70 citations · 272 across the 20 of their papers we have counts for
8 papers · 1 filter
: the GOTO project for real-time citizen science in time-domain astrophysics
T. L. Killestein, L. Kelsey, E. Wickens +51
Time-domain astrophysics continues to grow rapidly, with the inception of new surveys drastically increasing data volumes. Democratised, distributed approaches to training sets for…
Probing extreme environments with the Cherenkov Telescope Array
C. Boisson, A. M. Brown, A. Burtovoi +127
The physics of the non-thermal Universe provides information on the acceleration mechanisms in extreme environments, such as black holes and relativistic jets, neutron stars, super…
Light curve classification with recurrent neural networks for GOTO: dealing with imbalanced data
U. F. Burhanudin, J. R. Maund, T. Killestein +42
The advent of wide-field sky surveys has led to the growth of transient and variable source discoveries. The data deluge produced by these surveys has necessitated the use of machi…
Processing GOTO data with the Rubin Observatory LSST Science Pipelines II: Forced Photometry and light curves
L. Makrygianni, J. Mullaney, V. Dhillon +45
We have adapted the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) Science Pipelines to process data from the Gravitational-Wave Optical Transient Observer (GOTO)…
Transient-optimised real-bogus classification with Bayesian Convolutional Neural Networks -- sifting the GOTO candidate stream
T. L. Killestein, J. Lyman, D. Steeghs +45
Large-scale sky surveys have played a transformative role in our understanding of astrophysical transients, only made possible by increasingly powerful machine learning-based filte…
Processing GOTO data with the Rubin Observatory LSST Science Pipelines I : Production of coadded frames
J. R. Mullaney, L. Makrygianni, V. Dhillon +44
The past few decades have seen the burgeoning of wide field, high cadence surveys, the most formidable of which will be the Legacy Survey of Space and Time (LSST) to be conducted b…