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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Implementing machine learning methods on QICK hardware for qubit readout & control

Quantum readout and control is a fundamental aspect of quantum computing that requires accurate measurement of qubit states. Errors emerge in all stages, from initialization to readout, and identifying errors in post-processing necessitates resource-intensive statistical analysis. In our work, we use a lightweight fully-connected neural network (NN) to classify states of a transmon system with no prior processing. Our NN accelerator yields higher fidelities (92%) than the classical matched filter method (84%). By exploiting the natural parallelism of NNs and their placement near the source of data on field-programmable gate arrays (FPGAs), we can achieve ultra-low latency on the Quantum Instrumentation Control Kit (QICK). Integrating machine learning methods on QICK opens several pathways for efficient real-time processing of quantum circuits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Inhalation of Trace Metals in Secondhand and Thirdhand Tobacco Smoke Can Result in Increased Health Risks

Here, the presence of toxic metals in tobacco smoke is well documented. However, few studies have quantified trace metals in secondhand smoke (SHS) and thirdhand smoke (THS). Their presence in indoor air can contribute to nonsmokers’ exposures and health effects. In this study, emission and deposition rates of toxic trace metals were determined, and their airborne concentration in typical indoor scenarios was predicted. PM 2.5 was collected on Teflon-coated filters at various times following a smoking event in a room-sized chamber over a 43 h period. The concentration of 28 trace metals was determined by extraction and analysis using inductively coupled plasma-triple quadrupole-mass spectrometry (ICP-QQQ-MS). Emission and indoor deposition rates of cadmium, arsenic, chromium, manganese, beryllium and selenium were determined, and used to predict concentrations expected in a smokers’ home and a smoking bar. In most of the considered scenarios, average indoor concentrations of Cd, As, and Cr exceeded their corresponding cancer risk thresholds and, in some cases, also noncancer reference exposure levels, more than 3 h after smoking ended. The fraction of cadmium that remained airborne was significantly higher than those of other metal traces and that of PM 2.5 , suggesting an association of Cd traces with small particles.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 $\mu$m$^2$ in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e$^-$ and a total dispersion of $\sim$100e$^-$ The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4% - 75.4% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm$^2$ staying within the experimental constraints.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 µm\textsuperscript{2} in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e\textsuperscript{-} and a total dispersion of $\sim$100e\textsuperscript{-} The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4\% – 75.4\% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm\textsuperscript{2} staying within the experimental constraints.

Parpillon, Benjamin↗
DOE OSTI2021

Adaptive Spatially Aware I/O for Multiresolution Particle Data Layouts

Large-scale simulations on nonuniform particle distributions that evolve over time are widely used in cosmology, molecular dynamics, and engineering. Such data are often saved in an unstructured format that neither preserves spatial locality nor provides metadata for accelerating spatial or attribute subset queries, leading to poor performance of visualization tasks. Furthermore, the parallel I/O strategy used typically writes a file per process or a single shared file, neither of which is portable or scalable across different HPC systems. We present a portable technique for scalable, spatially aware adaptive aggregation that preserves spatial locality in the output. We evaluate our approach on two supercomputers, Stampede2 and Summit, and demonstrate that it outperforms prior approaches at scale, achieving up to 2.5× faster writes and reads for nonuniform distributions. Furthermore, the layout written by our method is directly suitable for visual analytics, supporting low-latency reads and attribute-based filtering with little overhead.

Usher, Will↗
DOE OSTI2020

Measuring Neutrino Oscillations in the NOvA and CHIPS Detectors.

NOvA is a long baseline neutrino experiment which uses muon neutrinos produced by the NuMI beam at the Fermi National Accelerator Laboratory to measure muon neutrino disappearance and electron neutrino appearance, among other analyses. The Far/Near Extrapolation analysis framework (FNEX) was used to measure muon neutrino disappearance using the events observed by NOvA while the NuMI beam was in Forward Horn Current configuration (i.e. this analysis uses neutrino data, not antineutrino data). The values of the parameters measured in this analysis are sin 2 θ 23 - 0.499$^{+0.098}_{-0.069}$ and Δm$^2_{32}$ - 2.454$^{+0.108}_{0.119}$ × 10 -3 eV, which is consistent with the results of NOvA’s main muon neutrino disappearance analysis using the experiment’s usual framework, known as CAF. The CHIPS detector is a water Cherenkov detector currently in construction. It will also use the NuMI beam to perform muon neutrino disappearance and electron neutrino appearance analyses. The necessary water clarity for a detector with a diameter of 25 m and a height of 6 m is discussed, as well as the results of testing water filtration systems. The filtration that will be used for the detector is a 10 µm carbon block filter and a 0.5 µm filter in series, with no reverse osmosis or ultraviolet sterilisation being used. This provides an attenuation length of 16.63 ± 0.25 m for light of 532 nm wavelength (green), so light with a wavelength of 405 nm (violet) would have an attenuation length of 133±2 m. The greatest possible distance between a PMT and any point in the detector’s volume is approximately 26 m, so 133 m is sufficient for the detector to measure Cherenkov light produced anywhere in the detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Energy Exascale Earth System Model v2.0

First release of version 2 of the Energy Exascale Earth System Model. The atmosphere component remains EAM. Major changes since version 1 include: all column-physics parameterizations are computed on a separate grid that has approximately half the number of points of the dynamics grid, a new nonhydrostatic dynamical core (running in hydrostatic mode) with semi-Lagrangian tracer transport, CLUBB updated from v1 to v2, a new convective trigger (dCAPE/ULL) based on the dynamic Convective Available Potential Energy (CAPE) (dCAPE) and the Unrestricted Launch Level (ULL) concepts is used in ZM. minimum cloud droplet number changed, gravity wave drag energy conservation fixed and new tunings used, dust emission size distribution changed to emit more coarse dust particles The land component is still ELM. Major changes since version 1 include: using SNICAR-AD for radiation in snow to match the sea-ice model and fixing bugs in snow compaction and water state calculation. The ocean component remains MPAS-ocean. Major change since version 1 include: Redi isopycnal mixing has been updated, tested, and tuned in combination with the Gent-McWilliams parameterization, a sign error was fixed in the 3rd-order flux routines, the mesh used in low-resolution coupled cases was modified and the time steps adjusted, new regionally refined meshes were created, one focused on North America and another on the Southern Ocean, including ice shelf cavities. The sea-ice component remains MPAS-seaice. Major changes since version 1 include: A new heat- and freshwater-conserving coupling of frazil ice, turning off of SSH filtering, addition of SNICAR-AD and snow grain aging. The land-ice component remains MPAS-Albany-landIce (MALI) and is a static ice sheet. There is more out-of-the-box support for cryosphere configurations including the new regionally refined configuration around Antarctica with ice shelf cavities. The river model is MOSART. The half-degree river mesh was redone so it no longer treats Black and Caspian seas as ocean. The coupler remains cpl7/MCT. Major changes since version 1 include handling of ice shelf melt fluxes (heat / freshwater exchange with the ocean), and data icebergs. All components allow regional refinement of their meshes and two separate example of refinement, one in and around North America and one around Antarctica and the Southern Ocean, are provided.

E3SM Project, DOE↗
DOE OSTI2021

Assessment of filtered cameras for quantitative 2D analysis of divertor conditions during detachment in JET L-mode plasmas

We report that estimates for 2D distributions of electron temperature, T e , electron density, n e , and atomic deuterium density, n o , in the JET divertor volume have been inferred from deuterium Balmer line intensity ratios obtained from tomographic reconstructions of divertor camera measurements. This enables also investigation of ionization, S ion , and recombination, S rec , rates. The analysis shows a decrease of T e to 0.5–1.0 eV throughout the outer divertor during detachment in low-confinement (L-mode) plasmas. Simultaneously, the high-n e region and the n 0 distribution in the outer divertor are observed to elongate and shift from the outer strike point towards the X-point. The observations are in qualitative agreement and follow the same sequence with modelling predictions of EDGE2D-EIRENE simulations of a density scan. While the method was found to provide good representation of the evolution of volumetric recombination during detachment, in agreement with the simulations, the movement of the ionization front upstream could not be followed due to lack of spatial overlap between the ionization region and the necessary emission distributions. Consequently, the representation of the ionization conditions and the particle balance in the detached outer divertor are compromised.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

The Squeezed Bispectrum from CHIME H I Emission and Planck Cosmic Microwave Background Lensing: Current Sensitivity and Forecasts

Line intensity mapping using atomic hydrogen (H I) has the potential to efficiently map large volumes of the Universe if the signal can be successfully separated from overwhelmingly bright radio foreground emission. This motivates cross correlations, to ascertain the cosmological nature of measured H I fluctuations, and to study their connections with galaxies and the underlying matter density field. However, these same foregrounds render the cross correlation with projected fields such as the lensing of the cosmic microwave background (CMB) difficult. Indeed, the correlated Fourier modes vary slowly along the line of sight and are thus most contaminated by the smooth-spectrum radio continuum foregrounds. In this paper, we implement a method that avoids this issue by attempting to measure the nonlinear gravitational coupling of the small-scale 21 cm power from the Canadian Hydrogen Intensity Mapping Experiment (CHIME) with large-scale Planck CMB lensing. This measurement is a position-dependent power spectrum, i.e., a squeezed integrated bispectrum. Using 94 nights of CHIME data between 1.0 < z < 1.3 and aggressive foreground filtering, we find that the expected signal is 5 times smaller than the current noise. We forecast that incorporating the additional nights of CHIME data already collected would enable a signal-to-noise ratio of 3, without any further improvements in filtering for foreground cleaning.

21cm↗
DOE OSTI2023

Closed Loop Testing of Microphonics Algorithms Using a Cavity Emulator

An analog crystal filter based cavity emulator is modified with reverse biased varactor diodes to provide a tuning range of around 160 Hz. The piezo drive voltage of the resonance controller is used to detune the cavity through the bias voltage. A signal conditioning and summing circuit allows the introduction of microphonics disturbance from a signal source or using real microphonics data from cavity testing. This setup is used in closed loop with a cavity controller and resonance controller to study the effectiveness of resonance control algorithms suitable for superconducting cavities.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

On finite-dimensional smoothed-particle Hamiltonian reductions of the Vlasov equation

The inclusion of spatial smoothing in finite-dimensional particle-based Hamiltonian reductions of the Vlasov equation and related models is considered. Here, this work investigates the underlying Hamiltonian structure of such smoothed particle-based methods for Hamiltonian systems and the small-scale regularization such methods implicitly make in approximating the continuum theory. In the context of the Vlasov–Poisson equation and other mean-field Lie–Poisson systems, of which Vlasov–Poisson is a special case, smoothing amounts to a convolutive regularization of the Hamiltonian. This regularization may be interpreted as a change of the inner product structure used to identify the dual space in the Lie–Poisson Hamiltonian formulation. In particular, the shape function used for spatial smoothing may be identified as the kernel function of a reproducing kernel Hilbert space whose inner product is used to define the Lie–Poisson Hamiltonian structure. It is likewise possible to introduce smoothing in the Vlasov–Maxwell system, but in this case the Poisson bracket must be modified rather than the Hamiltonian. The smoothing applied to the Vlasov–Maxwell system is incorporated by inserting smoothing in the map from canonical to kinematic coordinates. In the filtered system, the Lorentz force law and the current, the two terms coupling the Vlasov equation with Maxwell’s equations, are spatially smoothed.

Hamiltonian mechanics↗
DOE OSTI2025

Lanczos Algorithm, the Transfer Matrix, and the Signal-to-Noise Problem

This Letter introduces a method for determining the energy spectrum of lattice quantum chromodynamics by applying the Lanczos algorithm to the transfer matrix and using a bootstrap generalization of the Cullum-Willoughby method to filter out spurious eigenvalues. Proof-of-principle analyses of the simple harmonic oscillator and the lattice quantum chromodynamics proton mass demonstrate that this method provides faster ground-state convergence than the “effective mass,” which is related to the power-iteration algorithm. Lanczos provides more accurate energy estimates than multistate fits to correlation functions with small imaginary times while achieving comparable statistical precision. Two-sided error bounds are computed for Lanczos results and guarantee that excited-state effects cannot shift Lanczos results far outside their statistical uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

SPARTAN and IMPROVE Comparison Experiment (SPICE) Interim Campaign Report

SPICE (the SPARTAN and IMPROVE Comparison Experiment) aims to obtain and quantify comparisons between aerosol PM 2.5 mass concentration measurements from the University of Oklahoma (OU) Surface Particulate Matter Network (SPARTAN) station and the U.S. Environmental Protection Agency (EPA) Interagency Monitoring of Protected Visual Environments (IMPROVE) station hosted by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility at ARM’s Southern Great Plains (SGP) observatory in Oklahoma. Aerosols—both natural and anthropogenic—affect human populations in multiple ways. Much of ARM’s research focuses on how aerosols influence weather and climate through their optical and radiative effects, as well as their impacts on clouds and precipitation. However, aerosols also pose direct risks to humans and other organisms through inhalation, with the severity of health impacts depending on particle size, chemical composition, and duration of exposure. The IMPROVE network was established by the U.S. EPA to monitor air quality, including visible clarity as well as total and chemically speciated aerosol mass concentrations. The ARM SGP site hosts the IMPROVE SOGP station. Separately, the SPARTAN network operates a globally distributed set of stations similar to IMPROVE but with an emphasis on remote deployment and semi-autonomous operation for use beyond the borders of the United States (IMPROVE only operates within the U.S.). The University of Oklahoma operates a SPARTAN station. To establish confidence in the OU SPARTAN instrumentation and measurement protocol relative to the EPA-certified IMPROVE station, the OU SPARTAN station is currently deployed at SGP in close proximity to the IMPROVE SOGP station. The SPICE campaign was envisioned as a contiguous calendar-year effort for 2025 to capture seasonal variation in mass loading as well as composition. However, independent of the SPICE campaign, the SPARTAN network adopted a new filter construction part-way through the year, interrupting our contiguous data set. Thus, to obtain a contiguous data set with a uniform consistent configuration, SPICE desires an extension through 2026.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Enhancements and Deployment of the TDAQ System for the Mu2e Experiment

The Real Time Processing Systems Division at Fermilab has deployed new features to the Off-The-Shelf Data Acquisition framework (otsdaq) for the Mu2e experiment. The Mu2e experiment will search for the coherent neutrino-less conversion of a muon into an electron in the field of an aluminum nucleus with a sensitivity improvement of 10,000 times over existing limits. Such a charged lepton flavor-violating reaction probes new physics at a scale unavailable at present or planned high-energy colliders. The Mu2e Trigger and Data Acquisition (TDAQ) system uses otsdaq as its online Data Acquisition System (DAQ) framework. otsdaq integrates the artdaq and art frameworks for event transfer, filtering, and processing. otsdaq is a web-based DAQ software suite focusing on flexibility and scalability and provides a multi-user interface accessible through a web browser. artdaq handles the entire data stream, which is read over the peripheral component interconnect express (PCIe) bus to a software filter algorithm that selects events combined with the data flux coming from a cosmic-ray veto (CRV) system. Detector front-ends are configured through the PCIe bus by customized otsdaq plugins. The otsdaq slow controls infrastructure has been further developed using the experimental physics and industrial control system (EPICS) open-source platform for monitoring, controlling, alarming, and archiving. The detector control system (DCS) for Mu2e has been integrated into otsdaq. The production TDAQ and DCS system has been deployed at the experimental hall and is being debugged and optimized for experiment operations. We report on the feature enhancements and deployment of otsdaq for Mu2e.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Thermal Model Heat Rate Predictions of the AGR-5/6/7 Experiment

Several fuel and material irradiation experiments have been planned for the U.S. Department of Energy Advanced Gas Reactor Fuel Development and Qualification Program, which supports the development and qualification of tristructural isotropic (TRISO) coated particle fuel for use in high-temperature gas-cooled reactors. The goals of these experiments are to provide irradiation performance data to support fuel process development, qualify fuel for normal operating conditions, support development of fuel performance models and codes, and provide irradiated fuel and materials for post-irradiation examination and safety testing. Originally planned and named as separate fuel experiments, but subsequently combined into a single test train. AGR-5/6/7 will test low-enriched uranium oxycarbide (UCO – a heterogeneous mixture of uranium oxide and uranium carbide) TRISO fuel. The AGR-5/6 portion of the experiment will provide data to support qualification of the selected reference fuel design, while the AGR-7 portion will serve as a margin test, irradiating the fuel beyond normal operating conditions. During irradiation, the temperature in each capsule is controlled by varying the helium / neon gas mixture flowing through the capsule until the desired thermocouple temperature is reached. Further adjustments can be made by changing the lobe power and the neutron filter. Three neutron filters are available to use as the experiment burns up the fissionable fuel. A thermal finite element model has been created for the five capsules comprising the AGR-5/6/7 experiment. Heat rates from a physics analysis are imported into the model along with fast neutron fluence. Graphite shrinkage due to the fast neutron fluence is incorporated into the model. Gas gaps change as a function of fast neutron fluence. Radiation heat transfer is a major contributor in this model. This is a large model with more than 1 million finite element brick elements. More than 150 different parts are modeled in the finite element model and communicate with each other from a heat transfer sense. More than 50 thermocouples are used in the experiment and are compared to actual measurements. The experiment is composed of five separate stainless steel capsules all welded together. This paper presents a method used to predict the gas mixture in the event that all of the thermocouples fail in a particular capsule. Curve fitting of heat rates from previous cycles and projecting them into the future is the basis of the method.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Spent Crystalline Silicotitanate Storage Study

Washington River Protection Solutions is working to support initial production of immobilized low-activity waste (LAW) by feeding Hanford tank supernate from tank farms to the Hanford Waste Treatment and Immobilization Plant (WTP) LAW Facility. This goal incorporates the design of a Tank-Side Cesium Removal (TSCR) system, which filters tank waste supernate to remove suspended solids and then removes Cs by processing it through crystalline silicotitanate (CST) ion exchange media manufactured by Honeywell UOP, LLC. The 137 Cs-depleted product is intended to be sent to the WTP for vitrification. The Cs-loaded CST columns will be stored indefinitely, with a goal of eventual CST removal and treatment. Thus, the spent CST needs to be recoverable. The testing described herein looks to potential upset process conditions where CST storage may be required before various rinse steps are completed. This study evaluated upset conditions at three sequential processing steps envisioned for TSCR (feed, 0.1 M NaOH rinse, water rinse), and in-column drying with compressed air (normal end step) to assess impacts on the nature of the CST bed. Testing was conducted at the small scale (12-mL bed volume); simulated AP-105 tank waste was used as the feed. Following process disruption, the CST bed was dried in place at 70 °C. Post-dried CST bed physical properties (angle of repose, penetration depth, particle morphological changes) were measured to evaluate how CST moved and flowed. The testing is intended to provide a preliminary assessment of issues that may arise from desiccation of CST with the indicated salt solutions in place. Since these were small-scale tests, the processing conditions will not match full scale conditions exactly; however, the tests do provide insight into the impact of stopping processing at an earlier step than normal. Except for the feed that was dried in-place, all other process stop-conditions showed the CST bed flowed well after drying. At this small scale, CST beds would not present an issue for retrievability. The feed that was dried in place had solidified into a rock-hard monolith with no movement possible. Samples had to be chipped from the surface.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Application of electron beam technology to decompose persistent emerging drinking water contaminants: poly- and perfluoroalkyl substances (PFAS) and 1,4 dioxane.

Fermi Research Alliance, LLC (FRA) operates Fermilab under contract with the U.S. Department of Energy and has patents on technologies and applications of a novel mobile electron beam accelerator. A high-power version of this mobile accelerator based on FRA-developed SRF technology is under development at Illinois Accelerator Research Center (IARC) and can enable several new applications that have significant commercial potential. One such application is the e-beam treatment of persistent emerging contaminants in drinking water. The contaminants of concern are poly- and perfluoroalklyl substances (PFAS) and 1,4-dioxine. Both PFAS and 1,4-D are highly resistant to degradation and are not effectively removed by conventional drinking water treatment systems. Existing technologies, such as granular activated carbon (GAC) filters and reverse osmosis (RO) systems do not decompose. The Center for Clean Water Technology (CCWT) at Stony Brook University (SBU) is in the process of identifying and testing effective technologies to remove PFAS and/or 1,4-D from drinking waters. se PFAS, but rather concentrate them either by adsorption (GAC) or membrane rejection (RO). The Center for Clean Water Technology (CCWT) at Stony Brook University (SBU) is in the process of identifying and testing effective technologies to remove PFAS and/or 1,4-D from drinking waters to demonstrate the full-scale application of novel water treatment technologies and is experienced in conducting research to understand treatment performance with a particular focus on 1,4-D and PFAS contamination.

43 PARTICLE ACCELERATORS↗