Predicting the Cosmos: A Multiwavelength Approach to Classify Active and Star Forming Galaxies

Distinguishing between active galactic nuclei (AGN) and star forming galaxies (SFG) using spectroscopic analysis has been done since the 1980s using a BPT diagram, using the traditional log(OIII/HB) vs log(NII/HA) lines. Through this paper, I aim to supplement the traditional emission lines used with infrared and ultraviolet photometry to find the best predictors of SFGs vs. AGNs. Successfully distinguishing between AGN and SFGs can inform us about the true demographics of these systems and how they evolve through cosmic time. I use various baseline models to predict SFG vs. AGN. For the traditional emission lines, I achieved an accuracy of 90.0%. However, with multiwavelength data, I was able to achieve an accuracy of 95.15%, indicating that there are better predictors than the ones traditionally used.

Authors

Institutions

Publication Details

Journal
Journal of Student Research
Published
2024-11-30
DOI
https://doi.org/10.47611/jsrhs.v13i4.8194
Primary Topic
Astronomy and Astrophysical Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predicting the Cosmos: A Multiwavelength Approach to Classify Active and Star Forming Galaxies

S. R. Kulkarni, Tony Rodriguez
1 links
Journal of Student Research
Astronomy and Astrophysical Research
article

Predicting the Cosmos: A Multiwavelength Approach to Classify Active and Star Forming Galaxies

S. R. Kulkarni, Tony Rodriguez
article en

Abstract

Distinguishing between active galactic nuclei (AGN) and star forming galaxies (SFG) using spectroscopic analysis has been done since the 1980s using a BPT diagram, using the traditional log(OIII/HB) vs log(NII/HA) lines. Through this paper, I aim to supplement the traditional emission lines used with infrared and ultraviolet photometry to find the best predictors of SFGs vs. AGNs. Successfully distinguishing between AGN and SFGs can inform us about the true demographics of these systems and how they evolve through cosmic time. I use various baseline models to predict SFG vs. AGN. For the traditional emission lines, I achieved an accuracy of 90.0%. However, with multiwavelength data, I was able to achieve an accuracy of 95.15%, indicating that there are better predictors than the ones traditionally used.

Journal of Student ResearchVol. 13(4)
Green Valley High School (US)
Openalex Percentile: Top 77%
Astronomy and Astrophysical Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Predicting the Cosmos: A Multiwavelength Approach to Classify Active and Star Forming Galaxies — S. R. Kulkarni, Tony Rodriguez · Journal of Student Research (2024) | TGRS Research Map | TGRS