Complexity Heliophysics: A lived and living history of systems and complexity science in Heliophysics

In this piece we study complexity science in the context of Heliophysics, describing it not as a discipline, but as a paradigm. In the context of Heliophysics, complexity science is the study of a star, interplanetary environment, magnetosphere, upper and terrestrial atmospheres, and planetary surface as interacting subsystems. Complexity science studies entities in a system (e.g., electrons in an atom, planets in a solar system, individuals in a society) and their interactions, and is the nature of what emerges from these interactions. It is a paradigm that employs systems approaches and is inherently multi- and cross-scale. Heliophysics processes span at least 15 orders of magnitude in space and another 15 in time, and its reaches go well beyond our own solar system and Earth's space environment to touch planetary, exoplanetary, and astrophysical domains. It is an uncommon domain within which to explore complexity science. After first outlining the dimensions of complexity science, the review proceeds in three epochal parts: 1) A pivotal year in the Complexity Heliophysics paradigm: 1996; 2) The transitional years that established foundations of the paradigm (1996-2010); and 3) The emergent literature largely beyond 2010. This review article excavates the lived and living history of complexity science in Heliophysics. The intention is to provide inspiration, help researchers think more coherently about ideas of complexity science in Heliophysics, and guide future research. It will be instructive to Heliophysics researchers, but also to any reader interested in or hoping to advance the frontier of systems and complexity science

Linked Autonomous Interplanetary Satellite Orbit Navigation

A navigation technology known as LiAISON (Linked Autonomous Interplanetary Satellite Orbit Navigation) has been known to produce very impressive navigation results for scenarios involving two or more cooperative satellites near the Moon, such that at least one satellite must be in an orbit significantly perturbed by the Earth, such as a lunar halo orbit. The two (or more) satellites track each other using satellite-to-satellite range and/or range-rate measurements. These relative measurements yield absolute orbit navigation when one of the satellites is in a lunar halo orbit, or the like. The geometry between a lunar halo orbiter and a GEO satellite continuously changes, which dramatically improves the information content of a satellite-to-satellite tracking signal. The geometrical variations include significant out-of-plane shifts, as well as inplane shifts. Further, the GEO satellite is almost continuously in view of a lunar halo orbiter. High-fidelity simulations demonstrate that LiAISON technology improves the navigation of GEO orbiters by an order of magnitude, relative to standard ground tracking. If a GEO satellite is navigated using LiAISON- only tracking measurements, its position is typically known to better than 10 meters. If LiAISON measurements are combined with simple radiometric ground observations, then the satellite s position is typically known to better than 3 meters, which is substantially better than the current state of GEO navigation. There are two features of LiAISON that are novel and advantageous compared with conventional satellite navigation. First, ordinary satellite-to-satellite tracking data only provides relative navigation of each satellite. The novelty is the placement of one navigation satellite in an orbit that is significantly perturbed by both the Earth and the Moon. A navigation satellite can track other satellites elsewhere in the Earth-Moon system and acquire knowledge about both satellites absolute positions and velocities, as well as relative positions and velocities in space. The second novelty is that ordinarily one requires many satellites in order to achieve full navigation of any given customer s position and velocity over time. With LiAISON navigation, only a single navigation satellite is needed, provided that the satellite is significantly affected by the gravity of the Earth and the Moon. That single satellite can track another satellite elsewhere in the Earth- Moon system and obtain absolute knowledge of both satellites states

Complexity Heliophysics: A [New] System Science that Transcends the Previous Boundaries of our Field

Synopsis 1. The 21st century is the time of complexity. We delineate it and its importance as necessary to solve ‘wicked problems.’ 2. Inherently transdisciplinary, trans-scale, and interconnected to living systems, the solution to Heliophysics’ identity crisis and to unlock the next generation of scientific discovery may be to embrace complexity. 3. With the right foresight, direction, and incentive over the next ten years, Heliophysics can become a beacon for how all of society thinks about and does complexity science

Cultivating a culture of inclusivity in heliophysics

A large number of heliophysicists from across career levels, institution types, and job titles came together to support a poster at Heliophysics 2050 and the position papers for the 2024 Heliophysics decadal survey titled “Cultivating a Culture of Inclusivity in Heliophysics,” “The Importance of Policies: It’s not just a pipeline problem,” and “Mentorship within Heliophysics.” While writing these position papers, the number of people who privately shared disturbing stories and experiences of bullying and harassment was shocking. The number of people who privately expressed how burned out they were was staggering. The number of people who privately spoke about how they considered leaving the field for their and their family’s health was astounding. And for as much good there is in our community, it is still a toxic environment for many. If we fail to do something now, our field will continue to suffer. While acknowledging the ongoing growth that we as individuals must work toward, we call on our colleagues to join us in working on organizational, group, and personal levels toward a truly inclusive culture, for the wellbeing of our colleagues and the success of our field. This work includes policies, processes, and commitments to promote: accountability for bad actors; financial security through removing the constant anxiety about funding; prioritization of mental health and community through removing constant deadlines and constant last-minute requests; a collaborative culture rather than a hyper-competitive one; and a community where people can thrive as whole persons and do not have to give up a healthy or well-rounded life to succeed

Space Weather research in the Digital Age and across the full data lifecycle: Introduction to the Topical Issue

The onset and rapid advance of the Digital Age have brought challenges and opportunities for scientific research characterized by a continuously evolving data landscape reflected in the four V’s of big data: volume, variety, veracity, and velocity. The big data landscape supersedes traditional means of storage, processing, management, and exploration, and requires adaptation and innovation across the full data lifecycle (i.e., collection, storage and processing, analytics, and representation). The Topical Issue, “Space Weather research in the Digital Age and across the full data lifecycle”, collects research from across the full data lifecycle (collection, management, analysis, and communication; collectively “Data Science”) and offers a tractable compendium that illustrates the latest computational and data science trends, tools, and advances for Space Weather research. We introduce the paradigm shift in Space Weather and the articles in the Topical Issue. We create a network view of the research that highlights the contribution to the change of paradigm and reveals the trends that will guide it hereafter

The cultural-social nucleus of an open community: A multi-level community knowledge graph and NASA application

The challenges faced by science, engineering, and society are increasingly complex, requiring broad, cross-disciplinary teams to contribute to collective knowledge, cooperation, and sensemaking efforts. However, existing approaches to collaboration and knowledge sharing are largely manual, inadequate to meet the needs of teams that are not closely connected through personal ties or which lack the time to respond to dynamic requests for contextual information sharing. Nonetheless, in the current remote-first, complexity-driven, time-constrained workplace, such teams are both more common and more necessary. For example, the NASA Center for HelioAnalytics (CfHA) is a growing and cross-disciplinary community that is dedicated to aiding the application of emerging data science techniques and technologies, including AI/ML, to increase the speed, rigor, and depth of space physics scientific discovery. The members of that community possess innumerable skills and competencies and are involved in hundreds of projects, including proposals, committees, papers, presentations, conferences, groups, and missions. Traditional structures for information and knowledge representation do not permit the community to search and discover activities that are ongoing across the Center, nor to understand where skills and knowledge exist. The approaches that do exist are burdensome and result in inefficient use of resources, reinvention of solutions, and missed important connections. The challenge faced by the CfHA is a common one across modern groups and one that must be solved if we are to respond to the grand challenges that face our society, such as complex scientific phenomena, global pandemics and climate change. We present a solution to the problem: a community knowledge graph (KG) that aids an organization to better understand the resources (people, capabilities, affiliations, assets, content, data, models) available across its membership base, and thus supports a more cohesive community and more capable teams, enables robust and responsible application of new technologies, and provides the foundation for all members of the community to co-evolve the shared information space. We call this the Community Action and Understanding via Semantic Enrichment (CAUSE) ontology. We demonstrate the efficacy of KGs that can be instantiated from the ontology together with data from a given community (shown here for the CfHA). Finally, we discuss the implications, including the importance of the community KG for open science

Navigation Between Geosynchronous and Lunar L1 Orbiters

Linked Autonomous Interplanetary Satellite Orbit Navigation (LiAISON) is a new technique that takes advantage of the asymmetrical gravity field present in a three-body system in order to perform absolute tracking of satellites using only relative satellite-to-satellite observations. Previous studies have demonstrated LiAISON's practical applications for lunar missions, including a satellite in a halo orbit about either the Earth-Moon L1 or L2 point. This paper studies the viability of applying LiAISON measurements between a lunar halo orbiter and a satellite in a geosynchronous orbit. Simulations demonstrate that the absolute positions and velocities of both satellites are observable using only relative measurements with an achieved uncertainty on the order of observation noise

Liaison-Supplemented Navigation for Geosynchronous and Lunar L1 Orbiters

No abstract availabl

Supporting Crewed Lunar Exploration with LiAISON Navigation

This paper examines the benefits of navigating a crewed vehicle between the Earth and the Moon using both ground tracking and satellite-to-satellite tracking. Linked Autonomous Interplanetary Satellite Orbit Navigation (LiAISON) is a new technique that has been shown to dramatically improve the navigation of lunar satellites, libration orbiters, and Earth orbiting satellites using scalar intersatellite observations. In this paper, LiAISON is applied to the problem of navigating a crewed vehicle to the Moon. It has been found that LiAISON observations improve the navigation accuracy enough to reduce the number of active ground tracking stations from six to three