PSRDISP models pulsar dispersive noise from epoch-wise DMs with Gaussian processes, isolating it from achromatic red noise.

Summary. The manuscript introduces PSRDISP, a Gaussian-process framework that models deterministic and stochastic dispersive processes by operating on high-precision epoch-wise dispersion-measure (DM) estimates (derived from narrowband ToAs or measured as wideband DMs) rather than on frequency-resolved times of arrival. The authors argue that this paradigm-agnostic approach is expected to reduce contamination from achromatic red noise relative to conventional single-pulsar noise analyses. They report that, on simulated narrowband and wideband datasets with realistic noise injections, the recovered dispersive signals agree closely with the injections and are independent of the DM estimation technique. The method is positioned as a diagnostic tool for single-pulsar noise models in precision timing experiments such as the Indian Pulsar Timing Array.

Significance. If the isolation claim and recovery performance hold under realistic PTA conditions, PSRDISP would supply a useful complementary diagnostic that can cross-check conventional frequency-resolved noise analyses and help separate chromatic from achromatic processes. The explicit support for both narrowband-derived and wideband DMs is practically relevant for current PTA pipelines. Credit is due for framing a falsifiable, simulation-based validation strategy and for targeting a concrete operational need (epoch-wise DM series already produced by many pipelines). Full significance, however, cannot be assessed from the abstract alone: quantitative recovery metrics, kernel choices, residual comparisons, and any real-data tests are required to judge whether the method advances the state of the art beyond existing DM-series GP analyses.