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Berz, M.

Publications and source records attributed to Berz, M..

7 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Detailed report on the measurement of the positive muon anomalous magnetic moment to 0.20 ppm

We present details on a new measurement of the muon magnetic anomaly, a μ =(g μ −2)/2. The result is based on positive muon data taken at Fermilab’s Muon Campus during the 2019 and 2020 accelerator runs. The measurement uses 3.1 GeV/c polarized muons stored in a 7.1-m-radius storage ring with a 1.45 T uniform magnetic field. The value of a μ is determined from the measured difference between the muon spin precession frequency and its cyclotron frequency. This difference is normalized to the strength of the magnetic field, measured using nuclear magnetic resonance. The ratio is then corrected for small contributions from beam motion, beam dispersion, and transient magnetic fields. We measure a μ =116592057(25)×10 −11 (0.21 ppm). This is the world’s most precise measurement of this quantity and represents a factor of 2.2 improvement over our previous result based on the 2018 dataset. In combination, the two datasets yield a μ (FNAL)=116592055(24)×10 −11 (0.20 ppm). Combining this with the measurements from Brookhaven National Laboratory for both positive and negative muons, the new world average is a μ (exp)=116592059(22)×10 −11 (0.19 ppm).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Measurement of the Positive Muon Anomalous Magnetic Moment to 0.20 ppm

We present a new measurement of the positive muon magnetic anomaly, a μ ≡ ( g μ - 2 ) / 2 , from the Fermilab Muon g - 2 Experiment using data collected in 2019 and 2020. We have analyzed more than 4 times the number of positrons from muon decay than in our previous result from 2018 data. The systematic error is reduced by more than a factor of 2 due to better running conditions, a more stable beam, and improved knowledge of the magnetic field weighted by the muon distribution, ω ˜ p ′ , and of the anomalous precession frequency corrected for beam dynamics effects, ω a . From the ratio ω a / ω ˜ p ′ , together with precisely determined external parameters, we determine a μ = 116 592 057 ( 25 ) × 10 - 11 (0.21 ppm). Combining this result with our previous result from the 2018 data, we obtain a μ ( FNAL ) = 116 592 055 ( 24 ) × 10 - 11 (0.20 ppm). The new experimental world average is a μ ( exp ) = 116 592 059 ( 22 ) × 10 - 11 (0.19 ppm), which represents a factor of 2 improvement in precision.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Simulations of future particle accelerators: issues and mitigations

The ever increasing demands placed upon machine performance have resulted in the need for more comprehensive particle accelerator modeling. Computer simulations are key to the success of particle accelerators. Many aspects of particle accelerators rely on computer modeling at some point, sometimes requiring complex simulation tools and massively parallel supercomputing. Examples include the modeling of beams at extreme intensities and densities (toward the quantum degeneracy limit), and with ultra-fine control (down to the level of individual particles). In the future, adaptively tuned models might also be relied upon to provide beam measurements beyond the resolution of existing diagnostics. Much time and effort has been put into creating accelerator software tools, some of which are highly successful. However, there are also shortcomings such as the general inability of existing software to be easily modified to meet changing simulation needs. In this paper possible mitigating strategies are discussed for issues faced by the accelerator community as it endeavors to produce better and more comprehensive modeling tools. This includes lack of coordination between code developers, lack of standards to make codes portable and/or reusable, lack of documentation, among others.

43 PARTICLE ACCELERATORS↗