Rob Sharp

Professor

Australian National University
Country flagAustralia

Research Interests

Explore related searches

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Professor Rob Sharp is a faculty member at the Australian National University in Australia. His research focuses on areas including metasurface-enabled polarisation imaging, multi-object reverberation mapping, and stellar population trends as observed in the SAMI Galaxy Survey. His contributions to the field enhance our understanding of astrophysics and observational techniques within cosmology.

Articles (3)

Year:

2025

Contemporary reverberation mapping campaigns are employing wide-area photometric data and high-multiplex spectroscopy to efficiently monitor hundreds of active galactic nuclei (AGNs). However, the interaction of the window function(s) imposed by the observation cadence with the reverberation lag and AGN variability time-scales (intrinsic to each source over a range of luminosities) impact our ability to recover these fundamental physical properties. Time dilation effects due to the sample source redshift distribution introduce added complexity. We present comprehensive analysis of the implications of observational cadence, seasonal gaps, and campaign baseline duration (i.e. the survey window function) for reverberation lag recovery. We find that the presence of a significant seasonal gap dominates the efficacy of any given campaign strategy for lag recovery across the parameter space, particularly for those sources with observed-frame lags above 100 d. Using the Australian Dark Energy Survey as a baseline, we consider the implications of this analysis for the 4MOST/Time-Domain Extragalactic Survey campaign providing concurrent follow-up of the Legacy Survey of Space and Time deep-drilling fields, as well as upcoming programmes. We conclude that the success of such surveys will be critically limited by the seasonal visibility of some potential field choices, but show significant improvement from extending the baseline. Optimizing the sample selection to fit the window function will improve survey efficacy.

Year:

2022

Year:

2021

Collaborators (4)

Josh Calcino

University of Queensland

AUSTRALIA
View details

Nuria P. F. Lorente

Macquarie University

AUSTRALIA
View details

Sarah Sweet

Lecturer & ARC DECRA Fellow 2022

University of Queensland

AUSTRALIA
View details

Michael Goodwin

Macquarie University

AUSTRALIA
View details
ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.