyond the standard model of particle physics at broad energy scales. The Mu2e experiment at Fermilab will search for charged lepton flavor violation via the muon to electron conversion process, which is suppressed in the Standard Model. Mu2e will be operated at a low energy, yet can probe New Physics at very high mass scales (O(1e3 - 1e4 ) TeV). At high energies, the CMS experiment at the CERN LHC continues to deliver an impressive suite of Standard Model measurements and limits on a variety of New Physics signatures. Mu2e is under construction and slated to collect its first physics data in the coming years. This thesis describes work done during the construction phase of Mu2e and focuses on two critical areas: magnetic field modeling and statistical analysis. We describe a novel method for field modeling which we validate using a simulated dataset representing the expected magnetic field in the Detector Solenoid. This method blends a standard least-squares fitting technique that utilizes physically motivated analytical model functions with a novel physics informed network that is constructed to obey Maxwell’s equations. We show the technique can model the field with an accuracy of 10−7 despite the presence of injected noise in the pseudo-measurements at the 10−5 level. We then present preliminary results of the calibration of 3D Hall probes at the sub-10−4 level. These probes will be used to directly measure the Mu2e Detector Solenoid magnetic field on a sparse grid; these measurements serve as the input to the field model fitting. Finally, we describe the first implementation of both an unbinned shape analysis and a Bayesian interpretation applied to Mu2e pseudo-data. Up to 20% tighter limits can be set by the shape analysis compared to a standard cut & count analysis. The AlCap experiment collected data at PSI in 2015 to measure several important quantities related to nuclear muon capture on an aluminum target, which is a significant background process for Mu2e. The neutron emission from muon capture can introduce background hits in the Mu2e detectors and can increase radiation damage in various elements of the apparatus. We present measurements of the neutron group fluence and mean neutron multiplicity for muon capture on aluminum nuclei. Finally, we discuss an analysis of triboson production at CMS using an Effective Field Theory framework. Standard Model triboson production, which was first observed at CMS in 2020, has a relatively small cross section and provides direct access to both anomalous triple gauge couplings and quartic gauge couplings. These couplings, interpreted in the Standard Model Effective Field Theory, are studied in the present work. We target the boosted regime where the background rate is low and yields are enhanced when dimension-6 and dimension-8 Wilson coefficients are non-zero. We do not observe an excess in the data and therefore set bounds on the Wilson coefficients. For dimension-6 coefficients the tightest observed (expected) bounds are set on cW /Λ2 where Λ is the mass scale of new physics; the bounds are [−0.13, 0.12] TeV−2 ([−0.12, 0.12] TeV−2 ) at 95% CL. The tightest bounds in dimension-8 are set on fT,0 / Λ4 ; the observed (expected) bounds at 95% CL are [−0.63, 0.69] TeV−4 ([−0.54, 0.62] TeV−4 ). Additional results are presented which include scenarios where multiple Wilson coefficients are non-zero, the application of signal model clipping to address unitarity violation in Effective Field Theories, and a novel template fit developed for easier reinterpretation of our results.

Kampa, Cole Erik [Northwestern U. (main)] (ORCID:0↗

Neutron detector response modeling in NOvA

Neutrons can present a significant challenge for neutrino experiments in which energy reconstruction is critical. With the ability to escape detection completely and with a weak correlation between their kinetic energy and any eventual energy deposition, it is difficult to fully account for neutrons produced in neutrino interactions. This in turn leads to significant model dependence when evaluating neutron-related systematic uncertainties. The NOvA experiment is a long-baseline neutrino oscillation experiment with a high-statistics sample of antineutrino data collected by its near detector. We report an excess relative to data of simulated neutron candidates with low energy depositions when using standard Geant4 physics lists. The simulation excess is traced to an overabundance of secondary photons produced from interactions of neutrons with kinetic energy greater than \SI{20}{\mega\eV}. Improved agreement with data is obtained by applying the data-driven neutron-on-carbon \menate model for neutrons between \SI{20}{\mega\eV} and ${\sim}$\SI{100}{\mega\eV}. With \menate, the residual oversimulation is more uniform across the calorimetric neutron energy spectrum, suggesting possible overproduction of primary neutrons by the GENIE neutrino interaction generator. These results motivate the adoption of \menate-supplemented Geant4 simulation as the nominal simulation in the production of future \nova simulation.

Abubakar, S.↗

Xenon bubble chambers for direct dark matter detection

The search for dark matter is one of today's most exciting fields. As bigger detectors are being built to increase their sensitivity, background reduction is an ever more challenging issue. To this end, a new type of dark matter detector is proposed, a xenon bubble chamber, which would combine the strengths of liquid xenon TPCs, namely event by event energy resolution, with those of a bubble chamber, namely insensitivity to electronic recoils. In addition, it would be the first time ever that a dark matter detector is active on all three detection channels, ionization and scintillation characteristic of xenon detectors, and heat through bubble formation in superheated fluids. Preliminary simulations show that, depending on threshold, a discrimination of 99.99% to 99.9999+% can be achieved, which is on par or better than many current experiments. Furthermore, a prototype is being built at the University at Albany, SUNY. The prototype is currently undergoing seals, thermal, and compression testing.

Dark Matter detectors↗

Deeply learning deep inelastic scattering kinematics

We study the use of deep learning techniques to reconstruct the kinematics of the neutral current deep inelastic scattering (DIS) process in electron–proton collisions. In particular, we use simulated data from the ZEUS experiment at the HERA accelerator facility, and train deep neural networks to reconstruct the kinematic variables Q 2 and x. Our approach is based on the information used in the classical construction methods, the measurements of the scattered lepton, and the hadronic final state in the detector, but is enhanced through correlations and patterns revealed with the simulated data sets. We show that, with the appropriate selection of a training set, the neural networks sufficiently surpass all classical reconstruction methods on most of the kinematic range considered. Rapid access to large samples of simulated data and the ability of neural networks to effectively extract information from large data sets, both suggest that deep learning techniques to reconstruct DIS kinematics can serve as a rigorous method to combine and outperform the classical reconstruction methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Reconstruction of Six-Dimensional Phase Space

A phase space is a mathematical representation of all possible physical states of a system. Particle beams at Fermilab exist within a six-dimensional (6D) phase space defined by three positional components, (x, y, z) and three momentum components, (px, py, pz). To reconstruct this space implies taking measurement data from detectors and mapping out particle behavior using computational methods. The beam detectors, however, are only able to detect spatial distribution among the events of the beam, therefore being limited to positional data. Also, due to the vast number of events in a particle beam, it is extremely difficult to analyze and differentiate every single one’s behavior. However, with Machine Learning (ML), which can distinguish between patterns and map out particle behavior more efficiently. We first used the particle beam software, G4beamline, to simulate a 10,000-event muon beam, adjusting parameters such as initial momentum magnitude (p¬0) and virtual detector position. Using ten virtual detectors, we analyzed p0 values such that minimum 9,990 events were analyzed by every detector. We then input the data from these beam simulations to a C++ program, that randomly selects 100 events, and creates a 2D histogram based on spatial distribution, detector position, and event intensity. This process is repeated 100 times to create 100 histograms per p0 value. These images were then input to a modified ResNet18 Convolutional Neural Network (CNN) for training, and to predict p0 from some unseen set of histograms. The model was accurate when trained on momentum increments of 5 MeV/c and provided with denser training samples around highly variable test values. These results displayed machine learning being able to accurately predict p0 from being trained on different particle behaviors.

Shirlee, Jermain [Fermilab]↗

An X-ray Intensity Operations Monitor (AXIOM) (Final LDRD Project Report)

The Saturn accelerator has historically lacked the capability to measure time-resolved spectra for its 3-ring bremsstrahlung x-ray source. This project aimed to create a spectrometer called AXIOM to provide this capability. The project had three major development pillars: hardware, simulation, and unfold code. The hardware consists of a ring of 24 detectors around an existing x-ray pinhole camera. The diagnostic was fielded on two shots at Saturn and over 100 shots at the TriMeV accelerator at Idaho Accelerator Center. A new Saturn x-ray environment simulation was created using measured data to validate. This simulation allows for timeresolved spectra computation to compare the experimental results. The AXIOM-Unfold code is a new parametric unfold code using modern global optimizers and uncertainty quantification. The code was written in Python, uses Gitlab version control and issue tracking, and has been developed with long term code support and maintenance in mind.

43 PARTICLE ACCELERATORS↗

Searching for dark clumps with gravitational-wave detectors

Dark compact objects (“clumps”) transiting the Solar System exert accelerations on the test masses (TM) in a gravitational-wave (GW) detector. We reexamine the detectability of these clump transits in a variety of current and future GW detectors, operating over a broad range of frequencies. TM accelerations induced by clump transits through the inner Solar System have frequency content around f ~ μ Hz . Some of us [Fedderke et al., Phys. Rev. D 105, 103018 (2022)] recently proposed a GW detection concept with μ Hz sensitivity, based on asteroid-to-asteroid ranging. From the detailed sensitivity projection for this concept, we find both analytically and in simulation that purely gravitational clump–matter interactions would yield one detectable transit every ~ 20 yrs , if clumps with mass m cl ~ 10 14 kg saturate the dark-matter (DM) density. Other (proposed) GW detectors using local TMs and operating in higher frequency bands are sensitive to smaller clump masses and have smaller rates of discoverable signals. We also consider the case of clumps endowed with an additional attractive long-range clump–matter fifth force significantly stronger than gravity (but evading known fifth-force constraints). For the μ Hz detector concept, we use simulations to show that, for example, a clump–matter fifth-force ~ 10 3 times stronger than gravity with a range of ~ AU would boost the rate of detectable transits to a few per year for clumps in the mass range 10 11 kg ≲ m cl ≲ 10 14 kg , even if they are a ~ 1 % subcomponent of the DM. The ability of μ Hz GW detectors to probe asteroid-mass-scale dark objects that may otherwise be undetectable bolsters the science case for their development.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Modeling and Analysis of Hybrid Pixel Detector Deficiencies for Scientific Applications

Semiconductor hybrid pixel detectors often consist of a pixellated sensor layer bump bonded to a matching pixelated readout integrated circuit (ROIC). The sensor can range from high resistivity Si to III-V materials, whereas a Si CMOS process is typically used to manufacture the ROIC. Independent, device physics and electronic design automation (EDA) tools are used to determine sensor characteristics and verify functional performance of ROICs respectively with significantly different solvers. Some physics solvers provide the capability of transferring data to the EDA tool. However, single pixel transient simulations are either not feasible due to convergence difficulties or are prohibitively long. A simplified sensor model, which includes a current pulse in parallel with detector equivalent capacitor, is often used; even then, spice type top-level (entire array) simulations range from days to weeks. In order to analyze detector deficiencies for a particular scientific application, accurately defined transient behavioral models of all the functional blocks are required. Furthermore, various simulations, such as transient, noise, Monte Carlo, inter-pixel effects, etc. of the entire array need to be performed within a reasonable time frame without trading off accuracy. The sensor and the analog front-end can be modeling using a real number modeling language, as complex mathematical functions or detailed data can be saved to text files, for further top-level digital simulations. Parasitically aware digital timing is extracted in a standard delay format (sdf) from the pixel digital back-end layout as well as the periphery of the ROIC. For any given input, detector level worst-case and best-case simulations are performed using a Verilog simulation environment to determine the output. Each top-level transient simulation takes no more than 10-15 minutes. The impact of changing key parameters such as sensor Poissonian shot noise, analog front-end bandwidth, jitter due to clock distribution etc. can be accurately analyzed to determine ROIC architectural viability and bottlenecks. Hence the impact of the detector parameters on the scientific application can be studied.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The Upgrade of Horizon-T Detector

The Horizon-T experiment is located at the elevation of 3346 m above sea level near the city of Almaty, Republic of Kazakhstan. A thorough comparison of the spatial and temporal characteristics of charged components of Extended Air Showers (EAS) with delayed particles has been conducted between the simulated EAS using CORSIKA simulation package and the selection from the experimental data set of events with two pulses recorded by a detector at ~600 m distance from axis [1]. This comparison has shown that events with delayed particles cannot be described within existing simulation models. The significance of these results prompted the upgrade of the Horizon-T experiment. New detector points have been added at the ~600m to enhance data at that distance. Fast glass-based detector has been added to the scintillator-based detector at center point for accurate measurements of the pulse widths.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

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↗

Oscillation-independent probes of nonstandard neutrino interactions from supernovae

Extreme astrophysical environments provide unique laboratories for testing fundamental neutrino interactions. We present the first oscillation-independent astrophysical probe of nonstandard neutrino interactions (NSI), using coincident neutral-current signals across diverse detectors to break degeneracies that have long limited sensitivity reach. Using self-consistent NSI supernova simulations and flavor-independent neutral-current scattering we show that anticorrelated signatures between JUNO liquid scintillator and dark matter detectors such as DARWIN/XLZD, ARGO, or RES-NOVA enable clear discrimination between NSI and flavor-conversion effects. For a Galactic supernova at Betelgeuse distance our approach enables an independent probe of neutrino-quark NSI couplings in parameter space that can reach and extend beyond current terrestrial limits. This multidetector approach enables breaking degeneracies in terrestrial searches and is broadly applicable to a wide range of upcoming experiments, establishing a new principle for testing fundamental interactions with astrophysical data.

Beatty, Angela R. [San Francisco State U.; LBL, Be↗