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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Measurement of the anomalous spin precession frequency $\omega_a$ in the Muon $g-2$ experiment at Fermilab

The muon anomaly, $a_\mu=(g_{\mu}-2)/2$, is a low-energy observable which can be both measured and computed to high precision, making it a sensitive test of the Standard Model (SM) and a probe for new physics. The current discrepancy between the experimental value and the Standard Model calculation from the Muon $g-2$ Theory Initiative is $a_{\mu}^{exp}-a_{\mu}^{SM}=(251\pm59)\cdot10^{-11}$, with a significance of $4.2\,\sigma$.The Fermilab E989 experiment aims, with the full statistical power, to improve by a factor of four the precision of the measurement.In April 2021 the collaboration published the first measurement, based on the first year of data taking.This paper will present the status of the measurement of the anomalous muon spin precession frequency, $\omega_a$, performed on the datasets collected during Run-2 and Run-3 (2019 and 2020 campaigns), with a preliminary projection of the systematic uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Measurement of the muon anomalous precession frequency $\omega_a$ in the Fermilab $g-2$ experiment

The Fermilab Muon $g-2$ Experiment was designed to measure the muon's anomalous magnetic moment $a_{\mu} = (g-2)/2$ to 140 parts per billion. The value of $a_{\mu}$ is proportional to the difference frequency $\omega_a=\omega_s-\omega_c$ between the muon's cyclotron frequency and spin precession frequency in the uniform magnetic field of the $g-2$ storage ring. The frequency $\omega_a$ is extracted from the time distribution of the mu-decay positrons recorded by 24 electromagnetic calorimeters positioned around the inner circumference of the storage ring. We will discuss the various approaches to the frequency determination including the reconstruction, fitting of time distributions, and procedures for handling the effects of gain changes, positron pileup and beam dynamics. We also discuss the data consistency checks and the strategy for the averaging of $\omega_a$ across the different analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Measurement of the anomalous spin precession frequency $\omega_\alpha$ in the Muon g-2 experiment at Fermilab

The Muon $g-2$ Experiment at Fermilab aims to measure the muon magnetic moment anomaly, $a_{\mu} = (g-2)/2$, with a final accuracy of 0.14 parts per million (ppm). A $3.1$-GeV muon beam is injected into a storage ring of $14\,$m diameter, in the presence of a $1.45\,$T magnetic field. The anomaly $a_\mu$ can be extracted by accurately measuring the anomalous muon spin precession frequency $\omega_a$, based on the arrival time distribution of decay positrons observed by $24$ calorimeters, and the magnetic field. In 2023, the experiment published its second result based on the two datasets Run-2 and Run-3, reaching the unprecedented sensitivity of $0.21\,$ppm --- a factor $\sim2.2$ improvement since its first result published in 2021, based on the first dataset (Run-1). In this paper, we will focus on the measurement of the $\omega_a$ frequency, describing the techniques and major sources of systematic uncertainty in the 2023 publication, and outlining the improvements since the 2021 result. We will also cover the status of the ongoing $\omega_a$ analysis for the last three datasets, collected from 2020 to 2023, along with the projected uncertainties on the final Muon $g-2$ measurement at Fermilab.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Precision Measurement of the Muon Spin Precession Frequency in the Fermilab Muon g-2 Experiment

The Fermilab Muon $g-2$ Experiment is designed to measure the muon's anomalous magnetic moment, $ a_\mu = (g-2)/2 $ with an accuracy of 140 parts per billion. This quantity is determined from two key measurements; the difference between the muon's spin precession frequency and its cyclotron frequency, given by $\omega_a = \omega_s - \omega_c$, and $\tilde{\omega_p^\prime}$, proportional to the muon-weighted magnetic field.In this talk, we focus on presenting the methodology for determining $\omega_a$. Muons with a momentum of 3.1 GeV are injected into a storage ring, and $\omega_a$ is extracted from the time distribution of decay positrons recorded by 24 electromagnetic calorimeters placed symmetrically inwards around the ring. We present the final result from the muon g-2 collaboration and analysis techniques based on data collected from 2020 to 2023.

Zaid, Estifa'a [Liverpool U.]↗
DOE OSTI2017

AR Sco: A Precessing White Dwarf Synchronar?

The emission of the white dwarf–M dwarf binary AR Sco is driven by the rapid synchronization of its white dwarf, rather than by accretion. Synchronization requires a magnetic field ∼100 Gauss at the M dwarf and ∼10{sup 8} Gauss at the white dwarf, larger than the fields of most intermediate polars but within the range of fields of known magnetic white dwarfs. The spindown power is dissipated in the atmosphere of the M dwarf, within the near zone of the rotating white dwarf’s field, by magnetic reconnection, accelerating particles that produce the observed synchrotron radiation. The displacement of the optical maximum from conjunction may be explained either by dissipation in a bow wave as the white dwarf’s magnetic field sweeps past the M dwarf or by a misaligned white dwarf rotation axis and oblique magnetic moment. In the latter case the rotation axis precesses with a period of decades, predicting a drift in the orbital phase of the optical maximum. Binaries whose emission is powered by synchronization may be termed synchronars, in analogy to magnetars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

AI ensemble for signal detection of higher order gravitational wave modes of quasi-circular, spinning, non-precessing binary black hole mergers

We introduce spatiotemporal-graph models that concurrently process data from the twin advanced LIGO detectors and the advanced Virgo detector. We trained these AI classifiers with 2.4 million IMRPhenomXPHM waveforms that describe quasi-circular, spinning, non-precessing binary black hole mergers with component masses m{1,2}∈[3M⊙,50M⊙], and individual spins sz{1,2}∈[−0.9,0.9]; and which include the (ℓ,|m|)={(2,2),(2,1),(3,3),(3,2),(4,4)} modes, and mode mixing effects in the ℓ=3,|m|=2 harmonics. We trained these AI classifiers within 22 hours using distributed training over 96 NVIDIA V100 GPUs in the Summit supercomputer. We then used transfer learning to create AI predictors that estimate the total mass of potential binary black holes identified by all AI classifiers in the ensemble. We used this ensemble, 3 classifiers for signal detection and 2 total mass predictors, to process a year-long test set in which we injected 300,000 signals. This year-long test set was processed within 5.19 minutes using 1024 NVIDIA A100 GPUs in the Polaris supercomputer (for AI inference) and 128 CPU nodes in the ThetaKNL supercomputer (for post-processing of noise triggers), housed at the Argonne Leadership Computing Facility. These studies indicate that our AI ensemble provides state-of-the-art signal detection accuracy, and reports 2 misclassifications for every year of searched data. This is the first AI ensemble designed to search for and find higher order gravitational wave mode signals.

Tian, Minyang↗
NASA NTRS1971

On hydromagnetic precession in a cylinder

Rotating fluid cylinder in magnetic field parallel to rotation axis, discussing hydromagnetic precession rate, resonance phenomena and magnetic Reynolds number flows

Gans, R. F.↗