quantumquirkxyz Contract
- Input: experimental data file(s), calibration constants, analysis goal.
- Output: analysis script + report.
- Side effects: none.
- Dependencies: none.
- Stop condition: script runs; report complete.
- Risk: low.
- Boundary: analyses data; does not change raw files.
Physics Data Analysis — ROOT / Python
Analyse experimental physics data with reproducible scripts, explicit calibration, and a complete error budget.
When to use
- Experimental data needs statistical analysis.
- A result needs a systematic error table.
- Data must be preserved with analysis linked.
Process
1. Data loading and validation
- Load data (ROOT / HDF5 / CSV / binary); verify schema.
- Check for missing values, outliers, inconsistent units.
- Confirm file provenance (run number, detector state, date).
Completion criterion: data validated; provenance recorded.
2. Calibration
Apply:
- Energy / momentum scale — calibration from standard source.
- Efficiency correction — acceptance and reconstruction efficiency.
- Background subtraction — with statistical error.
Record the calibration constants with their uncertainties.
Completion criterion: calibration applied; constants with errors saved.
3. Statistical analysis
- Histogram / fit — with appropriate model (Gaussian, Poisson, exponential, custom).
- Hypothesis test — chi² / Kolmogorov-Smirnov / likelihood ratio.
- Confidence interval — 68% / 95% (bootstrap or analytic).
- Systematic table — each source (calibration, model, background, acceptance) with contribution.
Completion criterion: statistical result with error budget saved; systematic table present.
4. Results and plots
- Plots: data points + model / fit; systematic bands; labels with units.
- Result summary: value ± statistical ± systematic.
- Reproducibility: script saved; data file linked by DOI or path.
Completion criterion: plots saved; result summary present; script linked.