25 citations · 49 across the 5 of their papers we have counts for
6 papers
Revisiting AGN Placement on the BPT Diagram: A Spectral Decomposition Approach
Hossen Teimoorinia, Sara Shishehchi, Finn Archinuk +5
Traditional single-fibre spectroscopy provides a single galaxy spectrum, forming the basis for crucial parameter estimation. However, its accuracy can be compromised by various sou…
Stellar Populations With Optical Spectra: Deep Learning vs. Popular Spectrum Fitting Codes
Joanna Woo, Dan Walters, Finn Archinuk +4
We compare the performance of several popular spectrum fitting codes (Firefly, starlight, pyPipe3D and pPXF), and a deep-learning convolutional neural network (StarNet), in recover…
Mitigating the Non-Linearities in a Pyramid Wavefront Sensor
Finn Archinuk, Rehan Hafeez, Sébastien Fabbro +2
For natural guide start adaptive optics (AO) systems, pyramid wavefront sensors (PWFSs) can provide significant increase in sensitivity over the traditional Shack-Hartmann, but at…
Mapping the Diversity of Galaxy Spectra with Deep Unsupervised Machine Learning
Hossen Teimoorinia, Finn Archinuk, Joanna Woo +2
Modern spectroscopic surveys of galaxies such as MaNGA consist of millions of diverse spectra covering different regions of thousands of galaxies. We propose and implement a deep u…
Forecasting Wavefront Corrections in an Adaptive Optics System
Rehan Hafeez, Finn Archinuk, Sébastien Fabbro +2
We use telemetry data from the Gemini North ALTAIR adaptive optics system to investigate how well the commands for wavefront correction (both Tip/Tilt and high-order turbulence) ca…
An astronomical image content-based recommendation system using combined deep learning models in a fully unsupervised mode
Hossen Teimoorinia, Sara Shishehchi, Ahnaf Tazwar +4
We have developed a method that maps large astronomical images onto a two-dimensional map and clusters them. A combination of various state-of-the-art machine learning (ML) algorit…