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DOE OSTI2025

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

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

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

DOE OSTI2026

Reliable statistics-based detection and investigation of anomalies in a SMART valve system

Reliable anomaly detection and diagnosis are critical for the safe operation of complex engineered systems. This study presents a unified framework that integrates statistical, model-based, and data-driven techniques for anomaly detection and investigation, demonstrated on SMART valve systems in hybrid energy applications. Four detection methods—mean deviation, seasonal extreme studentized deviate, ARIMA forecasting, and matrix profiling—were implemented and compared. Matrix profiling was particularly effective in revealing subtle deviations and hidden relationships among variables. Anomaly investigation was performed by analyzing variable-level and grouped signal profiles, with system topology incorporated to distinguish primary faults from propagated effects. Grouping signals by type enhanced interpretability, enabling accurate localization of anomalies across multi-dimensional datasets. Experimental results confirmed the framework's capability to consistently detect and isolate anomalies while providing actionable insights into system interdependencies. The proposed methodology offers a robust, interpretable, and scalable solution for condition monitoring, with potential applications in safety-critical domains such as nuclear energy, aerospace, and process industries.

ARIMA models↗

NASA NTRS2006

The Sloan Lens ACS Survey. I. A Large Spectroscopically Selected Sample of Massive Early-Type Lens Galaxies

The Sloan Lens ACS (SLACS) Survey is an efficient Hubble Space Telescope (HST) Snapshot imaging survey for new galaxy-scale strong gravitational lenses. The targeted lens candidates are selected spectroscopically from the Sloan Digital Sky Survey (SDSS) database of galaxy spectra for having multiple nebular emission lines at a redshift significantly higher than that of the SDSS target galaxy. The SLACS survey is optimized to detect bright early-type lens galaxies with faint lensed sources in order to increase the sample of known gravitational lenses suitable for detailed lensing, photometric, and dynamical modeling. In this paper, the first in a series on the current results of our HST Cycle 13 imaging survey, we present a catalog of 19 newly discovered gravitational lenses, along with nine other observed candidate systems that are either possible lenses, nonlenses, or nondetections. The survey efficiency is thus >=68%. We also present Gemini 8 m and Magellan 6.5 m integral-field spectroscopic data for nine of the SLACS targets, which further support the lensing interpretation. A new method for the effective subtraction of foreground galaxy images to reveal faint background features is presented. We show that the SLACS lens galaxies have colors and ellipticities typical of the spectroscopic parent sample from which they are drawn (SDSS luminous red galaxies and quiescent MAIN sample galaxies), but are somewhat brighter and more centrally concentrated. Several explanations for the latter bias are suggested. The SLACS survey provides the first statistically significant and homogeneously selected sample of bright early-type lens galaxies, furnishing a powerful probe of the structure of early-type galaxies within the half-light radius. The high confirmation rate of lenses in the SLACS survey suggests consideration of spectroscopic lens discovery as an explicit science goal of future spectroscopic galaxy surveys.

galaxies↗

NASA NTRS1993

Satellite orbit and data sampling requirements

Climate forcings and feedbacks vary over a wide range of time and space scales. The operation of non-linear feedbacks can couple variations at widely separated time and space scales and cause climatological phenomena to be intermittent. Consequently, monitoring of global, decadal changes in climate requires global observations that cover the whole range of space-time scales and are continuous over several decades. The sampling of smaller space-time scales must have sufficient statistical accuracy to measure the small changes in the forcings and feedbacks anticipated in the next few decades, while continuity of measurements is crucial for unambiguous interpretation of climate change. Shorter records of monthly and regional (500-1000 km) measurements with similar accuracies can also provide valuable information about climate processes, when 'natural experiments' such as large volcanic eruptions or El Ninos occur. In this section existing satellite datasets and climate model simulations are used to test the satellite orbits and sampling required to achieve accurate measurements of changes in forcings and feedbacks at monthly frequency and 1000 km (regional) scale.

Rossow, William↗

DOE OSTI2025

Collaborative: in situ visual analytics technologies for extreme scale combustion simulations

This project aims to drastically enhance the usability of in situ analysis and visualization for extreme-scale scientific simulations. Current exascale computing capabilities promise to offer greater predictive ability of simulations and to further push the frontiers of science and technology. However, to validate the simulation output at extreme scale, examine the modeled phenomena, and discover previously unknowns from the output data, the output must be reduced or transformed in situ as it is being generated during the simulation such that the amount of data to examine and store is kept to a minimum. Such in situ approaches allow us to process and analyze the data and any embedded geometry to an extent that would be prohibitively expensive, if not impossible, to perform as a post hoc task. While in situ processing has been demonstrated to be a feasible and promising approach, its full potential has not yet been leveraged. In this project, we have developed comprehensive enhancements to in situ technology based on probability distributions in data. Our research focuses on jointly developing new ways of interacting with massive statistical samples while creatively utilizing new state-of-the-art computational resources to push the boundaries of in situ exploration. Moreover, we have developed new time-dependent techniques to enable previously unattainable capabilities in areas such as intelligent simulation steering and precise feature identification. We have experimentally studied our design and implementation at NERSC and OLCF, and are able to leverage existing in situ infrastructures whenever possible. While the exemplar in this project is combustion, many other fields for which turbulent transport is important, e.g., fusion, climate, astrophysics among others, encounter similar issues as simulations scale up to the exascale. This project shows its potential to generate high impact on DOE missions since the resulting technology promises to improve scientists’ ability to rapidly and correctly interpret and tune extreme-scale simulations, leading to new scientific understanding and advancements.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1994

Magnetospheric-ionospheric Poynting flux

Over the past three years of funding SRI, in collaboration with the University of Texas at Dallas, has been involved in determining the total electromagnetic energy flux into the upper atmosphere from DE-B electric and magnetic field measurements and modeling the electromagnetic energy flux at high latitudes, taking into account the coupled magnetosphere-ionosphere system. This effort has been very successful in establishing the DC Poynting flux as a fundamental quantity in describing the coupling of electromagnetic energy between the magnetosphere and ionosphere. The DE-B satellite electric and magnetic field measurements were carefully scrutinized to provide, for the first time, a large data set of DC, field-aligned, Poynting flux measurement. Investigations describing the field-aligned Poynting flux observations from DE-B orbits under specific geomagnetic conditions and from many orbits were conducted to provide a statistical average of the Poynting flux distribution over the polar cap. The theoretical modeling effort has provided insight into the observations by formulating the connection between Poynting's theorem and the electromagnetic energy conversion processes that occur in the ionosphere. Modeling and evaluation of these processes has helped interpret the satellite observations of the DC Poynting flux and improved our understanding of the coupling between the ionosphere and magnetosphere.

Thayer, Jeffrey P.↗

NASA NTRS2009

Bayes Analysis and Reliability Implications of Stress-Rupture Testing a Kevlar/Epoxy COPV using Temperature and Pressure Acceleration

Composite Overwrapped Pressure Vessel (COPVs) that have survived a long service time under pressure generally must be recertified before service is extended. Sometimes lifetime testing is performed on an actual COPV in service in an effort to validate the reliability model that is the basis for certifying the continued flight worthiness of its sisters. Currently, testing of such a Kevlar49(registered TradeMark)/epoxy COPV is nearing completion. The present paper focuses on a Bayesian statistical approach to analyze the possible failure time results of this test and to assess the implications in choosing between possible model parameter values that in the past have had significant uncertainty. The key uncertain parameters in this case are the actual fiber stress ratio at operating pressure, and the Weibull shape parameter for lifetime; the former has been uncertain due to ambiguities in interpreting the original and a duplicate burst test. The latter has been uncertain due to major differences between COPVs in the data base and the actual COPVs in service. Any information obtained that clarifies and eliminates uncertainty in these parameters will have a major effect on the predicted reliability of the service COPVs going forward. The key result is that the longer the vessel survives, the more likely the more optimistic stress ratio is correct. At the time of writing, the resulting effect on predicted future reliability is dramatic, increasing it by about one nine , that is, reducing the probability of failure by an order of magnitude. However, testing one vessel does not change the uncertainty on the Weibull shape parameter for lifetime since testing several would be necessary.

Phoenix, S. Leigh↗

NASA NTRS2005

CSAM Metrology Software Tool

CSAM Metrology Software Tool (CMeST) is a computer program for analysis of false-color CSAM images of plastic-encapsulated microcircuits. (CSAM signifies C-mode scanning acoustic microscopy.) The colors in the images indicate areas of delamination within the plastic packages. Heretofore, the images have been interpreted by human examiners. Hence, interpretations have not been entirely consistent and objective. CMeST processes the color information in image-data files to detect areas of delamination without incurring inconsistencies of subjective judgement. CMeST can be used to create a database of baseline images of packages acquired at given times for comparison with images of the same packages acquired at later times. Any area within an image can be selected for analysis, which can include examination of different delamination types by location. CMeST can also be used to perform statistical analyses of image data. Results of analyses are available in a spreadsheet format for further processing. The results can be exported to any data-base-processing software.

Vu, Duc↗

DOE OSTI2025

Moving beyond post hoc explainable artificial intelligence: a perspective paper on lessons learned from dynamical climate modeling

AI models are criticized as being black boxes, potentially subjecting climate science to greater uncertainty. Explainable artificial intelligence (XAI) has been proposed to probe AI models and increase trust. In this review and perspective paper, we suggest that, in addition to using XAI methods, AI researchers in climate science can learn from past successes in the development of physics-based dynamical climate models. Dynamical models are complex but have gained trust because their successes and failures can sometimes be attributed to specific components or sub-models, such as when model bias is explained by pointing to a particular parameterization. We propose three types of understanding as a basis to evaluate trust in dynamical and AI models alike: (1) instrumental understanding, which is obtained when a model has passed a functional test; (2) statistical understanding, obtained when researchers can make sense of the modeling results using statistical techniques to identify input–output relationships; and (3) component-level understanding, which refers to modelers' ability to point to specific model components or parts in the model architecture as the culprit for erratic model behaviors or as the crucial reason why the model functions well. We demonstrate how component-level understanding has been sought and achieved via climate model intercomparison projects over the past several decades. Such component-level understanding routinely leads to model improvements and may also serve as a template for thinking about AI-driven climate science. Currently, XAI methods can help explain the behaviors of AI models by focusing on the mapping between input and output, thereby increasing the statistical understanding of AI models. Yet, to further increase our understanding of AI models, we will have to build AI models that have interpretable components amenable to component-level understanding. We give recent examples from the AI climate science literature to highlight some recent, albeit limited, successes in achieving component-level understanding and thereby explaining model behavior. The merit of such interpretable AI models is that they serve as a stronger basis for trust in climate modeling and, by extension, downstream uses of climate model data.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1975

Regional tectonic evaluation of the Tuscan Apenine, vulcanism, thermal anomalies and the relation to structural units

The author has identified the following significant results. The geological interpretation on data exhibiting the Italian peninsula led to the recognition of tectonic features which are explained by a clockwise rotation of various blocks along left-handed transform faults. These faults can be interpreted as resulting from shear due to main stress directed north-eastwards. A land use map of the mountainous regions of Italy was produced on a scale of 1:250,000. For the digital treatment of MSS-CCTs an image processing software was written in FORTRAN 4. The software package includes descriptive statistics and also classification algorithms.

Bodechtel, J.↗

NASA NTRS1987

Study of one-dimensional spectral dynamic equations of the Reynolds stresses in homogeneous anisotropic turbulence: Application to split-spectrum modeling

The CTR numerical data base generated by direct simulation of homogeneous anisotropic turbulence was used to calculate all of the terms in the spectral balance equations for the turbulent Reynolds stresses. The aim in not only to test the main closure assumptions used in the split-spectrum models, but also to try to devise improved hypotheses deduced from the statistical information. Numerical simulations of turbulent flows provide a large amount of data, a thought provoking wealth of information. The main advantage of this type of comparison is that a great variety of flows can be considered, and this is necessary to test closure hypotheses. Moreover various initial conditions can be introduced in the calculation, even if they are not experimentally feasible. All the terms in the spectral equations can be calculated. The limited Reynolds numbers of the simulations and the statistical noise caused by a small sample, particularly at the large scales, causes some difficulty in the interpretation of the results, but the method of approach proved to be a powerful tool for testing and improving spectral closures.

Schiestel, R.↗

NASA NTRS2019

Intensity Mapping in the Presence of Foregrounds and Correlated Continuum Emission

Intensity mapping has attracted significant interest as an approach to measuring the properties of the interstellar medium in typical galaxies at high redshift. Intensity mapping measures the statistics of surface brightness as a function of frequency, making it sensitive to not only all line emission of interest but also radiation from all other sources. Significant effort has gone into developing approaches that reject foreground contamination. Additionally, the target galaxies have multiple sources of emission that can complicate the interpretation of the line brightness.We describe the problem of jointly estimating correlated continuum emission and cleaning uncorrelated continuum emission, such as from the Milky Way. We apply these considerations to a cross-correlation of Planck data with BOSS quasars for a determination of [C II] for 2 < z < 3.2. Intensity mapping surveys with few bands have unique challenges for treating foregrounds and avoiding bias from correlated continuum emission. We show how a future intensity mapping survey with many bands can separate line from continuum emission in cross-correlation.

Switzer, E. R.↗

DOE OSTI2026

Can ERA5 Be Used to Study Mesoscale Convective System Climatological Characteristics?

Mesoscale convective systems (MCSs) produce more than half of tropical rainfall and are central to the global hydrologic cycle. As the climate warms, environments favorable for MCSs may become more common; however, limited observational records hamper understanding of how MCSs respond to variations and changes in their environments. Here, we evaluate how well MCSs are represented in ERA5, a widely used global high‐resolution reanalysis product. Using PyFLEXTRKR, which jointly tracks top‐of‐atmosphere infrared brightness temperature and surface precipitation, we identified MCSs in ERA5 and compared them with those identified in satellite observations using the same detection algorithm. This comparison analysis spans 2007–2020 using hourly data at 0.25° horizontal resolution focusing over the tropics. ERA5 reproduces observed brightness‐temperature statistics and captures the geographic distribution and seasonal and diurnal cycles of MCS cold cloud shields. However, ERA5 precipitation exhibits an intensity bias—too much light rain and too little heavy rain—which shifts the rain‐rate distribution and reduces the frequency of MCSs relative to observations. Within MCSs, ERA5 precipitation exhibits the same pattern of bias, yielding a systematic underestimation of MCS precipitation intensity. Consistent with these biases, ERA5 underestimates the contribution of MCS to tropical rainfall by 25%–34% in key regions. Overall, ERA5 is suitable for studying MCS cold cloud‐shield climatology and evolution, but precipitation‐based MCS characteristics (including event‐level precipitation features and the geospatial distribution of MCS precipitation) should be interpreted with caution. These findings clarify which aspects of MCS behavior are robustly represented in ERA5 for climatological applications.

mesoscale convection↗

NASA NTRS1975

Utilization of satellite data for inventorying prairie ponds and lakes. LANDSAT-1 data were used to discriminate ponds and lakes for waterfowl management

The author has identified the following significant results. The mapping of open water as an indicator of waterfowl habitat quality was carried out by using two different recognition techniques, a single waveband thresholding approach and a multiple waveband approach termed proportion estimation. The single waveband technique has proven simple to implement. Its computer algorithm was rapid and accurately recognized prairie lakes and large ponds. The resultant products of this processing technique were thematic maps and statistical tabulations describing open surface water conditions. The maps served to portray visually the location and frequency of surface water bodies but usually necessitated additional interpretation.

Gilmer, D. S.↗

NASA NTRS1994

Searching for hard X-ray directivity during the rise, peak, and decay phases of solar flares

We have identified 72 large solar flares (peak counting rates more than 1000 counts/s) observed by Hard X-ray Burst Spectroscopy (HXRBS) on-board the Solar Maximum Mission (SMM). Using a database of these flares, we have studied hard X-ray (50-850 keV) spectral center-to-limb variation and its evolution with time. The major results are the following: (1) During the rise phase, the center-to-limb spectral variation is small, with a hardness of delta delta = 0.02 +/- 0.25, and a statistical significance of 0.1 sigma. (2) During the peak phase, the center-to-limb variation is delta delta = 0.13 +/- 0.13, with a statistical significance of 1 sigma. (3) During the decay phase, the center-to-limb variation changes to softening. The softness is relatively large with delta delta = -0.25 +/- 0.21, and a statistical significance of 1.2 sigma. (4) The linear least-squares fits to the spectral center-to-limb variations do not have slopes significantly different from zero during all those three phases. (5) The center events and limb events spectral distributions are shown to be not different by using Kolmogorov-Smirnov two-samples test. (6) The fraction of events detected near the limb is marginally consistent with that expected from isotropically emitting flares. (7) On average, flares evolve as soft-hard-soft. These results suggest that there is no statistically significant evidence for hard X-ray directivity during the rise, peak, and decay phases of solar flares. The hard X-ray radiation pattern at those energies is almost isotropic during all those phases. This lack of directivity (or anisotropy) found in this study is not in agreement with the results discovered by Vestrand et al. (1987) in which they found energetic photon source is anisotropic, using SMM Gamma-Ray Spectrometer (GRS) data at a much higher energy band of 0.3-1 MeV. If we want to interpret the results of Vestrand et al. (1987) and our present results in a self-consistent way, we must conclude that at energies of greater than 50 keV, the Compton backscattering suppresses the hard X-ray anisotropy sufficiently so that no significant directivity can be measured during the rise, peak, and decay phases of solar flares. during the rise, peak, and decay phases of solar flares.

Li, Peng↗

NASA NTRS2005

Evolution of Galaxies and the Star Formation Rate in the Infrared

A central goal of extragalactic observational astronomy is to understand how normal galaxies evolve with redshift, and particularly when galaxies formed their stars. While optical and rest-frame UV observations have begun to address these issues, the interpretation of such data is particularly challenging because of the sensitivity to dust obscuration (at optical and UV wavelengths). The absorbed light is re-radiated at IR wavelengths, hence the optimal indicators of the star formation rate (SFR) is at a rest-frame wavelength of approx. 60 microns. The Spitzer Space Telescope mission is revolutionizing the study of the global properties and evolution of galaxies. Spitzer reaches nearly two orders of magnitude more sensitivity than previous IR space missions. This research program is to study the SFR using statistical samples of galaxies in the local universe, at intermediate redshifts, and set the stage for continuing studies up to z=5. The overall research program is divided into three main investigations: A Mid-IR Hubble Atlas and SFR estimators in the local universe, Evolution of the SFR at 0 < z < 1 using pencil beam redshift surveys, and Galaxy formation and evolution at 1 < z < 5. The first papers from Spitzer were published during the last year, including ten refereed journal papers where the PI was first or co-author.

Pahre, Michael A.↗

NASA NTRS1976

Substorm observations of magnetic perturbations and ULF waves at synchronous orbit by ATS-1 and ATS-6

In the empirical study of the geomagnetic cavity, the synchronous equatorial orbit has been shown to be a most advantageous site for scientific measurements. Satellites in this orbit are fixed in the earth's main magnetic field so that the records are not dominated by changes due to satellite motion through this field. Also, the satellites traverse the same geometric region of space daily, thus facilitating statistical studies of magnetospheric phenomena. Thirdly, the magnetic field lines leaving the earth's surface near the auroral zone cross the equatorial plane close to this orbit, thus subjecting the region to a number of such phenomena. Previous observations at synchronous orbit with the UCLA fluxgate magnetometers on ATS-1 and ATS-6 have revealed a variety of substorm-associated field variations. These effects may be divided tentatively into two classes, those resulting from instabilities (ULF waves) and those produced by changes in macroscopic current systems. The data and their interpretations will be reviewed in order to illustrate the potential importance of observations in the synchronous orbit during the International Magnetospheric Study.

Coleman, P. J., Jr.↗

NASA NTRS2004

Evolution of Galaxies and the Star Formation Rate in the Infrared

A central goal of extragalactic observational astronomy is to understand how normal galaxies evolve with redshift, and particularly when galaxies formed their stars. While optical and rest-frame UV observations have begun to address these issues, the interpretation of such data is particularly challenging because of the sensitivity to dust obscuration (at optical and UV wavelengths). The absorbed light is reradiated at IR wavelengths, hence the optimal indicators of the star-formation rate (SFR) is at a rest-frame wavelength of approx. 60 microns. The Spitzer Space Telescope mission is beginning to revolutionize the study of the global properties and evolution of galaxies. Spitzer reaches nearly two orders of magnitude more sensitivity than previous IR space missions. This research program is to study the SFR using statistical samples of galaxies in the local universe, at intermediate redshifts, and set the stage for continuing studies up to z=5. The overall research program is divided into three main investigations: A Mid-IR Hubble Atlas and SFR estimators in the local universe, Evolution of the SFR at 0 < z < 1 using pencil beam redshift surveys, and Galaxy formation and evolution at 1 < z < 5. The Spitzer Space Telescope launched during the past year and the first papers from it are currently being submitted to The Astrophysical Journal. This is clearly an exciting time for IR astronomy!

Pahre, Michael A.↗