A toy Monte Carlo study of the muon g-2 measurement: generating synthetic decay-positron time spectra with the characteristic exponential decay modulated by the anomalous precession ("wiggle plot"), then fitting the precession frequency back out and studying how statistics and systematic effects move the result.
The muon's anomalous magnetic moment is one of the most precisely measured quantities in physics, and the experimental method — extracting the anomalous precession frequency ωa from the time distribution of decay positrons — is a beautiful exercise in statistics. This project rebuilds that pipeline at toy scale: generate pseudo-data, check the distributions behave as expected, and verify that the fit recovers the input parameters without bias.
A toy event generator for the five-parameter wiggle function N(t) = N₀ e−t/τ[1 + A cos(ωat + φ)], histogramming and visualization of the generated spectra, and a fitting stage that recovers the parameters and examines pulls and uncertainties as a function of sample size.
Python · NumPy for event generation · SciPy / least-squares fitting · Matplotlib for the wiggle plots and residuals.
【待填写】GitHub、Demo、报告或论文链接。
将视频放到 /assets/videos/ 后，替换下面 src。
如果你想嵌入 Bilibili / YouTube，把 iframe 粘贴到这里：
Planned extensions: add systematic-effect studies (gain shifts, pileup, lost muons) on top of the statistical toy, and compare fitting strategies (binned χ² vs. unbinned likelihood). Code and plots to be linked here.