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280 records · Page 16

SDSS-IV MaNGA: Modeling the Spectral Line-spread Function to Subpercent Accuracy

The Sloan Digital Sky Survey IV Mapping Nearby Galaxies at APO (MaNGA) program has been operating from 2014 to 2020, and has now observed a sample of 9269 galaxies in the low redshift universe (z ∼ 0.05) with integral-field spectroscopy. With rest-optical (λλ0.36–1.0 μm) spectral resolution R ∼ 2000 the instrumental spectral line-spread function (LSF) typically has 1σ width of about 70 km s{sup −1}, which poses a challenge for the study of the typically 20–30 km s{sup −1} velocity dispersion of the ionized gas in present-day disk galaxies. In this contribution, we present a major revision of the MaNGA data pipeline architecture, focusing particularly on a variety of factors impacting the effective LSF (e.g., under-sampling, spectral rectification, and data cube construction). Through comparison with external assessments of the MaNGA data provided by substantially higher-resolution R ∼ 10,000 instruments, we demonstrate that the revised MPL-10 pipeline measures the instrumental LSF sufficiently accurately (≤0.6% systematic, 2% random around the wavelength of Hα) that it enables reliable measurements of astrophysical velocity dispersions σ {sub Hα} ∼ 20 km s{sup −1} for spaxels with emission lines detected at signal-to-noise ratio > 50. Velocity dispersions derived from [O II], Hβ, [O III], [N II], and [S II] are consistent with those derived from Hα to within about 2% at σ {sub Hα} > 30 km s{sup −1}. Although the impact of these changes to the estimated LSF will be minimal at velocity dispersions greater than about 100 km s{sup −1}, scientific results from previous data releases that are based on dispersions far below the instrumental resolution should be reevaluated.

47 OTHER INSTRUMENTATION↗

First Discoveries of z > 6 Quasars with the DECam Legacy Survey and UKIRT Hemisphere Survey

In this paper, we present the first discoveries from a survey of z ≳ 6 quasars using imaging data from the DECam Legacy Survey (DECaLS) in the optical, the UKIRT Deep Infrared Sky Survey (UKIDSS) and a preliminary version of the UKIRT Hemisphere Survey (UHS) in the near-IR, and ALLWISE in the mid-IR. DECaLS will image 9000 deg 2 of sky down to z AB ~ 23.0, and UKIDSS and UHS will map the northern sky at 0 < decl. < +60°, reaching J VEGA ~ 19.6 (5-σ). The combination of these data sets allows us to discover quasars at redshift z ≳ 7 and to conduct a complete census of the faint quasar population at z ≳ 6. In this paper, we report on the selection method of our search, and on the initial discoveries of two new, faint z ≳ 6 quasars and one new z = 6.63 quasar in our pilot spectroscopic observations. The two new z ~ 6 quasars are at z = 6.07 and z = 6.17 with absolute magnitudes at rest-frame wavelength 1450 Å being M 1450 = -25.83 and M 1450 = -25.76, respectively. These discoveries suggest that we can find quasars close to or fainter than the break magnitude of the Quasar Luminosity Function (QLF) at z ≳ 6. The new z = 6.63 quasar has an absolute magnitude of M 1450 = -25.95. This demonstrates the potential of using the combined DECaLS and UKIDSS/UHS data sets to find z ≳ 7 quasars. Finally, extrapolating from previous QLF measurements, we predict that these combined data sets will yield ~200 z ~ 6 quasars to z AB < 21.5, ~1000 z ~ 6 quasars to z AB < 23, and ~30 quasars at z > 6.5 to J VEGA < 19.5.

79 ASTRONOMY AND ASTROPHYSICS↗

NEUTRAL HYDROGEN OPTICAL DEPTH NEAR STAR-FORMING GALAXIES AT z Almost-Equal-To 2.4 IN THE KECK BARYONIC STRUCTURE SURVEY

We study the interface between galaxies and the intergalactic medium by measuring the absorption by neutral hydrogen in the vicinity of star-forming galaxies at z Almost-Equal-To 2.4. Our sample consists of 679 rest-frame UV-selected galaxies with spectroscopic redshifts that have impact parameters <2 (proper) Mpc to the line of sight of one of the 15 bright, background QSOs and that fall within the redshift range of its Ly{alpha} forest. We present the first two-dimensional maps of the absorption around galaxies, plotting the median Ly{alpha} pixel optical depth as a function of transverse and line-of-sight separation from galaxies. The Ly{alpha} optical depths are measured using an automatic algorithm that takes advantage of all available Lyman series lines. The median optical depth, and hence the median density of atomic hydrogen, drops by more than an order of magnitude around 100 kpc, which is similar to the virial radius of the halos thought to host the galaxies. The median remains enhanced, at the >3{sigma} level, out to at least 2.8 Mpc (i.e., >9 comoving Mpc), but the scatter at a given distance is large compared with the median excess optical depth, suggesting that the gas is clumpy. Within 100 (200) kpc, and over {+-}165 km s{sup -1}, the covering fraction of gas with Ly{alpha} optical depth greater than unity is 100{sup +0}{sub -32}% (66% {+-} 16%). Absorbers with {tau}{sub Ly{alpha}} > 0.1 are typically closer to galaxies than random. The mean galaxy overdensity around absorbers increases with the optical depth and also as the length scale over which the galaxy overdensity is evaluated is decreased. Absorbers with {tau}{sub Ly{alpha}} {approx} 1 reside in regions where the galaxy number density is close to the cosmic mean on scales {>=}0.25 Mpc. We clearly detect two types of redshift space anisotropies. On scales <200 km s{sup -1}, or <1 Mpc, the absorption is stronger along the line of sight than in the transverse direction. This 'finger of God' effect may be due to redshift errors, but is probably dominated by gas motions within or very close to the halos. On the other hand, on scales of 1.4-2.0 Mpc the absorption is compressed along the line of sight (with >3{sigma} significance), an effect that we attribute to large-scale infall (i.e., the Kaiser effect).

79 ASTRONOMY AND ASTROPHYSICS↗

UV luminosity functions at Redshifts z ∼ 4 TO z ∼ 10: 10,000 galaxies from HST legacy fields

The remarkable Hubble Space Telescope (HST) data sets from the CANDELS, HUDF09, HUDF12, ERS, and BoRG/HIPPIES programs have allowed us to map the evolution of the rest-frame UV luminosity function (LF) from z∼10 to z∼4. We develop new color criteria that more optimally utilize the full wavelength coverage from the optical, near-IR, and mid-IR observations over our search fields, while simultaneously minimizing the incompleteness and eliminating redshift gaps. We have identified 5859, 3001, 857, 481, 217, and 6 galaxy candidates at z∼4, z∼5, z∼6, z∼7, z∼8, and z∼10, respectively, from the ∼1000 arcmin{sup 2} area covered by these data sets. This sample of >10,000 galaxy candidates at z⩾4 is by far the largest assembled to date with HST. The selection of z ∼ 4–8 candidates over the five CANDELS fields allows us to assess the cosmic variance; the largest variations are at z⩾7. Our new LF determinations at z∼4 and z∼5 span a 6 mag baseline and reach to –16 AB mag. These determinations agree well with previous estimates, but the larger samples and volumes probed here result in a more reliable sampling of >L{sup ∗} galaxies and allow us to reassess the form of the UV LFs. Our new LF results strengthen our earlier findings to 3.4σ significance for a steeper faint-end slope of the UV LF at z>4, with α evolving from α=−1.64±0.04 at z∼4 to α=−2.06±0.13 at z∼7 (and α=−2.02±0.23 at z∼8), consistent with that expected from the evolution of the halo mass function. We find less evolution in the characteristic magnitude M{sup *} from z∼7 to z∼4; the observed evolution in the LF is now largely represented by changes in ϕ{sup ∗}. No evidence for a non-Schechter-like form to the z ∼ 4–8 LFs is found. A simple conditional LF model based on halo growth and evolution in the M/L ratio (∝(1+z){sup −1.5}) of halos provides a good representation of the observed evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

Reionization after Planck: The derived growth of the cosmic ionizing emissivity now matches the growth of the galaxy UV luminosity density

Thomson optical depth τ measurements from Planck provide new insights into the reionization of the universe. In pursuit of model-independent constraints on the properties of the ionizing sources, we determine the empirical evolution of the cosmic ionizing emissivity. We use a simple two-parameter model to map out the evolution in the emissivity at z ≳ 6 from the new Planck optical depth τ measurements, from the constraints provided by quasar absorption spectra and from the prevalence of Lyα emission in z ∼ 7–8 galaxies. We find the redshift evolution in the emissivity N-dot {sub ion}(z) required by the observations to be (dlog{sub 10} N-dot {sub ion}/dz){sub z=8}=−0.15{sub −0.11}{sup +0.08} ((dlog{sub 10} N-dot {sub ion}/dz){sub z=8}=−0.19{sub −0.11}{sup +0.09} for a flat prior), largely independent of the assumed clumping factor C{sub H ii} and entirely independent of the nature of the ionizing sources. The trend in N-dot {sub ion}(z) is well-matched by the evolution of the galaxy UV-luminosity density (dlog{sub 10}ρ{sub UV}/dz=−0.11±0.04) to a magnitude limit ≳−13 mag, suggesting that galaxies are the sources that drive the reionization of the universe. The role of galaxies is further strengthened by the conversion from the UV luminosity density ρ{sub UV} to N-dot {sub ion}(z) being possible for physically plausible values of the escape fraction f{sub esc}, the Lyman-continuum photon production efficiency ξ{sub ion}, and faint-end cut-off M{sub lim} to the luminosity function. Quasars/active galactic nuclei appear to match neither the redshift evolution nor normalization of the ionizing emissivity. Based on the inferred evolution in the ionizing emissivity, we estimate that the z ∼ 10 UV-Iuminosity density is 8{sub −4}{sup +15}× lower than at z ∼ 6, consistent with the observations. The present approach of contrasting the inferred evolution of the ionizing emissivity with that of the galaxy UV luminosity density adds to the growing observational evidence that faint, star-forming galaxies drive the reionization of the universe.

79 ASTRONOMY AND ASTROPHYSICS↗

COPSS II: the molecular gas content of ten million cubic megaparsecs at redshift z ∼ 3

We present a measurement of the abundance of carbon monoxide in the early universe, utilizing the final results from the CO Power Spectrum Survey (COPSS). Between 2013 and 2015, we performed observations with the Sunyaev–Zel’dovich Array to measure aggregate CO emission from z∼3 galaxies with the intensity mapping technique. Data were collected on 19 fields, covering an area of 0.7 square degrees, over the frequency range 27--35 GHz. With these data, along with data analyzed in COPSS I, we are able to observe the CO(1–0) transition within the redshift range z=2.3--3.3 for spatial frequencies between k=0.5--10 h Mpc{sup −1}, spanning a comoving volume of 4.9×10{sup 6} h{sup −3} Mpc{sup 3}. We present estimates of contributions from continuum sources and ground illumination within our measurement. We constrain the amplitude of the CO power spectrum to P{sub CO}=3.0{sub −1.3}{sup +1.3}×10{sup 3} μK{sup 2}(h{sup −1}Mpc){sup 3}, or Δ{sub CO}{sup 2}(k=1 h Mpc{sup −1})=1.5{sub −0.7}{sup +0.7}×10{sup 3} μK{sup 2}, at 68% confidence, and P{sub CO}>0 at 98.9% confidence. These results are a factor of 10 improvement in sensitivity compared to those of COPSS I. With this measurement, we constrain on the CO(1–0) galaxy luminosity function at z∼3. Assuming that CO emission is proportional to halo mass and using theoretical estimates of the scatter in this relationship, we constrain the ratio of CO(1--0) luminosity to halo mass to A{sub CO}=6.3{sub −2.1}{sup +1.4}×10{sup −7} L{sub ⊙} M{sub ⊙}{sup −1}. Assuming a Milky Way-like linear relationship between CO luminosity and molecular gas mass, we estimate a mass fraction of molecular gas of f{sub H{sub 2}}=5.5{sub −2.2}{sup +3.4}×10{sup −2} for halos with masses of ∼10{sup 12}M{sub ⊙}. Using theoretical estimates for the scaling of molecular gas mass fraction and halo mass, we estimate the cosmic molecular gas density to be ρ{sub z∼3}(H{sub 2})=1.1{sub −0.4}{sup +0.7}×10{sup 8} M{sub ⊙} Mpc{sup −3}.

79 ASTRONOMY AND ASTROPHYSICS↗

Multi-wavelength seds of Herschel-selected galaxies in the cosmos field

We combine Herschel Photodetector Array Camera and Spectrometer and Spectral and Photometric Imaging Receiver maps of the full 2 deg{sup 2} Cosmic Evolution Survey (COSMOS) field with existing multi-wavelength data to obtain template and model-independent optical-to-far-infrared spectral energy distributions (SEDs) for 4218 Herschel-selected sources with log(L {sub IR}/L {sub ☉}) = 9.4-13.6 and z = 0.02-3.54. Median SEDs are created by binning the optical to far-infrared (FIR) bands available in COSMOS as a function of infrared luminosity. Herschel probes rest-frame wavelengths where the bulk of the infrared radiation is emitted, allowing us to more accurately determine fundamental dust properties of our sample of infrared luminous galaxies. We find that the SED peak wavelength (λ{sub peak}) decreases and the dust mass (M {sub dust}) increases with increasing total infrared luminosity (L {sub IR}). In the lowest infrared luminosity galaxies (log(L {sub IR}/L {sub ☉}) = 10.0-11.5), we see evidence of polycyclic aromatic hydrocarbon (PAH) features (λ ∼ 7-9 μm), while in the highest infrared luminosity galaxies (L {sub IR} > 10{sup 12} L {sub ☉}) we see an increasing contribution of hot dust and/or power-law emission, consistent with the presence of heating from an active galactic nucleus (AGN). We study the relationship between stellar mass and star formation rate of our sample of infrared luminous galaxies and find no evidence that Herschel-selected galaxies follow the SFR/M {sub *} 'main sequence' as previously determined from studies of optically selected, star-forming galaxies. Finally, we compare the mid-infrared to FIR properties of our infrared luminous galaxies using the previously defined diagnostic, IR8 ≡ L {sub IR}/L {sub 8}, and find that galaxies with L {sub IR} ≳ 10{sup 11.3} L {sub ☉} tend to systematically lie above (× 3-5) the IR8 'infrared main sequence', suggesting either suppressed PAH emission or an increasing contribution from AGN heating.

79 ASTRONOMY AND ASTROPHYSICS↗

Mapping the Lyα Emission around a z ∼ 6.6 QSO with MUSE: Extended Emission and a Companion at a Close Separation

We utilize the Multi Unit Spectroscopic Explorer (MUSE) on the Very Large Telescope to search for extended Lyα emission around the z ∼ 6.6 QSO J0305−3150. After carefully subtracting the point spread function, we reach a nominal 5σ surface-brightness limit of SB{sub 5σ} = 1.9 × 10{sup −18} erg s{sup −1} cm{sup −2} arcsec{sup −2} over a 1 arcsec{sup 2} aperture, collapsing five wavelength slices centered at the expected location of the redshifted Lyα emission (i.e., at 9256 Å). Current data suggest the presence (5σ accounting for systematics) of a Lyα nebula that extends for 9 kpc around the QSO. This emission is displaced and redshifted by 155 km s{sup −1} with respect to the location of the QSO host galaxy traced by the [C II] 158 μm emission line. The total luminosity is L(Lyα) = (3.0 ± 0.4) × 10{sup 42} erg s{sup −1}. Our analysis suggests that this emission is unlikely to rise from optically thick clouds illuminated by the ionizing radiation of the QSO. It is more plausible that the Lyα emission is due to the fluorescence of the highly ionized optically thin gas. This scenario implies a high hydrogen volume density of n{sub H}∼6 cm{sup −3}. In addition, we detect a Lyα emitter (LAE) in the immediate vicinity of the QSO, i.e., with a projected separation of ∼12.5 kpc and a line-of-sight velocity difference of 560 km s{sup −1}. The luminosity of the LAE is L(Lyα) = (2.1 ± 0.2) × 10{sup 42} erg s{sup −1} and its inferred star-formation rate is SFR ∼ 1.3 M {sub ⊙} yr{sup −1}. The probability of finding such a close LAE is one order of magnitude above the expectations based on the QSO–galaxy cross-correlation function. This discovery is in agreement with a scenario where dissipative interactions favor the rapid build-up of supermassive black holes at early cosmic times.

79 ASTRONOMY AND ASTROPHYSICS↗

Field evaluation of remote wind sensing technologies: Shore-based and buoy mounted LIDAR systems

In developing a national energy strategy, the United States has a number of objectives, including increasing economic growth, improving environmental quality, and enhancing national energy security. Wind power contributes to these objectives through the deployment of clean, affordable and reliable domestic energy. To achieve U.S. wind generation objectives, the Wind and Water Power Program within the Department of Energy’s (DOE) Office of Energy Efficiency and Renewable Energy (EERE) instituted the U.S. Offshore Wind: Removing Market Barriers Program in FY 2011. Accurate and comprehensive information on offshore wind resource characteristics across a range of spatial and temporal scales is one market barrier that needs to be addressed through advanced research in remote sensing technologies. There is a pressing need for reliable offshore wind-speed measurements to assess the availability of the potential wind energy resource in terms of power production and to identify any frequently occurring spatial variability in the offshore wind resource that may impact the operational reliability and lifetime of wind turbines and their components and to provide a verification program to validate the “bankability” of the output of these alternative technologies for use by finance institutions for the financing of offshore wind farm construction. The application of emerging remote sensing technologies is viewed as a means to cost-effectively meet the data needs of the offshore wind industry. In particular, scanning and buoy mounted LIDAR have been proposed as a means to obtain accurate offshore wind data at multiple locations without the high cost and regulatory hurdles associated with the construction of offshore meteorological towers. However; before these remote sensing technologies can be accepted the validity of the measured data must be evaluated to ensure their accuracy. The proposed research will establish a unique coastal ocean test-bed in the Mid-Atlantic for the evaluation of LIDAR-based wind measurement systems to validate the accuracy of remotely measured wind data in marine applications. Specifically, the test-bed will be utilized to systematically evaluate the capability of emerging scanning LIDAR and buoy mounted vertically profiling LIDAR by: (1) Evaluating a fixed scanning LIDAR against land-based 50 and 60 meter high meteorological masts fitted with research quality cup-vane and/or sonic anemometers; (2) Evaluating a buoy mounted vertically profiling LIDAR fixed on land and floating in a sheltered bay against a co-located 60 meter high meteorological mast fitted with a research quality cup-vane and/or sonic anemometers and the fixed scanning LIDAR; and (3) Offshore field evaluation of both LIDAR platforms through a comparison of the fixed scanning LIDAR data and data obtained by the buoy mounted LIDAR located 10 miles offshore. The proposed research will systematically validate Light Detection and Ranging (LIDAR) based wind measurement systems and assess the temporal and spatial variability of the offshore wind resource in the Mid-Atlantic east of New Jersey. The goal of the proposed project is to address the technical and commercial challenges of the offshore wind energy industry by validating and assessing cost-effective, over ocean wind resource characterization technologies. The objective is to systematically evaluate the capability of both scanning and vertically profiling LIDARs to accurately measure 3D wind fields through comparison with fixed met masts and intercomparison among LIDAR platforms. Once validated, data collected by both buoy mounted vertically profiling LIDARs and shore-based, pulsed horizontally scanning LIDARs can be used to accurately assess offshore wind resources and to quantify the spatial and temporal variability in the offshore wind fields. One of the fundamental research questions to be addressed in phase 1 is the assessment of various measurement and data processing schemes to retrieve accurate wind vectors in the marine environment over large sampling ranges (10 to 12 km) and varying atmospheric aerosol levels. Atmospheric conditions and aerosol content within the coastal ocean region of the Mid-Atlantic seaboard of the US can vary significantly over short time periods in response to frontal passages and extratropical and tropical low pressure system passage offshore of the coast. Since aerosols provide the scattering medium for the determination of LIDAR Doppler shifts in the atmosphere the accuracy and range of LIDAR derived velocity measurements as a function of variation in aerosol content in the marine environment is a key research question to be addressed. In phase 1, it is desired to capture as much variation in atmospheric conditions and aerosol content as possible. To this end, collocated measurements of LIDAR and standard anemometer wind fields will be captured by the project PIs over all four seasons and during specific events (e.g., coastal low pressure system passage) in year 1. Additionally, since the meteorological masts are permanent structures, additional events can be captured over the three year duration of the field research project. All research instruments are owned by Fishermen’s Energy and made available to the PIs though a lease agreement as part of the DOE grant. Energy Fishermen’s Energy will be responsible for the operation and maintenance of the scanning LIDAR and met mast anemometers. On a daily basis, environmental data and systems performance indicators will be transmitted from each measurement station to the Fishermen’s project team consisting of both in-house personnel and equipment manufacturer engineers. Data sets include compiled LIDAR files as well as data sets from ancillary sensors. Diagnostic parameters to be monitored include standard deviations of measured values, battery levels and charging systems output, and the operational status. Once data have been confirmed as complete and reliable, files will be transferred to the Garrad Hassan (a subcontractor to Fishermen’s Energy) for incorporation in to the validation database, which is accessible to other scientific team members. Data collection times and durations will be determined by the PI and Co-PIs in consultation with instrument engineers to ensure the capture of data representative of the expected range of mid-Atlantic atmospheric conditions (e.g., temperature, moisture, coastal low pressure systems, tropical systems, rain, snow, fog). The collection and processing of the data is a function of site specific measurement requirements (Kelley et.al. 2007; Hannon et.al. 2008). To determine the optimal profiles of wind speed and direction from the LIDAR radial velocities as a function of azimuth angle, rigorous estimates of the bias and random error of each radial velocity estimate are required. Lockheed Martin Coherent Technologies, Inc., under contract with Fishermen’s Energy, will provide analyses of raw and processed data using various scan patterns to determine optimal performance settings for the pulsed scanning LIDAR. Once optimized, appropriate processing and analyses techniques will be evaluated by Garrad Hassan for use in validating the accuracy of the LIDAR wind field measurements against the standard anemometer measurements from the meteorological masts. The most attractive capability of the scanning LIDAR is the ability to provide high spatial resolution observations in a three-dimensional volume which provides superior statistical accuracy due to the large number of samples obtained. Each radial scan provides measurements in 100 range gates over a distance of 10 to 12 km at an update rate of 5 to 10 Hz and rotation of 2.5° per second. Each rotation at a fixed azimuth requires 2.4 minutes. Depending on the number of azimuths desired a complete scan can take up to 10 minutes or longer to complete. Once collected the radial velocities are processed to produce vector wind velocity estimates based on a set of data distributed in angle and range around points of interest, typically a standard grid within the radial wind map. To calculate wind vectors over a limited spatial area of interest for the comparison of data with other measurement platforms a localized least-squares approach has been applied by Hannon et.al. (2008) and a Variation Assimilation (VAR) processing technique has been applied by Chan and al Assimilation (VAR) processing technique has been applied by Chan and Shao (2006). Additionally, Kelley et.al. (2007) applied a “stare” technique that fixed a scanning LIDAR in both azimuth and elevation angles to measure over collocated sampling volumes of the LIDAR and a 3D sonic anemometer mounted to a fixed mast. Although the stare technique is limited to wind directions aligned with the sampling radial of the LIDAR, it does provide a direct comparison of sampling volumes. Each of the processing techniques described above (and possibly others) will be evaluated to determine the validity of the LIDAR derived wind fields in the marine environment. Numerical methods such as linear regression and comparison of probability density functions of wind fields measured by each instrument platform will be used to assess the processing techniques. Linear regression has the advantage of directly evaluating corresponding pairs of wind data measured by each instrument and can lend insight into deviations and bias between instruments as a function of wind speed. Assessment of the coherency between the probability density function of the wind measured by each instrument provides insight into processes that may not be accurately resolved by each instrument at specific frequencies. Once processed and assessed the most appropriate technique will be utilized to provide valid wind measurements from the pulsed scanning LIDAR. A detailed analysis of the measurement data from the LIDAR and the three meteorological towers and comparison of the coastal wind characteristics from the different systems will be performed by the CO_PI at NREL. This analysis will evaluate how the WT LIDAR performance and measurement of the wind characteristics vary with distance from the LIDAR and by atmospheric conditions; using the tower measurements at different distances (4.8, 9.6, and 19 km) from the LIDAR as a reference. The comparative analysis will include, to the extent possible, evaluation of parameters such as wind speed and direction distributions, wind shear, turbulence intensity and their variations by atmospheric conditions, month or season, and time of day.

17 WIND ENERGY↗

Uncrewed Lunar Surface Operations and Support Activities

Sustained human presence on the surface of the Moon and future missions to Mars require increased independence from surface crews and Earth-based mission control to operate efficiently, safely, and reliably. The time for surface crews to perform tasks will be limited. Extravehicular activities by surface personnel are burdensome and time-consuming, even when a continuous human presence on the surface occurs. Identifying and balancing human/automation roles and tasks and infusing automation and autonomy practices early in a system’s lifecycle will be essential to achieve mission objectives. Among these objectives are attaining a sustained human presence, improving performance and mission effectiveness, reducing operations and maintenance (O&M) costs, and ensuring operations that are robust to communication delays. To achieve these objectives, an operational shift toward increased automation and autonomy with less reliance on humans is needed. Uncrewed lunar surface operations and support activities occur when surface crews are not present or are independent of surface crew timeline activities requiring no surface crew oversight or intervention. These uncrewed surface opportunities can also be planned to minimize crew workload that avoids routine maintenance and support tasks, thus maximizing crew exploration time. Uncrewed preparations such as staging and prepositioning equipment and materials before the crew arrives could improve crew task efficiency. Additional opportunities exist to conduct uncrewed science, exploration, and utilization. Uncrewed surface architecture functions can include science and exploration; habitation; launch and landing support; surface communication and navigation; surface power generation and distribution; human surface mobility; lifting, handling, manipulating; excavation, construction, and site preparation; logistics management; maintenance and repair; surface resource utilization; integrated site operations and shared support services (e.g., site scheduling/prioritization, dust mitigation/contamination control, and surface safety). Early robotic lunar surface campaigns will provide information on the availability of resources, such as oxygen and water, and demonstrate surface-based technologies. After the Artemis III human lunar return mission, a series of landers will deliver surface systems, cargo, supplies, science packages, spare parts, and commodities. A balance of crewed and uncrewed surface operations will enable a sustained lunar surface presence at the South Pole of the Moon at a site that will be known as the Artemis Base Camp (ABC). It is envisioned that base camp operations on and around the Moon will then help prepare for the mission durations and activities needed to support the first human mission to Mars. Before long-duration crew missions to the base camp can occur, the necessary surface infrastructure will be pre-deployed and verified operational. Surface assets will be teleoperated and remotely managed from Earth. Additionally, robotic and short-duration crewed missions to the ABC will ensure the site’s merit to achieve long-term science objectives, availability of usable resources, and that terrain, seasonal variations, and illumination conditions are acceptable. ABC will consist of different areas where specific functions and services are rendered, including: • Launch and Landing Area • Habitation Area • Power Production Area • Resource Areas Launch and Landing Area—The launch and landing area will support associated functions for the arrival and departure of vehicles, such as crewed landing and ascent and uncrewed cargo deliveries and offloading. It will evolve from an unimproved site at the beginning of the exploration campaign to a more sustainable landing and launch area that can support repeated arrivals and departures. Initial uncrewed Lunar Terrain Vehicle (LTV) surface operations may include emplacement of navigation beacons and communication equipment, real-time video and photography of landing/liftoff events, and element repositioning, such as portable utility power (PUP) (applicable for other landed assets at other areas). Site preparations, such as surface leveling, soil compaction, and berm/path construction, may be needed for a more sustainable launch and landing area capable of accommodating vehicles that are increasingly more reusable and reduce the effects of plume surface interactions and ejecta impacts on nearby surface assets. During the ABC missions, cargo and logistics will be delivered to the lunar surface via robotic cargo landers before the crew arrives. These shipments, which can arrive in pressurized logistics carriers, will deliver the logistics necessary to support a crewed mission and include items such as food, water, equipment spares, etc. Providing the capability to retrieve, offload, and transport the logistics closer to the ABC site before the arrival of the crew will increase the overall efficiency of crew operations once they arrive. In the sustained phase of exploration, other supporting services may be needed, such as lander propellant servicing, surface power services, commodity refreshes, and additional inspection, maintenance, and repair capabilities, to sustain a cadence of extended personnel stays and cargo arrivals and departures. Habitation Area—Uncrewed support to surface habitation could involve supporting activation and pre-entry operations of the habitat while the crew is in orbit at the Gateway outpost preparing for a surface landing. Surface Habitat (SH) uncrewed operations may include bringing the cabin environment to a habitable temperature and air mix and activating other critical crew support systems. Potential crop production uncrewed tasks in the SH could also include autonomous watering and tending. Additionally, when the crew departs, the SH enters dormancy for the long period of uncrewed operation. A logistical staging area could also be collocated near the SH. If so, staging operations for crew supplies, waste re-location, and recycling operations may be opportunities for uncrewed operations. Power Production Area—The Fission Surface Power (FSP) element and its supporting distribution equipment provide power to surface elements as needed across the ABC to supplement day-to-day operations and survive lunar nights. Uncrewed support of this power system includes any initial LTV-assisted deployments of cables and other distributed equipment, associated electrical connections, and system testing and activation operations. Robotically performing some inspections, maintenance, or repair tasks on the power distribution equipment could reduce the surface crew workload. Resource Area— Uncrewed resource prospecting, mapping, and characterizing possible resource sites is likely to be time-consuming and represents an opportunity for uncrewed operations between crewed missions. Uncrewed mobile equipment operations will be needed in the extreme environments of permanently shadowed locations where resource extractions occur. As In-Situ Resource Utilization (ISRU) pilot plant operations begin, uncrewed surface support activities with available mobile and portable assets (LTV, PUP, etc.) will better support these operations. Any produced commodities can be stored at a centralized storage location for future use. Also associated with these operations is the use of mobile robotic excavators for resource acquisition and robotic/autonomous regolith processing. The waste tailings generated during excavation and regolith processing would also need to be transported and deposited at a dedicated location. Surface assets will continue operating between crew visits to maintain surface capabilities, conduct lunar surface science, technology demonstrations, and public outreach opportunities. Additionally, certain sustaining tasks that would consume valuable crew time could be performed before crew arrival, or after their departure. This capability may offer more affordable options to construct, activate, test, and maintain a broad set of surface assets. Telerobotically operated human surface mobility systems, such as the LTV and Pressurized Rover (PR), can be utilized for various tasks. Surface environmental conditions pose a distinct challenge for all these activities. Surface illumination and localized shadows are one such factor. Night-survival operations could consist of thermal management, battery pre-charging, and load shedding. Some surface systems may hibernate through the night and then awake and continue nominal operations. Uncrewed mobile assets may use a more adaptive approach to optimize their power and operations; one method is to follow the sunlight. Night-survival operations may be initiated remotely by teleoperation, automated, or accomplished by supervised autonomous operation. The ability to pre-deploy and control remote assets in orbit or on Mars before the arrival of the mission crew is a key capability that can be simulated on the moon. The base camp provides a venue where these advanced operational concepts, technologies, and autonomous methods and techniques, including the incorporation of time delays to simulate Earth-Mars latency can be replicated to help buy down future Mars mission risks. This paper will examine the evolution of uncrewed lunar surface operations and support activities. It will also discuss the lunar surface environmental conditions (thermal, lighting, terrain, topography, communications) along with the challenges they pose on uncrewed surface operations, and the performance of these activities with limited to minimal human interaction and/or teleoperation. Since lunar missions include Mars mission analogs, such investigation provides the framework for future uncrewed Mars mission support.

Mark E Lewis↗