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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Beam dynamics corrections in the measurement of the anomalous precession frequency at the Muon $g-2$ experiment at Fermilab

The Muon $g-2$ experiment at Fermilab (E989) aims to measure the anomalous magnetic moment of the muon with an accuracy of 140 ppb (parts per billions). This accuracy, obtained by adding in quadrature a statistical and a systematic contribution of comparable value (100 ppb), will allow to reduce the experimental uncertainty (from the previous E821 experiment at BNL \cite{bnl}) of a factor of 4, and represents one of the most precise tests of the Standard Model (SM) theory of elementary particles. The first result on the Run-1 dataset \cite{prl} was released on April 7, 2021, showing a very good agreement with the previous result from BNL experiment, with a slightly better uncertainty. The corresponding experimental average increases the significance of the discrepancy between the measured and Standard Model prediction of 4.2$\sigma$ \cite{white_paper}.\\ \noindent The measured quantity is the muon magnetic anomaly a$_\mu$=$\frac{g_\mu-2}{2}$ where g$_\mu$ is the gyromagnetic factor of the muon. Dirac's equation predicts g$_\mu$ = 2, while radiative corrections, dominated by the QED contribution due to an exchange of a virtual photon, causes a per-mille correction on this quantity. By including all the SM contributions, a$_\mu$ is known at 370 ppb. The E989 experiment measures $a_\mu$ injecting positive muons with momentum of 3.1 GeV/$c$ polarized longitudinally in bunches (called $fills$) with an average rate of 12 Hz, in a storage ring of 14 meters diameter. Due to the parity violation in the weak muon decay, high energy positrons produced are emitted preferably in the muon's spin direction. By counting the number of positrons with energy greater then 1.7 GeV in function of the time, the frequency precession of the muon spin is measured, that together with the measurement of the magnetic field, allows to extract $a_\mu$. The positrons are detected with 24 electromagnetic calorimeters, that measure the energy and the arrival time of the positrons, each made of 54 crystals of lead fluoride (PbF$_2$) read by silicon photomultipliers (SiPM). Together with calorimeters, two tracking detectors are used to make non-destructive measurements of the muon beam characteristic by reconstructing the muon decay position extrapolating backward the decay positrons. The knowledge of the beam motion inside the ring plays a fundamental role in the analysis of $a_{\mu}$, where the measured anomalous precession frequency $\omega_a$ must be corrected for four main beam dynamics effects. A first correction is associated with the presence of an electric field responsible of the vertical focusing on the storage ring, where vertical direction is orthogonal to the orbit and horizontal direction is along the storage ring radius. Due to the oscillations in the vertical direction, the so called vertical betatron oscillations, a second correction is necessary to account for an average angle associated with the muon motion off the ideal orbit. A third correction is caused by lost muons in the ring which have a different spin phase at the injection respect to the decay ones. Finally, due to the correlation between the vertical and horizontal beam motion of the muons and the acceptance of the calorimeter, a correction (called ``phase-acceptance") arises. In Run1, due to the presence of two damaged resistors in one electrostatic quadrupole, this correction had a prominent role. The replacement of the damaged resistors before Run2 decreased this effect by one order of magnitude, and a further reduction in Run-3 was provided by an improved orbit.\\ \noindent The work of this Thesis focuses on the beam dynamics corrections on $\omega_a$. Due to the prominent role in Run-1 a special attention has been put to the phase-acceptance correction\footnote{The effect of this correction on the E821 BNL measurement of the $g-2$ has been evaluated to be within the quoted systematic error.}. Chapter \ref{ch:anomalous_magnetic_moment} introduces the anomalous magnetic moment of the muon. Chapter \ref{ch:early_experiment} describes the history of the Muon $g-2$ experiments. Chapter \ref{ch:theory} discusses the Standard Model prediction and possible new physics scenario. Chapter \ref{ch:muon_g2_experiment} describes the E989 experiment, whose experimental technique and the apparatus are discussed focusing on the improvements needed to reach the final goal on $a_\mu$ measurement. The original work of the Thesis is discussed in the last 5 chapters. Chapter \ref{ch:experiment_technique} presents the analysis technique to extract $\omega_a$, Chapter \ref{ch:beam_dynamics} describes the beam dynamics in the E989 experiment, Chapter \ref{ch:beam_dynamics_correction} discusses the beam dynamics correction to $\omega_a$, and Chapter \ref{sec:pa_corr} focuses on the phase acceptance correction. Finally Chapter \ref{ch:run23_analysis_improvements} contains the Run-2/3 improvements which are expected to allow for an increased precision ons the beam dynamics co...

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2016

Precision Oxygen Isotope Measurements of Two C-Rich Hydrated Interplanetary Dust Particles

Introduction: Chondritic-smooth IDPs (Interplanetary Dust Particles) are low porosity objects whose mineralogy is dominated by aqueous alteration products such as Mg-rich phyllosilicates (smectite and serpentine group) and Mg-Fe carbonate minerals. Their hydrated mineralogy combined with low atmospheric entry velocities have been used to infer an origin largely from asteroidal sources. Spectroscopic studies show that the types and abundance of organic matter in CS IDPs is similar to that in CP IDPs. Although CS IDPs show broad similarities to primitive carbonaceous chondrites, only a few particles have been directly linked to specific meteorite groups such as CM and CI chondrites based on the presence of diagnostic minerals. Many CS IDPs however, have carbon contents that greatly exceed that of known meteorite groups suggesting that they either may derive from comets or represent samples of more primitive parent bodies than do meteorites. It is now recognized that many large, dark primitive asteroids in the outer main belt, as well as some trans-Neptunian objects, show spectroscopic evidence for aqueous alteration products on their surfaces. Some CS IDPs exhibit large bulk D enrichments similar to those observed in the cometary CP IDPs. While hydrated minerals in comets have not been unambiguously identified to date, the presence of the smectite group mineral nontronite has been inferred from infrared spectra obtained from the ejecta from comet 9P/Tempel 1 during the Deep Impact mission. Recent observations of low temperature sulfide minerals in Stardust mission samples suggest that limited aqueous activity occurred on comet Wild-2. All of these observations, taken together, suggest that the high-carbon hydrated IDPs are abundant and important samples of primitive solar system objects not represented in meteorite collections. Oxygen isotopic compositions of chondrites reflect mixing between a 16O-rich reservoir and a 17O,18O-rich reservoir produced via mass-independent fractionation. The composition of the 16O-rich reservoir is well constrained but material representing the 17O,18O-rich end-member is rare. Self-shielding models predict that cometary water, presumed to represent this reservoir, should be enriched in 17O and 18O by greater than 200 per mille. The high-carbon hydrated IDPs may be among the best materials available to search for preserved "cometary" H2O signatures. In order to better understand the origin and evolution of these particles, we have obtained 10 hydrated interplanetary dust particles for coordinated mineralogical, isotopic and organic analyses. We have previously reported the results of mineralogical and O isotopic measurements of two hydrated IDPs; here we present results of O isotopic measurements of three additional IDPs. Samples and Methods: Three interplanetary dust particles (L2079C35, L2083D46 and L2083E46) were embedded in S and partially ultramicrotomed into approximately 70 nanometer sections for analysis via transmission electron microscopy (TEM). The remainders of the unsliced particles were removed from S and pressed into high purity Au foil that was cleaned with HF acid and annealed at 800 degrees Centigrade. The pressed IDPs were analyzed via electron microprobe analysis (EPMA) for quantitative bulk chemical analysis. After EPMA analysis, the IDPs were subjected to precision O isotope analysis with the UCLA Cameca IMS-1270 ion probe. A 20 kiloelectronvolt, 0.5 nanoangstrom Cs+ primary beam of approximately 15 micrometers diameter was used for each measurement. Small particles of San Carlos olivine and Burma spinel were pressed into the Au foil for use as standards to correct for instrumental mass fractionation. The detection system was configured for multicollection, with 16O measured on a Faraday cup, and 17O and 18O measured on electron multipliers (EMs). Individual analyses consisted of 15 cycles of 10 seconds per cycle. Additionally, two microtome thin sections were measured for H isotopic compositions with the JSC NanoSIMS 50L ion probe. An 8 picoangstrom, 16 kiloelectronvolt Cs plus primary beam was used. Measurements consisted of H, C, 12C, 16O, and 18O collected with EMs in multicollection. Terrestrial biotite and kerogen were used for isotopic standards. A significant challenge in O isotope measurement of hydrated minerals is the interference from 16OH at mass 17O. We ensured that the 17O and 16OH peaks were fully resolved by using a mass resolution of greater than 7000 and by careful analyses of San Carlos olivine, Burma spinel and chlorite hydrated mineral standards. The hydride was further suppressed with a cold finger attached to an LN2 dewar to trap volatiles in the sample chamber. All sputtered ions were counted (i.e. presputtering was not used); after applying background, yield and deadtime corrections, we performed a change-point analysis on our data via R in order to determine when the sample reached sputtering equilibrium; data points collected prior to the change point were excluded. Change-point analysis was also used to determine whether the IDP had completely sputtered. Results: Mineralogy. IDPs C35 and E46 exhibited hydrated mineralogies, Fe-Ni sulfide grains, nanoglobules and occasional enstatite grains distributed throughout a fine-grained Mg-Fe saponite matrix. C35 also contained breunnerite (Mg,Fe)CO3; solar flare tracks were observed in enstatite, indicating minimal atmospheric entry heating. The mineralogy of D46 is dominated by a large FeS grain with a minor component of adhering silicate material. D46 was strongly heated during atmorpheric entry as evidenced by a well-developed magnetite rim. EPMA analyses show that both C35 and E46 have high carbon contents of 20 weight percentage (approximately 6X CI). D46 contains approximately 6 wt.weight percentage C. A significant amount of the carbon is present as carbon nanoglobules. Results: Hydrogen isotopes: Although the bulk delta D values of both sections of L2079C35 were within error of SMOW (minus 33 plus or minus 19 per mille, 1 plus or minus 14 per mille 1 sigma), several delta D-rich hotspots were also identified, reaching 2000 per mille. As shown in Fig. 1, these hotspots are clearly associated with discrete carbonaceous inclusions that are akin to nanoglobules found in many meteorites and other IDPs. Oxygen Isotopes. Results of the oxygen isotope measurements are shown in Figure 1. The oxygen isotope composition for L2079C35 was delta 18O equals plus11.6 plus or minus 1.9per mille, delta 17O equals plus 7.9 plus or minus 1.9per mille (2 standard errors). The oxygen isotope composition for L2083D46 was delta 18O equals minus 8.1 plus or minus 1.9 per mille, delta 17O equals minus 6.4 plus or minus 3.1 per mille (2 standard errors). The oxygen isotope composition for L2083E46 was delta 18O equals plus 12.0 plus or minus 1.9 per mille, delta 17O equals plus 9.2 plus or minus 2.0 per mille (2 standard errors). Discussion: Despite mineralogical similarities to highly aqueously altered carbonaceous chondrites, the hydrated IDPs we analyzed have oxygen isotopic compositions that are distinct from matrix materials in the CI, CM, and CR chondrites. The IDPs plot along the Young-Russell line, with delta 17O values for C35 and E46 suggestive of interaction with a 16O-poor reservoir. However, we have thus far not observed evidence of extreme 16O-poor reservoirs expected from self-shielding models and observed in Acfer 094 simplectite. The high carbon contents of the IDPs also set them apart from known meteoritic samples. The lack of atmospheric entry heating effects are consistent with low encounter velocities and suggest either an asteroidal source, or a low inclination, low eccentricity cometary origin. Conclusions: The unusual oxygen isotopic compositions, high carbon contents, and the abundance of Drich nanoglobules, together, suggest that the high-carbon, hydrated IDPs are derived from a primitive source that is not yet represented in meteorite collections.

Snead, C. J.↗
NASA NTRS2026

Machine Learning for Predicting Team Functioning in HERA Missions

Team functioning is integral to success in future long term space exploration missions. Proactively detecting declines in team functioning can mitigate conflict and ensure mission success. This project developed a speech-based artificial intelligence (AI) system that unobtrusively predicts degradation in team functioning, including performance and cohesion, in the Human Exploration Research Analog (HERA) Campaigns 4 and 5. The AI system conducted automated analysis of the prosodic (tone of voice) and linguistic (language content) components of speech, modeling interpersonal dynamics at both the turn-taking and day-wide levels. We investigated team functioning via observing structured interactions (i.e., multi-mission space exploration vehicle-extra vehicular activity [MMSEV-EVA], team interaction battery [TIB]) and unstructured interactions before the MMSEV-EVA task. We developed machine learning models to predict team functioning (objective task accuracy, self reported team efficacy and self reported team cohesion) by analyzing OpenSmile acoustic features, linguistic descriptors extracted via the linguistic inquiry and word count (LIWC) dictionary, and semantic embeddings. In the TIB, static models using logistic regression and random forests were not able to predict task accuracy, but predicted team efficacy and cohesion during both the decision making and relational tasks to a moderate level (60-70%). Majority voting on the individual turns to predict day long team efficacy further increased accuracies (70-80%). Finally, long short-term memory (LSTM) models showed the best performance across all variables (80-91%), including task performance. In the MMSEV-EVA, static models achieved an accuracy of 60% with majority voting, which increased to 80% through the incorporation of mission day as a variable, accounting for the learning effect. A key finding across both tasks was the "team-dependent" nature of these interactions; models achieved much higher accuracy when trained on prior days of the same team's data rather than attempting to generalize across entirely different teams, with even 1-2 days of prior data per team achieving 5-15% improvement over team-independent models. In addition, the incorporation of pre-task data from the same team also improves model performance, e.g., incorporating data from the decision-making task of the TIB, which preceded the relational task, improved the prediction of team efficacy and cohesion during the latter. We compared model performance when trained on machine-generated data compared to data that had been further corrected by human annotators. Overall, models trained on human-corrected data exhibited a modest improvement in performance, particularly when acoustic features were used. We found no significant correlation between word error rate (WER) and model accuracy (r(55) = -0.08, p = 0.51), but model’s accuracy was significantly higher for medium/high quality transcription (0.74 (SD = 0.48)) compared to the low-quality group (0.64 (SD = 0.36)) (t(63)=2.82, p = 0.006). Based on these, several design recommendation emerge, that could inform Standards at NASA. Models predicting team functioning should incorporate at least one to two days of historical interaction data, include brief pre-task discussions, and explicitly model temporal learning effects, especially for longer operational tasks. Minimum quality standards for automated speech-processing pipelines are needed, given the performance gains observed with manually corrected acoustic data. Finally, systems should leverage both acoustic features and language embeddings in complementary ways, with modality choices and fusion strategies tailored to mission context, task demands, and data quality requirements.

Shrivatsa Mishra↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗