2022arXiv (Cornell University)Open access

Newly discovered $z\sim5$ quasars based on deep learning and Bayesian information criterion

Suhyun Shin, Myungshin Im, Yongjung Kim, Lin‐Hua Jiang

Open full text 0 citations

Abstract

We report the discovery of four quasars with $M_{1450} \gtrsim -25.0$ mag at $z\sim5$ and supermassive black hole mass measurement for one of the quasars. They were selected as promising high-redshift quasar candidates via deep learning and Bayesian information criterion, which are expected to be effective in discriminating quasars from the late-type stars and high-redshift galaxies. The candidates were observed by the Double Spectrograph on the Palomar 200-inch Hale Telescope. They show clear Ly$α$ breaks at about 7000-8000 Å, indicating they are quasars at $4.7 < z < 5.6$. For HSC J233107-001014, we measure the mass of its supermassive black hole (SMBH) using its C\Romannum{4}$λ1549$ emission line. The SMBH mass and Eddington ratio of the quasar are found to be $\sim 10^8 M_{\odot}$ and $\sim 0.6$, respectively. This suggests that this quasar possibly harbors a fast growing SMBH near the Eddington limit despite its faintness ($L_{\rm Bol} < 10^{46}$ erg s$^{-1}$). Our 100 $\%$ quasar identification rate supports high efficiency of our deep learning and Bayesian information criterion selection method, which can be applied to future surveys to increase high-redshift quasar sample.

Open-access reader

About this research paper

What this paper is about

We report the discovery of four quasars with $M_{1450} \gtrsim -25.0$ mag at $z\sim5$ and supermassive black hole mass measurement for one of the quasars. They were selected as promising high-redshift quasar candidates via deep learning and Bayesian information criterion, which are expected to be effective in discriminating quasars from the late-type stars and high-redshift galaxies. The candidates were observed by the Double Spectrograph on the Palomar 200-inch Hale Telescope. They show clear Ly$α$ breaks at about 7000-8000 Å, indicating they are quasars at $4.7 < z < 5.6$. For HSC J233107-001014, we measure the mass of its supermassive black hole (SMBH) using its C\Romannum{4}$λ1549$ emission line. The SMBH mass and Eddington ratio of the quasar are found to be $\sim 10^8 M_{\odot}$ and $\sim 0.6$, respectively. This suggests that this quasar possibly harbors a fast growing SMBH near the Eddington limit despite its faintness ($L_{\rm Bol} < 10^{46}$ erg s$^{-1}$). Our 100 $\%$ quasar identification rate supports high efficiency of our deep learning and Bayesian information criterion selection method, which can be applied to future surveys to increase high-redshift quasar sample.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

We report the discovery of four quasars with $M_{1450} \gtrsim -25.0$ mag at $z\sim5$ and supermassive black hole mass measurement for one of the quasars. They were selected as promising high-redshift quasar candidates via deep learning and Bayesian information criterion, which are expected to be effective in discriminating quasars from the late-type stars and high-redshift galaxies. The candidates were observed by the Double Spectrograph on the Palomar 200-inch Hale Telescope. They show clear Ly$α$ breaks at about 7000-8000 Å, indicating they are quasars at $4.7 < z < 5.6$. For HSC J233107-001014, we measure the mass of its supermassive black hole (SMBH) using its C\Romannum{4}$λ1549$ emission line. The SMBH mass and Eddington ratio of the quasar are found to be $\sim 10^8 M_{\odot}$ and $\sim 0.6$, respectively. This suggests that this quasar possibly harbors a fast growing SMBH near the Eddington limit despite its faintness ($L_{\rm Bol} < 10^{46}$ erg s$^{-1}$). Our 100 $\%$ quasar identification rate supports high efficiency of our deep learning and Bayesian information criterion selection method, which can be applied to future surveys to increase high-redshift quasar sample.

Key concepts: Quasar, Supermassive black hole, Physics, Astrophysics, Redshift, Galaxy, Stars, Eddington luminosity

Related papers

Back to paper searchBrowse research topicsOriginal source
Newly discovered $z\sim5$ quasars based on deep learning and Bayesian information criterion — Research Paper | ScholarLens