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At least 127 records · Page 7

Measurement of the muon anomalous precession frequency in runs 4, 5, and 6 of the muon ${g}-2$ Experiment at Fermilab

The Fermilab E989 Muon $g-2$ experiment measures the muon's anomalous magnetic moment to a precision of 127 parts per billion, as reported in June 2025. The value is proportional to the difference between the muon's cyclotron frequency and the spin precession frequency in the presence of a uniform magnetic field, for muons contained within the $g-2$ storage ring. Spin precession frequency is extracted from the time distribution of the muon's decay positrons recorded by 24 electromagnetic calorimeters positioned around the inner circumference of the storage ring. The anomalous precession frequency is one of the primary experimental inputs necessary to estimate the anomalous magnetic moment, the other being the measurement of the magnetic field. This dissertation details the anomalous precession frequency extraction, including reconstruction, time-distribution fitting, and treatment of systematic uncertainties for the final three data-collection runs: Run-4, Run-5, and Run-6. This data represents a fourfold increase in statistics over the previous analysis release, halving the statistical uncertainty. The residual slow term from previous analyses is now well understood and documented in a systematic treatment. As of the writing of this dissertation, the theoretical prediction for the SM estimate of the muon's anomalous magnetic moment is under debate, with two competing prediction methods, so a definitive comparison with theory is not available. The results submitted for experimental release use the kernel-ratio asymmetry method, contributing 115 parts per billion to the statistical uncertainty and 34 parts per billion to the systematic uncertainty. When combined with the previous analyses in earlier data runs, this thereby improves the measurement beyond the experimental goal and sets the world's most precise measurement of the muon's anomalous magnetic moment.

Israel, Scott Nathan [Boston U.]↗

Measurement of the muon anomalous precession frequency in Runs 4, 5, and 6 of the Muon g-2 experiment at Fermilab

The Fermilab E989 Muon g − 2 experiment measures the muon’s anomalous magnetic moment to a precision of 127 parts per billion, as reported in June 2025. The value is proportional to the difference between the muon’s cyclotron frequency and the spin precession frequency in the presence of a uniform magnetic field, for muons contained within the g − 2 storage ring. Spin precession frequency is extracted from the time distribution of the muon’s decay positrons recorded by 24 electromagnetic calorimeters positioned around the inner circumference of the storage ring. The anomalous precession frequency is one of the primary experimental inputs necessary to estimate the anomalous magnetic moment, the other being the measurement of the magnetic field. This dissertation details the anomalous precession frequency extraction, including reconstruction, time-distribution fitting, and treatment of systematic uncertainties for the final three data-collection runs: Run-4, Run-5, and Run-6. This data represents a fourfold increase in statistics over the previous analysis release, halving the statistical uncertainty. The residual slow term from previous analyses is now well understood and documented in a systematic treatment. As of the writing of this dissertation, the theoretical prediction for the SM estimate of the muon’s anomalous magnetic moment is under debate, with two competing prediction methods, so a definitive comparison with theory is not available. The results submitted for experimental release use the kernel-ratio asymmetry method, contributing 115 parts per billion to the statistical uncertainty and 34 parts per billion to the systematic uncertainty. When combined with the previous analyses in earlier data runs, this thereby improves the measurement beyond the experimental goal and sets the world’s most precise measurement of the muon’s anomalous magnetic moment.

Israel, Scott Nathan [Boston U.]↗

Subsurface Nitrogen Dissociation Kinetics in Lithium Metal from Metadynamics

The dissociation of molecular nitrogen in lithium is of interest for several promising technologies, such as the catalytic synthesis of ammonia in ambient or mild conditions. In this work we simulate nitrogen dissociation in the lithium BCC (110) surface at ambient and elevated temperatures using density functional theory (DFT) metadynamics simulations. The rate constants at temperatures of 300, 400, and 500 K are calculated by statistical analysis of the reaction time distributions from the accelerated simulations. This approach finds and estimates rate constants for transition pathways out of the initial state; the required input is the stable initial state and a reasonable choice of collective variable. A single collective variable is used in this case: the N–N distance. The results are robust to changes in metadynamics parameters, and the reaction time distributions follow the expected exponential distribution. We show that the metadynamics-derived rate constants are in agreement with results from the conventional harmonic approximation approach using a climbing image nudged elastic band (NEB) transition state search. The reaction barriers from metadynamics and the NEB/harmonic approximation agree to within 0.02–0.04 eV at all temperatures studied. This paper demonstrates that the harmonic approximation provides an accurate description of the rate constants for nitrogen dissociation in lithium metal, even at temperatures near or above the melting point of lithium, lending credence to previous and future theoretical studies using this approximation. Moreover, this work demonstrates a step toward the automated exploration and discovery of reaction mechanisms and associated rate constants for elementary surface-catalyzed reactions using DFT-based metadynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks

This work proposes and develops an implementation of a fault location method to provide a fast and resilient protection scheme for power distribution systems. The method analyzes the transient dynamics of traveling waves (TWs) to generate features using the discrete wavelet transform (DWT), which are then used to train several graph convolutional network (GCN) models. Faults are simulated in the IEEE 34-node system, which is divided into three protection zones (PZs). The goal is to identify the PZ in which the fault occurs. The GCN models create a distributed protection scheme, as all nodes are able to retrieve a prediction. Given that message-passing between nodes occurs both during training and in the execution of the model, the resiliency of such schemes to communication losses was analyzed and demonstrated. One of the models, which only uses voltage measurements, was implemented on a Texas Instruments F28379D development board. The execution times were monitored to assess the speed of the protection scheme. It is shown that the proposed method can be executed in approximately a millisecond, which is comparable to existing TW protection in the transmission system. For experimental purposes, a DWT-based detection method is employed. A design of a setup to playback TWs using two development boards is also addressed.

Jiménez-Aparicio, Miguel (ORCID:000000016864461X)↗

Relationship between ATS-6 spacecraft-charging occurrences and warm plasma encounters

The occurrences in local time of spacecraft-charging and warm plasma events observed by the University of California at San Diego plasma detector on ATS-6 have been examined using data from 40 contiguous orbits. The local time distribution of charging events was found to maximize between local midnight and dawn and was also similar to the distribution of synchronous spacecraft anomalies reported by others. More than half of the charging events had potentials of -50 V or more, and potentials on the order of -1000 V were observed. All of the spacecraft charging events reported in this paper occurred during sunlit conditions. The warm plasma encounters were concentrated in the local noon-to-dusk sector, and the local-time distributions of charging events and warm plasma encounters were found to be anticorrelated.

Reasoner, D. L.↗

Engineering advancements in microfluidic systems for enhanced mixing at low Reynolds numbers

Mixing within micro- and millichannels is a pivotal element across various applications, ranging from chemical synthesis to biomedical diagnostics and environmental monitoring. The inherent low Reynolds number flow in these channels often results in a parabolic velocity profile, leading to a broad residence time distribution. Achieving efficient mixing at such small scales presents unique challenges and opportunities. This review encompasses various techniques and strategies to evaluate and enhance mixing efficiency in these confined environments. It explores the significance of mixing in micro- and millichannels, highlighting its relevance for enhanced reaction kinetics, homogeneity in mixed fluids, and analytical accuracy. We discuss various mixing methodologies that have been employed to get a narrower residence time distribution. The role of channel geometry, flow conditions, and mixing mechanisms in influencing the mixing performance are also discussed. Various emerging technologies and advancements in microfluidic devices and tools specifically designed to enhance mixing efficiency are highlighted. We emphasize the potential applications of micro- and millichannels in fields of nanoparticle synthesis, which can be utilized for biological applications. Additionally, the prospects of machine learning and artificial intelligence are offered toward incorporating better mixing to achieve precise control over nanoparticle synthesis, ultimately enhancing the potential for applications in these miniature fluidic systems.

Biochemistry & Molecular Biology↗

Designing and Developing Web-Based Administrative Tools for Program Management

The task assigned for this internship was to develop a new tool for tracking projects, their subsystems, the leads, backups, and other employees assigned to them, as well as all the relevant information related to the employee (WBS (time charge) codes, time distribution, certifications, and assignments). Currently, this data is tracked manually using a number of different spreadsheets and other tools simultaneously by a number of different people; some of these documents are then merged into one large document. This often leads to inconsistencies and loss in data due to human error. By simplifying the process of tracking this data and aggregating it into a single tool, it is possible to significantly decrease the potential for human error and time spent collecting and checking this information. II. Objective The main objective of this internship is to develop a web-based tool using Ruby on Rails to serve as a method of easily tracking projects, subsystems, and points of contact, along with employees, their assignments, time distribution, certifications, and contact information. Additionally, this tool must be capable of generating a number of different reports based on the data collected. It was important that this tool deliver all of this information using a readable and intuitive interface.

Material↗

Data and scripts associated with “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” (v3)

This data package is associated with the publication “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” submitted to Journal of Advances in Modeling Earth Systems (Butler et al. 2025). This study developed the Sequential Precipitation Input Tagging (SPIT) framework to tag input precipitation and estimate water transit times and hydrologic tracers. SPIT tags all precipitation events at regular intervals over an extended period (monthly tags over seven years) in a hydrologic model from 2016-2022. SPIT is applied at six National Ecological Observatory Network (NEON) sites across the continental United States to calculate transit time distributions (TTD) and derive from these mean transit times (MTT), fractions of young water (Fyw), and hydrologic tracer concentrations in stream water (δ18O) within a water-tagging enabled version of the Weather Research and Forecast (WT-WRF-Hydro) model with national water model (NWM) configurations. We go on to validate WT-WRF-Hydro estimates against Butler et al. (2023), who analyzed the same NEON sites using stable water isotope data to estimate water transit times. This new tracking method provides a detailed picture of water movement and helps improve predictions about water availability in the future. This data package was originally published in January 2025. It was updated May 2025 (v2; new and modified files) and October 2025 (v3; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. This data package contains the data and scripts used to develop the SPIT framework WT-WRF-Hydro (Water Tagging Weather Research and Forecasting Hydrologic) model and is associated with the following GitHub repository: https://github.com/zbutler33/SPIT-Framework. This data package contains five parent folders: (1) “Manipulated_outputs”, (2) “Metadata”, (3) “Observed”, (4) “Outputs”, and (5) “Scripts”. Each of these parent folders contains additional subfolders and files. Please see the FLMD (“v*_Butler_2024_WT_WRF_Hydro_flmd.csv”) for a list of all the files contained in this data package and descriptions for each. See the data dictionary (“v*_Butler_2024_WT_WRF_Hydro_dd.csv”) for definitions and units of all of the tabular (files ending in “.csv” and ".tsv") column headers.

54 ENVIRONMENTAL SCIENCES↗

Empirical Mode Decomposition and Hilbert Spectral Analysis

The difficult facing data analysis is the lack of method to handle nonlinear and nonstationary time series. Traditional Fourier-based analyses simply could not be applied here. A new method for analyzing nonlinear and nonstationary data has been developed. The key part is the Empirical Mode Decomposition (EMD) method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF) that serve as the basis of the representation of the data. This decomposition method is adaptive, and, therefore, highly efficient. The IMFs admit well-behaved Hilbert transforms, and yield instantaneous energy and frequency as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. Among the main conceptual innovations is the introduction of the instantaneous frequencies for complicated data sets, which eliminate the need of spurious harmonics to represent nonlinear and nonstationary signals. Examples from the numerical results of the classical nonlinear equation systems and data representing natural phenomena are given to demonstrate the power of this new method. The classical nonlinear system data are especially interesting, for they serve to illustrate the roles played by the nonlinear and nonstationary effects in the energy-frequency-time distribution.

Huang, Norden E.↗

Rates and properties of Type Ia supernovae in galaxy clusters within the dark energy survey

We identify 66 photometrically classified Type Ia supernovae (SNe Ia) from the Dark Energy Survey (DES) that have occurred within red-sequence selected galaxy clusters. We compare light-curve and host galaxy properties of the cluster SNe to 1024 DES SNe Ia located in field galaxies, the largest comparison of two such samples at high redshift (z > 0.1). We find that cluster SN light curves decline faster than those in the field (97.7 per cent confidence). However, when limiting these samples to host galaxies of similar colour and mass, there is no significant difference in the SN light-curve properties. Motivated by previous detections of a higher-normalized SN Ia delay-time distribution in galaxy clusters, we measure the intrinsic rate of SNe Ia in cluster and field environments. We find the average ratio of the SN Ia rate per galaxy between high-mass (⁠|$10\le \log \mathrm{(\mathit{ M}_{*}/{\rm \mathit{ M}}_{\odot })} \le 11.25$|⁠) cluster and field galaxies to be 0.594 ± 0.068. This difference is mass-dependent, with the ratio declining with increasing mass, which suggests that the stellar populations in cluster hosts are older than those in field hosts. We show that the mass-normalized rate (or SNe per unit mass) in massive–passive galaxies is consistent between cluster and field environments. Additionally, both of these rates are consistent with rates previously measured in clusters at similar redshifts. We conclude that in massive–passive galaxies, which are the dominant hosts of cluster SNe, the cluster delay-time distribution is comparable to the field.

79 ASTRONOMY AND ASTROPHYSICS↗

Dependence of ion-cyclotron range of frequencies instabilities on species mix and fast-ion distribution: II. Time evolution

Dedicated DIII-D experiments studied instabilities below the ion cyclotron frequency f ci and at cyclotron harmonics by injecting thirteen different neutral beam populations into plasmas with different thermal compositions of H and D at five different values of toroidal field. The resulting database of 2529 conditions is described in Part 1: Stability. This paper focuses on the temporal evolution. For some beam geometries, the ion cyclotron emission (ICE) is much stronger at the beginning of injection, suggesting the importance of ‘bump-on-tail’ energy drive. Sawtooth crashes cause the emission to cease for some beam types and emission bands, but the opposite effect occurs for others. When unstable, for virtually all conditions and frequency bands, the emission bursts in a cycle reminiscent of predator-prey oscillations. Evidence for nonlinear interaction between ICE harmonics is observed. Strongly unstable modes typically appear within 1 ms from the start of beam injection and often decay within 0.1 ms when the beam turns off, but both the initial rise and final decay of the mode power exhibit a wide variety of behavior.

electromagnetic ion cyclotron instabilities↗

Precise RF timing signal distribution to remote stations

A method and apparatus are disclosed for distributing a stable reference frequency from a hydrogen maser frequency standard, or similar RF source, to remote stations over great distances with very good phase stability, and with constant amplitude, at each distribution point using a light beam carrier. A technique for providing automatic gain control at an optical receiver with phase stability in the RF reference is provided.

Lutes, G. F.↗

Photon and radiowave emission from peeling pressure sensitive adhesives in air

During separation of an adhesive from a polymer substrate in air, intense bursts of photons ('phE', for photon emission) and long wavelength electromagnetic radiation ('RE', for radiowave emission), similar to those reported earlier by Deryagin, et al. (1978) have been observed. In this paper, careful measurements of the phE time distributions, as well as time correlations between bursts of phE and RE, are reported. These results support the view that patches of electrical charge produced by charge separation between dissimilar materials lead to microdischarges in and near the crack tip. The role of these discharges in producing sustained phE after the discharge has been extinguished is also discussed.

Donaldson, E. E.↗

Performance issues for domain-oriented time-driven distributed simulations

It has long been recognized that simulations form an interesting and important class of computations that may benefit from distributed or parallel processing. Since the point of parallel processing is improved performance, the recent proliferation of multiprocessors requires that we consider the performance issues that naturally arise when attempting to implement a distributed simulation. Three such issues are: (1) the problem of mapping the simulation onto the architecture, (2) the possibilities for performing redundant computation in order to reduce communication, and (3) the avoidance of deadlock due to distributed contention for message-buffer space. These issues are discussed in the context of a battlefield simulation implemented on a medium-scale multiprocessor message-passing architecture.

Nicol, David M.↗

Some observations on the role of planetary waves in determining the spring time ozone distribution in the Antarctic

Ozone measurements from 1970 to 1984 from the Nimbus 4 backscattered ultraviolet and the Nimbus 7 solar backscattered ultraviolet spectrometers show significant decrease in total ozone only after 1979. The downward trend is most apparent in October south of 70 deg S in the longitude zone 0 to 30 deg W where planetary wave activity is weak. Outside this longitude region, the trend in total ozone is much smaller due to strong interannual variability of wave activity. This paper gives a phenomenological description of ozone depletion in the Antarctic region based on vertical advection and transient planetary waves.

Chandra, S.↗