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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

PvaPy streaming framework for real-time data processing

User facility upgrades, new measurement techniques, advances in data analysis algorithms as well as advances in detector capabilities result in an increasing amount of data collected at X-ray beamlines. Some of these data must be analyzed and reconstructed on demand to help execute experiments dynamically and modify them in real time. In turn, this requires a computing framework for real-time processing capable of moving data quickly from the detector to local or remote computing resources, processing data, and returning results to users. In this paper, we discuss the streaming framework built on top of PvaPy, a Python API for the EPICS pvAccess protocol. We describe the framework architecture and capabilities, and discuss scientific use cases and applications that benefit from streaming workflows implemented on top of this framework. We also illustrate the framework's performance in terms of achievable data-processing rates for various detector image sizes.

EPICS pvAccess↗
NASA NTRS1998

Polar Hydra Data Analysis

The science activities are: 1) Hydra is still operating successfully on orbit. 2) A large amount of analysis and discovery has occurred with the Hydra ground data processing this past year. 3) Full interdetector calibration has been implemented and documented. This intercalibration was necessitated by the incorrect installation of bias resistors in the pre-acceleration stage to the electron channeltrons. This had the effect of making the counting efficiency for electrons energy dependent as well as channeltron specific. The nature of the error had no impact on the ion detection efficiency since they have a different bias arrangement. This intercalibration is so effective, that the electron and ion moment densities are routinely produced with a level of agreement better than 20%. 4) The data processing routinely removes glint in the sensors and produces public energy time spectrograms on the web overnight. 6) Routine, but more intensive computer processing codes are operational that determine for electrons and ions, the density, the flow vector, the pressure tensor and the heat flux by numerical integration. These codes use the magnetic field to sustain the quality of their output. To gain access to this high quality magnetic field within our data stream we have monitored Russell's web page for zero levels and timing files (since his data acquisition is not telemetry synchronous) and have a local reconstruction of B for our use. We have also detected a routine anomaly in the magnetometer data stream that we have documented to Chris Russell and developed an editing algorithm to intercept these "hits" and remove them from the geophysical analysis.

Scudder, J. D.↗
DOE OSTI2024

Measurement of the muon spin precession frequency using the straw tracking detectors at the Fermilab Muon g-2 experiment

The measurement of the anomalous magnetic dipole moment of the muon ($a_{\mu}$) has long stood as an excellent precision test of the Standard Model (SM). The Fermilab Muon g-2 experiment has recently finished data-taking and in July 2023 published its latest determination of $a_\mu$ with a world-leading precision of 0.2\,ppm. In this publication, it surpassed the systematic uncertainty goal defined in the TDR. The analyses of a dataset approximately four times larger than this recent publication is now underway. The principle measurement of the Muon g-2 experiment measures $a_{\mu}$ by taking the ratio of two frequencies; the anomalous precession frequency ($\omega_a$) and the muon-weighted magnetic field of the experiment's storage ring measured from the precession frequency of protons in water using nuclear magnetic resonance (NMR) probes. In all publications to date, $\omega_a$ has been determined using energy deposits in the 24 calorimeters. However, the Fermilab experiment has t wo straw tracker detectors measuring the time and momentum of charged particles which can in principle also be used to to measure $\omega_a$ and such a measurement can provide an invaluable cross-check of the calorimeter result with different, and reduced, systematic uncertainties. This thesis presents the first (blinded) determination of $\omega_a$ using just charged tracks from the straw tracking detectors as opposed to calorimeter energy deposits. This analysis was undertaken using the Run-2/3 dataset which represents approximately 25\% of the final dataset. A total uncertainty of 2.19\,ppm on $\omega_a$ was obtained which is dominated by the statistical uncertainty of 2.16\,ppm. Additionally two new methodologies important to the analysis of the straw tracking data have been developed: one to better determine the track arrival time ($t_0$) and one to determine the level of pileup in the tracking detectors. The new $t_0$ algorithm which incorporates angular information improves t he resolution on the determination of the $t_0$ by a factor of two and results in 19\% more tracks being successfully reconstructed. The data from the trackers is also used to determine the beam profile that weights the magnetic field in the determination of $a_\mu$ and in determining several of the systematic uncertainties in the calorimeter-based $\omega_a$ analysis. A detailed study of the impact of the internal alignment of the tracker, the $t_0$ and pileup on the determination of the beam position was undertaken and propagated through to an uncertainty in the $\omega_a$ determination. These uncertainties were used in the Fermilab Muon g-2 experiment's recent publication in Phys. Rev. Lett.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Muon momentum reconstruction in ICARUS-T600 LArTPC via Multiple Scattering

The SBN program at Fermilab investigates the possible existence of eV-scale sterile neutrinos. This work focuses on reconstructing muon momentum in $\nu$-Ar interactions within the ICARUS-T600 LArTPC detector using Multiple Coulomb Scattering (MCS), the only viable method for non-contained muons. Two algorithms are evaluated: the Gran Sasso algorithm (2D, Collection view) and the MicroBooNE algorithm (3D angles), applied to 2391 simulated and 2255 real stopping muon tracks (0.4-1 GeV/c). Performance is assessed via bias and resolution, using range-based momentum as a reference. Two enhanced versions of the Gran Sasso algorithm are also developed: one combining all three wire plane views, and one using 3D angles. Results show that the MicroBooNE algorithm performs slightly better, with resolution down to 14\% in simulation and 16\% in real data. These improvements significantly boost $\nu_\mu$ CC statistics, enhancing sensitivity to $\nu_\mu$ disappearance and 3+1 oscillation signals.

Chiello, Giovanni [Pisa U.] (ORCID:000900064571071↗
DOE OSTI2025

Quantitative phase retrieval and characterization of magnetic nanostructures via Lorentz (scanning) transmission electron microscopy

Magnetic materials phase reconstruction using Lorentz transmission electron microscopy (LTEM) measurements have traditionally been achieved using longstanding methods such as off-axis holography (OAH) fast-Fourier transform technique and the transport-of-intensity equation (TIE). The increase in access to processing power alongside the development of advanced algorithms have allowed for phase retrieval of nanoscale magnetic materials with greater efficacy and resolution. Specifically, reverse-mode automatic differentiation (RMAD) and the extended electron ptychography iterative engine (ePIE) are two recent developments of phase retrieval that can be applied to analyzing micro-to-nano- scale magnetic materials. This work evaluates phase retrieval using TIE, RMAD, and ePIE in simulations of Permalloy (Ni 80 Fe 20 ) nanoscale islands, or nanomagnets. Extending beyond simulations, we demonstrate total phase retrieval and image reconstructions of a NiFe nanowire using OAH and RMAD in LTEM and ePIE in Lorentz-mode-4D scanning transmission electron microscopy experiments and determine the saturation magnetization through corroborations with micromagnetic modeling. Finally, we demonstrate the efficacy of these methods in retrieving the total phase and highlight its use in characterizing and analyzing the proximity effect of the magnetic nanostructures.

Lorentz transmission electron microscopy↗
DOE OSTI2024

The Simons Observatory: Combining cross-spectral foreground cleaning with multitracer B -mode delensing for improved constraints on inflation

The Simons Observatory (SO), due to start full science operations in early 2025, aims to set tight constraints on inflationary physics by inferring the tensor-to-scalar ratio r from measurements of cosmic microwave background (CMB) polarization B-modes. Its nominal design including three small-aperture telescopes (SATs) targets a precision σ⁡(r = 0) ≤ 0.003 without delensing. Achieving this goal and further reducing uncertainties requires a thorough understanding and mitigation of other large-scale B-mode sources such as Galactic foregrounds and weak gravitational lensing. We present an analysis pipeline aiming to estimate r by including delensing within a cross-spectral likelihood, and demonstrate it for the first time on SO-like simulations accounting for various levels of foreground complexity, inhomogeneous noise and partial sky coverage. As introduced in an earlier SO delensing paper, lensing B-modes are synthesized using internal CMB lensing reconstructions as well as Planck-like cosmic infrared background maps and LSST-like galaxy density maps. We then extend SO’s power-spectrum-based foreground-cleaning algorithm to include all auto- and cross-spectra between the lensing template and the SAT B-modes in the likelihood function. This allows us to constrain r and the parameters of our foreground model simultaneously. Within this framework, we demonstrate the equivalence of map-based and cross-spectral delensing and use it to motivate an optimized pixel-weighting scheme for power spectrum estimation. We start by validating our pipeline in the simplistic case of uniform foreground spectral energy distributions. In the absence of primordial B-modes, we find that the 1⁢σ statistical uncertainty on r, σ⁡(r), decreases by 37% as a result of delensing. Tensor modes at the level of r = 0.01 are successfully detected by our pipeline. Even when using more realistic foreground models including spatial variations in the dust and synchrotron spectral properties, we obtain unbiased estimates of r both with and without delensing by employing the moment-expansion method. In this case, uncertainties are increased due to the higher number of model parameters, and delensing-related improvements range between 27% and 31%. These results constitute the first realistic assessment of the delensing performance at SO’s nominal sensitivity level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Enhanced material identification via momentum-integrated muon scattering tomography

Cosmic ray muons, originating from interactions in the upper atmosphere, possess high energy and unique penetrative capabilities suitable for non-traditional radiographic inspection. This study explores their application in various fields such as nuclear fuel cask monitoring, nuclear reactor imaging, and archaeology, leveraging the principle of multiple Coulomb scattering for imaging dense materials. While muon scattering tomography has shown promise, accurately measuring muon momentum remains challenging. This research introduces the Momentum Integrated Point-of-Closest Approach (mPoCA) algorithm, integrating muon momentum data into the traditional Point-of-Closest Approach (PoCA) framework. Utilizing the Cherenkov muon spectrometer, renowned for precise muon momentum estimation, the mPoCA algorithm offers a novel imaging approach. Simulations conducted with GEANT4 evaluate the mPoCA algorithm’s performance against the standard PoCA method, demonstrating superior image resolution and enhanced material identification capabilities, particularly in distinguishing materials like uranium and lead. These findings underscore the potential of the mPoCA algorithm for advancing muon scattering tomography applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Constraints on Neutrino Oscillation Parameters from Neutrinos and Antineutrinos with Machine Learning

NOvA is a two detector, long baseline neutrino oscillation experiment measuring the oscillations of muon neutrinos from the \numi neutrino beam over a baseline of \SI{810}{km}. The experiment uses four oscillation channels, $\numu \rightarrow \numu$, $\numubar \rightarrow \numubar$, $\numu \rightarrow \nue$, and $\numubar \rightarrow \nuebar$, with a peak neutrino energy of \SI{1.8}{GeV}. This dissertation describes the analysis of these channels using a dataset of $13.6\times10^{20}$ protons on target neutrino beam mode and $12.5\times10^{20}$ protons on target antineutrino beam mode. The analysis makes use of improvements in the treatment of systematic uncertainties and machine learning techniques to reconstruct neutrino interactions. A technique for decorrelating systematic errors using principle component analysis was utilized to reduce and optimize neutrino cross section and beam related uncertainties. The improved machine learning algorithms make use of convolutional ne ural net works for neutrino event classification, particle classification, and instance segmentation. The selection of neutrino signal events utilizing the neutrino event classifier shows an efficiency of 63\% for the selection of electron neutrinos in neutrino beam mode and 75\% for electron antineutrinos in antineutrino beam mode. Using this algorithm, 82 appearing electron neutrino candidates and 33 appearing electron antineutrino candidates were observed with expected backgrounds of 26.8 and 14.0 respectively. In addition, 211 surviving muon neutrino candidates and 105 muon antineutrino candidates were identified with a purity of more than 96\% using the same neutrino event classifier. Fitting these data to the three flavor neutrino oscillation model, using constraints on \thetaonetwo, \thetaonethree, and \dmsqonetwo from solar and reactor neutrino experiments, the oscillation parameters are measured to be $\sintwothree = 0.57^{+0.04}_{-0.03}$, $\dmsqthreetwo = \SI[parse-numbers= false]{+ 2.41\pm0.07 \times 10^{-3}}{eV^2}$, and $\dcp=0.82^{+0.27}_{-0.87}\pi$ with a preference for the normal neutrino mass hierarchy. Leading systematic uncertainties for these measurements come from detector calibration and neutrino interaction models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1975

Engineering studies of vectorcardiographs in blood pressure measuring systems, appendix 3

The following subjects were covered: (1) ASM80 manual, (2) signal preprocessing as an aid to on-line EKG analysis, and (3) high speed evaluation of magnetic tape recordings of electrocardiograms. A description of the ASM80 symbolic assembly program for the INTEL 8080 microprocessor and a user's manual were presented. The capability of three redundancy reduction algorithms to produce adequate representations of electrocardiographic data was examined. A hardware device was constructed which carried out zero order interpolation on a signal. Examination of the zero order interpolators reconstructed signal indicated that this representation was adequate for analysis of rhythm. A system to analyze magnetic tapes of electrocardiograms recorded over 24 hour intervals was designed. The recordings are sampled 200 times per second using a Nova computer and a special interface system. This system was tested on several recordings of clinical data, containing over 75 premature ventricular contractions, each one of which was flagged.

Mark, R. G.↗
DOE OSTI2021

Evaluating the ProtoDUNE-SP Detector Performance to Measure a 6 GeV/c Positive Kaon Inelastic Cross Section on Argon

The ProtoDUNE Single-Phase Liquid Argon Time Projection Chamber \\ (ProtoDUNE-SP LArTPC) is a prototype for the Deep Underground Neutrino Experiment (DUNE), a future long-baseline neutrino oscillation experiment. Based at the CERN Neutrino Platform, ProtoDUNE-SP LArTPC collected data from a charged test beam in the fall of 2018. It then took data of cosmic-ray muons from November 2018 to the summer of 2020. The main goals of the prototype were to measure parameters related to charged particle passage in argon and evaluate the performance of the detector to inform future DUNE Far Detector development. The test beam provided kaons, pions, muons, protons, and electrons to the detector. These particles represent common final state particles in neutrino interactions, therefore providing information to DUNE on modeling charged particles in argon for its neutrino physics program. In addition to neutrino physics, DUNE has proposed an analysis using the DUNE Far Detector module to set limits for proton decay through the decay channel $p\rightarrow K^++\bar{\nu}$. This measurement would require information on kaons in argon, providing ProtoDUNE-SP LArTPC another opportunity to aid DUNE. This thesis describes the calibration of ProtoDUNE-SP and its detector performance, which serves as a benchmark for the performance of the DUNE Far Detector modules. A specific calibration highlighted is the evaluation of the liquid argon purity in the detector. These measurements use cosmic-ray muons reconstructed in the detector that are calibrated and matched to data from scintillator strips external to the TPC, known as the Cosmic Ray Tagger (CRT). The thesis will discuss the algorithms to match the data between the ProtoDUNE-SP LArTPC and the CRT and discuss the liquid argon purity measurements using one of the algorithms. Data sets of calibrated tracks measured the liquid argon contamination as consistently below 100 ppt oxygen equivalent. After these discussions on the ProtoDUNE-SP LArTPC detector, the thesis will present an evaluation of the inclusive inelastic, sometimes referred to as a reactive, cross section on argon of kaons from the ProtoDUNE-SP test beam with an average momentum of 6 GeV/c.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Segmentation of RDX and TNT in X‐Ray Computed Tomography Reconstructions of Melt‐Cast Explosives

ABSTRACT Three‐dimensional mesoscale characterization of heterogeneous melt‐cast high explosives is challenging because of the difficulty differentiating binder from explosive crystals: two functionally different materials which are typically similar in density by design. Here, we report an algorithm which can differentiate hexahydro‐1,3,5‐trinitro‐1,3,5‐triazine (RDX) from 2,4,6‐trinitrotoluene (TNT) in x‐ray computed tomography (CT) volumes with tens of microns resolution. This method allows us to quantify RDX/TNT content, porosity, and RDX domain size. We calibrated the segmentation algorithm using simulated x‐ray CT volumes containing object models of RDX crystals within a TNT matrix. We then segmented and analyzed CT data for Composition B (Comp B), a 60/40 RDX/TNT mixture, and Cyclotol, a 75/25 RDX/TNT mixture. We examined melt‐cast samples fabricated with 100% theoretical maximum density (TMD) and 85% TMD. For the 100% TMD Comp B and Cyclotol samples, the RDX content values calculated by segmentation were 3% and 9% lower, respectively, than the values measured by high‐performance liquid chromatography on material from the same synthesis lots. This result is consistent with the expected underreporting of RDX content resulting from x‐ray CT resolution limits on RDX particles with diameters smaller than 25 µm. The 85% TMD samples were less accurately segmented with our algorithm due to the confounding presence of voids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Dual-map framework for noise characterization of quantum computers

In order to understand the capabilities and limitations of quantum computers, it is necessary to develop methods that efficiently characterize and benchmark error channels present on these devices. In this paper, we present a method that faithfully reconstructs a marginal (local) approximation of the effective noise (MATEN) channel, that acts as a single layer at the end of the circuit. We first introduce a dual-map framework that allows us to analytically derive expectation values of observables with respect to noisy circuits. These findings are supported by numerical simulations of the quantum approximate optimization algorithm (QAOA) that also justify the MATEN, even in the presence of nonlocal errors that occur during a circuit. Finally, we demonstrate the performance of the method on Rigetti's Aspen-11 quantum computer for QAOA circuits up to six qubits, successfully predicting the observed measurements on a majority of the qubits.

Sud, James↗
DOE OSTI2020

Topological analysis of X-ray CT data for the recognition and trending of subtle changes in microstructure under material aging

X-ray computed tomography (CT) is an established non-destructive tool for 3D imaging of multiphasic composites. Numerous applications of X-ray CT in medical diagnosis and materials characterization have been reported, many involving field-specific innovations in the imaging technology itself. Yet, quantitative summarization to link image features to properties of interest has been rare. Here we address this issue by employing state-of-the-art technics in scalar field topology for the summarization of X-ray CT images of an example biphasic system. By varying processing-parameters we create different microstructures, evolve them through accelerated thermal aging, CT-image them pre- and post-aged, and demonstrate the ability of our image summarization method to systematically track process- and age-related changes, which can often be very subtle. A novel aspect of the algorithm involves recognition over multiple resolution levels, which provides deeper insight into the pattern relationship between grain-like features and their neighbors. The method is general, adaptable to diverse image reconstruction methods and materials systems, and particularly useful in applications where practical constraints on the sample-size limits the reliable use of more complex models, e.g., convolutional neural networks.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Conservative discontinuous Galerkin schemes for nonlinear Dougherty–Fokker–Planck collision operators

Here, we present a novel discontinuous Galerkin algorithm for the solution of a class of Fokker–Planck collision operators. These operators arise in many fields of physics, and our particular application is for kinetic plasma simulations. In particular, we focus on an operator often known as the ‘Lenard–Bernstein’ or ‘Dougherty’ operator. Several novel algorithmic innovations, based on the concept of weak equality, are reported. These weak equalities are used to define weak operators that compute primitive moments, and are also used to determine a reconstruction procedure that allows an efficient and accurate discretization of the diffusion term. We show that when two integrations by parts are used to construct the discrete weak form, and finite velocity-space extents are accounted for, a scheme that conserves density, momentum and energy exactly is obtained. One novel feature is that the requirements of momentum and energy conservation lead to unique formulas to compute primitive moments. Careful definition of discretized moments also ensure that energy is conserved in the piecewise linear case, even though the kinetic-energy term, $v^2$ is not included in the basis set used in the discretization. A series of benchmark problems is presented and shows that the scheme conserves momentum and energy to machine precision. Empirical evidence also indicates that entropy is a non-decreasing function. The collision terms are combined with the Vlasov equation to study collisional Landau damping and plasma heating via magnetic pumping.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

The continuous readout stream of the MicroBooNE liquid argon time projection chamber for detection of supernova burst neutrinos

The MicroBooNE continuous readout stream is a parallel readout of the MicroBooNE liquid argon time projection chamber (LArTPC) which enables detection of non-beam events such as those from a supernova neutrino burst. The low energies of the supernova neutrinos and the intense cosmic-ray background flux due to the near-surface detector location makes triggering on these events very challenging. Instead, MicroBooNE relies on a delayed trigger generated by SNEWS (the Supernova Early Warning System) for detecting supernova neutrinos. The continuous readout of the LArTPC generates large data volumes, and requires the use of real-time compression algorithms (zero suppression and Huffman compression) implemented in an FPGA (field-programmable gate array) in the readout electronics. In this paper we present the results of the optimization of the data reduction algorithms, and their operational performance. To demonstrate the capability of the continuous stream to detect low-energy electrons, a sample of Michel electrons from stopping cosmic-ray muons is reconstructed and compared to a similar sample from the lossless triggered readout stream.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Track vs Shower Discrimination in the Event Reconstruction of the ICARUS Experiment

The ICARUS collaboration has employed the 760-ton T600 liquid argon TPC detector in a successful three-year physics run at the underground LNGS laboratory, performing a sensitive search for LSND-like anomalous appearance in the CERN Neutrino to Gran Sasso beam, which contributed to the constraints on the allowed neutrino oscillation parameters to a narrow region around 1 eV. After a significant overhaul at CERN, the T600 detector has been installed at Fermilab. The detector commissioning phase lasted until June 2022, then ICARUS moved to data taking for neutrino oscillation physics collecting events from the Booster Neutrino Beam (BNB) and the Neutrinos at the Main Injector (NuMI) beam off-axis. The initial experiment goals are to either confirm or refute the claim by Neutrino-4 short-baseline reactor experiment, perform measurements of neutrino cross sections with the NuMI beam and several Beyond Standard Model searches. Then, ICARUS will jointly search for evidence of sterile neutrinos with the Short-Baseline Near Detector (SBND). In this contribution, we discuss recent changes to the standard TPC event reconstruction that uses Pandora, a pattern recognition software common to liquid argon-based detectors. In particular, we performed a new training of the Boosted Decision Tree (BDT) employed to separate track-like and shower-like reconstructed particles using Monte Carlo simulations of neutrino events from BNB in ICARUS. We compare the discrimination capabilities of the old and new BDT training and discuss further improvements of this algorithm.

43 PARTICLE ACCELERATORS↗
NASA NTRS1992

Conceptual issues of softcopy photogrammetric workstations

A conceptual approach to digital photogrammetry is presented. Automation of photogrammetric processes on digital photogrammetric workstations is considered with particular attention given to the automatic orientation and the surface reconstruction module. It is suggested that major progress toward autonomous softcopy workstations depends more on advances on the conceptual level rather than on refinement of system components such as hardware and algorithms.

Schenk, Toni↗
DOE OSTI2020

Data-Driven Event Detection of Power Systems Based on Unequal-Interval Reduction of PMU Data and Local Outlier Factor

With the deployment of phasor measurement units (PMU) and wide area measurement system (WAMS), it is feasible to have an insight into the events occurred in power systems based on measured data. Thus, a novel data-driven algorithm based on local outlier factor (LOF) is proposed in this work to detect and locate events in power systems using reduced PMU data. First, the unequal-interval reduction method is presented to reduce the scale of PMU data in sub-stations and reconstruct it in master station of WAMS, which can relieve the burden of communication systems. Then, principle component analysis (PCA)-based similarity search method is proposed to measure the differences of operation state between any two buses. Next, LOF is presented to detect the abnormal events in power systems, and employed to determine the region of the event source. Finally, six cases from the Western electricity coordinating council (WECC) 179-bus power system, a case from the South China power system (SCPS), and a case from the Guangdong power system (GDPS) are utilized to demonstrate the effectiveness of the proposed algorithm. Overall, the results show that proposed algorithm is effective and can be applied to event detection, event location, and online monitoring, which can enhance the situation awareness ability of power system operators.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗