230 citations · 778 across the 56 of their papers we have counts for
8 papers · 1 filter
The Leiden/ESA Astrophysics Program for Summer Students (LEAPS)
S. Bellotti, A. D. Sellek, P. Sharda +3
International student mobility plays a critical role in shaping future research careers, particularly in highly globalized fields such as astrophysics. The Leiden/ESA Astrophysics…
Luminous Fast Blue Optical Transients in the 2040s
A. A. Chrimes, N. Sarin, D. Coppejans +6
Luminous Fast Blue Optical Transients (LFBOTs) are a class of extragalactic transient of uncertain origin. Several hypotheses have been put forward which could feasibly be consiste…
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…
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…
Machine Learning for Transient Recognition in Difference Imaging With Minimum Sampling Effort
Yik-Lun Mong, Kendall Ackley, Duncan Galloway +45
The amount of observational data produced by time-domain astronomy is exponentially in-creasing. Human inspection alone is not an effective way to identify genuine transients fromt…