arXiv subjects

Cristian Di Pietrantonio

Publications and source records attributed to Cristian Di Pietrantonio.

4 recordsLinked to original sources

arXiv2026

A fast radio burst from a non-targeted low-frequency survey

Fast radio bursts (FRBs) are bright, millisecond-duration transient radio signals of extragalactic origin with unknown source and emission mechanisms. While several thousand FRBs have been discovered at frequencies above 400 MHz, detections at lower frequencies have been exceptionally rare. Contributing to their rarity are the magnified dispersive delay, in the tens of seconds, and signal scattering that make low-frequency searches with established techniques computationally prohibitive. In particular, the only confirmed detection below 300 MHz came from a Low-Frequency Array observing campaign targeted at FRB 20180916B, a source already known to emit at higher frequencies. Here we present the first non-targeted detection of an FRB below 300 MHz, achieved in a wide-field, imaging-based survey with the Murchison Widefield Array. The implied FRB rate is consistent with that observed at higher frequencies, demonstrating that non-targeted wide-field surveys can uncover an unbiased, large low-frequency FRB population. This result challenges models invoking severe scattering or absorption to explain previous non-detections, and strengthens the case of low-frequency observations as promising avenue to study the local environment of FRBs.

astro-ph.HE↗

arXiv2026

A signal dedispersion algorithm for imaging-based transient searches

Dedispersion is the computational process of correcting for the frequency-dependent time delay affecting a radio signal that propagates through the interstellar and intergalactic media. It is a crucial component of transient search pipelines that maximises the signal-to-noise ratio, especially when targeting highly dispersed signals: for instance, pulsar emissions making their way through a dense cloud of ionised gas, and fast radio bursts travelling cosmological distances. This paper introduces Streaming high Time-Resolution Imaging DEdispersion (STRIDE), a novel dedispersion algorithm to generate per-pixel dedispersed time series from high time and frequency resolution interferometric images. Unlike straightforward approaches to image dedispersion, STRIDE does not involve expensive manipulation of the input data layout, such as explicitly building dynamic spectra or shifting images. Furthermore, it is the first dedispersion algorithm to partition a dispersive sweep over the time dimension, in addition to frequency. As a consequence, images corresponding to the entire time span of the target dispersive delay are not required all at once. Instead, the algorithm works with an arbitrarily-sized subset of images at a time, adopting an incremental, streaming-based approach to dedispersion. In evaluating STRIDE on the presented test case, it is shown that the minimum memory requirement is reduced by 97.9%, going from 684.5 GB to 14.4 GB. As current and future generations of widefield interferometers increasingly turn to imaging techniques for detection and localisation of radio transients, STRIDE positions itself as a strong alternative to traditional dedispersion methodologies. It arguably is the only viable option for imaging-based searches with low-frequency instruments such as the Murchison Widefield Array (MWA) and low-frequency Square Kilometre Array (SKA-Low).

astro-ph.IM↗

arXiv2025

BLINK: an End-To-End GPU High Time Resolution Imaging Pipeline for Fast Radio Burst Searches with the Murchison Widefield Array

Petabytes of archival high time resolution observations have been captured with the Murchison Widefield Array. The search for Fast Radio Bursts within these using established software has been limited by its inability to scale on supercomputing infrastructure, necessary to meet the associated computational and memory requirements. Hence, past searches used a coarse integration time, in the scale of seconds, or analysed an insufficient number of hours of observations. This paper introduces BLINK, a novel radio interferometry imaging software for low-frequency FRB searches to be run on modern supercomputers. It is implemented as a suite of software libraries executing all computations on GPU, supporting both AMD and NVIDIA hardware vendors. These libraries are designed to interface with each other and to define the BLINK imaging pipeline as a single executable program. Expensive I/O operations between imaging stages are not necessary because the stages now share the same memory space and data representation. BLINK is the first imaging pipeline implementation able to fully run on GPUs as a single process, further supporting AMD hardware and enabling Australian researchers to take advantage of Pawsey's Setonix supercomputer. In the millisecond-scale time resolution imaging test case illustrated in this paper, representative of what is required for FRB searches, the BLINK imaging pipeline achieves a 3687x speedup compared to a traditional MWA imaging pipeline employing WSClean.

astro-ph.IM↗

arXiv2021

Energy-based Accounting Model for Heterogeneous Supercomputers

In this paper we present a new accounting model for heterogeneous supercomputers. An increasing number of supercomputing centres adopt heterogeneous architectures consisting of CPUs and hardware accelerators for their systems. Accounting models using the core hour as unit of measure are redefined to provide an appropriate charging rate based on the computing performance of different processing elements, as well as their energy efficiency and purchase price. In this paper we provide an overview of existing models and define a new model that, while retaining the core hour as a fundamental concept, takes into account the interplay among resources such as CPUs and RAM, and that bases the GPU charging rate on energy consumption. We believe that this model, designed for Pawsey Supercomputing Research Centre's next supercomputer Setonix, has a lot of advantages compared to other models, introducing carbon footprint as a primary driver in determining the allocation of computational workflow on heterogeneous resources.

cs.DC↗