Learning objectives
- fit a nu^-2 dispersion delay, estimate DM uncertainty, and distinguish dispersion from achromatic timing residuals.
- Propagate a statistical or calibration uncertainty and report a limitation.
- Preserve a reproducible record of inputs, transformations, and outputs.
Preparation, materials, and setup
Use Python 3 with the standard library (or a spreadsheet capable of regression and plotting), the supplied ../data/pulsar_arrivals.csv, and the relevant lecture notes. Record file name, row count, columns, units, and provenance level before editing. No facility observing time is assumed.
Dataset status: the supplied compact record is synthetic/instructor-provided (level 3), not an archived observation. Compare its analysis workflow with the real survey or observatory source cited in ../reference-log.md.
Computed check: completeness = 0.84 .
Apparatus and procedure
- Plot arrival-time offset against observing frequency and fit t=t_inf+K DM nu^-2 with uncertainty weights.
- Compare fitted DM with the supplied reference DM and report residuals in milliseconds.
- Calculate intra-channel dispersive smearing for the listed channel widths at the lowest observing frequency.
- Test a pulse-broadening term proportional to nu^-4 and compare residual structure before and after the fit.
- Explain why a survey's measured detection fraction depends on pulse width, DM, and cadence.
Measurement record and uncertainty
| Record | Required entry |
|---|---|
| Input | File, release/source, units, masks or flags, and provenance level. |
| Model | Equation, parameter values, convention, and approximation. |
| Statistics | Fit covariance or counting error plus one calibration/selection/systematic term. |
| Validation | Independent recomputation, residual plot, and limiting-case check. |
Deliver fitted DM, uncertainty, residual plot, channel-smearing table, and a statement separating measured delay from inferred distance.
Deliverables and criteria
- Reproducible code or spreadsheet with inputs and units documented.
- One publication-quality labeled plot and a short interpretation (400-700 words).
- Uncertainty budget that separates random, common-mode, and model terms where relevant.
- Credit requires correct method, units, interpretation, provenance, and a limitation; a copied numeric result without an audit trail earns at most half credit.
Interpretive boundary
A frequency-dependent delay is consistent with dispersion, but frequency-dependent intrinsic profile shape can bias a simple timing fit. State explicitly which parts of your result are facts about this prepared teaching record and which are transferable inference methods.
References and provenance
Course teaching record: ../data/pulsar_arrivals.csv, level 3. Real facility/survey context: reference log. No external image is used.