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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Direct reactions for astrophysical p-capture rates with ORRUBA and GODDESS

Understanding the nucleosynthesis and energy generation in quiescent and explosive stellar burning requires a detailed understanding of reaction rates on many unstable nuclides. Such reaction rates are often governed by the properties of low-lying, isolated proton resonances. Though direct measurements of resonance strengths are ultimately desired, and are a focus of rare isotope beam facilities worldwide, such tour-de-force experiments must be guided by indirect techniques, in order to know resonance energies, J π assignments, and estimated widths, to inform targeted measurements. Furthermore, some important low-lying resonances may be too weak for direct measurements with radioactive beams, and indirect techniques provide the only practical constraints. Additionally, there has been growing interest in the astrophysical role of isomeric states, which can influence the reaction flow in nucleosynthetic reaction networks, and hence impact the quantitative interpretation of astronomical observables, such as γ-ray signatures, and elemental and isotopic ratios. Properties of single-proton resonances can be obtained by exploiting the selectivity of direct reactions, such as single-nucleon transfer and charge-exchange reactions. Constraining proton-capture rates via direct reactions has been a focus of the astrophysics program at ORNL for over two decades, spurring the development of the ORRUBA and GODDESS detector systems. Herein, a review of recent developments in instrumentation and radioactive beam delivery (including isomeric beam experiments) is presented, along with some specific examples of astrophysically interesting sd-shell nuclides, which have been a target of recent ORRUBA and GODDESS experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1961

Radiation Observations with Satellite 1958 Alpha Explorer I

On 1 February 1958 at 0348 U.T. earth satellite 1958 Alpha (Explorer I) was launched from Cape Canaveral. This satellite contained a Geiger Muller tube for the measurement of the flux of energetic charged particles, and detectors for determining the micrometeorite flux and satellite temperature (see Figure 1), The high power transmitter and its associated instrumentation operated until partial exhaustion of the transmitter batteries on 12 February 1958. The transmitter reappeared briefly on 24 February, The low power system operated properly until about 0700 U,T, on 16 March, at which time the batteries powering the G.M. tube circuits became exhausted. During the operating time a large amount of data was recorded by a network of seventeen receiving stations. A sampling of early recordings was reduced and analyzed as they arrived from the receiving stations. These data, in conjunction with data from the first few orbits of 1958 Gamma (Explorer III), resulted in the announcement on 1 May 1958 of the region of high intensity radiation surrounding the earth (Van Allen, 1958), The detailed, complete reduction of the 1958 Alpha data has now been completed, This paper is a tabulation of all the data received from this satellite. It consists primarily of two parts. The first part is the master recording log on which are listed all recordings of the satellite signals obtained by the receiving station network. The actual data tabulation is contained in part two.

RADIATION↗
NASA NTRS1997

Results from Two Years of Global Lightning Observation with the Optical Transient Detector

The Optical Transient Detector (OTD) is an instrument designed specifically to detect and locate lightning during either daytime or nighttime. A predecessor of the Lightning Imaging Sensor (LIS), it has been in orbit for over two and half years. During this time global lightning activity has been observed on a quasi continuous basis. During this time an extensive effort has been under way to quantify and verify the OTD performance. OTD data has been compared with both the National Lightning Detection Network (NLDN) and the Lightning Detection and Ranging (LDAR) system at KSC. Results of these intercomparisons will be presented as well as estimates of OTD overall performance parameters. In addition, one year of OTD results will be presented showing the strong influence of the sun on global lightning activity. A month by month collage of global lightning maps will be used to demonstrate both the first order forcing and more subtle influences. Finally, initial results form the Lightning Imaging Sensor, an instrument on the Tropical Rainfall Measuring Mission (TRMM) will be presented.

Christian, H. J.↗
DOE OSTI2022

A Wrapper to Use a Machine-Learning-Based Algorithm for Earthquake Monitoring

Seismology is one of the main sciences used to monitor volcanic activity worldwide. Fast, efficient, and accurate seismicity detectors are crucial to assess the activity level of a volcano in near–real time and to issue timely warnings. Traditional real–time seismic processing software uses phase onset pickers followed by a phase association algorithm to declare an event and estimate its location. The pickers typically do not identify whether the detected phase is a P or S arrival, which can have a negative impact on hypocentral location quality and complicates phase association. We implemented the deep–neural–network–based method PhaseNet to identify in real time P and S seismic waves on data from one– and three–component seismometers. We tuned the Earthworm binder_ew associator module to use the phase identification from PhaseNet to detect and locate the events, which we archive in a SeisComP3 database. We assessed the performance of the algorithm by comparing the results with existing catalogs built to monitor seismic and volcanic activity in Mayotte and the Lesser Antilles region. Our algorithm, which we refer to as PhaseWorm, showed promising results in both contexts and clearly outperformed the previous automatic method implemented in Mayotte. As a result, this innovative real–time processing system is now operational for seismicity monitoring in Mayotte and Martinique.

58 GEOSCIENCES↗
DOE OSTI2020

DUNE DAQ R&D integration in ProtoDUNE Single-Phase at CERN

The DAQ system of ProtoDUNE-SP successfully proved its design principles and met the requirements of the beam run of 2018. The technical design of the DAQ system for the DUNE experiment has major differences compared to the prototype due to different requirements placed on the detector, as well as a radically different location of operation. The single-phase prototype at CERN is a major integration facility for R&D aspects of the DUNE DAQ system. The facility allows for the exploration of additional data processing capabilities and optimization of the FELIX system, which is the chosen TPC readout solution for the DUNE single-phase detectors. One of the fundamental differences from the prototype is that the DUNE DAQ relies on self-triggering. Therefore, real-time processing of the data stream for hit and trigger primitive finding is essential for the requirement of continuous readout. The supernova burst trigger requires a large and fast buffering technique, where 3D XPoint persistent memory solutions are evaluated and integrated. In order to maximize resource utilization of the FELIX hosting servers, the elimination of the 100 Gb network communication stack is desired. This implies the design and development of a single-host application layer, which is a fundamental element of the self-triggering chain. This paper discusses the evaluation and integration of these developments for the DUNE DAQ, in the ProtoDUNE environment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Femtosecond pulse parameter estimation from photoelectron momenta using machine learning

Abstract Deep learning models have provided huge interpretation power for image-like data. Specifically, convolutional neural networks (CNNs) have demonstrated incredible acuity for tasks such as feature extraction or parameter estimation. Here we test CNNs on strong-field ionization photoelectron spectra, training on theoretical data sets to ‘invert’ experimental data. Pulse characterization is used as a ‘testing ground’, specifically we retrieve the laser intensity, where ‘traditional’ measurements typically lead to 20% uncertainty. We report on crucial data augmentation techniques required to successfully train on theoretical data and return consistent results from experiments, including accounting for detector saturation. The same procedure can be repeated to apply CNNs in a range of scenarios for strong-field ionization. Using a predictive uncertainty estimation, reliable laser intensity uncertainties of a few percent can be extracted, which are consistently lower than those given by traditional techniques. Using interpretability methods can reveal parts of the distribution that are most sensitive to laser intensity, which can be directly associated with holographic interferences. The CNNs employed provide an accurate and convenient ways to extract parameters, and represent a novel interpretational tool for strong-field ionization spectra.

Szołdra, Tomasz (ORCID:0000000228970506)↗
DOE OSTI2024

Moment extraction using an unfolding protocol without binning

Deconvolving (“unfolding”) detector distortions is a critical step in the comparison of cross-section measurements with theoretical predictions in particle and nuclear physics. However, most existing approaches require histogram binning while many theoretical predictions are at the level of statistical moments. We develop a new approach to directly unfold distribution moments as a function of another observable without having to first discretize the data. Our moment unfolding technique uses machine learning and is inspired by Boltzmann weight factors and generative adversarial networks (GANs). We demonstrate the performance of this approach using jet substructure measurements in collider physics. With this illustrative example, we find that our moment unfolding protocol is more precise than bin-based approaches and is as or more precise than completely unbinned methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2010

SBIR Technology Applications to Space Communications and Navigation (SCaN)

This slide presentation reviews the mission of the Space Communications and Navigation (SCaN) Office with particular emphasis on opportunities for technology development with SBIR companies. The SCaN office manages NASA's space communications and navigation networks: the Near Earth Network (NEN), the Space Network (SN), and the Deep Space Network (DSN). The SCaN networks nodes are shown on a world wide map and the networks are described. Two types of technologies are described: Pull technology, and Push technologies. A listing of technology themes is presented, with a discussion on Software defined Radios, Optical Communications Technology, and Lunar Lasercom Space Terminal (LLST). Other technologies that are being investigated are some Game Changing Technologies (GCT) i.e., technologies that offer the potential for improving comm. or nav. performance to the point that radical new mission objectives are possible, such as Superconducting Quantum Interference Filters, Silicon Nanowire Optical Detectors, and Auto-Configuring Cognitive Communications

Liebrecht, Phil↗
DOE OSTI2025

Search for Higgs boson decays into a Z boson and a light hadronically decaying resonance in pp collisions at s =13 TeV with the ATLAS detector

A search for decays of the Higgs boson into a Z boson and a light resonance, with a mass of 0.5–3.5 GeV, is performed using the full 140 fb−1 dataset of 13 TeV proton–proton collisions recorded by the ATLAS detector during LHC Run 2. Leptonic decays of the Z boson and hadronic decays of the light resonance are considered. The resonance can be interpreted as a J / ψ or η c meson, an axion-like particle, or a light pseudoscalar predicted in two-Higgs-doublet models. Due to its low mass, this resonance is produced with a high Lorentz boost in the laboratory frame and therefore reconstructed as a single small-radius jet of hadrons. A neural network is used to correct the Monte Carlo simulation of the total expected background using data from sideband regions. Two additional neural networks are used to distinguish signal from background, enhancing the purity of the signal region. A binned profile-likelihood fit is performed on the final-state invariant mass distribution. No significant excess of events relative to the expected background is observed, and upper limits at 95% confidence level are set on the Higgs boson's branching fraction to a Z boson and a light resonance. The exclusion limit is ∼10% for the lower masses, and increases for higher masses. Upper limits on the effective coupling C Z H eff / Λ of an axion-like particle to a Higgs boson and Z boson are also set at 95% confidence level, and range from 0.9 to 2 TeV−1.

Aad, G↗
DOE OSTI2024

Design and assembling status of the Mu2e electromagnetic calorimeter mechanical structures

The muon-to-electron conversion (Mu2e) experiment at Fermilab will search for the Charged Lepton Flavour Violating neutrino-less coherent conversion of a muon into an electron in the field of an aluminum nucleus. The observation of this process would be the unambiguous evidence of physics beyond the Standard Model. The detector has been designed as a state-of-the-art crystal calorimeter and employs 1348 pure Cesium Iodide (CsI) crystals readout by UV-extended silicon photosensors and fast front-end and digitization electronics. A design consisting of two identical annular matrices (named disks ) positioned at the relative distance of 70 cm, downstream the aluminum target along the muon beamline, satisfies the Mu2e physics requirements. The hostile Mu2e operational conditions, in terms of radiation levels (total ionizing dose of 12 krad and a neutron fluence of 5 10^{10} n/cm2 @ 1 MeVeq (Si)/y), magnetic field intensity (1 T) and vacuum level (10−4 Torr) have posed tight constraints on the design of the detector mechanical structures and materials choice. The support structure of the two 674 crystal matrices employs two aluminum hollow rings and parts made of open- cell vacuum-compatible carbon fiber. The photosensors and service front-end electronics for each crystal are assembled in a unique mechanical unit inserted in a machined copper holder. The 674 units are supported by a machined plate made of vacuum-compatible plastic material. The plate also integrates the cooling system made of a network of copper lines flowing a low temperature radiation-hard fluid and placed in thermal con- tact with the copper holders. The data acquisition electronics is hosted in aluminum custom crates positioned on the external lateral surface of the two disks. The crates also integrate the electronics cooling system. In this poster we will review the constraints on the calorimeter mechanical structures, the technological choices, and the status of assembling at Fermilab.

Pasciuto, D.↗
DOE OSTI2022

Development, construction and qualification tests of the mechanical structures of the electromagnetic calorimeter of the Mu2e experiment at Fermilab

The “muon-to-electron conversion” (Mu2e) experiment at Fermilab will search for the Charged Lepton Flavour Violating neutrino-less coherent conversion of a muon into an electron in the field of an aluminum nucleus. The observation of this process would be the unambiguous evidence of physics beyond the Standard Model. Mu2e detectors comprise a straw-tracker, an electromagnetic calorimeter and an external veto for cosmic rays. The calorimeter provides excellent electron identification, complementary information to aid pattern recognition and track reconstruction, and a fast calorimetric online trigger. The detector has been designed as a state-of-the-art crystal calorimeter and employs 1340 pure Cesium Iodide (CsI) crystals readout by UV-extended silicon photosensors and fast front-end and digitization electronics. A design consisting of two identical annular matrices (named “disks”) positioned at the relative distance of 70 cm downstream the aluminum target along the muon beamline satisfies the Mu2e physics requirements.The hostile Mu2e operational conditions, in terms of radiation levels (total ionizing dose of 12 krad and a neutron fluence of 5x1010 n/cm2 @ 1 MeVeq (Si)/y), magnetic field intensity (1 T) and vacuum level (10$^{-4}$ Torr) have posed tight constraints on the design of the detector mechanical structures and materials choice. The support structure of the two 670 crystal matrices employs two aluminum hollow rings and parts made of open-cell vacuum-compatible carbon fiber. The photosensors and service front-end electronics for each crystal are assembled in a unique mechanical unit inserted in a machined copper holder. The 670 units are supported by a machined plate made of vacuum-compatible plastic material. The plate also integrates the cooling system made of a network of copper lines flowing a low temperature radiation-hard fluid and placed in thermal contact with the copper holders to constitute a low resistance thermal bridge. The data acquisition electronics is hosted in aluminum custom crates positioned on the external lateral surface of the two disks. The crates also integrate the electronics cooling system as lines running in parallel to the front-end system.The constraints on the calorimeter mechanical structures design, the development from the conceptual design to the specifications of all the structural components, the status of components production and the components quality assurance tests are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Measuring the β-decay Properties of Neutron-rich Exotic Pm, Sm, Eu, and Gd Isotopes to Constrain the Nucleosynthesis Yields in the Rare-earth Region

Abstract The β -delayed neutron-emission probabilities of 28 exotic neutron-rich isotopes of Pm, Sm, Eu, and Gd were measured for the first time at RIKEN Nishina Center using the Advanced Implantation Detector Array (AIDA) and the BRIKEN neutron detector array. The existing β -decay half-life ( T 1/2 ) database was significantly increased toward more neutron-rich isotopes, and uncertainties for previously measured values were decreased. The new data not only constrain the theoretical predictions of half-lives and β -delayed neutron-emission probabilities, but also allow for probing the mechanisms of formation of the high-mass wing of the rare-earth peak located at A ≈ 160 in the r -process abundance distribution through astrophysical reaction network calculations. An uncertainty quantification of the calculated abundance patterns with the new data shows a reduction of the uncertainty in the rare-earth peak region. The newly introduced variance-based sensitivity analysis method offers valuable insight into the influence of important nuclear physics inputs on the calculated abundance patterns. The analysis has identified the half-lives of 168 Sm and of several gadolinium isotopes as some of the key variables among the current experimental data to understand the remaining abundance uncertainty at A = 167–172.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Deep spectral CNN for laser induced breakdown spectroscopy

This work proposes a spectral convolutional neural network (CNN) operating on laser induced breakdown spectroscopy (LIBS) signals to learn to (1) disentangle spectral signals from the sources of sensor uncertainty (i.e., pre-process) and (2) get qualitative and quantitative measures of chemical content of a sample given a spectral signal (i.e., calibrate). Once the spectral CNN is trained, it can accomplish either task through a single feed-forward pass, with real-time benefits and without any additional side information requirements including dark current, system response, temperature and detector-to-target range. Our experiments demonstrate that the proposed method outperforms the existing approaches used by the Mars Science Lab for pre-processing and calibration for remote sensing observations from the Mars rover, ‘Curiosity’.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Real-time signal detection for Cyclotron Radiation Emission Spectroscopy measurements using antenna arrays

Cyclotron Radiation Emission Spectroscopy (CRES) is a technique for precision measurement of the energies of charged particles, which is being developed by the Project 8 Collaboration to measure the neutrino mass using tritium beta-decay spectroscopy. Project 8 seeks to use the CRES technique to measure the neutrino mass with a sensitivity of 40 meV, requiring a large supply of tritium atoms stored in a multi-cubic meter detector volume. Antenna arrays are one potential technology compatible with an experiment of this scale, but the capability of an antenna-based CRES experiment to measure the neutrino mass depends on the efficiency of the signal detection algorithms. Here, in this paper, we develop efficiency models for three signal detection algorithms and compare them using simulations from a prototype antenna-based CRES experiment as a case-study. The algorithms include a power threshold, a matched filter template bank, and a neural network based machine learning approach, which are analyzed in terms of their average detection efficiency and relative computational cost. It is found that significant improvements in detection efficiency and, therefore, neutrino mass sensitivity are achievable, with only a moderate increase in computation cost, by utilizing either the matched filter or machine learning approach in place of a power threshold, which is the baseline signal detection algorithm used in previous CRES experiments by Project 8.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Improving an Acoustic Vehicle Detector Using an Iterative Self-Supervision Procedure

In many non-canonical data science scenarios, obtaining, detecting, attributing, and annotating enough high-quality training data is the primary barrier to developing highly effective models. Moreover, in many problems that are not sufficiently defined or constrained, manually developing a training dataset can often overlook interesting phenomena that should be included. To this end, we have developed and demonstrated an iterative self-supervised learning procedure, whereby models are successfully trained and applied to new data to extract new training examples that are added to the corpus of training data. Successive generations of classifiers are then trained on this augmented corpus. Using low-frequency acoustic data collected by a network of infrasound sensors deployed around the High Flux Isotope Reactor and Radiochemical Engineering Development Center at Oak Ridge National Laboratory, we test the viability of our proposed approach to develop a powerful classifier with the goal of identifying vehicles from continuously streamed data and differentiating these from other sources of noise such as tools, people, airplanes, and wind. Using a small collection of exhaustively manually labeled data, we test several implementation details of the procedure and demonstrate its success regardless of the fidelity of the initial model used to seed the iterative procedure. Finally, we demonstrate the method’s ability to update a model to accommodate changes in the data-generating distribution encountered during long-term persistent data collection.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Search for higgsinos in compressed mass spectra using low-momentum tracks in pp collisions at s=13 TeV with the ATLAS detector

This paper presents two searches for the electroweak production of higgsinos with compressed mass spectra using 140 fb−1 of s=13$$ \sqrt{s}=13 $$ TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider. Events are required to feature an energetic jet, large missing transverse momentum, and at least one low-momentum charged particle that serves as a candidate higgsino decay product. In the first search, targeting higgsino mass splittings in the range of 0.3–1 GeV, the higgsinos are expected to predominantly decay into pions that are identified as low-momentum charged particles with large transverse impact parameters due to the long higgsino lifetime (cτ ≈ ?(0.1–10 mm)), and neural networks are used to discriminate between signal and background processes. The second search targets larger mass splittings in the range of 1–3 GeV, where the higgsinos are expected to decay promptly into low-momentum leptons, one of which is identified by dedicated low-momentum electron or muon taggers based on neural networks utilising tracking and calorimeter information. No significant excess above the Standard Model prediction is observed in either search and the results are interpreted within simplified models, to set lower limits on the masses of the higgsino-like charginos and neutralinos. Together, these searches exclude chargino masses below 126 GeV at 95% confidence level for mass splittings between the chargino and lightest neutralino in the range of 0.3–2 GeV. This represents the first ATLAS constraints in a portion of this parameter space and surpasses the limits previously set by other experiments.

Aad, G↗
DOE OSTI2022

Development and construction status of the Mu2e electromagnetic calorimeter mechanical structures

Abstract The Mu2e experiment at Fermilab will search for the CLFV neutrino-less coherent conversion of a muon into an electron in the field of an aluminum nucleus. The observation of this process would be the evidence of physics beyond the Standard Model. Mu2e comprises a straw-tracker, an electromagnetic calorimeter and an external veto for cosmic rays. The calorimeter provides electron identification, a fast trigger and aids track reconstruction. It is a state-of-the-art crystal calorimeter and employs 1340 pure CsI crystals readout by UV-extended SiPM and fast electronics. The design consists of two identical annular disks positioned at the relative distance of 70 cm downstream the target.The hostile Mu2e conditions (total ionizing dose of 12 krad and a neutron fluence of 5 × 10 10 n/cm 2 @ 1 MeVeq (Si)/y, 1 T magnetic field and vacuum level of 10 −4 Torr) posed tight constraints on the mechanical structures and materials choice. The support structure of the two crystal matrices employs two aluminum hollow rings and parts made of open-cell vacuum-compatible carbon fiber. SiPMs and front-end electronics for each crystal are assembled in one mechanical unit inserted in a machined copper holder. The units are supported by a plate made of vacuum-compatible material. The plate integrates the cooling system made of a network of copper lines flowing a low temperature fluid and placed in thermal contact with the copper holders. The DAQ is hosted in aluminum crates positioned on the lateral surface of the disks. The crates also integrate the DAQ electronics cooling system. We review the constraints on the calorimeter structures design, the development of all the structural components, including the simulations that have determined the materials and technological choices and the specifications of the cooling station, components production and quality assurance tests, the procedures for detector assembly, transportation and installation in the experimental area.

Instruments & Instrumentation↗
DOE OSTI2024

The DUNE DAQ Application Framework

The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment that will probe the properties of these elusive particles with unparalleled precision. It will also act as an observatory for neutrino bursts caused by nearby supernovae, in the event that one occurs while the experiment is in operation. Given these goals, the DUNE trigger and DAQ system must be able to maintain extremely high uptime and provide a path for full readout of the detectors for very long times (up to 100s). To achieve these ends, we have designed the DUNE DAQ system around a flexible “application framework”, which provides a modular interface for specific tasks while handling the interconnections between them. The application framework collects modules into applications which can then be interacted with as units by the control, configuration and monitoring systems. One of the key features of the framework is its communications abstraction layer, which allows for modules to interact with both internal queues and external network connections with a single transport-agnostic interface. We will report on the architecture and features of the framework.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗