Estimating Bolometric Luminosities of Type 1 Quasars with Self-Organizing Maps

TL;DR

This paper introduces a novel method using self-organizing maps to estimate bolometric luminosities of type 1 quasars more accurately by accounting for SED diversity, improving upon traditional correction methods.

Contribution

The authors develop a self-organizing map-based approach to better estimate quasar bolometric luminosities, addressing limitations of existing bolometric correction techniques.

Findings

Reduces systematic uncertainties in luminosity estimates.

Successfully applied to SDSS DR16 quasar sample.

Provides publicly available code for broader use.

Abstract

We present a new method to calculate bolometric luminosities for unobscured, type 1 quasars with multi-band photometric data. Bolometric luminosity is a fundamental property to understand quasars and it is commonly estimated from monochromatic luminosities using bolometric corrections that often neglect quasar SED diversity. We take advantage of the fact that most quasars now have multi-band observations from UV to mid-IR, and construct SEDs for a well-defined sample of SDSS quasars at $0.5\leq z\leq 2$. Based on this fiducial sample, we explore quasar SEDs, their diversity, and their relations with bolometric luminosities. We then use unsupervised neural network self-organizing maps (SOM) to describe the SED diversity and compute the bolometric luminosities with a fully-trained SOM model. This method reduces systematical uncertainties compared to the traditional method. In addition, we update the multi-linear regression relations between bolometric luminosity and monochromatic luminosities at restframe 1450\r{A}, 3000\r{A}, and 5100\r{A}. Our method is applicable to large quasar samples with a wide range of luminosity and redshift. We have applied it to the SDSS DR16 quasars. We have also made our code publicly available.