Acknowledgement
This research was supported by the National Research Foundation of Korea (NRF) grants No. 2020R1A2C3011091 and No. 2021M3F7A1084525, funded by the Ministry of Science and ICT (MSIT). S. S. acknowledges the support from the Basic Science Research Program through the NRF funded by the Ministry of Education (No. 2020R1A6A3A13069198). Y. K. was supported by the NRF grant funded by the MSIT (No. 2021R1C1C2091550). He acknowledges the support from the China Postdoc Science General (2020M670022) and Special (2020T130018) Grants funded by the China Postdoctoral Science Foundation. This research uses data obtained through the Telescope Access Program (TAP) (PID: CTAP2020-B0043 and CTAP2021-A0032), which has been funded by the National Astronomical Observatories of China, the Chinese Academy of Sciences, and the Special Fund for Astronomy from the Ministry of Finance. Observations obtained with the Hale Telescope at Palomar Observatory were obtained as part of an agreement between the National Astronomical Observations, Chinese Academy of Sciences, and the California Institute of Technology. The Hyper Suprime-Cam (HSC) collaboration includes the astronomical communities of Japan and Taiwan, and Princeton University. The HSC instrumentation and software were developed by the National Astronomical Observatory of Japan (NAOJ), the Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU), the University of Tokyo, the High Energy Accelerator Research Organization (KEK), the Academia Sinica Institute for Astronomy and Astrophysics in Taiwan (ASIAA), and Princeton University. Funding was contributed by the FIRST program from the Japanese Cabinet Office, the Ministry of Education, Culture, Sports, Science and Technology (MEXT), the Japan Society for the Promotion of Science (JSPS), Japan Science and Technology Agency (JST), the Toray Science Foundation, NAOJ, Kavli IPMU, KEK, ASIAA, and Princeton University. This paper makes use of software developed for the Large Synoptic Survey Telescope. We thank the LSST Project for making their code available as free software at http://dm.lsst.org. This paper is based on data collected at the Subaru Telescope and retrieved from the HSC data archive system, which is operated by the Subaru Telescope and Astronomy Data Center (ADC) at National Astronomical Observatory of Japan. Data analysis was in part carried out with the cooperation of Center for Computational Astrophysics (CfCA), National Astronomical Observatory of Japan. The Subaru Telescope is honored and grateful for the opportunity of observing the Universe from Maunakea, which has the cultural, historical and natural significance in Hawaii.
References
- Aihara, H., AlSayyad, Y., Ando, M., et al. 2019, Second data release of the Hyper Suprime-Cam Subaru Strategic Program, PASJ, 71, 114
- Akiyama, M., He, W., Ikeda, H., et al. 2018, The quasar luminosity function at redshift 4 with the Hyper Suprime-Cam Wide Survey, PASJ, 70, S34
- Allard, F., Homeier, D., Freytag, B., et al. 2013, Progress in modeling very low mass stars, brown dwarfs, and planetary mass objects, Memorie della Societa Astronomica Italiana Supplementi, 24, 128
- Banados, E., Venemans, B. P., Mazzucchelli, C., et al. 2018, An 800-million-solar-mass black hole in a significantly neutral Universe at a redshift of 7.5, Nature, 553, 473
- Chaves-Montero, J., Bonoli, S., Salvato, M., et al. 2017, ELDAR, a new method to identify AGN in multi-filter surveys: the ALHAMBRA test case, MNRAS, 472, 2085
- Coatman, L., Hewett, P. C., Banerji, M., et al. 2017, Correcting CIV-based virial black hole masses, MNRAS, 465, 2120
- Coupon, J., Czakon, N., Bosch, J., et al. 2018, The bright-star masks for the HSC-SSP survey, PASJ, 70, S7
- Dark Energy Survey Collaboration, Abbott, T., Abdalla, F. B., et al. 2016, The Dark Energy Survey: more than dark energy - an overview, MNRAS, 460, 1270
- De Rosa, G., Decarli, R., Walter, F., et al. 2011, Evidence for Non-evolving Fe ii/Mg ii Ratios in Rapidly Accreting z ~ 6 QSOs, ApJ, 739, 56
- Fan, X., Strauss, M. A., Richards, G. T., et al. 2006, Constraining the Evolution of the Ionizing Background and the Epoch of Reionization with z ~ 6 Quasars. II. A Sample of 19 Quasars, AJ, 131, 1203
- Foreman-Mackey, D., Hogg, D. W., Lang, D., et al. 2013, emcee: The MCMC Hammer, PASP, 125, 306
- Greene, J. E., Strader, J., & Ho, L. C. 2020, Intermediate-Mass Black Holes, ARA&A, 58, 257
- Gwyn, S. D. J. 2012, The Canada-France-Hawaii Telescope Legacy Survey: Stacked Images and Catalogs, AJ, 143, 38
- Hickox, R. C. & Alexander, D. M. 2018, Obscured Active Galactic Nuclei, ARA&A, 56, 625
- Ikeda, H., Nagao, T., Matsuoka, K., et al. 2017, An Optically Faint Quasar Survey at z ~ 5 in the CFHTLS Wide Field: Estimates of the Black Hole Masses and Eddington Ratios, ApJ, 846, 57
- Inoue, A. K., Shimizu, I., Iwata, I., et al. 2014, An updated analytic model for attenuation by the intergalactic medium, MNRAS, 442, 1805
- Jeon, Y., Im, M., Kim, D., et al. 2017, The Infrared Medium-deep Survey. III. Survey of Luminous Quasars at 4.7 ≤ z ≤ 5.4, ApJS, 231, 16
- Jiang, L., Fan, X., Vestergaard, M., et al. 2007, Gemini Near-Infrared Spectroscopy of Luminous z ~ 6 Quasars: Chemical Abundances, Black Hole Masses, and Mg II Absorption, AJ, 134, 1150
- Jiang, L., McGreer, I. D., Fan, X., et al. 2016, The Final SDSS High-redshift Quasar Sample of 52 Quasars at z > 5.7, ApJ, 833, 222
- Jun, H. D., Im, M., Lee, H. M., et al. 2015, Rest-frame Optical Spectra and Black Hole Masses of 3 < z < 6 Quasars, ApJ, 806, 109
- Kaiser, N., Burgett, W., Chambers, K., et al. 2010, The Pan-STARRS wide-field optical/NIR imaging survey, Proc. SPIE, 7733, 77330E
- Kim, Y., Im, M., Jeon, Y., et al. 2018, The Infrared Medium-deep Survey. IV. The Low Eddington Ratio of A Faint Quasar at z ~ 6: Not Every Supermassive Black Hole is Growing Fast in the Early Universe, ApJ, 855, 138
- Kim, Y., Im, M., Jeon, Y., et al. 2019, The Infrared Medium-deep Survey. VI. Discovery of Faint Quasars at z ~ 5 with a Medium-band-based Approach, ApJ, 870, 86
- Kim, Y., Im, M., Jeon, Y., et al. 2020, The Infrared Medium-deep Survey. VIII. Quasar Luminosity Function at z ~ 5, ApJ, 904, 111
- Leauthaud, A., Massey, R., Kneib, J.-P., et al. 2007, Weak Gravitational Lensing with COSMOS: Galaxy Selection and Shape Measurements, ApJS, 172, 219
- Liddle, A. R. 2007, Information criteria for astrophysical model selection, MNRAS, 377, L74
- Lusso, E., Worseck, G., Hennawi, J. F., et al. 2015, The first ultraviolet quasar-stacked spectrum at z ≃ 2.4 from WFC3, MNRAS, 449, 4204
- Matsuoka, Y., Iwasawa, K., Onoue, M., et al. 2018, Subaru High-z Exploration of Low-luminosity Quasars (SHELLQs). IV. Discovery of 41 Quasars and Luminous Galaxies at 5.7 ≤ z ≤ 6.9, ApJS, 237, 5
- Matsuoka, Y., Strauss, M. A., Kashikawa, N., et al. 2018, Subaru High-z Exploration of Low-luminosity Quasars (SHELLQs). V. Quasar Luminosity Function and Contribution to Cosmic Reionization at z = 6, ApJ, 869, 150
- Matsuoka, Y., Onoue, M., Kashikawa, N., et al. 2019, Discovery of the First Low-luminosity Quasar at z > 7, ApJL, 872, L2
- Marziani, P., del Olmo, A., Martinez-Carballo, M. A., et al. 2019, Black hole mass estimates in quasars. A comparative analysis of high- and low-ionization lines, A&A, 627, A88
- Mazzucchelli, C., Banados, E., Venemans, B. P., et al. 2017, Physical Properties of 15 Quasars at z ≳ 6.5, ApJ, 849, 91
- McGreer, I. D., Jiang, L., Fan, X., et al. 2013, The z = 5 Quasar Luminosity Function from SDSS Stripe 82, ApJ, 768, 105
- McGreer, I. D., Fan, X., Jiang, L., et al. 2018, The Faint End of the z = 5 Quasar Luminosity Function from the CFHTLS, AJ, 155, 131
- Mortlock, D. J., Warren, S. J., Venemans, B. P., et al. 2011, A luminous quasar at a redshift of z = 7.085, Nature, 474, 616
- Niida, M., Nagao, T., Ikeda, H., et al. 2020, The Faint End of the Quasar Luminosity Function at z ~ 5 from the Subaru Hyper Suprime-Cam Survey, ApJ, 904, 89
- Oke, J. B. & Gunn, J. E. 1983, Secondary standard stars for absolute spectrophotometry, ApJ, 266, 713
- Onoue, M., Kashikawa, N., Matsuoka, Y., et al. 2019, Subaru High-z Exploration of Low-luminosity Quasars (SHELLQs). VI. Black Hole Mass Measurements of Six Quasars at 6.1 ≤ z ≤ 6.7, ApJ, 880, 77
- Paris, I., Petitjean, P., Aubourg, E., et al. 2018, The Sloan Digital Sky Survey Quasar Catalog: Fourteenth data release, A&A, 613, A51
- Prochaska, J. X., Hennawi, J., Westfall, K., et al. 2020, PypeIt: The Python Spectroscopic Data Reduction Pipeline (v1.3), Zenodo:4323006
- Prochaska, J., Hennawi, J., Westfall, K., et al. 2020, PypeIt: The Python Spectroscopic Data Reduction Pipeline, The Journal of Open Source Software, 5, 2308
- Reed, S. L., McMahon, R. G., Martini, P., et al. 2017, Eight new luminous z ≥ 6 quasars discovered via SED model fitting of VISTA, WISE and Dark Energy Survey Year 1 observations, MNRAS, 468, 4702
- Runnoe, J. C., Brotherton, M. S., & Shang, Z. 2012, Updating quasar bolometric luminosity corrections, MNRAS, 422, 478
- Schlegel, D. J., Finkbeiner, D. P., & Davis, M. 1998, Maps of Dust Infrared Emission for Use in Estimation of Reddening and Cosmic Microwave Background Radiation Foregrounds, ApJ, 500, 525
- Selsing, J., Fynbo, J. P. U., Christensen, L., et al. 2016, An X-Shooter composite of bright 1 < z < 2 quasars from UV to infrared, A&A, 585, A87
- Shin, S., Im, M., Kim, Y., et al. 2020, The Infrared Medium-deep Survey. VII. Faint Quasars at z ~ 5 in the ELAIS-N1 Field, ApJ, 893, 45
- Shin, S., Im, M., & Kim, Y. 2022, The quasar luminosity function at z ~ 5 via deep learning and Bayesian information criterion, ApJ, in press
- Shen, Y., Richards, G. T., Strauss, M. A., et al. 2011, A Catalog of Quasar Properties from Sloan Digital Sky Survey Data Release 7, ApJS, 194, 45
- Shen, Y., Wu, J., Jiang, L., et al. 2019, Gemini GNIRS Near-infrared Spectroscopy of 50 Quasars at z ≳ 5.7, ApJ, 873, 35
- Sulentic, J. W., del Olmo, A., Marziani, P., et al. 2017, What does CIV λ1549 tell us about the physical driver of the Eigenvector quasar sequence?, A&A, 608, A122
- Trakhtenbrot, B., Netzer, H., Lira, P., et al. 2011, Black Hole Mass and Growth Rate at z ≃ 4.8: A Short Episode of Fast Growth Followed by Short Duty Cycle Activity, ApJ, 730, 7
- Trakhtenbrot, B., Volonteri, M., & Natarajan, P. 2017, On the Accretion Rates and Radiative Efficiencies of the Highest-redshift Quasars, ApJL, 836, L1
- Vestergaard, M. & Peterson, B. M. 2006, Determining Central Black Hole Masses in Distant Active Galaxies and Quasars. II. Improved Optical and UV Scaling Relationships, ApJ, 641, 689
- Wang, F., Yang, J., Fan, X., et al. 2021, A Luminous Quasar at Redshift 7.642, ApJL, 907, L1
- Willott, C. J., Albert, L., Arzoumanian, D., et al. 2010, Eddington-limited Accretion and the Black Hole Mass Function at Redshift 6, AJ, 140, 546
- Woo, J.-H., Schulze, A., Park, D., et al. 2013, Do Quiescent and Active Galaxies Have Different MBH-σ∗ Relations?, ApJ, 772, 49
- Yang, J., Wang, F., Fan, X., et al. 2020, Poniua'ena: A Luminous z = 7.5 Quasar Hosting a 1.5 Billion Solar Mass Black Hole, ApJL, 897, L14
- Yang, J., Wang, F., Fan, X., et al. 2020, Measurements of the z ~ 6 Intergalactic Medium Optical Depth and Transmission Spikes Using a New z > 6.3 Quasar Sample, ApJ, 904, 26
- Zuo, W., Wu, X.-B., Fan, X., et al. 2020, CIV Emission-line Properties and Uncertainties in Black Hole Mass Estimates of z ~ 3.5 Quasars, ApJ, 896, 40