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The NASA Exoplanet Archive and the Exoplanet Follow-up Observing Program service are two widely used resources for the exoplanet community. The NASA Exoplanet Archive provides a complete and accurate accounting of exoplanetary systems published by NASA missions and by the community in the refereed literature. In anticipation of continued exponential growth in the number of exoplanetary systems, and the increasing complexity in our characterization of these systems, the NASA Exoplanet Archive has restructured its primary tables and interfaces, as well as extending and standardizing their modes of access. The Exoplanet Follow-up Observing Program service provides the exoplanet community with a venue for coordinating and sharing follow-up and precursor data for exoplanets, their host stars, and stars that might eventually be targets for future planet searches, and recently reached one million files uploaded by the community. In this paper we describe the updates to our data holdings, functionality, accessibility, and tools, as well as future priorities for these two services.

The NASA Great Observatories Maturation Program is a development plan to efficiently and effectively develop large, strategic astrophysics missions. Suborbital rocket and balloon programs have long been a key development tool for enabling large missions in NASA astrophysics. We review the significance of these suborbital missions in the preceding decades to demonstrate their contributions to the Great Observatories Maturation Program for the Habitable Worlds Observatory and beyond. We show that suborbital instruments have obtained new science observations of astrophysical sources across the electromagnetic spectrum, matured high-priority component technologies, and served as a training ground for principal investigators of Explorer-class astrophysics satellites. A brief discussion of emerging CubeSat and SmallSat missions and their place in the NASA astrophysics portfolio is also provided.

The NASA Lucy mission is scheduled to fly-by the main belt asteroid (52246) Donaldjohanson on April 20, 2025. Donaldjohanson (DJ hereafter) is a member of the primitive (C-type class) Erigone collisional asteroid family located in the inner main belt in proximity of the source regions of asteroid (101955)~Bennu and (162173)~Ryugu, visited respectively by OSIRIS-REx and Hayabusa2 missions. In this paper we provide an updated model for the Erigone family age, and discuss DJ evolution resulting from non-gravitational forces (namely Yarkovsky and YORP), as well as its collisional evolution. We conclude the best-fit family age to be $\sim 155$~Myr, and that, on such timescales, both Yarkovsky and YORP effects may have affected the orbit and spin properties of DJ. Furthermore, we discuss how the NASA Lucy mission could provide independent insights on such processes, namely by constraining DJ shape, surface geology and cratering history.

Microgravity induces profound metabolic adaptations in mammalian physiology, yet the molecular mechanisms governing thermogenesis in female white adipose tissue (WAT) remain poorly characterized. This paper presents the first machine learning (ML) analysis of NASA Open Science Data Repository (OSDR) dataset OSD-970, derived from the Rodent Research-1 (RR-1) mission. Using RT-qPCR data from 89 adipogenesis and thermogenesis pathway genes in gonadal WAT of 16 female C57BL/6J mice (8 flight, 8 ground control) following 37 days aboard the International Space Station (ISS), we applied differential expression analysis, multiple ML classifiers with Leave-One-Out Cross-Validation (LOO-CV), and Explainable AI via SHapley Additive exPlanations (SHAP). The most striking finding is a dramatic 12.21-fold upregulation of Ucp1 (Delta-Delta-Ct = -3.61, p = 0.0167) in microgravity-exposed WAT, accompanied by significant activation of the thermogenesis pathway (mean pathway fold-change = 3.24). The best-performing model (Random Forest with top-20 features) achieved AUC = 0.922, Accuracy = 0.812, and F1 = 0.824 via LOO-CV. SHAP analysis consistently ranked Ucp1 among the top predictive features, whil

One of the most practical, and sought after, applications of quantum mechanics in the field of information science is the use of entanglement distribution to communicate quantum information effectively. Similar to the continued improvements of functional quantum computers over the past decade, advances in demonstrations of entanglement distribution over long distances may enable new applications in aeronautics and space communications. The existing NASA Quantum Communications Analysis Suite (NQCAS) software models such applications, but limited experimental data exists to verify the model's theoretical results. There is, however, a large body of experimental data in the relevant literature for entanglement-based quantum key distribution (QKD). This paper details a Monte Carlo-based QKD model that uses NQCAS input parameters to generate an estimated QKD link budget for verification of NQCAS. The model generates link budget statistics like key rates, error rates, and S values that can then be compared to the experimental values in the literature. Preliminary comparisons show many similarities between the simulated and experimental data, supporting the model's validity. A verified NQC

Open-source Large Language Models enable projects such as NASA SciX (i.e., NASA ADS) to think out of the box and try alternative approaches for information retrieval and data augmentation, while respecting data copyright and users' privacy. However, when large language models are directly prompted with questions without any context, they are prone to hallucination. At NASA SciX we have developed an experiment where we created semantic vectors for our large collection of abstracts and full-text content, and we designed a prompt system to ask questions using contextual chunks from our system. Based on a non-systematic human evaluation, the experiment shows a lower degree of hallucination and better responses when using Retrieval Augmented Generation. Further exploration is required to design new features and data augmentation processes at NASA SciX that leverages this technology while respecting the high level of trust and quality that the project holds.

In line with the Astro2020 Decadal Report State of the Profession findings and the NASA core value of Inclusion, the NASA Science Mission Directorate (SMD) Bridge Program was created to provide financial and programmatic support to efforts that work to increase the representation and inclusion of students from under-represented minorities in the STEM fields. To ensure an effective program, particularly for those who are often left out of these conversations, the NASA SMD Bridge Program Workshop was developed as a way to gather feedback from a diverse group of people about their unique needs and interests. The Early Career Perspectives Working Group was tasked with examining the current state of bridge programs, academia in general, and its effect on students and early career professionals. The working group, comprised of 10 early career and student members, analyzed the discussions and responses from workshop breakout sessions and two surveys, as well as their own experiences, to develop specific recommendations and metrics for implementing a successful and supportive bridge program. In this white paper, we will discuss the key themes that arose through our work, and highlight sele

Historically, astronomy has prioritized visuals to present information, with scientists and communicators overlooking the critical need to communicate astrophysics with blind or low-vision audiences and provide novel channels for sighted audiences to process scientific information. This study sonified NASA data of three astronomical objects presented as aural visualizations, then surveyed blind or low-vision and sighted individuals to elicit feedback on the experience of these pieces as it relates to enjoyment, education, and trust of the scientific data. Data analyses from 3,184 sighted or blind or low-vision survey participants yielded significant self-reported learning gains and positive experiential responses. Results showed that astrophysical data engaging multiple senses could establish additional avenues of trust, increase access, and promote awareness of accessibility in sighted and blind or low-vision communities.

The Astro 2020 Decadal Survey "Pathways to Discovery in Astronomy and Astrophysics for the 2020s" has recommended that "after a successful mission and technology maturation program, NASA should embark on a program to realize a mission to search for biosignatures from a robust number of about ~25 habitable zone planets and to be a transformative facility for general astrophysics," and prescribing that the high-contrast direct imaging mission would have "a target off-axis inscribed diameter of approximately 6 meters." The Decadal Survey assumed an exo-Earth frequency of ~25%, requiring that approximately 100 cumulative habitable zones of nearby stars should be surveyed. Surveying the nearby bright stars, and taking into account inputs from the LUVOIR and HabEx mission studies (but without being overly prescriptive in the required starlight suppression technology or requirements), we compile a list of 164 stars whose exo-Earths would be the most accessible for a systematic imaging survey of habitable zones with a 6-m-class space telescope in terms of angular separation, planet brightness in reflected light, and planet-star brightness ratio. We compile this star list to motivate observ

Multiplication is arguably the most cost-dominant operation in modern deep neural networks (DNNs), limiting their achievable efficiency and thus more extensive deployment in resource-constrained applications. To tackle this limitation, pioneering works have developed handcrafted multiplication-free DNNs, which require expert knowledge and time-consuming manual iteration, calling for fast development tools. To this end, we propose a Neural Architecture Search and Acceleration framework dubbed NASA, which enables automated multiplication-reduced DNN development and integrates a dedicated multiplication-reduced accelerator for boosting DNNs' achievable efficiency. Specifically, NASA adopts neural architecture search (NAS) spaces that augment the state-of-the-art one with hardware-inspired multiplication-free operators, such as shift and adder, armed with a novel progressive pretrain strategy (PGP) together with customized training recipes to automatically search for optimal multiplication-reduced DNNs; On top of that, NASA further develops a dedicated accelerator, which advocates a chunk-based template and auto-mapper dedicated for NASA-NAS resulting DNNs to better leverage their algo

The size of the National Aeronautics and Space Administration (NASA) Science Mission Directorate (SMD) is growing exponentially, allowing researchers to make discoveries. However, making discoveries is challenging and time-consuming due to the size of the data catalogs, and as many concepts and data are indirectly connected. This paper proposes a pipeline to generate knowledge graphs (KGs) representing different NASA SMD domains. These KGs can be used as the basis for dataset search engines, saving researchers time and supporting them in finding new connections. We collected textual data and used several modern natural language processing (NLP) methods to create the nodes and the edges of the KGs. We explore the cross-domain connections, discuss our challenges, and provide future directions to inspire researchers working on similar challenges.

The Exoplanet Modeling and Analysis Center (EMAC) at NASA Goddard Space Flight Center is a web-based catalog, repository, and integration platform for modeling and analysis resources focused on the study of exoplanet characteristics and environments. EMAC hosts user-submitted resources ranging in category from planetary interior models to data visualization tools. Other features of EMAC include integrated web tools developed by the EMAC team in collaboration with the tools' original author(s) and video demonstrations of a growing number of hosted tools. EMAC aims to be a comprehensive repository for researchers to access a variety of exoplanet resources that can assist them in their work, and currently hosts a growing number of code bases, models, and tools. EMAC is a key project of the NASA GSFC Sellers Exoplanet Environments Collaboration (SEEC) and can be accessed at https://emac.gsfc.nasa.gov.

The purpose of the 2010 NASA Laboratory Astrophysics Workshop (LAW) was, as given in the Charter from NASA, "to provide a forum within which the scientific community can review the current state of knowledge in the field of Laboratory Astrophysics, assess the critical data needs of NASA's current and future Space Astrophysics missions, and identify the challenges and opportunities facing the field as we begin a new decade". LAW 2010 was the fourth in a roughly quadrennial series of such workshops sponsored by the Astrophysics Division of the NASA Science Mission Directorate. In this White Paper, we report the findings of the workshop.

* Aims. We describe here the main functionalities of the LAEX (Laboratorio de Astrofisica Estelar y Exoplanetas/Laboratory for Stellar Astrophysics and Exoplanets) and NASA portals for CoRoT Public Data. The CoRoT archive at LAEX was opened to the community in January 2009 and is managed in the framework of the Spanish Virtual Observatory. NStED (NASA Star and Exoplanet Database) serves as the CoRoT portal for the US astronomical community. NStED is a general purpose stellar and exoplanet archive with the aim of providing support for NASA planet finding and characterisation goals, and the planning and support of NASA and other space missions. CoRoT data at LAEX and NStED can be accessed at http://sdc.laeff.inta.es/corotfa/ and http://nsted.ipac.caltech.edu,respectively. * Methods. Based on considerable experience with astronomical archives, the aforementioned archives are designed with the aim of delivering science-quality data in a simple and efficient way. * Results. LAEX and NStED not only provide access to CoRoT Public Data but furthermore serve a variety of observed and calculated astrophysical data. In particular, NStED provides scientifically validated information on stellar

In an increasingly connected and networked world, the National Aeronautics and Space Administration (NASA) recognizes the value of the public as a strategic partner in addressing some of our most pressing challenges. The agency is working to more effectively harness the expertise, ingenuity, and creativity of individual members of the public by enabling, accelerating, and scaling the use of open innovation approaches including prizes, challenges, and crowdsourcing. As NASA's use of open innovation tools to solve a variety of types of problems and advance of number of outcomes continues to grow, challenge design is also becoming more sophisticated as our expertise and capacity (personnel, platforms, and partners) grows and develops. NASA has recently pivoted from talking about the benefits of challenge-driven approaches, to the outcomes these types of activities yield. Challenge design should be informed by desired outcomes that align with NASA's mission. This paper provides several case studies of NASA open innovation activities and maps the outcomes of those activities to a successful set of outcomes that challenges can help drive alongside traditional tools such as contracts, gra

We review some key issues pertaining to NASA's Research and Analysis programs, and offer recommended actions to mitigate or resolve these issues. In particular, we recommended that NASA increases funding to support a healthy selection rate (~40%) for R&A programs, which underpin much scientific discovery with NASA mission data, and on which the majority of the U.S. planetary science community relies (either in part or wholly). We also recommend additional actions NASA can take to ensure a more equitable and sustainable planetary science research community in the U.S., including supporting the next generations of planetary researchers, working to minimize biases in peer review, and reducing the burden of scientists as they prepare R&A proposals.

While there have been far fewer missions to the outer Solar System than to the inner Solar System, spacecraft destined for the giant planets have conducted a wide range of fundamental investigations, returning data that continues to reshape our understanding of these complex systems, sometimes decades after the data were acquired. These data are preserved and accessible from national and international planetary science archives. For all NASA planetary missions and instruments the data are available from the science discipline nodes of the NASA Planetary Data System (PDS). Looking ahead, the PDS will be the primary repository for giant planets data from several upcoming missions and derived datasets, as well as supporting research conducted to aid in the interpretation of the remotely sensed giant planets data already archived in the PDS.

NASA's new age of space exploration augurs great promise for deep space exploration missions whereby spacecraft should be independent, autonomous, and smart. Nowadays NASA increasingly relies on the concepts of autonomic computing, exploiting these to increase the survivability of remote missions, particularly when human tending is not feasible. Autonomic computing has been recognized as a promising approach to the development of self-managing spacecraft systems that employ onboard intelligence and rely less on control links. The Autonomic System Specification Language (ASSL) is a framework for formally specifying and generating autonomic systems. As part of long-term research targeted at the development of models for space exploration missions that rely on principles of autonomic computing, we have employed ASSL to develop formal models and generate functional prototypes for NASA missions. This helps to validate features and perform experiments through simulation. Here, we discuss our work on developing such missions with ASSL.