pqc.detect.transients

Detect exponential-recovery transient events in timing residuals.

Transient candidates are modeled as one-sided exponential recoveries:

\[m(t; A,t_0,\tau) = A\exp(-(t-t_0)/\tau)\,\mathbf{1}[t\ge t_0]\]

Candidate epochs t0 are scanned at observed TOAs and scored by weighted improvement in fit versus a null model using \(\Delta\chi^2\).

Notes

Why this model

Recovery-like disturbances in timing data are often well captured by a single exponential relaxation template over finite windows.

Statistic

For weighted least squares with weights \(w_i=1/\sigma_i^2\), \(\Delta\chi^2 = \chi^2_{\mathrm{null}} - \chi^2_{\mathrm{model}}\).

Interpretation

Larger \(\Delta\chi^2\) indicates stronger evidence for a transient shape relative to no-event model within the tested window.

Caveats

Dense overlapping events or non-exponential systematics can bias recovered A and t0.

References

[1]

Edwards, R. T., Hobbs, G. B., & Manchester, R. N. (2006), MNRAS 372.

[2]

Lorimer, D. R., & Kramer, M. (2005), Handbook of Pulsar Astronomy.

Functions

scan_transients(df, *[, mjd_col, resid_col, ...])

Scan for transient exponential recoveries and annotate affected rows.