Reverberation Mapping (eBOSS)

The Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) program is a multi-epoch spectroscopic survey designed to enable use of the reverberation mapping technique to measure black hole masses in quasars at a wide range of redshifts.


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Yue Shen
University of Illinois

Finding Targets

An object whose ANCILLARY_TARGET2 value includes one or more of the bitmasks in the following table was targeted for spectroscopy as part of this ancillary target program. See SDSS bitmasks to learn how to use these values to identify objects in this ancillary target program.

Program (bit name) Bit number Target Description Spectra Unique Primary Objects
RM_TILE1 54 Reverberation mapping program, high priority 11,270 230
RM_TILE2 55 Reverberation mapping program, low priority 30,331 619


The broad emission lines in Type 1 AGN spectra respond to variations in continuum emission that is emitted from the AGN accretion disk. However, there is a time delay between the two signals that corresponds to the light-travel time between the continuum-emitting region and the broad-line-emitting region. Measuring this time delay — a technique known as reverberation mapping (RM) — allows researchers to determine a characteristic radius of the broad-line region, which can then be combined with velocity information to yield a measurement of the black hole mass of the supermassive black hole. In addition to measuring black hole masses, RM techniques can be used to study the structure and kinematics of the broad-line regions of AGN.

The SDSS Reverberation Mapping (SDSS-RM) program obtained repeated spectroscopy of 849 spectroscopically-confirmed quasars during 2014-2019 (within SDSS-III/BOSS and SDSS-IV/eBOSS), with the main goal of measuring ~100 black hole masses using RM techniques. Observations were scheduled with a cadence of four to five days in 2014 (SDSS-III), 2/month in 2015-2017 (SDSS-IV), and 1/month in 2018-2020 (SDSS-IV), weather permitting, in order to detect broad-line time delays on both short (<6 months) and long timescales. Typical exposure times were 2 hours/epoch for the 2014 observations and 1 hour/epoch for the 2015-2020 observations. Supplementary photometric data were obtained using the Canada-France-Hawaii Telescope from 2014-2017 and with the Steward Observatory Bok telescope in 2014-2020. Building on SDSS-RM, an expanded multi-object RM program is included in the Black Hole Mapper program in SDSS-V.

The survey is described by Shen et al. (2015a) and has been largely successful in obtaining RM measurements: Shen et al (2016a) reported several reverberation-mapping measurements from the program after analyzing the first year of spectroscopic data only, and Li et al. (2017) measured composite RM signals in the same dataset. Grier et al. (2017) combined the first year of spectroscopy with the first year of photometry and recovered 44 lag measurements in the lowest-redshift subsample using the Hbeta emission line. With the additional years of SDSS-IV monitoring included, Grier et al. (2019) reported 52 lag measurements using the CIV emission line; the addition of another year of SDSS spectroscopy and the inclusion of the PS1 photometric monitoring from 2010–2013 allowed additional lags to be measured (Shen et al. 2019b). Homayouni et al. (2019) measured inter-band continuum lags in many sources, allowing for investigations of accretion-disk properties. Additional studies based off of SDSS-RM data that aim to evaluate and improve RM and black hole-mass measurement methodologies have also been completed (Wang et al. 2019, Li et al. 2019). The final SDSS-RM dataset, which will include all of the PS1 data and seven years of SDSS spectroscopic monitoring, will span more than ten years and allow for the measurement of lags in the highest-luminosity subset of the quasar sample.

The high cadence sequence of observations and the resulting deep co-added spectra allow additional unique analyses beyond reverberation mapping. The SDSS-RM group has also reported on many other topics, such as studies of quasar host galaxies (Shen et al. 2015b; Matsuoka et al. 2015; Yue et al. 2018), broad absorption-line variability (Grier et al. 2015; Hemler et al. 2019), studies of extreme quasar variablity (Dexter et al. 2019) and investigations of quasar emission-line properties (Sun et al. 2015; Denney et al. 2016a; Shen et al. 2016b; Denney et al. 2016b; Sun et al. 2018; Dyer et al. 2019).

Target Selection

Previous spectroscopy of the PS1 Medium Deep Field MD07 (RA = 213.704 deg, DEC = +53.083 deg) provided redshifts of roughly 1,200 quasars in the redshift range 0 < z < 5 over the area of a single plate. The sample was limited to quasars with i < 21.7.

Quasars whose time delay should be easier to measure (e.g., lower redshifts, strong broad emission lines) were given higher priority, and these are indicated by the RM_TILE1 target class; essentially all of these targets were assigned a fiber.

Lower-priority targets, indicated by the RM_TILE2 target class, were tiled with the remaining fibers.

Three plates containing identical science targets were drilled at varying hour angle to ensure that the field was visible for six months. Each plate was given the normal number of sky fibers (80), but was allocated a substantially larger number of standard star fibers (70 rather than the usual ~20) to allow more rigorous tests of spectrophotometric calibration.

A known issue is that a very small number of targets were assigned an incorrect fiberID in one of the epochs. In DR16, the plate-mjd known to suffer from this error (7339-57518) was reprocessed using a manual fix to the plPlugMap file that largely fixed the mismatched fiber issue. Spectra with ZWARNING gt 0 are flagged as dropped fibers and can be discarded. However, it is possible that additional objects on this plate (and rarely on other plates) are still mismatched. We are in the process of manually fixing any remaining mismatched cases on a plate-by-plate basis, and will publish such corrections in the final SDSS-RM papers (in prep). The frequency of these events, however, is low (< 0.1%).

Papers describing (results from) the RM program

Dalla Bonta, E., et al., 2020, ApJ, 903, 112
Denney, K.D., et al. 2016, ApJ, 833, 33
Denney, K.D., et al. 2016, ApJS, 224, 14
Dexter, J., et al. 2019, ApJ, 885, 44
Dyer, J. et al., 2019, ApJ, 880, 78
Fonseca Alvarez, G., et al., 2020, ApJ, 899, 73
Grier, C.J., et al. 2015, ApJ, 806, 111
Grier, C.J., et al. 2017, ApJ, 851, 21
Grier, C.J., et al. 2019, ApJ, 887, 38
Hemler, Z.S., et al. 2019, ApJ, 872, 21
Homayouni, Y., et al. 2019, ApJ, 880, 126
Homayouni, Y., et al., 2020, ApJ, 901, 55
Homayouni, Y., et al., 2021, ApJ, submitted, arXiv:2105.02884
Kinemuchi, K., et al., 2020, ApJS, 250, 10
Li, J., et al. 2017, ApJ, 846, 79
Li, J., et al. 2019, ApJ, 884, 119
Li, J., et al. 2021, ApJ, 906, 103
Liu, T., et al., 2020, ApJS, 250, 32
Matsuoka, Y., et al. 2015, ApJ, 811, 91
Shen, Y., et al. 2015a, ApJS, 216, 4
Shen, Y., et al. 2015b, ApJ, 805, 96
Shen, Y., et al. 2016a, ApJ, 818, 30
Shen, Y., et al. 2016b, ApJ, 831, 7
Shen, Y., et al. 2019a, ApJS, 241, 34
Shen, Y., et al. 2019b, ApJL, 883, 1, L14
Sun, M., et al. 2015, ApJ, 811, 42
Sun, M., et al. 2018, ApJ, 854, 128
Wang, S., et al. 2019, ApJ, 882, 1, 4
Wang, S., et al., 2020, ApJ, 903, 51
Yue M., et al. 2018, ApJ, 863, 21