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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…
Photometric Redshift Estimation for Gamma-Ray Bursts from the Early Universe
H. M. Fausey, A. J. van der Horst, N. E. White +16
Future detection of high-redshift gamma-ray bursts (GRBs) will be an important tool for studying the early Universe. Fast and accurate redshift estimation for detected GRBs is key…
The Gravitational-wave Optical Transient Observer (GOTO): prototype performance and prospects for transient science
D. Steeghs, D. K. Galloway, K. Ackley +50
The Gravitational-wave Optical Transient Observer (GOTO) is an array of wide-field optical telescopes, designed to exploit new discoveries from the next generation of gravitational…
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…