activity
20202026
most citedA MeerKAT view of pre-processing in the Fornax A group

41 citations · 48 across the 6 of their papers we have counts for

collaborators

6 papers

astro-ph.IM2026

Towards the exploration of astrophysical datacubes through volumetric rendering within CARTA

Ixaka Labadie-García, Adrianna Pińska, Angus Comrie +5

Data products from astrophysical observations may contain three or more dimensions: most commonly two spatial dimensions and a third spectral dimension, and possibly additional axe…

astro-ph.IM2026★ 2 cited

iDaVIE v1.0: A virtual reality tool for interactive analysis of astronomical data cubes

Alexander Sivitilli, Lucia Marchetti, Angus Comrie +10

As modern astronomy confronts unprecedented data volumes, automated pipelines and machine-learning techniques have become essential for processing and analysis. As these workflows…

astro-ph.IM2021

Virtual Reality and Immersive Collaborative Environments: the New Frontier for Big Data Visualisation

Alexander K. Sivitilli, Angus Comrie, Lucia Marchetti +1

The IDIA Visualisation Laboratory based at the University of Cape Town is exploring the use of virtual reality technology to visualise and analyse astronomical data. The iDaVIE sof…

astro-ph.GA2021★ 41 cited

A MeerKAT view of pre-processing in the Fornax A group

D. Kleiner, P. Serra, F. M. Maccagni +18

We present MeerKAT neutral hydrogen (HI) observations of the Fornax A group, that is likely falling into the Fornax cluster for the first time. Our HI image is sensitive to 1.4 x 1…

astro-ph.IM2020★ 2 cited

iDaVIE-v: immersive Data Visualisation Interactive Explorer for volumetric rendering

Lucia Marchetti, Thomas H. Jarrett, Angus Comrie +4

We present the beta release of iDaVIE-v, a new Virtual Reality software for data cube exploration. The beta release of iDaVIE-v (immersive Data Visualisation Interactive Explorer f…

astro-ph.IM2020★ 3 cited

Exploring and Interrogating Astrophysical Data in Virtual Reality

T. H. Jarrett, A. Comrie, L. Marchetti +9

Scientists across all disciplines increasingly rely on machine learning algorithms to analyse and sort datasets of ever increasing volume and complexity. Although trends and outlie…