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A typological framework of non-floodplain wetlands for global collaborative research and sustainable use

Non-floodplain wetlands (NFWs) are important but vulnerable inland freshwater systems that are receiving increased attention and protection worldwide. However, a lack of consistent terminology, incohesive research objectives, and inherent heterogeneity in existing knowledge hinder cross-regional information sharing and global collaboration. To address this challenge and facilitate future management decisions, we synthesized recent work to understand the state of NFW science and explore new opportunities for research and sustainable NFW use globally. Results from our synthesis show that although NFWs have been widely studied across all continents, regional biases exist in the literature. We hypothesize these biases in the literature stem from terminology rather than real geographical bias around existence and functionality. To confirm this observation, we explored a set of geographically representative NFW regions around the world and characteristics of research focal areas. We conclude that there is more that unites NFW research and management efforts than we might otherwise appreciate. Furthermore, opportunities for cross-regional information sharing and global collaboration exist, but a unified terminology will be needed, as will a focus on wetland functionality. Based on these findings, we discuss four pathways that aid in better collaboration, including improved cohesion in classification and terminology, and unified approaches to modeling and simulation. In turn, legislative objectives must be informed by science to drive conservation and management priorities. Finally, an educational pathway serves to integrate the measures and to promote new technologies that aid in our collective understanding of NFWs. Our resulting framework from NFW synthesis serves to encourage interdisciplinary collaboration and sustainable use and conservation of wetland systems globally.

54 ENVIRONMENTAL SCIENCES↗

Landsat-8: Science and Product Vision for Terrestrial Global Change Research

Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared. Landsat 8 extends the remarkable 40 year Landsat record and has enhanced capabilities including new spectral bands in the blue and cirrus cloud-detection portion of the spectrum, two thermal bands, improved sensor signal-to-noise performance and associated improvements in radiometric resolution, and an improved duty cycle that allows collection of a significantly greater number of images per day. This paper introduces the current (2012-2017) Landsat Science Team's efforts to establish an initial understanding of Landsat 8 capabilities and the steps ahead in support of priorities identified by the team. Preliminary evaluation of Landsat 8 capabilities and identification of new science and applications opportunities are described with respect to calibration and radiometric characterization; surface reflectance; surface albedo; surface temperature, evapotranspiration and drought; agriculture; land cover, condition, disturbance and change; fresh and coastal water; and snow and ice. Insights into the development of derived 'higher-level' Landsat products are provided in recognition of the growing need for consistently processed, moderate spatial resolution, large area, long-term terrestrial data records for resource management and for climate and global change studies. The paper concludes with future prospects, emphasizing the opportunities for land imaging constellations by combining Landsat data with data collected from other international sensing systems, and consideration of successor Landsat mission requirements.

Landsat↗

Development of Community, Capabilities and Understanding Through Unmanned Aircraft-Based Atmospheric Research: The LAPSE-RATE Campaign

Members of the international community developing unmanned aircraft for atmospheric research conducted a highly-successful coordinated flight week in Colorado during summer 2018 to collect measurements, develop capabilities, and enhance community in the field. Because unmanned aircraft systems (UAS) offer new perspectives on the atmosphere, their use in atmospheric science is expanding rapidly. In support of this growth, the International Society for Atmospheric Research using Remotely-piloted Aircraft (ISARRA) has been developed and have convened annual meetings and 'flight weeks'. The 2018 flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE), involved a one-week deployment to Colorado's San Luis Valley. Between 14-20 July 2018 over 100 students, scientists, engineers, pilots and outreach coordinators conducted an intensive field operation using unmanned aircraft and ground-based assets to develop datasets, community, and capabilities. In addition to a coordinated 'community day' which offered a chance for groups to share their aircraft and science with the San Luis Valley community, LAPSE-RATE participants conducted nearly 1300 research flights totaling over 250 flight hours. The measurements collected have been used to advance capabilities (instrumentation, platforms, sampling techniques and modeling tools), conduct a detailed system intercomparison study, develop new collaborations, and foster community support for the use of UAS in atmospheric science.

54 ENVIRONMENTAL SCIENCES↗

The DUNE Phase II Detectors

The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy for the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the previous European Strategy for Particle Physics. The construction of DUNE Phase I is well underway. DUNE Phase II consists of a third and fourth far detector module, an upgraded near detector complex, and an enhanced > 2 MW beam. The fourth FD module is conceived as a 'Module of Opportunity', aimed at supporting the core DUNE science program while also expanding the physics opportunities with more advanced technologies. The DUNE collaboration is submitting four main contributions to the 2026 Update of the European Strategy for Particle Physics process. This submission to the 'Detector instrumentation' stream focuses on technologies and R&D for the DUNE Phase II detectors. Additional inputs related to the DUNE science program, DUNE software and computing, and European contributions to Fermilab accelerator upgrades and facilities for the DUNE experiment, are also being submitted to other streams.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Virtual Microscope Views of the Apollo 11 and 12 Lunar Samples

The Apollo virtual microscope is a means of viewing, over the Internet, polished thin sections of every rock in the Apollo lunar sample collections via software, duplicating many of the functions of a petrological microscope, is described. Images from the Apollo 11 and 12 missions may be viewed at: www.virtualmicroscope.org/content/apollo. Introduction: During the six NASA missions to the Moon from 1969-72 a total of 382 kilograms of rocks and soils, often referred to as "the legacy of Apollo", were collected and returned to Earth. A unique collection of polished thin sections (PTSs) was made from over 400 rocks by the Lunar Sample Curatorial Facility at the Johnson Spacecraft Center (JSC), Houston. These materials have been available for loan to approved PIs but of course they can't be simultaneously investigated by several researchers unless they are co-located or the sample is passed back and forward between them by mail/hand carrying which is inefficient and very risky for irreplaceable material. When The Open University (OU), the world's largest Distance Learning Higher Education Establishment found itself facing a comparable problem (how to supply thousands of undergraduate students with an interactive petrological microscope and a personal set of thin sections), it decided to develop a software tool called the Virtual Microscope (VM). As a result it is now able to make the unique and precious collection of Apollo specimens universally available as a resource for concurrent study by anybody in the world's Earth and Planetary Sciences community. Herein, we describe the first steps of a collaborative project between OU and the Johnson Space Center (JSC) Curatorial Facility to record a PTS for every lunar rock, beginning with those collected by the Apollo 11 and 12 missions. Method: Production of a virtual microscope dedicated to a particular theme divides into four main parts - photography, image processing, building and assembly of virtual microscope components, and publication on a website. Two large research quality microscopes are used to collect all the images required for a virtual microscope. The first is part of an integrated package that utilizes Leica PowerMosaic software and a motorised XYZ stage to generate large area mosaics. It includes a fast acquisition camera and depending on the PTS size normally is used to produce seamless mosaic images consisting of 100-500 individual photographs. If the sample is suitable, three mosaics of each sample are recorded - plane polarised light, between crossed polars and reflected light. In order for the VM to be a true petrological microscope it is necessary to recreate the features of a rotating stage and perform observations using filters to produce polarised light. Thus the petrological VM includes the capability of seeing changes in optical properties (pleochroism and birefringence) during rotation allowing mineral identification. The second microscope in the system provides the functions of the rotating stage. To this microscope we have added a robotically controlled motor to acquire seventy-two images (5 degree intervals) in plane polarised light and between crossed polars. To process the images acquired from the two microscopes involves a combination of proprietary software (Photoshop) and our own in-house code. The final stage involves assembling all the components in an HTML5 environment. Pathfinder investigations: We have undertaken a number of pilot studies to demonstrate the efficacy of the petrological microscope with lunar samples. The first was to make available on-line images collected from the Educational Package of Apollo samples provided by NASA to the UK STFC (Science and Technical Facilities Council) for loan as educational material e.g. for schools. The real PTSs of the samples are now no longer sent out to schools removing the risks associated with transport, accidental breakage and eliminating the possibility of loss. The availability of lunar sample VM-related material was further extended to include twenty-eight specimens from all of the Apollo missions. Some of these samples were made more generally available through an ibook entitled "Moon Rocks: an introduction to the Geology of the Moon," free from the Apple Bookstore. Research possibilities: Although the Virtual Microscope was originally conceived as a teaching aid and was later recognised as a means of public outreach and engagement, we now realize that it also has enormous potential as a high level research tool. Following discussions with the JSC Curators we have received Curation and Analysis Planning Team for Extraterrestrial Materials (CAPTEM) permission to embark on a programme of digitizing the entire lunar sample PTS collection for all three of the above purposes. By the time of the 47th Lunar and Planetary Science Conference (LPSC) we will have completed 81 rocks collected during the Apollo 11 and 12 missions and the data, with cross-links to the Lunar Sample Compendium will go live on the Web at the 47th LPSC. The VM images of the Apollo 11 (41 VM images) and 12 (40 VM images) missions can be viewed at: http:/www.virtualmicroscope.org/content/apollo. The lunar sample VM will enable large numbers of skilled/unskilled microscopists (professional and amateur researchers, educators and students, enthusiasts and the simply curious non-scientists) to share the information from a single sample. It will mean that all the PTSs already cut, even historical ones, could be available for new joint investigations or private study. The scientific return from the collection will increase exponentially as a result of further debate and discussion. Simultaneously the VM will remove the need for making unnecessary multiple samplings, avoid consignment of delicate/breakable specimens (all of which are priceless) to insecure mail/courier services and reduce direct labour and indirect costs, travel budgets and unproductive travelling time necessary for co-location of collaborating researchers. For the future we have already recognized further potential for virtual technology. There is nothing that a petrologist likes more than to see the original rock as a hand specimen. It is entirely possible to recreate virtual hand specimens with 3-D hard and software, already developed for viewing fossils, located within the Curatorial Facility, http://curator.jsc.nasa.gov/lunar/lsc/index.cfm.

Gibson, E. K.↗

NASA Open Science Data Repository: Open Science for Life in Space

Space biology and health data are critical for the success of deep space missions and sustainable human presence off-world. At the core of effectively managing biomedical risks is the commitment to open science principles, which ensure that data are findable, accessible, interoperable, reusable, reproducible and maximally open. The 2021 integration of the Ames Life Sciences Data Archive with GeneLab to establish the NASA Open Science Data Repository significantly enhanced access to a wide range of life sciences, biomedical-clinical, and mission telemetry data alongside existing ‘omics data from GeneLab. This paper describes the new database, its architecture, and new data streams supporting diverse data types and enhancing data submission, retrieval, and analysis. Features include the Biological Data Management Environment for improved data submission, a new user interface, controlled data access, an enhanced API, and comprehensive public visualization tools for environmental telemetry, radiation dosimetry data, and ‘omics analyses. By fostering global collaboration through its Analysis Working Groups and training programs, the Open Science Data Repository promotes widespread engagement in space biology, ensuring transparency and inclusivity in research. It supports the global scientific community in advancing our understanding of spaceflight's impact on biological systems, ensuring humans will thrive in future deep space missions.

OSDR↗

Investigation of the Crystal Growth of Dielectric Materials by the Bridgman Technique Using Vibrational Control

The principal goal of this ground-based program, which started on February 1, 1998 and concluded on April 30, 2002, was to investigate the influence of low frequency vibrations on the fluid flow and quality of dielectric oxide crystals grown by the vertical Bridgman method. This experimental program was a collaborative effort between Stanford University and the General Physics Institute of the Russian Academy of Sciences in Moscow, and included a strong emphasis on both physical modeling and the growth of some technologically important materials. Additionally it was carried out initially in collaboration with the theoretical and numerical investigations of A.Fedoseyev and I.Alexander (ongoing in another NASA sponsored program). This latter program involved a study of vibro-convective buoyancy-driven flows in cylindrical configurations with the expectation of being able to use vibrational flows to control buoyancy driven fluid transport to off-set the effect of "g-jitter" during microgravity Bridgman crystal growth. These two programs taken together, were designed to lead to a new parametric control variable which can be used to either suppress or control convection, and thereby heat and mass transport during Bridgman crystal growth. It was expected to be effective in either a terrestrial or space environment.

Feigelson, Robert S.↗

VEDA: Visualization, Exploration, & Data Analysis

NASA's Visualization, Exploration, and Data Analysis (VEDA) project is an open-source science cyberinfrastructure for data processing, visualization, exploration, and geographic information systems (GIS) capabilities. Developed collaboratively and mostly reusing existing open-source components, VEDA consolidates GIS delivery mechanisms, processing platforms, analysis services, and visualization tools and provides an ecosystem of open tools for addressing Earth science research and application needs through the public-facing VEDA Dashboard. In this presentation, Dr. Freitag will provide an overview of VEDA and how it can potentially serve the AOS community.

Brian Freitag↗

MSLICE Science Activity Planner for the Mars Science Laboratory Mission

MSLICE (Mars Science Laboratory InterfaCE) is the tool used by scientists and engineers on the Mars Science Laboratory rover mission to visualize the data returned by the rover and collaboratively plan its activities. It enables users to efficiently and effectively search all mission data to find applicable products (e.g., images, targets, activity plans, sequences, etc.), view and plan the traverse of the rover in HiRISE (High Resolution Imaging Science Experiment) images, visualize data acquired by the rover, and develop, model, and validate the activities the rover will perform. MSLICE enables users to securely contribute to the mission s activity planning process from their home institutions using off-the-shelf laptop computers. This software has made use of several plug-ins (software components) developed for previous missions [e.g., Mars Exploration Rover (MER), Phoenix Mars Lander (PHX)] and other technology tasks. It has a simple, intuitive, and powerful search capability. For any given mission, there is a huge amount of data and associated metadata that is generated. To help users sort through this information, MSLICE s search interface is provided in a similar fashion as major Internet search engines. With regard to the HiRISE visualization of the rover s traverse, this view is a map of the mission that allows scientists to easily gauge where the rover has been and where it is likely to go. The map also provides the ability to correct or adjust the known position of the rover through the overlaying of images acquired from the rover on top of the HiRISE image. A user can then correct the rover s position by collocating the visible features in the overlays with the same features in the underlying HiRISE image. MSLICE users can also rapidly search all mission data for images that contain a point specified by the user in another image or panoramic mosaic. MSLICE allows the creation of targets, which provides a way for scientists to collaboratively name features on the surface of Mars. These targets can also be used to convey instrument-pointing information to the activity plan. The software allows users to develop a plan of what they would like the rover to accomplish for a given time period. When developing the plan, the user can input constraints between activities or groups of activities. MSLICE will enforce said constraints and ensure that all mission flight rules are satisfied.

Powell, Mark W.↗

Phase Field Modeling of Microstructure Development in Microgravity

This newly funded project seeks to extend our NASA-sponsored project on modeling of dendritic microstructures to facilitate collaboration between our research group and those of other NASA investigators. In our ongoing program, we have applied advanced computational techniques to study microstructural evolution in dendritic solidification, for both pure isolated dendrites and directionally solidified alloys. This work has enabled us to compute dendritic microstructures using both realistic material parameters and experimentally relevant processing conditions, thus allowing for the first time direct comparison of phase field computations with laboratory observations. This work has been well received by the materials science and physics communities, and has led to several opportunities for collaboration with scientists working on experimental investigations of pattern selection and segregation in solidification. While we have been able to pursue these collaborations to a limited extent, with some important findings, this project focuses specifically on those collaborations. We have two target collaborations: with Prof. Glicksman's group working on the Isothermal Dendritic Growth Experiment (IDGE), and with Prof. Poirier's group studying directional solidification in Pb-Sb alloys. These two space experiments match well with our two thrusts in modeling, one for pure materials, as in the IDGE, and the other directional solidification. Such collaboration will benefit all of the research groups involved, and will provide for rapid dissemination of the results of our work where it will have significant impact.

Dantzig, Jonathan A.↗

Earth Science Data Analysis in the Era of Big Data

Anyone with even a cursory interest in information technology cannot help but recognize that "Big Data" is one of the most fashionable catchphrases of late. From accurate voice and facial recognition, language translation, and airfare prediction and comparison, to monitoring the real-time spread of flu, Big Data techniques have been applied to many seemingly intractable problems with spectacular successes. They appear to be a rewarding way to approach many currently unsolved problems. Few fields of research can claim a longer history with problems involving voluminous data than Earth science. The problems we are facing today with our Earth's future are more complex and carry potentially graver consequences than the examples given above. How has our climate changed? Beside natural variations, what is causing these changes? What are the processes involved and through what mechanisms are these connected? How will they impact life as we know it? In attempts to answer these questions, we have resorted to observations and numerical simulations with ever-finer resolutions, which continue to feed the "data deluge." Plausibly, many Earth scientists are wondering: How will Big Data technologies benefit Earth science research? As an example from the global water cycle, one subdomain among many in Earth science, how would these technologies accelerate the analysis of decades of global precipitation to ascertain the changes in its characteristics, to validate these changes in predictive climate models, and to infer the implications of these changes to ecosystems, economies, and public health? Earth science researchers need a viable way to harness the power of Big Data technologies to analyze large volumes and varieties of data with velocity and veracity. Beyond providing speedy data analysis capabilities, Big Data technologies can also play a crucial, albeit indirect, role in boosting scientific productivity by facilitating effective collaboration within an analysis environment. To illustrate the effects of combining a Big Data technology with an effective means of collaboration, we relate the (fictitious) experience of an early-career Earth science researcher a few years beyond the present, interlaced and contrasted with reminiscences of its recent past (i.e., the present).

Kuo, K.-S.↗

Enabling modern data discovery for atmospheric measurements

The Atmospheric Radiation Measurement (ARM) user facility is a US Department of Energy Office of Science user facility that is managed and operated through a collaborative effort led by nine US Department of Energy national laboratories. The ARM Data Center, located at Oak Ridge National Laboratory, is responsible for the timely collection, processing, and delivery of data products to the scientific community. The ARM Data Center holds more than 11,000 data products, including metadata collected from field campaigns, instruments, value-added products, and principal investigator–contributed data. These data sets are checked for successful transfer (for most data, this transfer is carried out automatically via the network; however, some of the largest data sets and some of the most remote sites require manual shipping of hard disks) and both the data and metadata are processed to a standard format, which is an ARM-standardized structure, via the Network Common Data Form. The Network Common Data Form is a self-describing binary format with many compatible software tools. Once processed, the data are cataloged, stored in the ARM Data Archive, and made discoverable through association with an array of metadata-characterizing information, such as location and measurement classification. These metadata enable powerful search capabilities through the ARM Data Center Data Discovery interface. This paper discusses the workflow of how the new discovery system has been redesigned from user requirements and how the data are distributed to the scientific community.

54 ENVIRONMENTAL SCIENCES↗

NNSA-IAEC Area: Workshop on Nuclear Waste Management and Subsurface Science (8-10 November 2022)

The 7 th workshop of the NNSA-IAEC collaboration was conducted on November 8-10 2022. The workshop was held at the geologic survey of Israel, Jerusalem. The IAEC hosted the workshop. The main topic of the workshop evolved around the results of the characterization borehole drilled in the Yamin plain during 2022 and associated experimental work and modeling results. The new data will be integrated for the applicability analysis of intermediate depth borehole (IDB) disposal for spent fuel in the Yamin plain. The first day of the workshop (November 8 th ) was dedicated to a geological field trip in the Judea desert depicting a similar cross section to that found in the Yamin plain. During the 9 th and 10 th of November the characterization BH results were presented, results of new work on the Miocene Hazeva fm. were presented, and this year’s outcome of the different collaboration groups were given.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Activities at Pacific Northwest National Laboratory to Advance Nuclear Radiation Science among Underrepresented STEM Students

The Partnership for Radiation Studies (PaRS) consortium is a collaboration between two minority-serving institutions and two U.S. national laboratories. The five-year consortium is funded by the U.S. Department of Energy’s (DOE) National Nuclear Security Administration (NNSA), and it aims enhance workforce of underrepresented students in STEM disciplines. PaRS’ long-term goal is to train students for their prospective hiring in DOE laboratories and sites. As one of the two integral national laboratory partners, the Pacific Northwest National Laboratory (PNNL) is playing an integral role in achieving this goal via pertinent lectures, seminars, hands-on trainings, and outreach activities. This paper summarizes PNNL’s key activities and initiatives to train the next generation of underrepresented students in STEM disciplines.

Minority Serving Institutions Partnership Program,↗

Bioimaging Science Program: 2022 Principal Investigator Meetings Proceedings

The mission of the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program’s Bioimaging Science Program (BSP) is to understand the translation of genomic information into the mechanisms that power living cells, communities of cells, and whole organisms. The goal of BSP is to develop new imaging and measurement technologies to visualize the spatial and temporal relationships of key metabolic processes governing phenotypic expression in plants and microbes. The extended goal of dynamic imaging is to functionally connect cellular components and interdependent organisms. Information about the time and place of chemical reactions in situ can identify causal relationships between biological activators and downstream effectors. BSP held its annual PI meeting virtually February 28–March 1. Contributing investigators are convened to review progress and current state-of-the-art bioimaging research. Holding the 2022 BSP meeting as part of the broader Genomic Science Program (GSP) PI meeting allowed researchers to interact with the extended GSP community. This convergence provided a platform for networking and exchange of ideas with experts in other technologies and in target BSP application areas, helping to forge new multidisciplinary collaborations among investigators from the sister programmatic areas within BER’s Biological Systems Science Division. An important highlight of the BSP meeting was the keynote presentation by Nobel Laureate Dr. Joachim Frank on Time-Resolved Macromolecular Imaging using Cryo-EM. He discussed microfluidic mixing and fast freezing to capture nonequilibrium intermediate states during molecular binding and conformational changes. The action of molecular machines can be captured at nanometer resolution and millisecond discrimination. BSP PIs made presentations describing their research focus and progress in plenary sessions on bioimaging science and on quantum-enabled bioimaging science research projects. BSP research at universities and DOE laboratories is presented in this report. A final discussion of the BSP was organized by meeting plenary session chairs, who prepared the following Executive Summary of current BSP research, research challenges, future opportunities, and potential ideas for expanding the BSP’s impact and interactions.

59 BASIC BIOLOGICAL SCIENCES↗

The stellar origins of 96 Zr excesses in presolar graphites from the Murchison meteorite

Context. Zirconium-96 is a stable isotope that can be synthesized under different neutron-rich nucleosynthetic conditions. Astrophysical models predict its production to occur in various stellar environments: from low-to-intermediate-mass asymptotic giant branch (AGB) stars to massive stars and core-collapse supernovae. Aims. Detections of 96Zr excesses, in combination with other isotopic measurements from presolar grains can provide unique constraints on its stellar origin. Presolar grains are microscopic particles found in primitive Solar System materials, which formed in stellar winds and supernova ejecta. The isotopic composition of each grain can provide us a snapshot of the nucleosynthetic processes that took place during the parent star’s lifetime. Methods. In this study, we measured the stable isotopes of C, N, O, Mo, Zr, and Ru in high-density presolar graphite grains from the Murchison meteorite and found four grains that contain positive isotopic anomalies in 96 Zr carried by their internal subgrains. We analyzed multi-element isotopic datasets from each grain to explore the source of the observed 96 Zr excesses. Results. Comparisons with stellar models indicate that two grains likely condensed in an intermediate-mass AGB star with initial metallicity of Z ≤ 0.014. Their 96 Zr/ 94 Zr ratios also match those predicted for born-again AGB stars undergoing a very late thermal pulse and rapidly accreting white dwarfs. After comparing the relative populations of the aforementioned dust-producing stars, we propose rapidly accreting white dwarfs as a new, and more likely, stellar source for one of the presolar grains. The remaining two grains could have originated in the supernova ejecta of massive stars, due to correlated excesses in the p-nuclides, 92, 94 Mo. Thus, grains with 96 Zr anomalies can have a variety of stellar origins, in agreement with theoretical studies. Conclusions. Our study highlights the importance of multi-element analysis in constraining the types of stars where presolar grains have condensed. These data will help improve our understanding of various nucleosynthesis processes in different stellar phases.

79 ASTRONOMY AND ASTROPHYSICS↗

The Photometric LSST Astronomical Time-series Classification Challenge PLAsTiCC: Selection of a Performance Metric for Classification Probabilities Balancing Diverse Science Goals

Classification of transient and variable light curves is an essential step in using astronomical observations to develop an understanding of the underlying physical processes from which they arise. However, upcoming deep photometric surveys, including the Large Synoptic Survey Telescope (LSST), will produce a deluge of low signal-to-noise data for which traditional type estimation procedures are inappropriate. Probabilistic classification is more appropriate for such data but is incompatible with the traditional metrics used on deterministic classifications. Furthermore, large survey collaborations like LSST intend to use the resulting classification probabilities for diverse science objectives, indicating a need for a metric that balances a variety of goals. We describe the process used to develop an optimal performance metric for an open classification challenge that seeks to identify probabilistic classifiers that can serve many scientific interests. The Photometric LSST Astronomical Time-series Classification Challenge (PLASTICC) aims to identify promising techniques for obtaining classification probabilities of transient and variable objects by engaging a broader community beyond astronomy. Using mock classification probability submissions emulating realistically complex archetypes of those anticipated of PLASTICC, we compare the sensitivity of two metrics of classification probabilities under various weighting schemes, finding that both yield results that are qualitatively consistent with intuitive notions of classification performance. We thus choose as a metric for PLASTICC a weighted modification of the cross-entropy because it can be meaningfully interpreted in terms of information content. Finally, we propose extensions of our methodology to ever more complex challenge goals and suggest some guiding principles for approaching the choice of a metric of probabilistic data products.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantum Computing for Biomedical Computational and Data Sciences: A Joint DOE-NIH Roundtable

The overlap of quantum computing and biomedical research, while less explored, presents significant near-term opportunities. The Department of Energy (DOE) and the National Institutes of Health (NIH) are interested in exploiting the DOE community’s capabilities and expertise in quantum computing to potentially advance biomedical research, targeting fundamental studies of biological and molecular structures, understanding of human health as well as mental and physical disorders and diseases, and deriving insights from clinical data. NIH’s approach to quantum computing is guided by its Strategic Plan for Data Science, emphasizing the importance of findable, accessible, interoperable, and reusable (FAIR) data assets, security and privacy of data, and efficient computing and storage. DOE’s Office of Science (SC), and more specifically the Advanced Scientific Computing Research (ASCR) program, supports quantum information science (QIS) research, contributing to a unique portfolio of quantum computing and communications expertise. This roundtable was assembled to consider the opportunities and challenges in the near-, medium-, and long-term at the intersection of quantum computing, data science, and biomedical research and how these could be addressed through inter-agency collaboration and multi-disciplinary partnerships.

59 BASIC BIOLOGICAL SCIENCES↗