The Lick AGN Monitoring Project 2016

Transcription

1 SCIENTIFIC JUSTIFICATION The Lick AGN Monitoring Project 2016 Introduction: Reverberation Mapping Fundamentals. The discovery in 2000 of the correlation between the masses of supermassive black holes (BHs) in galactic nuclei and the stellar velocity dispersions of the host-galaxy bulges (the M BH σ relation; Ferrarese & Merritt 2000; Gebhardt+ 2000) forged a crucial connection between the previously disparate fields of active galactic nuclei (AGNs) and galaxy evolution. With this discovery came the realization that not only are BHs present in most or possibly all massive galaxies, but that the growth of BHs and their host galaxies must be fundamentally and tightly linked. Now, a central challenge in extragalactic astronomy is to understand the cosmological accretion and growth history of the supermassive BH population, to determine both how the growth of a BH can be limited or constrained by its host-galaxy environment (Silk & Rees 1998) and how feedback effects from BH accretion episodes in AGNs can play a role in shaping the star-formation history of galaxies, as suggested by a variety of theoretical models (e.g., Springel+ 2005; Croton+ 2006). Measurements of BH masses as a function of cosmic time, coupled with observations of the masses and dynamical properties of their host galaxies, can provide a direct means to study these co-evolutionary processes. Since dynamical detection of supermassive BHs is only possible in very nearby galaxies, observations of AGNs provide us the only means to investigate the evolution of BH masses at high redshifts. The best available method for determining BH masses in broad-lined AGN is reverberation mapping (Blandford & McKee 1982), which resolves the structure of the broad-line region (BLR) in the time domain, on scales of light-days to light-months around the BH. To briefly summarize the technique, the emission-line response to continuum variations in an AGN can be described by a transfer equation of the form L(v r,t) = Ψ(v r,τ)c(t τ)dτ, (1) where C(t) is the continuum light curve, L(v r,t) is the emission-line luminosity at line-of-sight velocity v r and observed at time t, and Ψ(v r,t) is the transfer function that maps continuum variability to the emission-line response. Determination of the shape of the transfer function (also known as the velocity-delay map) can in principle yield a wealth of information on the structure and kinematics of the BLR (Horne+ 2004). However, due to the limitations of temporal sampling and signal-to-noise ratio (S/N) of most reverberation datasets, it has only recently become possible to obtain much velocity-resolved information on the structure of Ψ(v r,t). More typically, the primary derived quantity is simply the response-weighted mean lag time τ for an entire emission line, usually determined from the cross-correlation of the continuum and emission-line light curves (e.g., Peterson+ 2004), which then gives the mean radius of the BLR as c τ. The basic dataset for a reverberation-mapping measurement consists of light curves for the AGN continuum and for at least one broad emission line, most often Hβ, obtained over an extended time period. Combining the measured lag time τ with the velocity width of the broad line ( V ) allows a simple virial estimate of the BH mass to be computed as M BH = f (c τ)( V ) 2 /G. The linewidth V is generally measured either as the FWHM or the second moment of the emission line width. The term f is a scaling factor that depends on the details of the geometry, inclination, and kinematics of the BLR, which are not known for individual objects. Since details of BLR structure cannot easily be determined on an object by object basis, the standard approach has been to apply a single value of the f factor to all AGNs. This value can be set either by making specific assumptions about the BLR geometry (i.e., a flattened disk structure) or by finding the value of f that results in the best agreement between the reverberation-based BH masses and the masses predicted from host galaxy kinematics via the M BH σ relationship (Onken+ 2004; Woo+ 2010). The spatial scales probed by reverberation mapping (of order light-days) are so small that the enclosed mass within r BLR = (c τ) is completely dominated by the mass of the BH. The inferred BH masses are thought to be accurate to roughly a factor of 3 (Onken+ 2004), with most of this error coming from the systematic uncertainty in the virial f factor which is generally unknown for individual AGNs. 1

2 Figure 1: Example results from our 2011 campaign, for Mrk 40. Left: Light curves of the U-band continuum (3650 Å) and emission lines including Hα, Hβ, Hγ, Hδ, He II λ4686, and the Fe II blends. Center: Cross-correlation functions for each line, measured against the V -band continuum. Right: Velocity-resolved reverberation results for Hβ, illustrating the lag in multiple velocity bins across the line profile. The lower panels show the mean and rms line profiles. From Barth+ (2015) and Barth+ (in prep). One of the most important applications of reverberation-mapping results has been to calibrate singleepoch methods for estimating BH masses in broad-lined AGNs (Shen 2013). This technique uses the observed correlation between BLR radius and AGN continuum luminosity (the r L relation; Bentz+ 2013) as a shortcut to obtain a simple estimate of the BLR size (c τ) from a single measurement of the continuum flux. This makes it possible to derive virial mass estimates for enormous samples of AGNs, extending out to the highest redshifts, for which detailed reverberation mapping would be impossible (e.g., Mortlock+ 2011). These single-epoch methods have become an essential tool for studying the cosmological evolution of the supermassive BH population, the distribution of Eddington ratios and its redshift evolution, and the correlations between BHs and their host galaxies (Shen 2013). However, single-epoch mass estimates suffer from the uncertain value of the virial normalization factor f, which is fundamentally a result of the unknown geometry and kinematics of the BLR. Consequently, different single-epoch recipes can yield M BH values differing by as much as 0.4 dex (McGill+ 2008). This uncertainty limits the accuracy to which we can infer the cosmological growth history of supermassive BHs. Nearly all research on BH masses in AGNs fundamentally relies on the reverberation sample for the calibration of the BH mass scale, and the accuracy of the derived masses is ultimately limited by our lack of understanding of the kinematic structure of the BLR. The Lick AGN Monitoring Project: Results and Accomplishments. The LAMP team began working on reverberation mapping in We have conducted large campaigns comprising 64 nights at the Lick 3m in 2008 and 69 nights in 2011, as well as single-object cadence-mode monitoring programs targeting Keplerfield AGNs in 2010 and 2012 and the bright Seyfert 1 galaxy NGC 5548 in All of these programs focused primarily on low-luminosity and low-mass Seyferts having Hβ lags in the range 3 15 days. Our results (published in 21 papers to date) have included the following: Successful reverberation lag measurements and virial mass determinations for 18 AGNs (Bentz+ 2009; Barth+ 2011ab,2013,2015, Pei+ 2014, Barth+ in prep.), which account for about 25% of the total reverberationmapped sample to date. The first clear detections of velocity-resolved reverberation in Hβ, illustrating a variety of kinematic behaviors in different AGNs, and development of new methods for measurement of 2-d transfer functions 2

3 (Bentz+ 2009,2010; Skielboe+ 2015, Barth+ in prep.). Major improvements to AGN scaling relationships including the M BH σ relation (Woo+ 2010; Park+ 2012) and the broad-line region radius- luminosity correlation (Bentz+ 2013). These scaling relationships are the crucial low-z anchor for determination of BH masses in high-z quasars. BLR radii are found to scale with AGN luminosity as r BLR L 0.53, with scatter of only 0.13 dex (Bentz+ 2013; Figure 3). Development of new spectral decomposition methods to improve the quality of reverberation data analysis, leading to the first successful detections of reverberation in the optical Fe II emission blends, and giving important new details of BLR photoionization structure (Barth+ 2013,2015). The methods pioneered by our team are now being adopted by other groups as part of the standard toolkit for reverberation data analysis (e.g., Hu+ 2015; Troyer+ 2015). Development of new dynamical modeling methodology to derive BLR structural, geometric, and dynamical parameters and BH masses independent of any assumptions about the f factor (Pancoast+ 2011,2014; Brewer+ 2011). This work is described further below. The powerful combination of outstanding Kast data and innovative approaches to data analysis has established our LAMP team as one of the leading groups working in this increasingly active and competitive field. New Directions in Data Analysis: Structural and Dynamical Models of the BLR. Measurement of velocity-resolved lags across the Hβ line can provide qualitative clues to the kinematic state of the BLR; an example from LAMP2011 is shown in Figure 1 (right panel). A BLR dominated by Keplerian, disk-like rotation will show a velocity-delay pattern that is symmetric about the line center, with the shortest lags in the high-velocity wings, because the highest rotation speeds correspond to material orbiting closest to the BH. If instead the BLR is dominated by radial motions, the velocity-delay map will show an asymmetric pattern, with longer lags in the blue wing for radial inflow (since the blue wing of the line corresponds to the far side of the BLR for inflowing gas) or longer lags in the red wing for outflow-dominated kinematics. Our team s work (Bentz+ 2009,2010; Barth+ 2011,2015 in prep) and work by other groups over the past several years (e.g., Denney+ 2010) shows that while inflow or outflow are indicated in a subset of AGNs, the majority of Hβ velocity-delay maps appear roughly symmetric, consistent with rotationally dominated kinematics. This is an encouraging consistency check for BH virial masses, which implicitly rely on the assumption of virial motion, but does not directly provide any quantitative improvement to mass estimates based on the virial equation. A long-standing goal has been to carry out detailed comparisons between measured 2-d transfer functions and dynamical models for the BLR in order to place quantitative constraints on BLR structure and dynamics and derive black hole masses (e.g., Horne+ 2004), but such efforts are hampered by the difficulty of transfer function measurement and the enormous complexity of the parameter space of BLR models. During the past 4 years, Co-I Treu s group has pioneered an alternative approach to analysis of reverberation data, bypassing the traditional route of measuring and then interpreting the transfer function. In this approach, BLR models are used to produce simulated reverberation data in the form of a time series of variable emission-line profiles which can then be compared directly with the data to yield constraints on BLR parameters and black hole mass. The method (known as the CARAMEL modeling code) is described in detail by Pancoast+ (2011, 2014a). To summarize briefly, the BLR is modeled as an orbit library of clouds moving in the gravitational potential of the BH. The models can encompass a broad variety of structures including disks, tori, and shells, and can accommodate infalling, outflowing, and rotational orbits. The model BLR geometry is described by parameters representing the radial density profile of clouds, the opening angle, and inclination angle. For a given BLR model, the observed continuum light curve from a reverberation campaign can be propagated outward through the model to the locations of the clouds. The reprocessed emission-line light from each cloud is then propagated in the observer s direction to produce a simulated broad emission line whose flux and profile vary in response to the continuum fluctuations. This simulated time series of line profiles can be compared directly with the data after application of our team s spectral decomposition methods to obtain a set of pure Hβ emission line profiles free of contamination from other spectral components. Using sophisticated methods to explore the multidimensional parameter space of the BLR geometry, dynamics, and BH mass, inferences are then drawn on the model parameters. This highly computationally expensive method 3

4 Figure 2: Results from CARAMEL dynamical modeling code applied to LAMP2008 data (Pancoast+ 2014). Left: Posterior distributions of black hole mass, BLR inclination angle θ i, and BLR opening angle θ o, for Mrk 40. Right: Inferred f factors as a function of BLR inclination angle, illustrating the first clear demonstration that these quantities are anticorrelated. Horizontal lines show estimates of the mean f factor determined by different groups in past work. requires data of high cadence and S/N, exactly what our LAMP campaigns provide. CARAMEL modeling has thus far been applied to 6 AGNs from the LAMP 2008 and 2011 campaigns (Brewer+ 2011; Pancoast+ 2012,2014b), and analysis of additional objects is in progress. CARAMEL modeling yields BLR sizes that are in good agreement with traditional cross-correlation analysis, but providing far more detail on the radial extent and vertical thickness of the BLR cloud distribution as well as the overall dynamical state of the gas. One of the most important results from this work is the derivation of constraints on the BH mass that are totally independent of any assumptions about the virial f factor : the f factor does not enter into the model calculations in any way. Remarkably, the BH masses derived from this modeling method are in generally reasonable agreement with the more simplistic virial mass estimates for these same AGNs, typically agreeing within a factor of a few. We can then determine the actual f factor for individual AGNs by combining the CARAMEL-derived BH masses with the reverberation lag and line width in the standard virial equation. Results from Pancoast+ (2014b) are illustrated in Figure 2. The right panel illustrates the f factors as a function of inferred BLR inclination for AGNs from the LAMP2008 program. This demonstrates the crucial result that higher f factors are indicated for AGNs for which the model finds lower BLR inclinations. An anticorrelation between inclination and f factor is exactly what would be anticipated because a nearly face-on BLR would have narrower lines and require a higher correction factor to obtain a correct mass from the virial equation. Our team s work is the first to demonstrate this fundamental trend. A long-term goal is to determine the distribution of f factors for a significant sample of AGNs over a broad range of BH mass and luminosity, so that the single-epoch methods used to constrain the cosmological evolution of BH masses can be placed on a firm quantitative footing. Next Steps for Reverberation Mapping: LAMP2016 Project Goals. Our past Lick campaigns primarily targeted AGNs with Hβ lags ranging from 3 days to 3 weeks, and most of our results were obtained for AGNs with Hβ lags of 3 10 days, corresponding to continuum luminosities of λl λ (5100 Å) erg s 1 according to the BLR radius-luminosity correlation (Bentz+ 2013). Similarly, most of the recent high-quality reverberation results obtained by other teams fall in this same luminosity range (e.g., Denney+ 2010). Given the small number and limited luminosity range of AGNs having high-quality velocity-resolved reverberation measurements and dynamical modeling to date, it is not known whether the dynamical character of the BLR changes systematically as a function of luminosity or Eddington ratio (L/L Edd ). A critical goal is to determine 4

5 Figure 3: Left: The radius-luminosity relationship, i.e., the correlation between BLR radius as measured from Hβ reverberation mapping and the AGN optical continuum luminosity (Bentz+ 2013). Continuum luminosity is given as λl λ measured at 5100 Å. Open circles denote new points added from our LAMP2008 sample and other recent programs. To date, all of the objects having CARAMEL modeling based on high-fidelity reverberation mapping data have BLR radii below 10 light-days. Right: The luminosity and redshift distributions of Type 1 (broad-lined) AGNs in SDSS, from Sun & Shen (2015). This proposal focuses on AGNs in the luminosity range erg s 1, corresponding to Hβ lags of days. whether BLRs show increasing evidence of radial outflows at higher luminosity, since this would directly impact the accuracy of virial mass estimates in luminous quasars. It is widely recognized as a problem that the single-epoch methods used to determine quasar BH masses at high z have only been calibrated using local reverberation-mapped AGNs at relatively low luminosity and Eddington ratio (e.g., Richards+ 2011; Shen 2013). In order to make further progress in establishing a definitive black hole mass scale for quasars, it will be essential to obtain high-quality velocity-resolved reverberation mapping data for AGNs at higher luminosities than those targeted in our past programs. We have therefore designed a program to expand our work into a significantly higher luminosity range, λl λ (5100 Å) erg s 1, corresponding to Hβ lags of days. By conducting an extensive search of AGN catalogs, we have defined an excellent sample of targets to probe this region of parameter space. Several AGNs with lags in this range have been monitored in past campaigns by other groups (e.g., Kaspi+ 2000; Peterson+ 2004). However, none of these past datasets have yielded sufficient data quality to allow for measurement of velocity-resolved reverberation, and the data quality would fall far short of what is required for BLR dynamical modeling with CARAMEL. With a major new investment of Lick 3-m observing time, our proposed program will produce the first set of AGN monitoring data capable of extending our work on BLR dynamics into this higher-luminosity regime, extending 1 2 orders of magnitude higher in luminosity than objects from our past LAMP samples. Our proposed new sample contains AGNs with expected BH masses in the range M, compared with for our previous LAMP targets. Our primary goals for the LAMP2016 program are: To measure Hβ reverberation lags, calculate BH virial masses, and add new data points to the BLR radiusluminosity correlation and the AGN M BH σ relationship in this higher-luminosity regime. To measure lags for additional lines including Hα, Hγ, He II λ4686, and the optical Fe II emission blends, and test photoionization models for the radially-stratified structure of the BLR (e.g., Korista & Goad 2004; Mor & Netzer 2012). 5

6 To measure velocity-resolved reverberation and transfer function structure in AGNs at significantly higher luminosities compared with previous work. To carry out CARAMEL dynamical modeling using data for multiple emission lines to directly determine BLR structural and dynamical parameters and BH masses, determine virial f factors, and examine trends of f factor with inclination, luminosity, and other parameters. The new data will yield major new insights into BLR physics on scales of light-days to light-weeks around the central BH. This will allow us to address fundamental questions concerning the origin and fate of the BLR gas, to distinguish between competing scenarios of the BLR as part of the inward accretion flow (Gaskell & Goosmann 2013) or as part of an outflowing wind driven from the accretion disk surface (Murray & Chiang 1997), and to test for luminosity-dependent trends in BLR structure and dynamics. The push to higher AGN luminosities and longer reverberation lags necessitates a longer monitoring duration than our 2.5 month campaigns in 2008 and In order to observe a sample of AGNs with lags of 3 7 weeks, widely distributed in right ascension so that observing time can be used efficiently, we have designed a campaign of duration 9 months. During this time, individual AGNs in the sample can be observed for continuous periods of 4 9 months depending on their RA and dec. Fortunately, the longer timescales of AGN variability at higher luminosities also mean that a longer-duration campaign does not require a nightly observing cadence. As our past work has demonstrated, optimal results are obtained when the observing cadence yields at least 5 observations over a span corresponding to the AGN s mean lag time, in order to fully sample the BLR variations over the range of timescales present in the transfer function. For an AGN in our target luminosity range, this means that an observing cadence of 2 nights per week is in the optimal range. We describe our requested campaign duration and cadence in more detail in the technical section of the proposal. Extending the luminosity range: a staged approach. Our long-term goal is to obtain high-fidelity reverberation mapping data over the full luminosity range illustrated in Figure 3, not just for Hβ but also for the UV lines Mg II and C IV in higher-redshift quasars. This requires us to pursue observing campaigns having even longer durations. In a separate but closely related program, Co-I Jong-Hak Woo will be leading a three-year campaign targeting AGNs having anticipated lags of 100 days, using Shane nights purchased by Seoul National University starting in early A subset of our LAMP team will participate as collaborators in the SNU program. After the completion of our LAMP2016 program in early 2017, our next goal is to propose a longer-duration ( 5 year) program focusing on AGNs having day lags. Fortunately, the required cadence for detecting lags in such high luminosity AGNs is only 1 night per month. This combination of observing campaigns with durations spanning 9 months to 5 years will provide a wealth of new data for critically testing and calibrating the mass scale of supermassive black holes in quasars across the full range of black hole masses and luminosities. This proposal is focused solely on the 9-month campaign, representing the first component of this staged approach. The Competitive Landscape. An important new development in reverberation mapping is the advent of large, multi-object programs using multi-fiber spectroscopy, including SDSS-RM (Shen+ 2015) and OzDES (King+ 2015). These projects have the advantage of observing hundreds of targets over a multi-year duration, but the observing cadences are low and the quality of spectrophotometric calibration of fiber data is poor compared with Kast long-slit data. In a given SDSS or OzDES field, most of the AGNs are distant and faint, leading to relatively low S/N. Optimistically, these projects may be able to produce substantial numbers of reverberation lags for Hβ, Mg II, and C IV in quasars over a broad redshift range, but it is unlikely that they will yield data of sufficient S/N or cadence for velocity-resolved lag measurements or dynamical modeling. Another new development is the advent of fully robotic reverberation mapping, pioneered by the AGN Key Project of the LCOGT network. LCOGT has low-resolution spectrographs mounted on its two 2-m Faulkes telescopes, and the AGN Key Project team has recently submitted a paper describing their first spectroscopic monitoring results on one object (Valenti+ 2015, submitted to ApJL). While robotically acquired spectroscopy has the potential to provide an increasing number of reverberation measurements for 6

7 bright AGNs, these efforts are still in their very early stages. It is not yet feasible for the LCOGT AGN Key Project to mount a monitoring campaign on the scale of what our team can accomplish at Lick, and the data quality from the Kast Spectrograph is superior to that of the LCOGT spectroscopic data in every respect, including S/N, spectral resolution, and spectrophotometric calibration. Thus, although multi-fiber and robotic instruments are beginning to contribute to reverberation mapping, dedicated campaigns with instruments such as Kast still play a crucial role by providing the benchmark datasets of high cadence and high S/N. Our team has several strong advantages in this field that make the UC System and Lick Observatory the ideal environment to pursue this work. The Lick 3-m is one of the only telescopes in its class that is operated by a single institution with time allocated by a single TAC, enabling a large program like this to be carried out over an extended duration. Most other groups working in reverberation mapping are either using 1-m class telescopes (Denney+ 2010), which limits observations to a small set of the very brightest AGNs, or are using larger telescopes but with very poor time sampling, yielding inferior results (Kollatschny & Zetzl 2010). Furthermore, the Kast spectrograph is superior to any other instrument being used for reverberation work, and the Kast red CCD upgrade will provide a major improvement. The LAMP team has a demonstrated track record in this field, and team members have wide-ranging expertise in diverse areas of AGN physics, BH mass measurements, and AGN host galaxy studies. The LAMP project has earned a high degree of visibility in the AGN community, which is advantageous both for our team and for Lick Observatory in general. Reverberation mapping is a prime example of an area where Lick Observatory can be at the forefront of current research by enabling major progress in a key field of extragalactic astronomy. Proposed Duration, Cadence, and Sample Size. With this proposal, we are requesting a monitoring program of duration 9 months starting on or close to 5 May 2016, with a cadence of two nights per week, for 25 nights in 2016A and 52 nights in 2016B and a total of 77 nights. During the course of this campaign we will monitor 24 AGNs. Our past Lick reverberation programs have collectively achieved a success rate of 67% for measurement of Hβ reverberation lags in the AGNs that we have monitored, because some AGNs did not exhibit sufficiently strong variability for the lag to be recovered. Using this figure as a guide, we anticipate that our proposed program will lead to 16 new measurements of reverberation lag and datasets suitable for dynamical modeling. See the technical section below for full details of our sample selection and time request. Summary. We propose a 9-month reverberation-mapping campaign with the Kast Spectrograph, in order to expand the number of AGNs having high-quality, velocity-resolved reverberation measurements and push to AGN luminosities that are 1 2 orders of magnitude higher than targets from our previous Lick campaigns. The results will provide fundamental new information on the structure and kinematics of AGN broad-line regions and enable new progress in improving the methods used to estimate BH masses in AGNs. References. Barth et al. 2011a, ApJ, 732, 121 Barth et al. 2011b, ApJ, 743, L4 Barth et al. 2013, ApJ, 769, 128 Barth et al. 2015, ApJS, 217, 26 Bentz et al. 2008, ApJ, 689, L21 Bentz et al. 2009, ApJ, 705, 199 Bentz et al. 2010, ApJ, 720, L46 Bentz et al. 2013, ApJ, 767, 149 Blandford & McKee 1982, ApJ, 255, 419 Boroson & Green 1992, ApJS 80, 109 Brewer et al. 2011, ApJ, 733, L33 Croton et al. 2006, MNRAS 365, 11 Denney et al. 2010, ApJ 721, 715 Ferrarese & Merritt 2000, ApJ 539, L9 Gaskell & Goosmann 2013, ApJ, 769, 30 Gebhardt et al. 2000, ApJ 539, L13 Horne et al. 2004, PASP 116, 465 Hu et al. 2015, ApJ, 804, 138 Kaspi et al. 2000, ApJ, 533, 631 King et al. 2015, MNRAS, 453, 1701 Kollatschny & Zetzl, 2010, A&A, 522, 36 Korista & Goad 2004, ApJ 606, 749 Marziani et al. 2003, ApJS, 145, 199 McGill et al. 2008, ApJ 673, 703 Mor & Netzer 2012, MNRAS, 420, 526 Mortlock et al. 2011, Nature, 474, 616 Mushotzky et al. 2011, ApJ, 743, L12 Murray & Chiang 1997, ApJ, 474, 91 Onken et al. 2004, ApJ 615, 645 Pancoast et al. 2011, ApJ, 730, 139 Pancoast et al. 2014a, MNRAS, 445, 3055 Pancoast et al. 2014b, MNRAS, 445, 3063 Peterson et al. 2004, ApJ 613, 682 Richards et al. 2011, AJ, 141, 167 Shen 2013, arxiv: Shen et al. 2015, ApJS, 216, 4 Silk & Rees 1998, A&A 331, L1 Skielboe et al. 2015, arxiv:1502:02031 Springel et al. 2005, MNRAS, 365, 11 Sun & Shen 2015, ApJ, 804, L15 Troyer et al. 2015, arxiv: White & Peterson 1994, PASP, 106, 879 Woo et al. 2010, ApJ 716, 269 Zu et al. 2011, ApJ, 735, 80 7

8 TECHNICAL DETAILS Campaign Design- General Goals. Our program is designed for the goal of measuring reverberation lags in AGNs having anticipated lags of 3 7 weeks. This requires a combination of long duration and sufficient cadence to resolve the BLR variations. A further consideration is the predicted El Niño winter, which could lead to long stretches of bad weather through early spring Based on these general considerations and the simulations described below, we chose to plan a campaign of 9 months duration beginning at the start of the May 2016 dark run. Details of the sample selection and planned observing cadence are described below. Table 1: Primary Sample Object Name RA Dec z magnitude/ estimated Hβ lag monitoring duration filter (days) (days) Mrk :54:06 +23:25: V Mrk :31:05 +28:17: V Mrk :04:01 +10:26: r Mrk :05:56 +03:42: g SBS :19:21 +59:08: r c382 18:35:03 +32:41: B NPM1G :53:04 +27:50: B RX J :44:04 +28:33: r PG :11:54 +18:41: V PG :17:12 +14:14: B c445 22:23:49 02:06: r RBS :56:36 +05:25: r Zw :36:21 +45:39: B B B 01:41:58 +39:23: B Mrk :06:16 00:17: g Ark :16:11 00:08: B Mrk :14:15 +45:41: B Mrk 9 07:36:57 +58:46: B MCG :23:43 +22:54: g Mrk :25:13 +52:17: g Note: Magnitudes are quoted from NED and include at least a portion of the host galaxy, in addition to the AGN. These magnitudes are only approximate since the AGNs are variable sources. The monitoring duration is the duration of the longest continuous period during which the AGN can be observed at airmass < 2 during a campaign with our proposed start and end dates. Targets are listed in RA order starting at 13h, because our proposed campaign will begin in late Spring. We have a long list of additional alternate targets with expected lags slightly shorter or longer than our target range. Sample Selection Details. Our sample has been selected through a comprehensive search of AGN catalogs (e.g., Boroson & Green 1992; Marziani+ 2003; Sun & Shen 2015), the SDSS archives, and our own target lists from previous Lick survey programs. Our primary selection criteria are (a) estimated Hβ lag in the range days, based on applying the BLR radius-luminosity relation from Bentz+ (2013); (b) apparent magnitude V < 17; (c) redshift z < 0.08 to ensure that the [O III] λ5007 line falls below the D55 dichroic cutoff on the blue CCD; (d) declination > 5. For each AGN we determined the monitoring duration as being the longest continuous period when the AGN could be observed at airmass < 2 during a campaign with our chosen start and end dates. We placed a further constraint that our sample should only contain AGNs for which the monitoring duration was at least 5 times larger than the expected Hβ lag, in order to ensure that lags can be measured accurately. We do not specifically select based on broad-line FWHM or black hole mass. It is important to note that the lag predictions are only rough estimates, since the AGNs could have varied significantly in luminosity (hence changing the lag) in the time since SDSS spectra or other literature data were taken. We primarily select AGNs that have not previously been reverberation mapped, but we do include a few objects having older measurements of lesser quality. Table 1 lists the primary sample of AGNs satisfying our selection criteria. We also have a long list of alternate targets having predicted lags slightly shorter or longer than our preferred range, and we will continue 8

9 to search for additional targets that can be added to the monitoring sample in case any of the primary targets turn out to be unsuitable (for example if an AGN has made a transition to a very faint state). We have more than enough targets, well distributed in RA, to fill our observing nights efficiently. Justification of Campaign Duration and Cadence. While much previous ground-based reverberation work was focused on the relatively straightforward task of measuring the mean Hβ lag over the entire emission line, our project is focused on the much more demanding goal of determining the shape of the velocitydependent transfer function and obtaining data of high enough quality for dynamical modeling. That is, our measurements need to recover information on the time-dependent changes in Hβ profile shape, not just the changes in total line flux. This sets very stringent requirements for our observations. Namely, we require an observational cadence that is sufficiently frequent to resolve the time-dependent emission-line variations, and a campaign duration long enough that we are able to build up a significant reverberation signal from material across the entire radial extent of the BLR, out to its outermost radius. Longer durations are always better since a longer campaign has a higher probability of catching strong features or flares in the light curves, which carry the most power for determining the transfer function shape. Furthermore, longer-duration campaigns decrease the risk of catastrophic failures where even the mean lag cannot be measured due to a lack of sufficient variability during the monitoring period. Our aim is to design a project that will maximize the information our data will yield on BLR structure and kinematics, within the constraints of a logistically feasible and schedulable campaign. The quality of a reverberation measurement depends on several parameters, the most important being the duration and cadence of the spectroscopic and photometric campaigns, the S/N of the observations, and the variability amplitude of the AGN. To illustrate how cadence and duration affect the results, we carried out a suite of simulations of reverberation campaigns, in which we model the response of the Hβ line flux to continuum changes. Each simulation was carried out by generating a random continuum light curve with a power spectrum of fluctuations of the form P( f ) f α where f is the temporal frequency of fluctuations and with α = 2.5 based on Kepler results (Mushotzky+ 2011). The continuum variability was normalized to an amplitude of 15% RMS over a 1-year duration, typical of AGNs in this luminosity range, and we assumed that the emission lines respond linearly to continuum variability with a 1:1 response to changes in the optical continuum. (The ionizing UV continuum is much more highly variable but not directly observable.) Our simulations only model the response of the Hβ total flux; we do not attempt to model velocity-resolved variations. Thus, the transfer function becomes a 1-d convolution kernel. We assume a Gaussian shape for the reverberation transfer function, with a mean lag of 24 days (similar to the median value for our sample) and a Gaussian dispersion equal to 20% of the lag. To simulate the spectroscopic campaign, we computed models where either 1, 2, or 3 nights per week were allocated to our project. The simulated spectroscopic monitoring period ranged from 90 to 270 days. To model seasonal weather variations in an approximate way, we assume 15% random weather losses during the first half of the spectroscopic monitoring period, and 50% weather losses during the second half. We assumed that photometry observations would be taken on 60% of all nights, to account for scheduling efficiency and weather losses. Noise was added to the simulated data to yield S/N = 50 for both the photometric and spectroscopic light curves. For each combination of monitoring duration and cadence, we generated 500 simulations. The lag was measured from the simulated data using the interpolation cross-correlation method of White & Peterson (1994), as illustrated in Figure 4. Table 2 lists the median measurement error on the reverberation lag in days as a function of duration and cadence. These simulation results confirm our general expectations: in particular, increasing the duration and sampling rate of the campaign leads directly to higher-quality reverberation results with smaller errors. It is important to emphasize that these simulations only give a rough indication of the expected results, since every object will have a different variability amplitude and transfer function shape, and the fraction of time lost to weather is unpredictable. Nevertheless, the trend shown here remains true in general: a long-duration campaign is of the utmost importance in order to obtain high-quality results, particularly as we push toward AGNs at higher luminosity with longer lags. 9

10 Figure 4: Left panel: Example of a successful simulation for a target with 6-month spectroscopic monitoring duration, 2 nights/week of scheduled spectroscopic observations with 15% random weather losses during the first 3 months and 50% losses during the last 3 months, and photometric monitoring on 60% of all nights. The top two panels show the simulated continuum and Hβ light curves, and the bottom panel shows the cross-correlation function, which results in a measured lag of 23.8 ± 1.5 days, in agreement with the input lag of 24 days (marked with a dotted line). Right panel: Spectra of three targets, illustrating the strong, broad Hβ emission lines and AGN-dominated continuum. Table 2. Simulation results: Median error in lag measurement (in days) as a function of campaign duration and cadence, for input lag = 24 days # scheduled Kast Spectroscopic monitoring period (months) nights per week Note: Results in green represent the sweet spot where we can obtain excellent reverberation results in a logistically feasible and manageable program, and our time request for this program is matched to this cadence and duration range. While these simulations are somewhat simplified and do not capture the full complexity of a real reverberation campaign, a minimal goal is to achieve errors of < 10% for measurement of the overall lag of the Hβ line. According to the simulation results, the sweet spot for achieving this goal is in the combination of a 4 9 month monitoring duration and a 2 nights/week observing cadence (Table 2). A 1 night/week cadence only achieves < 10% errors for targets that can be observed for a continuous period of 9 months, which is only achievable for a small subset of our sample. Going from 1 to 2 nights/week of scheduled observations leads to a major reduction in measurement uncertainty for all monitoring durations. The simulations also illustrate that going to a 3 nights/week cadence begins to push into the regime of diminishing returns, in terms of improving the accuracy of the results. A 3 nights/week cadence would also pose more difficult logistical problems for observing and would be much more disruptive of other programs. We further emphasize that these simulations only illustrate the error on measuring the mean emission line lag, which only conveys a small part of the total information that we plan to extract from our data. In order to determine the transfer function shape, we need much more than just the bare minimum number of nights that would allow a simple lag measurement. Our experience from previous campaigns provides the best illustration that high-cadence reverberation datasets can provide a revolutionary new ability to extract constraints on BLR dynamics from the data. Further progress in this field can only be made with high-fidelity reverberation datasets for a substantial number of objects, and this requires dedicated campaigns of both long duration and high cadence. Based on all of these considerations, we propose to carry out an ambitious program which will yield an extremely high-quality dataset: a campaign of 9 months duration, with a cadence 10

11 of 2 nights per week, spanning May 2016 through January We urge the TAC to consider the importance of granting our full time request of 77 nights. As our simulations show, decreasing the number of nights for our program would directly diminish the quality of the science that we are able to extract from our project. Additionally, the unpredictable weather at Mt. Hamilton is an important factor to consider, and a full allocation of 77 nights will still allow us to get very good data even if the weather is worse than average (which is exactly what occurred during our Spring 2011 campaign). We are investing major financial and personnel resources into this project and it is critically important for us to obtain a dataset of the highest possible quality. Unlike typical survey programs, our project relies on a single observing campaign of fixed duration, and nights lost to scheduling gaps or bad weather cannot be made up in the following year. We have secured significant NSF funding to support this project, and UCR Chancellor s Postdoctoral Fellow Vivian U is fully supported during the and academic years to work on this project as her top research priority. With the current array of funding and resources available to our team, the 2016A/B semesters are the ideal time for us to carry out an ambitious reverberation mapping program. It has been 5 years since our team s last large program at Lick, and averaged over multi-year timescales our reverberation work only uses a small fraction of the total 3-m time. Since our project s nights will be distributed over a 9-month duration spanning two semesters, our program will allow for considerable scheduling flexibility to accommodate the needs of the UC observing community and allow for other timesensitive projects to proceed normally. Optimal Dates and Scheduling. As described above, several considerations drove us to choose a program starting in late spring and continuing for 9 months duration. We specifically request a start date close to May 5 corresponding to the start of the May dark run, and an end date of January (These start and end dates are certainly flexible by a small margin, but any substantial changes to the start or end dates would require revisions to our sample selection and logistical planning.) A cadence of 2 nights/week then leads to a request of 25 nights in 2016A and 52 nights in 2016B, for a total of 77 nights for the full program. It is important to avoid large gaps in our schedule, especially given the unpredictable Mt. Hamilton weather. Our request is for 2 nights per week during the campaign, but the specific distribution of those nights can be somewhat flexible if it is helpful in scheduling other programs during the gaps. In order to achieve the best cadence, our optimal scheduling would be two one-night runs per week, spaced roughly evenly in time (aside from full moon; see below). However, given the difficulty of optimizing the 3m schedule for many observing teams, it is acceptable for some of our time to be scheduled in 2-night runs if necessary on occasion. We do not request 3-night runs at any time, since that would detract from the more uniform cadence we require to have well-sampled light curves with only small gaps. Our targets are sufficiently bright that most of them can be observed even during bright time provided that they are not too close to the moon. (In past campaigns we successfully observed targets that were 20 from the full moon on occasion.) However, better data quality is obtained during darker nights. We therefore request that nights within ±2 nights of full moon not be assigned to our program, while still following the requested cadence of 2 nights/week as closely as possible given this constraint. Finally, we request that the maximum gap between scheduled nights for our program should be at most 7 nights during full moon and at most 5 nights at any other time during our campaign. Summary: We request 2 nights per week between 2016 May 5 and 2017 January 30, allocated mostly in 1-night runs with a roughly uniform cadence and with a maximum gap of 7 nights at full moon and 5 nights at other times, and only excluding time within 2 nights of full moon. Instrumental Setup and Calibrations. We will use the d55 dichroic, the 600 line grism on the blue side, and the 600/7500 grating on the red side, in order to have the best combination of broad spectral coverage and moderate spectral resolution. We will use a 4 slit width so as to be relatively insensitive to seeing variations, and each object will be observed at a fixed PA (optimized for each individual target) so that our spectroscopic aperture includes the same portion of the host galaxy in every observation. Typical exposure times will be minutes per object, split into 2 separate exposures for cosmic-ray cleaning. Exposure times will be 11

12 chosen to achieve S/N = per pixel in the extracted spectra, consistent with the data quality of our past campaigns. With the new red CCD, fringing will not be an issue, so it will not be necessary to take dome flats during the night at the position of each object. We will take standard calibrations (biases, arcs, and flats) each afternoon, and observe well-calibrated flux standards during the nights. Observing logistics. We plan to use our remote observing facilities for a substantial fraction of this project. We will still plan to do some observing at Mt. Hamilton, primarily for training new graduate students and postdocs who will be observing for the first time. New postdocs and graduate students will always observe with an experienced postdoc or faculty member to ensure quality and consistency in the observations. Our team maintains a project web site with very detailed instructions on setups, calibrations, and observations. This ensures that all team members obtain data of uniform and high quality throughout the long program. Supplementary Observations. In order to measure accurate light curves for the AGN continuum, it is essential to have photometric monitoring data. Following a strategy similar to our past projects, we will carry out nightly V -band monitoring of each AGN using robotic and queue-scheduled telescopes. These will include KAIT at Lick (run by Filippenko s group), the Las Cumbres Observatory Global Telescope Network (through Treu and Barth s participation in the LCOGT Reverberation Mapping Key Project led by PI Keith Horne of St. Andrews University), the Liverpool Telescope (through proposals submitted by Horne), the West Mountain Observatory 0.9-m (run by Brigham Young University, through collaboration with Mike Joner of BYU), Mount Laguna Observatory (through collaboration with SDSU faculty member Douglas Leonard), the Whipple Observatory 1.2-m (through Anna Pancoast at CfA), and the CSU San Bernardino Murillo Observatory (through collaboration with CSUSB faculty member Carol Hood). Our team has an informal commitment of telescope time (or commitment to submit proposals as needed) from each of these, and such arrangements have worked very well for our past AGN monitoring programs. Our goal is to obtain light curves with nightly or almost-nightly sampling by combining observations from all of these facilities. Use of multiple telescopes at widely separated locations also helps to guard against major losses of time if any one site should suffer equipment failures or long stretches of bad weather. Time swaps to extend our temporal baseline. Our sample contains targets with a very broad RA range, including objects in the 13 15h RA range which are observable early in our campaign but which will disappear by late summer. For objects having a monitoring duration of < 140 days as listed in Table 1, our goal is to extend the temporal coverage by 1 2 additional months if possible. In order to achieve this, the Filippenko group has agreed to observe a subset of these objects during their Shane nights in early spring 2016 (February April). In return, we can use a bit of time during the early portion of our May/June nights to observe any high-priority supernovae or other ToO targets. Similarly, we will work out a time swap arrangement in 2017A in order to extend the temporal coverage for objects at the end of our sample s RA distribution (around 9h), to add a further 1 2 months of light curve coverage. The points added to the light curves through these time swaps will have lower cadence than our main program but will still add value to the lag measurements by extending the time baseline significantly. Path to Science from Observations. We will reduce our photometric and spectroscopic data promptly so that we can update our continuum and emission-line light curves as soon as new data are available. This enables us to ensure data quality throughout the campaign and focus our attention on the highest-priority objects if weather conditions are not optimal. Our team has all of the tools needed for reductions and analysis. Members of our team have developed our own software for multi-component fitting and decomposition of the spectra (Barth+ 2015), cross-correlation analysis (Barth+ 2011a,b), fully automated measurement of photometric light curves including data from multiple telescopes (Pei+ 2014), and dynamical modeling to derive BLR structural and geometric parameters and black hole masses (Pancoast+ 2011,2014a). We will also carry out lag measurements using the publicly available JAVELIN code (Zu+ 2011), which measures lags by modeling the AGN light curve as a damped random walk. Technical Concerns. The observational techniques we are using are well-developed and our team has extensive experience in this field. Our team s reverberation analysis software is well tested and reliable. The 12