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R2-D2: Roman and Rubin -- From Data to Discovery

The NASA Nancy Grace Roman Space Telescope (Roman) and the Vera C. Rubin Observatory Legacy Survey of Space and Time (Rubin), will transform our view of the wide-field sky, with similar sensitivities, but complementary in wavelength, spatial resolution, and time domain coverage. Here we present findings from the AURA Roman+Rubin Synergy Working group, charged by the STScI and NOIRLab Directors to identify frontier science questions in General Astrophysics, beyond the well-covered areas of Dark Energy and Cosmology, that can be uniquely addressed with Roman and Rubin synergies in observing strategy, data products and archiving, joint analysis, and community engagement. This analysis was conducted with input from the community in the form of brief (1-2 paragraph)"science pitches"(see Appendix), and testimony from"outside experts"(included as co-authors). We identify a rich and broad landscape of potential discoveries catalyzed by the combination of exceptional quality and quantity of Roman and Rubin data, and summarize implementation requirements that would facilitate this bounty of additional science with coordination of survey fields, joint coverage of the Galactic plane, bulge, and ecliptic, expansion of General Investigator and Target of Opportunity observing modes, co-location of Roman and Rubin data, and timely distribution of data, transient alerts, catalogs, value-added joint analysis products, and simulations to the broad astronomical community.

of potential discoveries catalyzed by the combination of exceptional quality and quantity of Roman and Rubin data, and summarize implementation requirements that would facilitate this bounty of additional science with coordination of survey fields, joint coverage of the Galactic plane, bulge, and ecliptic, expansion of General Investigator and Target of Opportunity observing modes, co-location of Roman and Rubin data, and timely distribution of data, transient alerts, catalogs, value-added joint analysis products, and simulations to the broad astronomical community.
2. MILKY WAY AND SOLAR SYSTEM SCIENCE 2.1. What is the composition, physical state, and morphology of the small bodies in the solar system?
The Sun, Moon, comets and five planets have been observed and studied by humans since the time they became a distinct species, but new populations of objects in our solar system continue to be discovered. Within the past few decades our understanding of our solar system's formation and evolution has been revolutionized by e.g. the discovery of the trans-Neptunian objects, the irregular satellites of giant planets and, just within the past few years, the detection of the first two macroscopic interstellar objects (ISOs) passing through the inner solar system. These new classes of objects probe the edges of our understanding of the formation of our and exoplanetary systems, while the extreme members in color, physical state, and morphology of long-known populations test the limits of our ability to model the solar system's evolution.
One of Rubin's key science goals is to generate a catalog of the solar system that will contain an order of magnitude more objects than are currently known. Within its vast set of discoveries Rubin is likely to identify extreme objects within and passing through our solar system such as main belt object cratering or disruption events, small objects with outrageous morphologies, near-Earth objects on impact trajectories, interstellar objects, and perhaps even a distant planet in our own solar system. Roman will provide detailed observations of these faint, extreme objects to explore how they fit into the puzzle of our own solar system's formation and the larger picture of all planetary systems. High resolution Roman images of 'active' small objects will determine whether the events are due to thermal spin up, impacts, or other processes. High precision Roman photometry will allow the determination of the shapes of the faintest and most elongated objects in the solar system e.g. to determine whether 1I/Oumuamua's unusual shape remains uncommon when compared to similar-size objects in our solar system.
Roman and Rubin together will provide spectrophotometric characterization of interesting targets from the near-UV through the NIR while Roman's prism and grism will e.g. enable identifcation of H 2 O absorption features in asteroids and comets. If an object is detected on an Earth-impact trajectory, Roman's faint limiting magnitude and space-based vantage point will provide the necessary astrometry to refine its orbit and impact probability. Finally, the LSST provides the best opportunity in the foreseeable future of detecting a distant planetary-size object in our own solar system (Sheppard & Trujillo 2016;Batygin & Brown 2016). Roman's unique capabilities will be important to revealing its properties and establishing its dynamical and evolutionary trajectory to its current state and location.
Rubin's all-sky surveying, repeat cadence, and deep limiting magnitude are an ideal combination for detecting the extreme members of the population of small objects within and passing through our solar system. For instance, Rubin will detect asteroid collisions in the main belt (e.g. Bottke et al. 2005); interstellar objects passing through our solar system (e.g. Meech et al. 2017); objects with extremely slow and fast rotation rates (e.g. Pravec & Harris 2000); those with remarkable colors (e.g. Sheppard 2010); distant objects on cometary orbits that have not yet begun to sublimate volatiles (e.g. Jewitt 2005) and, perhaps, unknown planets bound to our Sun (e.g. Mustill et al. 2016). Holler et al. 2018 andHoller et al. 2021 provide an exhaustive discussion of the small body science potential with Roman and synergistic opportunities with Rubin. The two systems will operate in different but overlapping wavelength regimes that will enable calibrated spectrophotometry from the near-UV to the near-IR to determine the composition of the most compelling small bodies identified in our solar system. Roman's NIR capability makes it a powerful tool for characterizing active and disrupted objects because it will be sensitive to larger ejected dust particles that persist longer in a comet's and asteroid's environs than smaller dust particles.
Some of the objects detected by Rubin will be too faint for followup characterization by groundbased telescopes and their transient nature will require rapid acquisition and characterization with Roman's imaging filters, grism and prism. For instance, the first ISO, 1I/'Oumuamua, was discovered on 2017 Oct 19 and the last ground-based observations occurred on Nov 23, but observations with Hubble doubled the time range of observations and were critical to identifying its non-gravitational acceleration (Micheli et al. 2018).
One of the more compelling solar system science problems is measuring the distribution of water using small bodies as tracers. Some asteroids show evidence of hydration in an absorption feature at about 0.9µm (e.g. Rivkin et al. 2002). Roman's low-resolution prism instrument is well-suited to identifying and characterizing this broad band while the prism, grism and some of the filters will be important for identifying water-ice absorption features near 1.6µm and 2.0µm ( Figure 1). One of Roman Space Telescope's core scientific goals is to improve our understanding of exoplanet demographics through a dedicated microlensing campaign (Roman Galactic Bulge Time Domain Survey). Roman and Rubin have the potential to teach us much more about the prevalence and formation of planetary and substellar mass objects, beyond the baseline Roman program. How does accretion work during the star/planet formation processes? How does the low-mass initial mass function (IMF) vary as a function of environmental parameters such as metallicity? How prevalent are free-floating substellar objects compared to those orbiting higher-mass stars? These questions can be addressed through suitable combination of Roman and Rubin observations/capabilities in the following areas: (1) detection and characterization of substellar objects via photometry and microlensing, and (2) exploiting eruptive YSOs to understand the temporal evolution of accretion during star and planet formation.
At substellar masses, for example free-floating brown dwarfs, our knowledge of the initial mass function is limited by the small volume over which existing surveys can detect/discover these cold objects (Kirkpatrick et al. 2021). The combination of Roman and Rubin data at red-optical and near-infrared wavelengths will dramatically expand the volume over which we can detect L and T type brown dwarfs (e.g., Stauffer et al. 2019;Aganze et al. 2021). This will allow us for the first time to begin probing the low-mass initial mass function in the Galactic thick disk and halo, and thereby check for any metallicity dependence of the low-mass star formation process (e.g., Bromm 2013;Chabrier et al. 2014) [Meisner, Sainio pitches]. As shown in Figure 2, Roman monitoring of the Roman Galactic Bulge Time Domain Survey footprint will suffer from temporal gaps in coverage. By filling in these gaps, Rubin can help constrain models of Roman Galactic Bulge Time Domain Survey microlensing events, pushing to relatively high masses. Simultaneous Rubin monitoring during Roman Galactic Bulge Time Domain Survey observations can also break exoplanet microlensing degeneracies. [Street pitch] In terms of further understanding star and planet formation, Rubin (through its wide area, sensitivity and repeat coverage) will transform the study of young stellar object (YSO) outbursts (e.g., Audard et al. 2014;Elbakyan et al. 2021) by detecting them in greater numbers and to larger distances (in more varied environments) than ever before. Such outbursts may account for a significant fraction of accreted mass during star formation. Pre-existing Roman imaging (to characterize the quiescent state) and follow-up (both imaging and spectroscopy) will be needed to understand the physical properties of erupting YSOs (Figure 3) identified from Rubin. Although YSO outburst decay time scales can be up to years or even decades, obtaining prompt follow-up shortly after the eruption is highly valuable for constraining models of these events. [Ginsburg, Kastner pitches] See As end products of the most massive stars through mass loss and powerful supernova (SN) explosions, the demographics of neutron stars (NSs) and black holes (BHs) are central to our understanding of stellar evolution. While NSs have a hard surface, the gravitational influence of BHs is the only way  . High resolution Hubble Space Telescope (Hubble) imaging from the Hubble Legacy Archive of the nearby YSO PV Cep in outburst, which is one of the handful of objects with such imaging. The image reveals evidence of a conical nebula carved out by an outflow. Roman high resolution imaging follow-up of Rubin-discovered YSO outbursts will disambiguate the sources of the eruptions and establish the presence and morphologies of cavities carved by outflows from these YSOs.
to find and characterize them. Historically, BHs have been discovered primarily via X-ray emission from surrounding hot material accreted from a binary companion (e.g. Corral-Santana et al. 2016). We are now entering an era where multiplexed spectrographs like DESI and SDSS-V, and astrometric missions like Gaia can search for the long-sought population of non-accreting BHs in wide binaries via radial velocity (e.g. Gu et al. 2019;Wiktorowicz et al. 2020) and astrometric (e.g. Mashian & Loeb 2017;Yamaguchi et al. 2018) shifts, respectively. Yet, not only is our understanding of the accreting NS/BH population demographics severely incomplete (e.g. Gandhi et al. 2020;Jonker et al. 2021), we have just beginning to detect some of the estimated ∼ 10 7 − 10 8 isolated Galactic BHs (Fender et al. 2013;Olejak et al. 2020), or the 25,000 BHs expected to have clustered in the central parsec of the Galactic Center (Miralda-Escudé & Gould 2000).

Roman and Rubin synergies into the dark universe: Isolated compact objects
Microlensing is the only way to characterize free-floating Galactic BHs (Paczynski 1986). With ∼ 10 4 microlensing events expected during its Bulge survey (Penny et al. 2019), Roman could find ∼ 100 BHs and ∼ 300 NSs (Gould 2000a;Lam et al. 2020) that would offer a completely new window into the remnant mass function. As intrinsically massive objects, NSs/BHs are expected to be characterized by long-lived events (Wiktorowicz et al. 2019) spanning much longer than the planned ≈ 72 day observing seasons. A Rubin survey of the Roman bulge footprint to fill-in the gaps between the observing seasons ( Figure 2) would be crucial for photometric coverage to constrain the microlensing parallax (Gould 2000b), in addition to enhancing the overall rate of planets, substellar and stellar systems discovered via microlensing [Street pitch]. Also, unlike ground based surveys, Roman would be uniquely placed to detect the astrometric microlensing signal (WFIRST Astrometry Working Group et al. 2019a) and offer exquisite constraints on the lens mass to systematically search for these NS/BH lenses [Lu, Lam, Wyrzykowski pitches], as well as determine the masses for freefloating planet candidates. This has now been demonstrated with Hubble follow-up observations of candidate BH microlensing events from the ground-based OGLE survey, with the confirmation of astrometric microlensing by a 7.1 M BH (Sahu et al. 2022) as well as a catalog of several dark compact objects (Lam et al. 2022).
See Table of Implementation Requirements: 1.6, 1.7. 2.5. Roman and Rubin synergies into the dark universe: Accreting compact objects With its southern location, the Rubin observatory will be capable of creating an exquisite time domain movie of outbursting sources in the Galactic plane -dwarf novae, novae and X-ray binaries (Strader et al. 2018). Roman's planned high cadence time domain survey of the Galactic bulge will provide an excellent complement to Rubin's capabilities by providing unprecedented historical photometry of the progenitors, allowing us to map out the poorly understood roles of these eruptive episodes on their long term evolution (Johnson et al. 2019;Maccarone et al. 2019). Roman's Galactic bulge survey will also detect the most dust obscured events and completely new types of transient phenomena, where Rubin limits will be very constraining. A wide area Roman map of the Rubin Galactic plane footprint could routinely enable the characterization (e.g. distance, evolutionary state) of the progenitor systems, which remain poorly studied due to their very faint quiescent counterparts.
2.6. What is the distribution of stars and dust in our Galaxy?
What is the distribution of stars and dust throughout the Milky Way, and what does this tell us about our Galaxy's formation and evolution? Does the Milky Way have well-defined spiral arms, and what would it look like to an external observer? SDSS enabled detailed Milky Way tomography of (mostly) extragalactic fields (e.g., Jurić et al. 2008), revealing for the first time large-scale substructures in the Galactic distribution of stars, for instance the Sagittarius and Monoceros streams (Newberg et al. 2002). Pan-STARRS, covering 3/4 of the sky and most of the Galactic plane, took this one step further, allowing for novel three-dimensional maps of stars and dust (e.g., Green et al. 2015). Gaia has now complemented Pan-STARRS with high-accuracy trigonometric distances over the entire sky, another major step toward making the ultimate three-dimensional map of stars and dust in our Milky Way Galaxy (e.g., Green et al. 2019;Helmi et al. 2018;Antoja et al. 2018).
However, Gaia and Pan-STARRS are fundamentally limited in terms of their depths and wavelength coverage, which does not extend beyond ∼1 µm. This lack of depth and infrared sensitivity limits the extent to which the Galactic plane's distant and/or heavily dust-obscured reaches can be mapped.
The combination of very deep Rubin optical and Roman near-infrared photometry throughout the Galactic plane can make an unprecedented map of the 3D distribution of stars and dust in dense regions of the Milky Way. Roman's angular resolution is highly complementary to Rubin in terms of the improved deblending of Rubin sources that it can offer. Roman near-infrared photometry of the plane can push the 3D map to distances/reddenings at which Rubin has lost sensitivity (see Figure  4). [Zucker pitch] Focusing more specifically on the Milky Way bulge/nucleus, the combination of Roman and Rubin can complete the RR Lyrae census in this central region (e.g., Minniti et al. 2016), thereby unraveling mysteries about how the nuclear star cluster was assembled: did it form through merging of primordial globular clusters? How old is the Galactic nuclear star cluster? Multi-epoch Roman/Rubin data can also reveal clusters, streams and kinematics of old stellar populations near the Galactic center. For all of these Milky Way mapping applications, Roman's combination of large field of view plus Hubble-like angular resolution and depth uniquely enables this science. [Minniti, Fernández-Trincado pitches] See Table of Implementation Requirements: 1.8, 1.9, 2.3, 3.3.

TRANSIENT DISCOVERY AND TRANSIENT HOSTS
3.1. Using gravitationally lensed SNe as a time machine and an independent measure of H 0 . One of the most intriguing developments to arise in the era of "precision cosmology" is the tension between the value of Hubble's constant of expansion "H 0 " measured from direct local measurements, and the model-dependent value inferred from the Cosmological Microwave Background. Understanding if this tension is real, and not due to systematic errors or model assumptions, is critical for providing evidence for new physics beyond the standard model. Gravitationally lensed SNe provide a direct and completely independent measure of H 0 from these two methods.
A SN that explodes in a background galaxy that is strongly lensed by a foreground galaxy or cluster, resulting in multiple images due to gravitational bending of the SN light, can be used to measure H 0 by measuring the relative time delays between each SN image. SNe have several advantages for so-called "time delay cosmography" compared to other variable phenomena, such as variable quasars, including the fact that their intrinsic light curves and luminosities are well determined, especially for the class of Type Ia SNe. This method has been attempted in the only three known multiply imaged SNe: Type II SN Refsdal (Kelly et al. 2015), Type Ia SN 2016geu (Goobar et al. 2017); Type Ia SN AT2016jka . While each of these objects had unique challenges that limited their cosmological utility, high quality observations for dozens of such systems could, in principle, yield constraints on H 0 to better than 1% precision (Birrer & Treu 2021). Furthermore, one can use the magnification and time delays of the lensed SN images as a "time machine", to study a SN in its earliest explosive phase (Shu et al. 2018). This will be particularly valuable for SNe in cluster lens systems where the time delays are on the order of ∼ 100 days, giving time to predict the date and location of a subsequent SN image to shed light on the SN progenitor and pre-explosion mass-loss, as well as probing deviations from a smooth lensing model for the foreground mass distribution (Goobar et al. 2017).
A large enough sample of lensed SNe, could also be used as a competitive probe of dark energy. Fortunately, the rates of strongly lensed SNe expected from Rubin (hundreds: Oguri & Marshall 2010) and Roman (tens: Pierel et al. 2021) as calculated from mock catalogs, are reaching the levels relevant for such experiments. Roman and Rubin's lens samples will also be highly complementary in redshift, with Roman best suited to detect higher-redshift lensed SNe (z > 0.5) . There are several possible observational methods for finding and monitoring lensed SNe, from blind time domain searches by looking for an overluminous SNe ( Figure 6), to monitoring of known galaxy-galaxy or galaxy-cluster strong lens systems (Shu et al. 2018). Roman's high angular resolution imaging can be used to identify arcs surrounding the lensing galaxy, and multi-color imaging is essential to maximize the contrast of the lens arc and model the magnification. [Holwerda pitch] Identification of strong lenses at scale can be done with machine learning, a citizen science approach or from spectroscopic signatures of the blend of galaxies in a galaxy-galaxy lens system. A vetted list of strong lenses can then be monitored as a "watch list" in the Rubin transient alert stream for the signature of a SN going off in the source galaxy. With a pre-calculated catalog of photo-z's, when a candidate SN is detected in Rubin with an overluminous peak absolute magnitude, spectroscopic follow-up can confirm the SN redshift and trigger follow-up imaging with Roman to confirm the multiple images.
3.2. How do galaxies and black holes co-evolve through cosmic time?
The co-evolution of massive black holes and the galaxies that host them is supported by several observational and computational lines of evidence, yet the details of the physical mechanisms driving this symbiotic relationship are still uncertain. A fundamental question in the context of galaxy and black hole co-evolution is the nature of the black hole seeds (see the recent review by Volonteri et al. 2021). Observational evidence for ∼ 10 9 solar mass black holes when the universe is < 1 Gyr old (Fan et al. 2001) creates difficulties for models of galaxy evolution in which remnants from the first stars coalesce to form the central black hole seed. More massive black hole seeds from, for example, direct collapse of density fluctuations in the early universe can grow to these large sizes in a shorter time, yet we have no observational evidence to support such massive seeds nor the existence of the conditions required for them to form and grow. [Bentz pitch] The wide field, time domain nature of Rubin will allow for the identification of low-or intermediate-mass black holes in the local universe via the detection of stochastic nuclear variability in dwarf galaxies (Baldassare et al. 2018;Ward et al. 2021), as well as previously dormant black holes in quiescent galaxies that reveal themselves by tidally disrupting and accreting a star (Gezari 2021). The high resolution imaging, and wide area coverage of Roman will characterize the host galaxies of these accreting central black holes, including luminous quasars [Lacy pitch]. Thus Rubin and Roman together can map the properties of black holes and their host galaxies over a large range of mass scales, providing important constraints on the formation mechanisms of seeds in the early universe, and their growth through accretion and mergers over cosmic time (see Figure 7).
Black hole feeding, while easy to identify, still presents numerous challenges to our understanding of how gas is funneled from large galactic scales down into the nucleus and ultimately onto the black hole. The smallest relevant spatial scales cannot be resolved with imaging, and so time domain techniques such as reverberation mapping (or echo mapping) have been developed (Cackett et al. 2021). Using time resolution rather than spatial resolution to study light echoes in AGN allows their internal structures to be mapped. Yet the number of AGN that have been studied in this way remains small because of the typical necessity of targeting individual objects and monitoring them over long time scales. Reverberation mapping studies of a large number of AGN spanning a more diverse range of black hole and galaxy properties is needed to improve our understanding of black hole feeding [Homayouni, Lyu, Shen pitches]. Rubin light curves may provide an important component to facilitate such studies. If a time domain component is also provided by Roman then the mapping of AGN structures on spatially-unresolvable scales becomes possible through the combination of Roman and Rubin photometry (dust torus reverberation) and/or Roman grism spectroscopy plus Rubin photometry (emission line reverberation).
Finally, mergers provide a separate but important pathway for the growth of massive black holes. Galaxy mergers are relatively straightforward to identify and much progress has been made in understanding how the process unfolds, yet to date there are few observational constraints on the merger process between their massive black holes (De Rosa et al. 2019). High-resolution images of galaxies hosting dual AGN with separations ranging from scales of kpc to sub-arcsec are needed to inform the pairing and evolution of the merger process for massive black holes. [Shen, Liu pitches] Rubin monitoring will uncover dual or blended AGN through their variability, while high resolution Roman imaging will constrain their apparent separations as well as the merger stage of the host.

How do the rates and properties of all classes of transients depend on their host galaxy environments and stellar populations?
Observations of transient events provide brief windows to study stars, compact objects, and their underlying environments. Combining observations from Roman and Rubin will enable studies of transient environments on scales ranging from the integrated host galaxy, to localization within the host galaxy, to identification of the progenitor star. These studies will deepen our understanding of known transients and help to interpret the range of new transients that will be discovered with Roman and Rubin.
By combining photometry from Roman and Rubin, properties of transient host galaxies can be determined to help interpret known transients and to more efficiently prepare for detecting new transients [French pitch]. The stellar masses, star formation rates, recent star formation histories, photomet- ric redshifts, structural parameters, color gradients, and levels of dust extinction can be measured using the combined Rubin ugrizY and Roman 0.5 − 2µm photometry for transient host galaxies. Spectroscopic classification will only be possible for a small sub-set of the transients discovered with Rubin or Roman. The host galaxy properties of a transient can be used to interpret the likely class of the transient and to identify the most interesting transients for follow-up observations. Several studies have found that given the difference in progenitor systems for type Ia SNe and core-collapse SNe, the differing stellar populations in the host galaxies allow for transients to be classified based on the host galaxy information alone (Baldeschi et al. 2020;Gagliano et al. 2021). Tidal disruption events (TDEs) occur at high rates in post-starburst, green valley, and centrally-concentrated galaxies (Arcavi et al. 2014;French et al. 2016;Law-Smith et al. 2017;Graur et al. 2018;Hammerstein et al. 2021;Arcavi et al. 2021). Similarly, the host galaxies of changing-look AGN (Dodd et al. 2021) have also been found to lie preferentially in green valley host galaxies, and may provide clues on what is driving their extreme changes in accretion rate [Bentz pitch]. Using photometry from Roman and Rubin especially making use of Roman's spatial resolution to identify highly concentrated galaxies, likely host galaxies of interesting nuclear transients can be pre-identified, such that new transients can be rapidly flagged for multi-wavelength followup.
On more local scales, resolving the location of a transient within a galaxy can provide important information about the nature of a transient [Gezari pitch]. Even a single Roman observation of a transient would provide an improved localization constraint compared to the information available from Rubin. Localization with Rubin will be limited to ∼0.1 arcsec at best, whereas Roman can localize transients to few×10 −3 arcsec. If a transient can be constrained to be consistent with a galaxy nucleus on milliarcsecond scales, contamination from SNe can be all but removed when searching for TDEs or other SMBH transients. Similarly, the localization of a transient to a spiral arm or star forming region within a galaxy indicates the transient is likely to be associated with the death of a massive star. Good localization constraints can enable more detailed comparisons of SNe with the metallicities and stellar populations of their parent environment (e.g. Galbany et al. 2018). Type Ic SNe are found in more metal-rich environments and super-luminous SNe (SLSNe) are found in more metal-poor environments (Galbany et al. 2018;Izzo et al. 2018). These trends are obscured by the varying conditions across a galaxy, especially when comparing the central bulge -which may dominate the light in a fiber spectrum -and the conditions in the outer disk.
On the smallest scales, progenitor stars of SNe imaged years or decades before the explosion can provide direct links from massive star progenitors to the types of SNe we observe (Podsiadlowski et al. 1993;Smartt 2009). We show a recent example of the likely progenitor for SN 2019yvr in the host galaxy NGC 4666 from Kilpatrick et al. (2021) in Figure 8. While we cannot predict the locations of all future SNe, many SNe are discovered in nearby galaxy clusters such as Virgo and Fornax every year, even in the era before Rubin and Roman. A targeted Roman survey of these nearby clusters would provide deep pre-explosion imaging of SN to be discovered in the years after the targeted survey [Kilpatrick pitch]. The IR imaging capabilities of Roman are well-suited to investigate the progenitors of SNe in dusty star forming regions or cases of failed SN where the progenitors are obscured in the optical by circumstellar dust.
See 3.4. What are the electromagnetic properties of gravitational wave events, their relation to binary properties, and implications for r-process nucleosynthesis?
To address this question we require rapid, deep, and dedicated optical/NIR follow-up of gravitational wave events and short-duration gamma-ray bursts (SGRBs). In the case of GW-detected mergers, the sky localizations are expected to be at best ∼ 10 deg 2 and the distances will be tens to hundreds of Mpc. The resulting faintness of the optical/NIR emission may therefore necessitate the use of Rubin and/or Roman, and would benefit from mutual coordinated follow up to assess the presence of both optical and NIR emission. For example, in the case of the only existing GW-EM detected merger to date (GW170817) there appear to be two emission components: one peaking in the optical on a timescale of ∼ day and the other peaking in the NIR on a timescale of ∼ week. Whether this is ubiquitous to NS-NS mergers (or present in NS-BH mergers) is a key question that will help to address the origin of these two components.
In the case of SGRBs, the mergers are viewed along the axis of the relativistic jet and the emission is therefore significantly brighter at early time. Such events are predominantly located at higher redshifts than GW-detected events, up to z ∼ 1, and they therefore provide a complementary sample of NS-NS/NS-BH mergers to what the GW detectors can find. This sample can enable studies of redshift evolution in the properties of the mergers, as well as a different angular view (faceon orientation in SGRBs compared to all viewing angles in GW-detected mergers). However, the majority of SGRBs are localized poorly (detections by Fermi), with similar localizations to GW events. Roman+Rubin rapid coordinated follow-up of these events will increase the SGRB detection rate by at least a factor of three, and will more than double the NS-NS merger rate when combined with GW-detected events.
Another promising avenue for the detection of NS-NS and NS-BH merger counterparts is the "serendipitous" discovery of kilonovae in wide-field survey data, i.e. independently of external GW or SGRB triggers. These sources will likely be found at large distances beyond the horizon of the ground-based GW detectors. They will allow us to study the emission at all viewing angles, correlations with redshift, and possibly enable yet another type of cosmological studies (Coughlin et al. 2020). Recent works have shown that a few tens of kilonovae are expected to be discovered by the Rubin main survey (Setzer et al. 2019;Cowperthwaite et al. 2019;Andreoni et al. 2022). Remarkably, Roman will have the capability to detect kilonovae out to redshift z 1 (Chase et al. 2021).
The key scientific questions that will uniquely be addressed by Roman+Rubin synergy are: (i) How prevalent is r-process nucleosynthesis in NS-NS/NS-BH mergers? What are the typical ejecta masses and velocities? How do these quantities depend on the properties of the merging objects (NS vs. BH, masses, mass ratios)? (ii) What is the angular structure of the ejected matter, and what can this teach us about the merger process? (iii) Do all mergers produce relativistic jets? (iv) Is there significant evolution in the nature of the binaries and the properties of the ejected matter as a function of redshift (at z ∼ 0 − 1)?
The key requirement for implementation is rapid target-of-opportunity (TOO) follow up with both Roman and Rubin covering the larger localization regions to a sufficient depth to detect (or rule out) an optical/NIR counterpart (kilonova or afterglow). In practice, this means observations to as faint as ∼ 24 AB mag (and potentially fainter for more distant sources) over an area of up to tens of deg 2 . We generally expect the optical emission to peak first, so rapid response with Rubin may need to lead the rapid response with Roman. However, since we have only one example of an optical/NIR counterpart of a GW-detected merger, we do not yet know the relation between optical and NIR emission for the population. Note that in Andreoni et al. (2021) they show that with proper planning, TOO observations with Rubin would only interrupt ∼ 1% of the baseline survey. The capabilities of TOO observations with Roman have also been investigated. However, theoretically we expect the IR to be more ubiquitous for kilonovae than the optical -it is sensitive to a much wider range in viewing angle, mass ratio, lanthanide fraction and remnant lifetime. In fact, some NS-NS and NS-BH mergers may not even be discoverable by Rubin and only be accessible to Roman, making TOO NIR imaging and spectroscopy follow-up with Roman even more critical (see Kasliwal et al. whitepaper  3.5. What end-states of stars exist in nature that have yet to be discovered? The mapping between the lives of stars (as we observe them in our Milky Way Galaxy and nearby galaxies) and the deaths of stars (as we observe them as SNe or other transients, and as remnants) remains only crudely sketched. The textbook picture is that a star's death is controlled primarily by its initial mass, but this simple picture has slowly been unravelling in recent years. Observations have been a driving force in driving our understanding of stellar death, in particular the appreciation that the outcomes of stellar evolution are much more diverse than what appears in textbooks. The discovery of SNe that are extremely luminous or extremely feeble, those that are unusually long-lived or extremely short-lived, those with unusual spectral properties and so on have all provided new questions about the evolution and end-states of stars. This revolution remains incomplete due to the limited capabilities of current facilities, which have limited depth and largely only scan the optical range.
Roman and Rubin together provide the ability to cover major "blind spots" of current surveys. Roman's infrared survey capabilities allow it to survey for transients that are concealed by dustwhether that dust originates from the surrounding galaxy environment or from the stellar progenitor. This gives it a unique ability to probe a range of phenomena not accessible to optical surveys. In the central regions of LIRGs and ULIRGs, star-formation is at its most furious and the potential for unusual forms of stellar death due to enhancement of the high-mass IMF or dynamical interactions are maximized. It also has the power to survey for self-obscured transients, for which the optical display is shielded by shells of circumstellar dust synthesized by the progenitor. Any other end-of-life stellar outcome with a characteristic temperature that causes it to emit primarily in the infrared range will also be uniquely detected by Roman-kilonovae (case 3.4) are the classic example, but there may be other phenomena that peak in this region, as suggested by a recent Spitzer survey (see Figure 9), including electron-capture SNe from very low-mass stars, and mergers of massive stars Kasliwal et al. (2017). Finally very high-redshift transients from early generations of stars will inevitably be redshifted in the the infrared range.
The synergy with Rubin is critical to this effort, because the phenomena above would otherwise be lost in a sea of ordinary optical SNe without the benefit of deep optical limits and without accurate photometric redshift constraints. Rubin observations close in time with Roman ones will allow genuinely red transients to be picked out and the Rubin deep reference imaging will permit rapid estimates of their luminosity and distance, which are key to appropriately targeting follow-up with other facilities.
See The dozens of ultra-faint dwarf (UFD) galaxies and stellar streams located at distances up to ∼400 kpc from the Milky Way and Andromeda (M31) have dramatically augmented our understanding of galaxy formation and evolution at small scales. The continuous stream of precise radial velocity and 6D phase space information for MW and M31 halo stars are yet another rich dataset with which we can outline the evolutionary history of the Local Group's two most massive galaxies. However, the extent of our knowledge of hierarchical galaxy formation on the smallest scales is generally rooted in observations of only these two galaxy halos. Understanding the MW and M31 in a cosmological context requires a statistically significant sample of similar mass analogs and a census of their halo substructures at depths and wide-field areas that only Roman and Rubin can reach.
The Rubin observatory is roughly expected to discover all MW satellites with M V < 0 mag, µ < 32 mag/arcsec 2 in the Southern hemisphere, and it will nearly double the number of known satellite  Kasliwal et al. (2017) galaxies around nearby galaxies (∼3-4 Mpc) to put them on roughly equal footing with our current knowledge of M31's galaxy luminosity function (M V ∼ −6.5; E. Bell, Fig. 10; e.g., Drlica-Wagner et al. 2019;Mutlu-Pakdil et al. 2021). It will also yield the most thorough search for stellar streams in the outer halo (> 50 kpc) of the MW [Belokurov pitch] and around nearby galaxies (Pearson et al. 2019). Rubin will also enable the detection and characterization of stellar halos around dwarf and Milky-Way mass galaxies allowing for direct comparison to numerical simulations of hierarchical assembly [Williams pitch]. Together, dwarf galaxies, streams and stellar halos provide three unique probes to (i) reconstruct the dynamical history of the MW and analogous nearby galaxies, (ii) constrain the properties of dark matter halos (∼ 10 6 − 10 12 M ), and (iii) to test models of galaxy formation at small scales (see Bullock & Boylan-Kolchin 2017).
Owing to its dramatically improved star-galaxy separation and deep point-source limits, Roman will be more sensitive still to dwarf galaxies, streams and stellar halos. Roman will enable follow-up searches of satellite galaxies around nearby hosts (∼3-4 Mpc), probing nearly 10x deeper (M V ∼ −4 mag), yielding 10s−100s of dwarfs per galaxy system (Bell 2021). With a statistical sample of host galaxies and their corresponding satellite populations at these faint limits, Roman+Rubin will allow us to draw the first statistical connections between the faintest known satellite populations and their hosts, including (i) correlations between the presence of a massive satellite and satellite phase space configurations (e.g., Battaglia et al. 2022;Garavito-Camargo et al. 2021;Patel et al. 2020) and (ii) the subsequent imprints that satellite galaxies leave throughout their hosts' stellar halos, including stellar wakes and streams (e.g., Garavito-Camargo et al. 2019).
Such a large sample of UFDs across a variety of environments will also provide the most robust constraints on the formation, evolution, and properties of UFDs (i.e., initial mass functions), the oldest known stellar systems in the Universe (Simon 2019). Furthermore, UFDs and any potential evidence for perturbations and gaps in streams will illuminate the threshold for galaxy formation in subhalos, star formation in the early Universe, and further our understanding of reionization (i.e., the near/far connection, Weisz & Boylan-Kolchin 2019). Roman+Rubin will also reveal thousands of strong lens measurements (Oguri & Marshall 2010;Collett 2015;Weiner et al. 2020) that, along with precise measurements of UFD population statistics, will sharpen constraints on dark matter properties that influence the abundance and properties of small subhalos, including its primordial temperature, interactions, and particle mass (Nadler et al. 2021b,a) [Nadler, Bechtol pitches].
Fitting a simple Gaussian-process model of turbulence to reconcile the sky positions of point sources measured by a space-based telescope with their locations in ground-based surveys can drastically improve astrometry from the ground. Using Gaia positions and Dark Energy Survey images in the riz bands, Fortino et al. (2021) reduced astrometric variance due to atmospheric turbulence by a factor of about 12, resulting in RMS turbulence errors of ∼3-5 mas per exposure. Assuming 20 exposures over a nominal 5-year baseline this results in an expected proper-motion precision of ∼35 uas/yr with current data. This translates to a tangential velocity uncertainty of ∼50 km/s at ∼300 kpc from the Galactic center, comparable to measured orbital speeds of typical MW objects at that distance. Improvement by a factor ∼5 would allow us to determine precise orbits to the virial radius, while an improvement by a factor ∼10 would allow us to measure internal velocity dispersions of dwarfs ( Figure 11).
The biggest improvement in accuracy for this type of joint reduction comes from an increased density of astrometric sources (Fortino et al. 2021). Roman will provide much more densely sampled point-source data since a typical Roman exposure is both 4-6 mag deeper than Gaia and far less affected by extinction. Roman will be an exquisite astrometric instrument since the core-science bulge microlensing survey will deliver detailed knowledge of the point-spread function that is necessary for the success of the core-science weak lensing survey at high latitudes. In addition, Roman will benefit from using Gaia's full extended-mission catalog as its astrometric frame (WFIRST AWG 2018). Thus we can expect Roman to have far higher source density at similar astrometric accuracy to Gaia, facilitating a dramatic improvement in turbulence-reduction modeling for Rubin. Importantly, this strategy requires only catalog-level astrometric data from Roman to re-reduce the pixel-level data from Rubin.

Galaxy evolution and large-scale structure through cosmic time.
There is tremendous cosmological information available in the 3D distribution of galaxies, and together, Roman and Rubin will produce unprecedented, detailed maps of the sky. Photometric and spectroscopic galaxy surveys (including galaxy positions, redshifts, fluxes, and shapes) produced by these two observatories will offer new insight on cosmological models and the formation of large scale structure ( Figure 12).
The astronomical community is interested in a breadth of science cases that probe large scale structure and galaxy evolution. These include: Clusters & protoclusters -Rubin with its wider field and bluer imaging, probes a slightly different population of galaxy clusters than Roman which has higher resolution and redder imaging. As a result, Roman and Rubin will probe complementary redshift ranges (z = 0.1 − 0.2 and z = 0.5 − 0.7, respectively). At higher redshifts, Rubin's survey plus Roman's spectroscopic follow-up can be useful to identify and characterize galaxy composition of proto-clusters [Ettori pitch].
Reionization -The combined wavelength coverage of data from Roman and Rubin in particular Roman's near-infrared sensitivity and Rubin's variability monitoring capabilities, will allow us to select well-controlled samples of z > 6 sources. The nature and the global properties of these high-redshift sources, including galaxies and AGNs, such as the luminosity functions, star-formation rate densities, or the clustering properties, would be derived with unprecedented accuracy. The large survey footprint of the combined survey also benefits from sampling a variety of environment conditions, and allowing us to explore how different galaxy populations contribute to cosmic reionization. [Pello pitch]. A combined survey could also extend our ability to identify quasars out to z = 7 − 10, which would allow us to further map cosmic reionization. [Tee pitch] Low surface brightness Universe -To study the low surface brightness Universe statistically, one needs a large area, deep survey. Roman's high spatial resolution for object recognition and deblending, when combined with Rubin's unprecedented depth for finding faint sources, can provide the observations to explore this. In this case, having high-quality photometric redshifts will be crucial because objects will be too faint for spectroscopic follow-up. [Montes pitch] Lensing, morphologies, and distances -For many Roman+Rubin synergistic applications, having a robust calibration of Rubin photometric redshifts with Roman spectroscopy will be imperative [Wallman pitch]. Cosmological parallax may provide a new probe of cosmological geometry, but such a measurement requires a new lens sample for parallax measurements. Rubin's wide survey and photometric redshifts, plus Roman's high resolution to model the lenses are necessary for this work.

Data-driven discoveries with Roman and Rubin: Supporting simulations as parallel data sets
The Roman and Rubin telescopes will generate orders of magnitude more data than previous missions. Rare astronomical objects will be discoverable in statistical quantities; common populations will achieve large enough sample sizes to be sensitive to second-order effects; previously undiscovered populations will be unveiled for investigation. The majority of these new discoveries are likely to be data-driven: based on characterizing these huge data sets using the advanced techniques of modern data science and machine learning rather than choosing a single model to explain the data.
Examples of discoveries enabled by the data-driven approach include quantifying the number of dimensions (e.g., distinct physical parameters) needed to describe a data set, or identifying unusual objects that fall outside the manifolds that contain most of the data. Such data-driven discovery requires cross-matched catalogs in addition to the ability to do cross-catalog queries (that is, searching for targets that meet some criteria that requires both Roman and Rubin data products, such as optical and near-infared time domain signatures or image products). With large datasets like this, the only feasible way will be to co-locate the data sets.
The data-driven approach prescribes a fundamental role for simulations of the objects being studied. In particular, they are crucial to make quantitative comparisons with observations by multiple instruments, train machine learning models, deal with complex uncertainties, and connect observations in detail to the underlying physical processes that govern them. The intermediate step of synthetic observation-imprinting the error model of a particular instrument on the output of a simulationis the critical yet underappreciated link between the excitement of discovery and the resolution of scientific questions. To fully achieve the scientific promise of Roman and Rubin investment in the development of simulations and synthetic observation pipelines for frontier science is important, as well as publicizing them among the community, training its members to use them, and determining what functionalities need to be added are all key to maximizing the potential of these synergies.
In many of the most exciting potential synergies between these two observatories, Rubin acts as a discovery engine and Roman as the follow-up instrument. In this mode, it is crucial to understand the impact of the selection function on the results of the initial object census and the subsequent selection of candidates for follow-up [Nadler pitch]. Simulated catalogs allow the quantification of these effects, extending the impact of the few yet valuable targeted observations relative to the full population and lending statistical power to generalizations. Furthermore, detailed simulations allow for forecasting of follow-up observations to explore sensitivity to unconstrained physics within the constraints of the initial census results, reconciling observations by very different instruments to a common underlying source. Realizing the full potential of synergistic observations with Roman and Rubin will require community access to a standardized, maintained suite of flexible instrument models, validated by the instrument teams, for carrying out synthetic observations. Enormous and synergistic data sets also pose new challenges for data exploration, which hinges on responsive tools for visualization. As one pitch put it, How do we most effectively leverage humans' remarkable abilities to detect patterns and the unexpected when one instrument may generate petabytes of data spanning imagery, spectra, diagnostic telemetry, catalogs, MCMC outputs, and machine learning data products? (P.K.G. Williams, "Visualizing Big and Wide Data in the 21st Century") While each mission will develop its own data exploration tools, realizing the full combined potential of Roman and Rubin will require a coordinated effort to build an environment where the data can be visualized and explored side-by-side. The more seamless the transitions between the different data products, the more power it will have to generate new discoveries.
The vast size of the Roman and Rubin catalogs will allow many measurements to push to unprecedented sensitivity. This new regime comes with the challenge of coping with non-Gaussian uncertainties: for example in photometric redshifts, phase-space modeling, or stellar population modeling. Forward modeling with simulated data is the preferred tool for meeting these challenges, yet is currently extremely computationally demanding in almost all cases. New advances-in computational infrastructure, interpolation algorithms, and analytical statistics-are needed to speed up forward modeling of Roman+Rubin data for key science questions.
Acknowledgements: We would like to thank the ex-officio members of our Roman and Rubin Synergy working group for their guidance and input throughout this process, including Harry Ferguson (STScI),Željko Ivezić (University of Washington), Neill Reid (STScI), and Beth Willman (AURA). Data Products 2.1 Automated identification and specialized image processing for moving objects in the Roman images 2.2 Timely reporting of moving object detections by Roman and Rubin to the Minor Planet Center 2.3 Cross-matched catalogs, joint source detection, cross-survey forced photometry, and joint astrometric solutions 2.4 Cross-matched catalogs, joint source detection, cross-survey forced photometry for moving objects 2.5 Timely reporting of transient alerts by Roman to the community 2.6 Machine-learning classification of morphology on Roman data to identify structures such as strongly lenses systems 2.7 The ability to create a watchlist of interesting targets to be notified when Rubin detects a spatially coincident transient alert 2.8 Detailed understanding of instrumental effects, selection functions, and sources of systematic errors for both Roman and Rubin Joint Analysis Methods 3.1 Precovery of newly identified Rubin targets in earlier serendipitous Roman observations 3.2 Joint value-added catalogs of static targets (deblending, photo-z's, morphology, colors, SED fitting) 3.3 Forced photometry, including ability to forced photometer subsets of the data like individual epochs e.g., for moving (solar system) objects 3.4 Forced spectroscopic extraction in Roman using Rubin imaging as input catalog including moving objects 3.5 Astrometric cross-calibration of Rubin pixel-level data with turbulence-reduction modeling using Roman catalogs to enable precision proper motion measurements 3.6 Catalogs of key galaxy parameters constructed from joint Roman+Rubin catalogs should be made early, such that alert brokers can incorporate this information when processing new transients 3.7 Roman spectroscopic calibration of Rubin photo-z's Computing Infrastructure 4.1 Coordination and communication of Roman and Rubin with multi-messenger facilities, with a clear set of trigger criteria for TOO observations, and a clear (automated) implementation plan 4.2 Co-location of Roman and Rubin data in a common analysis environment to bring compute to the data 4.3 Support for simulated data: execution and documentation of a simulation database, up to date (versioned) instrument models for synthetic observations, parallel analysis of real and simulated data, catalog-level error modeling 4.4 Train the community in recent computational advances in big data (beyond querying databases, e.g., cloud computing) 4.5 New advances-in computational infrastructure, interpolation algorithms, and analytical statistics-are needed to speed up forward modeling of Roman+Rubin data 6. APPENDIX: COMMUNITY SCIENCE PITCHES First Author Title of Community Science Pitch MILKY WAY AND SOLAR SYSTEM SCIENCE Abrams, Natasha

TABLE OF IMPLEMENTATION REQUIREMENTS
Using microlensing distributions to perform Galactic population analysis.

Busa, Innocenza
Uncovering new sources of Galactic cosmic rays from coordinated optical and near-infrared monitoring of diffuse clouds in the Galactic Bulge.

Chakrabarti, Sukanya
Direct accelerations measurements of eclipsing binaries to probe dark matter in the Milky Way.

Couperus, Andrew
Rubin observations of the cycles of host stars of Roman detected exoplanets.

De, Kishalay
Accreting compact objects in the dynamic Galactic plane. The morphologies and environments of galaxies hosting changing-look AGN. What is the physical mechanism behind rapid and large changes in the accretion rates of active galactic nuclei?

Berger, Edo
Optical-infrared follow-up of gravitational wave events.
What are the electromagnetic properties of gravitational wave events, their relation to binary properties, and implications for r-process nucleosynthesis?

Chase, Eve
Roman and Rubin detection of kilonovae from follow-up of short-duration gamma-ray bursts or a gravitational-wave detections.

Coughlin, Michael
Identifying and Characterizing the Sources of r-process material in Rubin's alert stream. What fraction of heavy elements do neutron star mergers produce? Fox, Ori Probing the first stars, the evolution of the early Initial Mass Function (IMF), and the sources of reionization with transient astronomy in the early, high-redshift (z > 6) universe. French, Decker a) Measuring the Black Hole -Bulge relation across cosmic time. How do galaxies and supermassive black holes co-evolve? b) Connecting transients to their host galaxies. How can we best identify large numbers of transient events?

Gezari, Suvi
Pinpointing the environments and hosts of Rubin-discovered transients with Roman imaging. What are the progenitors and/or central engines of cosmic explosions? Holwerda, Benne Using lensed supernova observations as an independent measure of H 0 .

Holz, Daniel
EM follow-up of GW sources.

Homayouni, Yasaman
Census of black hole mass and accretion disks with Roman-Rubin.

Kilpatrick, Charlie
Early Roman survey of nearby galaxy groups and clusters in the Rubin LSST footprint, especially Fornax and Virgo. Systematically addressing massive star evolution and death.

Lacy, Mark
Quasar/AGN host galaxy studies in the era of the Nancy Grace Roman Space Telescope and Vera C. Rubin Observatory.

Liu, Xin
Sub-arcsec quasar pairs and lenses from combining Rubin and Roman.

Lyu, Jianwei
Infrared reverberation mapping of active galactic nuclei.

Matsuura, Mikako
How common is dust formation in supernovae?

Mattila, Seppo
Systematic study of dust emission in Rubin-discovered transients with Roman imaging.

Perley, Dan
Unusual and obscured transients at high redshift. What populations of transients remain unseen? Shen, Yue a. The discovery of a large statistical sample of ∼kpc-scale dual quasars from Roman+Rubin to improve our understanding of the pairing and evolution of binary SMBHs in galaxy mergers. b. Measuring the time lags from the dusty torus in AGN.

Villar, V. Ashley
Roman+Rubin observations of a Rubin Deep Drilling Field to finally unveil the late-time evolution of stripped-envelope core-collapse supernovae.

Vinko, Jozsef
Separating low-and high-redshift supernovae in a cosmological survey with Roman. How does the cosmic star formation rate behave at very high (z > 6) redshifts?

Windhorst, Rogier
Observing the first stars directly with Rubin and Roman through cluster caustic transits.

Zhang, Jielai
Kilonovae: A new window into fundamental physics, element creation, transient astronomy, and cosmology. What is the equation of state of dense dense matter, and are kilonovae responsible for producing more than half the elements heavier than iron? GALAXIES, LARGE SCALE STRUCTURE, AND DARK MATTER Bechtol, Keitha Roman and Rubin coordination to enhance astrophysical probes of dark matter.

Bell, Eric
Reshaping our understanding of small-scale cosmology and the hierarchical growth of galaxies in the Local Universe.

Belokurov, Vasily
Detecting and characterising Galactic halo sub-structure with Rubin and Roman Birrer, Simon Strong lensing tomography with joint Rubin+Roman deblending of strongly lensed arcs. What is the geometry of the Universe? Blain, Andrew The role of large-scale structure in controlling the morphology of the zoo of galaxies.

Dell'Antonio, Ian
Studying the structure and populations of galaxy clusters with Roman and Rubin.

Ettori, Stefano
Proto-clusters and first collapsed structure at z¿2. Identifying and characterizing the galaxy composition of the first structures that form on Mpc scales (with masses ¿1 ×10 13 M ) using Rubin imaging and Roman dedicated spectroscopic follow-up.

Laine, Seppo
Power of multiwavelength SEDs in deciphering stellar stream progenitors. What are the stellar population metallicities, masses, and star formation histories of stellar stream progenitors?

Masters, Daniel
A complete picture of galaxy evolution driven by the unparalleled statistical power of Roman and Rubin photometric data.

Montes, Mireia
Exploring the low-surface brightness universe statistically with Roman and Rubin.

Nadler, Ethan
How does dark matter cluster on the smallest observationally accessible scales, and what does this teach us about dark matter particle properties? Ntampaka, Michelle Enabling modern data analysis methods. Roman and Rubin will produce exquisitely detailed observations -how can our data analysis tools rise to the challenge and use these data to their fullest potential?

Patel, Ekta
Probing the faint end of the galaxy luminosity function beyond the Local Group. How do complete censuses of ultrafaint dwarf galaxies (to M V > −7) beyond the Local Group improve our understanding of small-scale structure? Pello, Roser Towards a complete census of ionizing sources during the first billion years. What is the relative contribution of the different galaxy populations to cosmic reionization?

Pierce, Michael
Measuring cosmological parallax with gravitationally lensed quasars and galaxies.

Rawls, Meredith
Quantifying the impact of low-Earth-orbit satellite proliferation on ground-based astronomy. How do increasing numbers of bright commercial satellites impact Rubin's science programs?

Scognamiglio, Diana
Relics with Rubin & Roman (R 3 ): constraining the assembly and cosmic evolution of the most massive galaxies in the Universe. How do the most massive galaxies form? How do they evolve in cosmic time?

Shivaei, Irene
The effect of environment on galaxy evolution processes at Cosmic Noon (z ∼ 1 − 3). How does galaxies morphologies, their distribution of star formation, stellar mass, and dust varies across environment? What is the connection between the AGN and their host galaxies' morphologies, stellar populations, and environment? Simon, Josh Stellar archaeology in ultra-faint dwarf galaxies. Tee, Wei Leong, The first quasars in the Universe: Roman+Rubin synergy.

Tran, Kim-Vy
Identifying strong lensing candidates with machine-learning on Rubin and modeling the lenses and sources with Roman high resolution imaging and grism spectroscopy.

Wallman, Bruce
Calibration of Rubin photometric redshifts with Roman spectroscopy Williams, Benjamin Fundamental improvement of our observational constraints on the structure and stellar content of the halos of nearby galaxies. Williams, Peter K. G.
Visualizing big and wide data in the 21st Century. What are the visualization tools that will empower astronomers to get the most science out of 21st-century datasets? Yoon, Ilsang Evolution of the rest-frame optical galaxy structure and environmental effect up to z=2.5.