Ranking Prompt--Plateau Correlations in Gamma-Ray Bursts with Symbolic Regression

Abstract

Gamma-ray burst (GRB) correlations probe central engines, relativistic outflows, and radiation processes. The Dainotti relation is an anticorrelation between the X-ray plateau luminosity $L_a$ and rest-frame plateau duration $T_a^{\rm rest}$. We use symbolic regression to compare it with other low-dimensional correlations in 251 GRBs with Swift-XRT plateau properties and Swift-BAT prompt-emission parameters. We perform a Dainotti-guided search, in which $\log T_a^{\rm rest}$ is always present, and an unrestricted search over subsets of at most three variables. The guided search recovers the Dainotti dependence; a D'Agostini fit gives $\log L_a=(51.92\pm0.30)-(1.31\pm0.09)\log T_a^{\rm rest}$, with intrinsic scatter $σ_{\rm int}=0.82\pm0.05$ dex. In the unrestricted ranking of 377 feature subsets, the classical Dainotti relation remains competitive, within the top $\sim25\%$ of the tested search spaces. The highest-ranked screened expression is $\log L_a\approx0.855\log L_{\rm peak}-0.782\log T_a^{\rm rest}$, with RMSE $\approx0.46$ and $R^2\approx0.88$. The highest-ranked runs repeatedly reduce to this prompt--plateau structure, without retaining additional spectral, absorption, or afterglow-shape variables. A direct regression gives $\log L_a=4.718+0.776\log L_{\rm peak}-0.805\log T_a^{\rm rest}$, with $R_{\rm P}=0.91$ for 246 bursts. An errors-in-variables refit gives consistent coefficients. After removing shared luminosity-distance dependence, the relation retains non-negligible explanatory power ($R^2\approx0.62$), consistent with a possible intrinsic component. Restricted Monte Carlo null tests give $p\approx0.01$. Plateau luminosity therefore shows a coupled dependence on prompt luminosity and plateau duration.