Optimising the FRB Search Pipeline for the Northern Cross Radio Telescope
FRB search pipelines are being developed to operate under strict real-time constraints while maintaining sensitivity to short-duration transient signals. In incoherent dedispersion based pipelines such as Heimdall, apart from observation bandwidth and number of beams, detection performance and computational throughput are strongly dependent on the choice of processing parameters, which are often selected heuristically. In this work, we present a systematic evaluation of key dedispersion and matched filtering parameters and quantify their impact on both detection accuracy and runtime performance. A controlled synthetic injection framework is developed in which artificial FRB pulses with known DMs, SNRs, and pulse widths are embedded into realistic filterbank data containing instrumental noise representative of observations from the Northern Cross radio telescope. Using this framework, a grid of Heimdall configurations is explored, spanning DM tolerance, boxcar filter width, and processing gulp size. Detection performance is assessed by comparing recovered and injected signal properties, while computational performance is evaluated through end-to-end processing time measurements. The results reveal clear trade-offs between sensitivity and throughput across parameter choices. We identify an empirically optimal configuration that provides burst recovery while maintaining processing speeds exceeding real-time requirements. While the specific optimal parameters are derived for the Northern Cross, the methodology and findings are broadly applicable to any real-time transient detection pipeline employing matched-filtering and dedispersion, and are particularly relevant for low-frequency radio telescopes with similar observing configurations. These findings demonstrate the value of data-driven parameter evaluation for improving the performance of real-time transient detection pipelines.