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Fast radio bursts were discovered just over a decade ago, and their origin remains a mystery. Despite this disadvantage, astronomers have been using them to investigate the matter through which their bright, impulsive radiation travels.
To date, one repeating and many apparently non-repeating fast radio bursts have been detected. This dichotomy has driven discussions about whether fast radio bursts stem from a single population of sources or two or more different populations. Here we present the arguments for and against.
The first fast radio burst (FRB) was discovered in 2007, and in the following decade ~25 more were detected. Now the field stands on the brink of an explosion of detections, largely driven by the availability of new radio facilities. One of the founders of the field, Duncan Lorimer, reviews the early years of FRB science.
Physical constraints on the sources of fast radio bursts are few, and therefore viable theoretical models are many. However, no one model can match all the available observational characteristics, meaning that these radio bursts remain one of the most mysterious phenomena in astrophysics.
The Australian Square Kilometre Array Pathfinder will be a key tool in future searches for fast radio bursts and other transient phenomena, and is already reaping rewards, explains Principal Engineer Keith Bannister.
Multi-wavelength and multi-messenger astronomy will reveal the phenomena that produce fast radio bursts, turning fast radio bursts into sharper tools with which to probe extragalactic plasma.
The second decade of fast radio burst (FRB) astronomy has started at pace, with detections of tens of new FRBs from newly operational facilities such as ASKAP and CHIME. Evan Keane looks forward to the upcoming years and the discoveries they will bring.
A convolutional neural network estimates cosmological parameters from simulated weak lensing convergence maps in an unbiased way. The network analysis motivates a new and robust convergence peak-counting algorithm based on the steepness of peak heights.
Large cosmological datasets have been probing the properties of our Universe and constraining the parameters of dark matter and dark energy with increasing precision. Deep learning techniques have shown potential to be smarter than — and greatly outperform — human-designed statistics.
Using commissioning data from the Australian Square Kilometre Array Pathfinder (ASKAP), parts of the Small Magellanic Cloud (SMC) have been mapped with ten times the resolution of before. Cold H i outflows are found to extend some 2 kpc from the SMC bar, containing up to 3% of the galaxy’s atomic mass. These will probably be stripped by interactions with neighbouring galaxies.
Blue supergiant stars (BSGs) can undergo core collapse, resulting in a type II supernova explosion. Here, Tobias Fischer et al. identify a novel phase transition from nuclear matter to a quark–gluon plasma for particularly massive BSGs (>50 M☉) that explains their explosion.
The study of the early stages of galaxy cluster formation and their evolutionary path is critical for testing our structure-formation models and cosmological paradigm. Recent observations have pushed the detection of ‘protoclusters’ further back in time.
