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Integration of fixed-frequency and FM-CW (frequency-modulated continuous-wave) reflectometers for coincident turbulence measurements on LTX- β (Lithium Tokamak eXperiment- β )

The fixed-frequency and frequency-modulated continuous-wave (FM-CW) reflectometers on LTX-β (Lithium Tokamak eXperiment-β) have been configured to use the same transmission lines and antenna arrays for coincident views of the core and edge plasma. The fixed-frequency channels (13.1–20.5 and 20–40 GHz, tunable between discharges) provide time-resolved measurements of density fluctuations, while the FM-CW channels (13.1–20.2 and 19.5–33.5 GHz) measure the density profile and fluctuations, with high spatial resolution and a sampling rate determined by the frequency sweep interval (5 μs). Data from both reflectometers are synchronously acquired to simultaneously leverage the wide bandwidth and high spatial resolution of the respective systems. Experiments showed that mutual crosstalk interference is momentary and does not diminish the capability of either system. Spectral analysis indicated broad power spectra (several hundreds of kHz) and suggests that the signals from the FM-CW system are consistent with under-sampled fixed-frequency signals. Radial correlations were explored using data from the two reflectometers, as well as from the FM-CW system alone. The core channels showed high levels of agreement between these two comparisons, suggesting that the data from the reflectometers are interchangeable for statistical estimates. For the edge channels, comparisons using data from the FM-CW reflectometer alone showed significant decorrelation due to time lag caused by the finite frequency up-sweep duration. Alternatively, this effect is eliminated when cross-correlating data from the different reflectometers. Finally, these results highlight the advantages of operating the fixed-frequency and FM-CW reflectometers in this manner, where the combined system can overcome the limitations of each separate system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

MINERvA s Open Data Product: A First for Neutrino Data Preservation

Access to information on neutrino nucleus interactions is critical to the success of all neutrino oscillation experiments. MINERvA's rich dataset covers a range of energies and nuclei unique amongst experiments, and as such is critical to the community in building the important shared knowledge needed to unravel the mysteries of the neutrino. In particular, its dataset provides the greatest statistical coverage in in the range of neutrino energies pertinent for DUNE until DUNE's near detector begins operation. Historically, such significant datasets in neutrino physics have been preserved primarily through their published results. While meaningful and useful, this limits the ability to explore the data to its fullest extent as new perspectives continue to form. MINERvA has undertaken a major effort to break this trend and preserve its data in a format to be as analyzable as possible from outside the collaboration. This has culminated in the officially-released MINERvA Open Data Product for the community to take advantage of and utilize. Maintaining direct access to the dataset in an analyzable form will allow new insights to continue to be extracted indefinitely. This talk will cover the contents of this product, the information included (and excluded), the tools provided to utilize the product effectively, the support MINERvA intends to provide in its use, and some lessons learned through the process.

Last, David [Rochester U.] (ORCID:0000000245147183↗

“Thought I’d Share First” and Other Conspiracy Theory Tweets from the COVID-19 Infodemic: Exploratory Study

Background: The COVID-19 outbreak has left many people isolated within their homes; these people are turning to social media for news and social connection, which leaves them vulnerable to believing and sharing misinformation. Health-related misinformation threatens adherence to public health messaging, and monitoring its spread on social media is critical to understanding the evolution of ideas that have potentially negative public health impacts. Objective: The aim of this study is to use Twitter data to explore methods to characterize and classify four COVID-19 conspiracy theories and to provide context for each of these conspiracy theories through the first 5 months of the pandemic. Methods: We began with a corpus of COVID-19 tweets (approximately 120 million) spanning late January to early May 2020. We first filtered tweets using regular expressions (n=1.8 million) and used random forest classification models to identify tweets related to four conspiracy theories. Our classified data sets were then used in downstream sentiment analysis and dynamic topic modeling to characterize the linguistic features of COVID-19 conspiracy theories as they evolve over time. Results: Analysis using model-labeled data was beneficial for increasing the proportion of data matching misinformation indicators. Random forest classifier metrics varied across the four conspiracy theories considered (F1 scores between 0.347 and 0.857); this performance increased as the given conspiracy theory was more narrowly defined. We showed that misinformation tweets demonstrate more negative sentiment when compared to non-misinformation tweets and that theories evolve over time, incorporating details from unrelated conspiracy theories as well as real-world events. Conclusions: Although we focus here on health-related misinformation, this combination of approaches is not specific to public health and is valuable for characterizing misinformation in general, which is an important first step in creating targeted messaging to counteract its spread. Initial messaging should aim to preempt generalized misinformation before it becomes widespread, while later messaging will

5g↗

C/NOFS Satellite Electric Field and Plasma Density Observations of Plasma Instabilities Below the Equatorial F-Peak -- Evidence for Approximately 500 km-Scale Spread-F "Precursor" Waves Driven by Zonal Shear Flow and km-Scale, Narrow-Banded Irregularities

As solar activity has increased, the ionosphere F-peak has been elevated on numerous occasions above the C/NOFS satellite perigee of 400km. In particular, during the month of April, 2011, the satellite consistently journeyed below the F-peak whenever the orbit was in the region of the South Atlantic anomaly after sunset. During these passes, data from the electric field and plasma density probes on the satellite have revealed two types of instabilities which had not previously been observed in the C/NOFS data set (to our knowledge): The first is evidence for 400-500km-scale bottomside "undulations" that appear in the density and electric field data. In one case, these large scale waves are associated with a strong shear in the zonal E x B flow, as evidenced by variations in the meridional (outward) electric fields observed above and below the F-peak. These undulations are devoid of smaller scale structures in the early evening, yet appear at later local times along the same orbit associated with fully-developed spread-F with smaller scale structures. This suggests that they may be precursor waves for spread-F, driven by a collisional shear instability, following ideas advanced previously by researchers using data from the Jicamarca radar. A second new result (for C/NOFS) is the appearance of km-scale irregularities that are a common feature in the electric field and plasma density data that also appear when the satellite is below the F -peak at night. The vector electric field instrument on C/NOFS clearly shows that the electric field component of these waves is strongest in the zonal direction. These waves are strongly correlated with simultaneous observations of plasma density oscillations and appear both with, and without, evidence of larger-scale spread-F depletions. These km-scale, quasi-coherent waves strongly resemble the bottomside, sinusoidal irregularities reported in the Atmosphere Explorer satellite data set by Valladares et al. [JGR, 88, 8025, 1983]. We interpret these new observations in terms of fundamental plasma instabilities associated with the unstable, nighttime equatorial ionosphere.

Pfaff, R.↗

Soda Pop: A Time-Series Clustering, Alarming and Disease Forecasting Application

To introduce Soda Pop, an R/Shiny application designed to be a disease agnostic time-series clustering, alarming, and forecasting tool to assist in disease surveillance “triage, analysis and reporting” workflows within the Biosurveillance Ecosystem (BSVE). In this poster, we highlight the new capabilities that are brought to the BSVE by Soda Pop with an emphasis on the impact of methodological decisions. The Biosurveillance Ecosystem (BSVE) is a biological and chemical threat surveillance system sponsored by the Defense Threat Reduction Agency (DTRA). BSVE is intended to be user-friendly, multi-agency, cooperative, modular and threat agnostic platform for biosurveillance. In BSVE, a web-based workbench presents the analyst with applications (apps) developed by various DTRA funded researchers, which are deployed on-demand in the cloud(e.g., Amazon Web Services). These apps aim to address emerging needs and refine capabilities to enable early warning of chemical and biological threats for multiple users across local, state, and federal agencies. Soda Pop is an app developed by Pacific Northwest National Laboratory (PNNL) to meet the current needs of the BSVE for early warning and detection of disease outbreaks. Aimed for use bya diverse set of analysts, the application is agnostic to data source and spatial scale enabling it to be generalizable across many diseases and locations. To achieve this, we placed a particular emphasis on clustering and alerting of disease signals within Soda Pop without strong prior assumptions on the nature of observed diseased counts. Although designed to be agnostic to the data source, Soda Pop was initially developed and tested on data summarizing Influenza-Like Illness in military hospitals from collaboration with the Armed Forces Health Surveillance Branch. Currently, the data incorporated also includes the CDC’s National Notifiable Diseases Surveillance System(NNDSS) tables and the WHO’s Influenza A/B Influenza Data(Flunet). These data sources are now present in BSVE’s Postgres data storage for direct access. Soda Pop is designed to automate time-series tasks of data summarization, exploration, clustering, alarming and forecasting. Built as an R/Shiny application, Soda Pop is founded on the powerful statistical tool R.. Where applicable, Soda Pop facilitates nonparametric seasonal decomposition of time-series; hierarchical agglomerative clustering across reporting areas and between diseases within reporting areas; and a variety of alarming techniques including Exponential Weighted Moving Average alarms and Early Aberration Detection. Soda Pop embeds these techniques within a user-interface designed to enhance an analyst’s understanding of emerging trends in their data and enables the inclusion of its graphical elements into their dossier for further tracking and reporting. The ultimate goal of this software is to facilitate the discovery of unknown disease signals along with increasing the speed of detection of unusual patterns within these signals. Soda Pop organizes common statistical disease surveillance tasks in a manner integrated with BSVE data source inputs and outputs. The app analyzes time-series disease data and supports a robust set of clustering and alarming routines that avoid strong assumptions on the nature of observed disease counts. This attribute allows for flexibility in the data source, spatial scale, and disease types making it useful to a wide range of analysts.

97 MATHEMATICS AND COMPUTING↗

Association Between Injection and Microseismicity in Geothermal Fields With Multiple Wells: Data-Driven Modeling of Rotokawa, New Zealand, and Húsmúli, Iceland

Understanding injection-induced microseismicity in geothermal systems can provide insight into reservoir connectedness. However, fault and reservoir complexity are difficult to represent in simple analytical models, which makes it difficult to discern clear relationships from incidental associations. Here, we have used data-driven models to study how fluid injection and microseismicity are related in the Rotokawa (New Zealand) and Hellisheiði (Iceland) geothermal fields. We tested two classes of model: (a) lagged linear regression of seismicity rate as a function of well injection rates; and (b) systematic extraction of injection time series features that are then evaluated for associations with the seismicity. These models allowed us to determine which wells had the greatest correlation with microseismicity and to explain this association in a reservoir context. Finally, exploring different data types and transformations, we were unable to establish a link between rapid changes in injection rate and seismicity spikes, as suggested by some theoretical models.

15 GEOTHERMAL ENERGY↗

Improved Regolith-Landform and Geological Mapping using AIRSAR Data as an Aid to Mineral Exploration in the North-Eastern Goldfields Region, Western Australia

The distinctive contribution of AIRSAR data in characterizing the regolith-landforms in a relatively vegetation free environment are discussed. AIRSAR frame processed data were initially MAF-cleaned to enhance the signal content of the data before geocoding to AMG coordinates. Colors in a three frequency single polarization combination image C-, L- P- bands, and in an enhancement of pedestal height, relate directly to the scale of surface roughness of the various regolith units Examination of the AIRSAR enhancements reveals that in mafic terrain, and to a lesser extent, in felsic terrain, AIRSAR data provides discrimination between the principle geomorphic regimes, relict, erosional and depositional. A multivariate statistical technique called an all-possible subsets calculation was used to examine the degree of polarimetric separation between selected regolith-landforms for all combinations of the nine band AIRSAR radar. An unanticipated aspect of the research was the identification on the AIRSAR imagery of previously unmapped structural features.

Tapley, Ian J.↗

Mars Radar Observations with the Goldstone Solar System Radar

The Goldstone Solar System Radar (GSSR) has successfully collected radar echo data from Mars over the past 30 years. As such, the GSSR has played a role as a specific mission element within Mars exploration. The older data provided local elevation information for Mars, along with radar scattering information with global resolution. Since the upgrade to the 70-m Deep Space Network (DSN) antenna at Goldstone completed in 1986, Mars data has been collected during all but the 1997 Mars opposition. Radar data, and non-imaging delay-Doppler data in particular, requires significant data processing to extract elevation, reflectivity and roughness of the reflecting surface. The spatial resolution of these experiments is typically some 20 km in longitude by some 150 km in latitude. The interpretation of these parameters while limited by the complexities of electromagnetic scattering, do provide information directly relevant to geophysical and geomorphic analyses of Mars. The usefulness of radar data for Mars exploration has been demonstrated in the past. Radar data were critical in assessing the Viking Lander 1 site as well as, more recently, the Pathfinder landing site. In general, radar data have not been available to the Mars exploration community at large. A project funded initially by the Mars Exploration Directorate Science Office at the Jet Propulsion Laboratory (JPL), and later funded by NASA's Mars Data Analysis Program has reprocessed to a common format a decade's worth of raw GSSR Mars delay-Doppler data in aid of landing site characterization for the Mars Program. These data will soon be submitted to the Planetary Data System (PDS). The radar data used were obtained between 1988 and 1995 by the GSSR, and comprise some 63 delay-Doppler radar tracks. Of these, 15 have yet to be recovered from old 9-track tapes, and some of the data may be permanently lost.

Haldemann, A. F. C.↗

Cosmological constraints from DES Y1 cluster abundances and SPT multiwavelength data

We perform a joint analysis of the counts of redMaPPer clusters selected from the Dark Energy Survey (DES) year 1 data and multiwavelength follow-up data collected within the 2500 deg2 South Pole Telescope (SPT) Sunyaev-Zel’dovich (SZ) survey. The SPT follow-up data, calibrating the richness-mass relation of the optically selected redMaPPer catalog, enable the cosmological exploitation of the DES cluster abundance data. To explore possible systematics related to the modeling of projection effects, we consider two calibrations of the observational scatter on richness estimates: a simple Gaussian model which account only for the background contamination (BKG), and a model which further includes contamination and incompleteness due to projection effects (PRJ). Assuming either a ΛCDM+∑mν or wCDM+∑mν cosmology, and for both scatter models, we derive cosmological constraints consistent with multiple cosmological probes of the low and high redshift Universe, and in particular with the SPT cluster abundance data. This result demonstrates that the DES Y1 and SPT cluster counts provide consistent cosmological constraints, if the same mass calibration data set is adopted. It thus supports the conclusion of the DES Y1 cluster cosmology analysis which interprets the tension observed with other cosmological probes in terms of systematics affecting the stacked weak lensing analysis of optically selected low–richness clusters. Finally, we analyze the first combined optically SZ selected cluster catalog obtained by including the SPT sample above the maximum redshift probed by the DES Y1 redMaPPer sample (z=0.65). Besides providing a mild improvement of the cosmological constraints, this data combination serves as a stricter test of our scatter models: the PRJ model, providing scaling relations consistent between the two abundance and multiwavelength follow-up data, is favored over the BKG model.

79 ASTRONOMY AND ASTROPHYSICS↗

A study of the large-scale infrared emission from a selected dark cloud

An investigation of the infrared emission energetics and embedded population in the rho Ophiuchi dark cloud is summarized. With a distance of approximately 140 pc, the rho Ophiuchi cloud is one of the closest regions of recent star formation. It is also one of the best studied such regions with numerous observations at all wavelengths. The Infrared Astronomy Satellite (IRAS) data of the cloud provided a new glimpse of the overall structure of the cloud. In particular, the interaction of radiation from the Sco-Oph OB Association on the external heating of the cloud was very evident on Skyflux and Survey CO-Add images produced by IRAS. The infrared survey also revealed a number of new embedded sources in the cloud which have subsequently been observed from the ground. In earlier study, the overall energies of the cloud using the IRAS data was explored. The main conclusions of that work were: (1) the overall luminosity of the cloud is well explained by the emission of the known B-stars, HD 147889, SR-3, and S1, along with a 15 percent contribution from the external radiation field; (2) the dust physical temperatures were significantly lower than the observed CO gas temperatures; and (3) dust grains are heated to only 10 percent to 20 percent of the total depth into the cloud. This analysis was extended by drawing on data from large-scale CO maps of Loren (1989) and from near-infrared surveys of the embedded population.

Young, Erick T.↗

Electric Field and Plasma Density Observations of Irregularities and Plasma Instabilities in the Low Latitude Ionosphere Gathered by the C/NOFS Satellite

The Vector Electric Field Investigation (VEFI) on the C/NOFS equatorial satellite provides a unique data set which includes detailed measurements of irregularities associated with the equatorial ionosphere and in particular with spread-F depletions. We present vector AC electric field observations gathered on C/NOFS that address a variety of key questions regarding how plasma irregularities, from meter to kilometer scales, are created and evolve. The talk focuses on occasions where the ionosphere F-peak has been elevated above the C/NOFS satellite perigee of 400 km as solar activity has increased. In particular, during the equinox periods of 2011, the satellite consistently journeyed below the F-peak whenever the orbit was in the region of the South Atlantic anomaly after sunset. During these passes, data from the electric field and plasma density probes on the satellite have revealed two types of instabilities which had not previously been observed in the C/NOFS data set: The first is evidence for 400-500km-scale bottomside "undulations" that appear in the density and electric field data. In one case, these large scale waves are associated with a strong shear in the zonal E x B flow, as evidenced by variations in the meridional (outward) electric fields observed above and below the F-peak. These undulations are devoid of smaller scale structures in the early evening, yet appear at later local times along the same orbit associated with fully-developed spread-F with smaller scale structures. This suggests that they may be precursor waves for spread-F, driven by a collisional shear instability, following ideas advanced previously by researchers using data from the Jicamarca radar. A second result is the appearance of km-scale irregularities that are a common feature in the electric field and plasma density data that also appear when the satellite is near or below the F-peak at night. The vector electric field instrument on C/NOFS clearly shows that the electric field component of these waves is strongest in the zonal direction. These waves are strongly correlated with simultaneous observations of plasma density oscillations and appear both with, and without, evidence of larger-scale spread-F depletions. These km-scale, quasi-coherent waves strongly resemble the bottomside, sinusoidal irregularities reported in the Atmosphere Explorer satellite data set by Valladares et al. and are believed to cause scintillations of VHF radiowaves. We interpret these new observations in terms of fundamental plasma instabilities associated with the unstable, nighttime equatorial ionosphere.

Pfaff, Robert F.↗

Machine learning applied to classifying neutron resonances

The performance of nuclear reactors and other nuclear systems depends on a precise understanding of the neutron interaction cross sections for materials used in these systems. These cross sections exhibit resonance structure whose shape is determined in part by the angular momentum quantum numbers of the resonances. The correct assignment of the quantum numbers of neutron resonances is therefore of paramount importance. In this project, we apply a machine learning technique, namely decision trees, to automate the quantum number assignments. The tree is trained from simulated data generated to mimic the errors found in real data. We explore the use of several physics-motivated features for training our trees, including the nearest neighbor spacing distribution, cumulative level distribution, and channel width distributions. Initial results using random matrix theory motivated fits which demonstrated that we can determine resonance spin groups somewhat reliably. If we use these fits as features in our trees, we can train them to spot outliers corresponding to misassigned resonances. We found that with the large number of features used in this project that the decision tree tended to over t training data resulting in poor performance with respect to the test data. By reducing the number of features, we can achieve nearly perfect assignment of quantum numbers with our training data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

LDEF archival system plan

The Long Duration Exposure Facility (LDEF) has provided the first significant opportunity to extensively study the space environment and its effects upon spacecraft systems and materials. The long-term value of the data obtained from LDEF, which is applicable to a wide range of areas including space environment definition, space environmental effects, and spacecraft design, will depend upon the system developed to archive and retrieve the data. Therefore, in addition to the large effort undertaken to analyze LDEF data, a substantial effort is also necessary in order to retain and disseminate LDEF resources for future research and design. W. J. Schafer Associates, Inc., has a task subcontract to develop the LDEF archival system. The LDEF resources include data, hardware, photographic records, and publications which cover the 20-year history of LDEF from concept design through data analysis. Chronologically, prelaunch resources include documentation of facility and experiment development, testing integration, and operation. Post-retrieval resources are the observations, testing, analysis, and publications since the January 1990 retrieval of LDEF. A third set of resources is the experiment and facility hardware and specimens, including more than 10,000 test specimens flown on LDEF and subsequently divided and distributed among investigators at numerous laboratories. Many valuable science and technology investigations were undertaken with LDEF experiments and hardware, and many more investigations are being identified in areas not yet explored. LDEF data applications encompass primarily low-Earth orbit spacecraft and structures. The nearly six-year space exposure of LDEF has provided data to evaluate materials, systems, and living specimens exposed to radiation, meteoroids, debris, and other constituents of the low-Earth environment. Structural, mechanical, electrical, optical, and thermal systems were studied, and materials with applications in all aspects of space systems were exposed to the space environment. The objectives of the LDEF archival system are to maintain the existing LDEF hardware, data, analysis, publications, and photographs as a long term resource, and to provide a quick and simple mechanism by which LDEF resources can be identified, located, and applied.

Wilson, Brenda K.↗

Cyber Safety and Security for Reduced Crew Operations (RCO)

NASA and the Aviation Industry is looking into reduced crew operations (RCO) that would cut today's required two-person flight crews down to a single pilot with support from ground-based crews. Shared responsibility across air and ground personnel will require highly reliable and secure data communication and supporting automation, which will be safety-critical for passenger and cargo aircraft. This paper looks at the different types and degrees of authority delegation given from the air to the ground and the ramifications of each, including the safety and security hazards introduced, the mitigation mechanisms for these hazards, and other demands on an RCO system architecture which would be highly invasive into (almost) all safety-critical avionics. The adjacent fields of unmanned aerial systems and autonomous ground vehicles are viewed to find problems that RCO may face and related aviation accident scenarios are described. The paper explores possible data communication architectures to meet stringent performance and information security (INFOSEC) requirements of RCO. Subsequently, potential challenges for RCO data communication authentication, encryption and non-repudiation are identified.

Communications↗

Cyber Safety and Security for Reduced Crew Operations (RCO)

NASA and the Aviation Industry is looking into reduced crew operations (RCO) that would cut today's required two-person flight crews down to a single pilot with support from ground-based crews. Shared responsibility across air and ground personnel will require highly reliable and secure data communication and supporting automation, which will be safety-critical for passenger and cargo aircraft. This paper looks at the different types and degrees of authority delegation given from the air to the ground and the ramifications of each, including the safety and security hazards introduced, the mitigation mechanisms for these hazards, and other demands on an RCO system architecture which would be highly invasive into (almost) all safety-critical avionics. The adjacent fields of unmanned aerial systems and autonomous ground vehicles are viewed to find problems that RCO may face and related aviation accident scenarios are described. The paper explores possible data communication architectures to meet stringent performance and information security (INFOSEC) requirements of RCO. Subsequently, potential challenges for RCO data communication authentication, encryption and non-repudiation are identified. The approach includes a comprehensive safety-hazard analysis of the RCO system to determine top level INFOSEC requirements for RCO and proposes an option for effective RCO implementation. This paper concludes with questioning the economic viability of RCO in light of the expense of overcoming the operational safety and security hazards it would introduce.

Aircraft Communication↗

Neutron stars in $$f(\mathtt {R,L_m})$$ gravity with realistic equations of state: joint-constrains with GW170817, massive pulsars, and the PSR J0030+0451 mass-radius from NICER data

Abstract In this work, we investigate neutron stars (NS) in $$f(\mathtt {R,L_m})$$ f ( R , L m ) theory of gravity for the case $$f(\mathtt {R,L_m})= \mathtt {R}+ \mathtt {L_m}+ \sigma \mathtt {R}\mathtt {L_m}$$ f ( R , L m ) = R + L m + σ R L m , where $$\mathtt {R}$$ R is the Ricci scalar and $$\mathtt {L_m}$$ L m the Lagrangian matter density. In the term $$\sigma \mathtt {R}\mathtt {L_m}$$ σ R L m , $$\sigma $$ σ represents the coupling between the gravitational and particles fields. For the first time the hydrostatic equilibrium equations in the theory are solved considering realistic equations of state and NS masses and radii obtained are subject to joint constrains from massive pulsars, the gravitational wave event GW170817 and from the PSR J0030+0451 mass-radius from NASA’s Neutron Star Interior Composition Explorer ( NICER ) data. We show that in this theory of gravity, the mass-radius results can accommodate massive pulsars, while the general theory of relativity can hardly do it. The theory also can explain the observed NS within the radius region constrained by the GW170817 and PSR J0030+0451 observations for masses around $$1.4~M_{\odot }$$ 1.4 M ⊙ .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The Diversity of Martian Volcanic features as Seen in the MOC, THEMIS, and MOM Data Sets

This one-year project (which included one-year no-cost tension) focused on the evolution of the summit areas of Martian volcanoes. It extended the studies conducted under an earlier MDAP project (Grant NAG5-9576, Principal Investigator P. Mouginis- Mark). By using data collected from the Mars Orbiter Camera (MOC), Thermal Emission Imaging System (THEMIS), and the Mars Orbiter Laser Altimeter (MOLA) instruments, we tried to better understand the diversity of constructional volcanism on Mars, and hence further understand the eruption processes. By inspecting THEMIS and MOC data, we explored the following four questions: (1) Where might near-surface volatiles have been released at the summits of the Tharsis volcanoes? Is the trapping and subsequent remobilization of degassed volatiles [Scott and Wilson, 19991 adequate to produce eruptions responsible for extensive deposits such as the ones identified on Arsia Mons [Mouginis-Mark, 2002]? To answer this question, we investigated the diversity of eruption styles by studying the summit areas of Arsia, Pavonis and Ascraeus Montes. (2) What are the geomorphic characteristics of the valley system on Hecates Tholus, a volcano that we have previously proposed experienced explosive activity [Mouginis-Murk et al., 1982]? Our inspection of THEMIS data suggests that water release on the volcano took place over an extended period of time, suggesting that hydrothermal activity may have taken place here. (3) How similar are the collapse processes observed at Martian and terrestrial calderas? New THEMIS data provide a more complete view of the entire Olympus Mons caldera, thereby enabling the comparison with the collapse features at Masaya volcano, Nicaragua, to be investigated. (4) What can we learn about the emplacement of long lava flows in the lava plains of Eastern Tharsis? The result of this work provided a greater understanding of the temporal and spatial variations in the eruptive history of volcanoes on Mars, and the influence of the volatiles within the top few kilometers of the volcanic edifice. This relationship in turn pertains to the availability of volatiles (both juvenile magmatic volatiles and ground water contained within the near-surface rocks) and to magma supply rates at appreciable distances (tens to hundreds of kilometers) from the centers of volcanoes. Explosive volcanism on Mars, a major factor in the release of water at the surface, may have been driven not only by volatiles within the parental melt, but also by magma encountering water or ice at shallow depth within the volcano [Mouginis-Mark et al., 1982, 1988; Crown and Greeley, 1993; Robinson et al., 19931.

Mouginis-Mark, Peter J.↗

Selection function of clusters in Dark Energy Survey year 3 data from cross-matching with South Pole Telescope detections

Context. Galaxy clusters selected based on overdensities of galaxies in photometric surveys provide the largest cluster samples. However, modeling the selection function of such samples is complicated by noncluster members projected along the line of sight (projection effects) and the potential detection of unvirialized objects (contamination). Aims. We empirically constrained the magnitude of these effects by cross-matching galaxy clusters selected in the Dark Energy Survey data with the redMaPPer algorithm with significant detections in three South Pole Telescope surveys (SZ, pol-ECS, pol-500d). Methods. For matched clusters, we augmented the redMaPPer catalog with the SPT detection significance. For unmatched objects we used the SPT detection threshold as an upper limit on the SZe signature. Using a Bayesian population model applied to the collected multiwavelength data, we explored various physically motivated models to describe the relationship between observed richness and halo mass. Results. Our analysis reveals a clear preference for models with an additional skewed scatter component associated with projection effects over a purely log-normal scatter model. We rule out significant contamination by unvirialized objects at the high-richness end of the sample. While dedicated simulations offer a well-fitting calibration of projection effects, our findings suggest the presence of redshift-dependent trends that these simulations may not have captured. Our findings highlight that modeling the selection function of optically detected clusters remains a complicated challenge that requires a combination of simulation and data-driven approaches.

79 ASTRONOMY AND ASTROPHYSICS↗