Scientific Return Research Articles

Lucy Mission to the Trojan Asteroids: Instrumentation and Encounter Concept of Operations

Abstract The Lucy Mission accomplishes its science during a series of five flyby encounters with seven Trojan asteroid targets. This mission architecture drives a concept of operations design that maximizes science return, provides redundancy in observations where possible, features autonomous fault protection, and utilizes onboard target tracking near closest approach. These design considerations reduce risk during the relatively short time-critical periods when science data is collected. The payload suite consists of a color camera and infrared imaging spectrometer, a high-resolution panchromatic imager, and a thermal infrared spectrometer. The mission design allows for concurrent observations of all instruments. Additionally, two spacecraft subsystems will also contribute to the science investigations: the Terminal Tracking Cameras will obtain wide field-of-view imaging near closest approach to determine the shape of each of the Trojan targets and the telecommunication subsystem will carry out Doppler tracking of the spacecraft to determine the mass of each of the Trojan targets.

A Comprehensive Approach to On-board Autonomy Verification and Validation

Deep space missions are characterized by severely constrained communication links. To meet the needs of future missions and increase their scientific return, future space systems will require an increased level of autonomy on-board. In this work, we propose a comprehensive approach to on-board autonomy. We rely on model-based reasoning, and we consider many important (on-line and off-line) reasoning capabilities such as plan generation, validation, execution and monitoring, runtime diagnosis, and fault detection, identification, and recovery. The controlled platform is represented symbolically, and the reasoning capabilities are seen as symbolic manipulation of such formal model. We have developed a prototype of our framework, and we have integrated it within an on-board Autonomous Reasoning Engine. Finally, we have evaluated our approach on three case-studies inspired by real-world projects and characterized it in terms of reliability, availability, and performance.

Assessing the readiness of numerical relativity for LISA and 3G detectors

Future detectors such as LISA promise signal-to-noise ratios potentially in the thousands and data containing simultaneous signals. Accurate numerical relativity waveforms will be essential to maximize the science return. A question of interest to the broad gravitational wave community is: Are the numerical relativity codes ready to face this challenge? Towards answering this question, we provide a new criteria to identify the minimum resolution a simulation must have as a function of signal-to-noise ratio in order for the numerical relativity waveform to be indistinguishable from a true signal. This criteria can be applied to any finite-differencing numerical relativity code with multiple simulations of differing resolutions for the desired binary parameters and waveform length. We apply this criteria to binary systems of interest with the fourth-order MAYA code to obtain the first estimate of the minimum resolution a simulation must have to be prepared for next generation detectors.

Astronomaly: Personalised active anomaly detection in astronomical data

Survey telescopes such as the Vera C. Rubin Observatory and the Square Kilometre Array will discover billions of static and dynamic astronomical sources. Properly mined, these enormous datasets will likely be wellsprings of rare or unknown astrophysical phenomena. The challenge is that the datasets are so large that most data will never be seen by human eyes; currently the most robust instrument we have to detect relevant anomalies. Machine learning is a useful tool for anomaly detection in this regime. However, it struggles to distinguish between interesting anomalies and irrelevant data such as instrumental artefacts or rare astronomical sources that are simply not of interest to a particular scientist. Active learning combines the flexibility and intuition of the human brain with the raw processing power of machine learning. By strategically choosing specific objects for expert labelling, it minimises the amount of data that scientists have to look through while maximising potential scientific return. Here we introduce Astronomaly: a general anomaly detection framework with a novel active learning approach designed to provide personalised recommendations. Astronomaly can operate on most types of astronomical data, including images, light curves and spectra. We use the Galaxy Zoo dataset to demonstrate the effectiveness of Astronomaly, as well as simulated data to thoroughly test our new active learning approach. We find that for both datasets, Astronomaly roughly doubles the number of interesting anomalies found in the first 100 objects viewed by the user. Astronomaly is easily extendable to include new feature extraction techniques, anomaly detection algorithms and even different active learning approaches. The code is publicly available at https://github.com/MichelleLochner/astronomaly.

HInet: Generating Neutral Hydrogen from Dark Matter with Neural Networks

Abstract Upcoming 21 cm surveys will map the spatial distribution of cosmic neutral hydrogen (Hi) over very large cosmological volumes. In order to maximize the scientific return of these surveys, accurate theoretical predictions are needed. Hydrodynamic simulations currently are the most accurate tool to provide those predictions in the mildly to nonlinear regime. Unfortunately, their computational cost is very high: tens of millions of CPU hours. We use convolutional neural networks to find the mapping between the spatial distribution of matter from N-body simulations and Hi from the state-of-the-art hydrodynamic simulation IllustrisTNG. Our model performs better than the widely used theoretical model: halo occupation distribution for all statistical properties up to the nonlinear scales k ≲ 1 h Mpc−1. Our method allows the generation of 21 cm mocks over very big cosmological volumes with similar properties to hydrodynamic simulations.

Cosmology with the Roman Space Telescope – multiprobe strategies

ABSTRACT We simulate the scientific performance of the Nancy Grace Roman Space Telescope High Latitude Survey (HLS) on dark energy and modified gravity. The 1.6-yr HLS Reference survey is currently envisioned to image 2000 deg2 in multiple bands to a depth of ∼26.5 in Y, J, H and to cover the same area with slit-less spectroscopy beyond z = 3. The combination of deep, multiband photometry and deep spectroscopy will allow scientists to measure the growth and geometry of the Universe through a variety of cosmological probes (e.g. weak lensing, galaxy clusters, galaxy clustering, BAO, Type Ia supernova) and, equally, it will allow an exquisite control of observational and astrophysical systematic effects. In this paper, we explore multiprobe strategies that can be implemented, given the telescope’s instrument capabilities. We model cosmological probes individually and jointly and account for correlated systematics and statistical uncertainties due to the higher order moments of the density field. We explore different levels of observational systematics for the HLS survey (photo-z and shear calibration) and ultimately run a joint likelihood analysis in N-dim parameter space. We find that the HLS reference survey alone can achieve a standard dark energy FoM of >300 when including all probes. This assumes no information from external data sets, we assume a flat universe however, and includes realistic assumptions for systematics. Our study of the HLS reference survey should be seen as part of a future community-driven effort to simulate and optimize the science return of the Roman Space Telescope.

Next frontier in planetary geological reconnaissance: Low-latency telepresence

The most compelling questions about the possibility of life on other planetary bodies will likely be answered only once the human mind can fully engage with the explored alien surface. Current interplanetary science operation models are primarily based on the paradigm of using robotic off-Earth assets for exploration. Conducting field geology research on other planetary bodies requires experts to use data collected from advanced technologies to substitute for their on-site presence to overcome the time delay (e.g., latency) and bandwidth constraints in the transfer of data. To overcome these constraints, astronauts will need to be placed either directly on the surface (e.g., “boots on the ground”) or robotic systems will need to be deployed and directed by humans from Earth with massive time delays. In the next major stage of planetary reconnaissance, as presented here, deployment of teleoperated robotic assets with humans sufficiently proximal to the exploration targets (referred to here as “Low-Latency Telepresence (LLT)”) will greatly enhance scientific return. Humans in orbit can be present electronically/digitally at multiple sites on a planetary surface, and that presence can be sterile, alleviating planetary protection concerns. Crewed astronauts using LLT, in partnership with robotic agents on the surface, will provide scientists the means to explore, for example, the mountains and vast canyon systems on Mars and the submarine environment of Jupiter's moon Europa. Consequently, because LLT does not require humans to be physically present at the exploration site, it is potentially advantageous in terms of schedule and cost, reduces human and planetary risks, while increasing the quantity and quality of the science data that can be returned.

Characterization of the Candidate Landing Region for Tianwen‐1—China's First Mission to Mars

AbstractThis paper presents our efforts to characterize the candidate landing region (109°–133°E, 23°–30°N) for Tianwen‐1, China's first mission to Mars, in terms of engineering safety and scientific significance. Topographic analysis reveals that the region has a low elevation around −4,230 m, and 98% of the region have slopes smaller than 8°. The geomorphological mapping and analysis show that the region has an average crater density of about 28 craters (≥200 m in diameter) per 100 square kilometers, with several clusters of high crater densities distributed around the center of the region. There are also pitted cones distributed mainly in the southern part of the region, with a density of approximately 6.6 cones per 100 square kilometers in specific local areas. The region has rock abundances ranging from 1% to 23%, with local clusters of low and high rock abundances. The region comprises four main geological units, including a lowland unit formed in the Late Hesperian and a volcanic unit formed in the Amazonian and Hesperian period. Their specific surface ages are estimated through the analysis of crater size‐frequency distribution. Combining the engineering constraints on surface slopes, crater density, cone density, and rock abundance, a hazard map of the candidate landing region is generated for landing site evaluation and safety assessment. Based on the results, we further discuss the potential scientific outcomes from the exploration in this region. The findings will be helpful for the mission planning and maximization of the scientific return from Tianwen‐1, and complement existing Martian scientific research.

Terminus: A Versatile Simulator for Space-based Telescopes

Abstract Space-based telescopes offer unparalleled opportunities for characterizing exoplanets, solar system bodies, and stellar objects. However, observatories in low-Earth orbits (e.g., Hubble, CHaracterising ExOPlanets Satellite, Twinkle, and an ever-increasing number of cubesats) cannot always be continuously pointed at a target due to Earth obscuration. For exoplanet observations consisting of transit, or eclipse, spectroscopy, this causes gaps in the light curve, which reduces the information content and can diminish the science return of the observation. Terminus, a time-domain simulator, has been developed to model the occurrence of these gaps to predict the potential impact on future observations. The simulator is capable of radiometrically modeling exoplanet observations as well as producing light curves and spectra. Here, Terminus is baselined on the Twinkle mission, but the model can be adapted for any space-based telescope and is especially applicable to those in a low-Earth orbit. Terminus also has the capability to model observations of other targets such as asteroids or brown dwarfs.

Influence of the nano-grain depletion in photon-dominated regions

Context. The large disparity in physical conditions from the diffuse interstellar medium (ISM) to denser clouds such as photon-dominated regions (PDRs) triggers an evolution of the dust properties (i.e. composition, size, and shape). The gas physics and chemistry are tightly connected to these dust properties and are therefore affected by dust evolution and especially the nano-grain depletion in the outer irradiated part of PDRs. Aims. We highlight the influence of nano-grain depletion on the gas physics and chemistry in the Horsehead nebula, a prototypical PDR. Methods. We used a model for atomic and molecular gas in PDRs, the Meudon PDR code, using diffuse ISM-like dust and Horsehead-like dust to study the influence of nano-grain depletion on the gas physics and chemistry, focusing on the impact on photoelectric heating and H2 formation and, therefore, on the H2 gas lines. Results. We find that nano-grain depletion in the Horsehead strongly affects gas heating through the photoelectric effect and thus the gas temperature and the H2 formation, hence the H → H2 position. Consequently, the first four pure rotational lines of H2 (e.g. 0–0 S(0), S(1), S(2), and S(3)) vary by a factor of 2 to 14. The 0–0 S(3) line that is often underestimated in models is underestimated even more when taking nano-grain depletion into account due to the decrease in gas heating through the photoelectric effect. This strongly suggests that our understanding of the excitation of H2 and/or of heating processes in the Horsehead, and more generally in PDRs, is still incomplete. Conclusions. Nano-grain depletion in the outer part of the Horsehead has a strong influence on several gas tracers that will be prominent in JWST observations of irradiated clouds. We therefore need to take this depletion into account in order to improve our understanding of the Horsehead, and more generally PDRs, and to contribute to the optimal scientific return of the mission.

The Ariel ground segment and instrument operations science data centre

The ground segment for the ESA M4 Ariel exoplanet space mission is introduced. The ground segment encompasses the framework necessary to support the development of the Ariel mission to launch, in-flight operations and calibration, data processing pipeline and data handling, including user support. The structure of the ground segment and assumed responsibilities between ESA and the Ariel mission consortium is explained, along with their interfaces. The operational phases for the mission are introduced, including the early commissioning/verification phases, the science operations and the calibration strategy. The smooth transition of the ground segment through the various pre/post launch mission phases to nominal operations will be paramount in guaranteeing the success, scientific return and impact of the Ariel mission. The expected science data products are defined and a representative data processing pipeline is presented.

Compression algorithms for high-data-volume instruments on planetary missions: a case study for the Cassini mission

We investigated data compression algorithms to boost science data return from high-data-volume instruments on planetary missions, particularly outer solar system missions where every bit of data represents an engineering triumph of over severe constraints on mass (limiting antenna size) and power (limiting signal strength). We developed a methodology to (1) investigate algorithms to improve compression and (2) to work with the science teams to evaluate the effects on the science. Our algorithm for compressing the Cassini Radio Plasma Wave Science (RPWS) data achieved a factor of 5 improvement in data compression (relative to what the RPWS team was using), and our algorithm for the Cassini Ultraviolet Imaging Spectrograph (UVIS) Saturn data set achieved a much higher factor (∼70). In both cases, the investigators on the science teams who evaluated our results reported that the science goals were not compromised. Our compression algorithm for Imaging Science Subsystem images achieved on average a factor of ∼1.7 improvement in lossless compression compared to the original algorithm. We also evaluated the compression effectiveness of JPL’s Fast Lossless EXtended (FLEX) hyperspectral/multispectral image compressor on Cassini’s Visible and Infrared Mapping Spectrometer data. FLEX lossless compression provides a factor of 2 improvement over the original compression. We also explore a different range of lossy compression, which can achieve an additional factor 2 to 5 depending on the fidelity required. Our findings have implications for the design of future space missions, particularly with respect to antenna size and overall size, weight, and power budgets, by demonstrating strategies to implement better data compression. In addition to improved algorithms, we show that an iterative process involving real-time science team evaluation and feedback to update the onboard compression algorithm is both essential and feasible. We make the case that a spacecraft facility compressor hosting a toolbox of compression algorithms, available to all of the science instruments and supported by a team of compression experts, convey significant benefits. Beyond the obvious benefits of increased science return and faster playback, better data compression enables design trades between antenna size and number of science instruments on the payload.

Identifying and Analyzing Astronomers' Preferences for the Next Decade of NASA

The aim of this research is to survey preferences in the astronomy and astrophysics community as they relate to the next decade of NASA. Preferences are key for understanding how decisions are made by individuals that could aid in projecting community preferences and likely outcomes. The study was performed using a survey methodology and evaluated preferences regarding the decadal survey by prioritizing space-based astrophysics missions and research activities. Thematic analysis was implemented to determine themes within participants' open survey responses. Our results show strong community preferences for observational astronomy and science versatility, capability, and scientific return for the upcoming decadal period. Moreover, our findings also show consensus among subgroups in the community. We elaborate on community preferences by presenting results on mission concepts, mission capabilities, and primary science that NASA should strategically invest in.

Automated Multi-Dataset Analysis (AMDA): An on-line database and analysis tool for heliospheric and planetary plasma data

Accessing, visualizing and analyzing heterogeneous plasma datasets has always been a tedious task that hindered students and senior researchers as well. Offering user friendly and versatile tools to perform basic research tasks is therefore pivotal for data centres including the Centre de Données de la Physique des Plasmas (CDPP http://www.cdpp.eu/) which holds a large variety of plasma data from various Earth, planetary and heliophysics missions and observatories in plasma physics. This clearly helps gaining increased attention, relevant feedback, and enhanced science return on data. These are the key ideas that crystallized at CDPP more than 15 years ago and resulted in the lay-out of the concepts, and then development, of AMDA, the Automated Multi-Dataset Analysis software (http://amda.cdpp.eu/). This paper gives a description of the architecture of AMDA, describes its functionalities, presents some use cases taken from the literature or fruitful collaborations and shows how it offers unique capabilities for educational purposes.

Multiprobe Mission Architecture Options for a Uranus Flagship Mission

In situ atmospheric measurements are a high priority for any future Flagship mission to the Ice Giants; however, most current mission concepts only include a single atmospheric entry probe in their designs. To maximize science returns and provide redundancy at a marginal cost, different mission architecture options are explored to deliver multiple atmospheric probes to Uranus. A methodology is developed for the consistent and generalized design of each architecture, integrating interplanetary trajectories, science orbits, probe entry and descent trajectories, telecommunication and data transfer performances, and to a certain extent, risks. A baseline single-probe mission is first designed using this methodology. Then, different architecture options to add a small secondary probe to this baseline mission are explored one by one and compared with each other and the original baseline mission. During the design of these different architectures, it is found that operational conflicts and data transmission capabilities are key drivers for the mission design and render some configurations infeasible. Comparisons are then made on the impact to the baseline single-probe mission, and it is determined that an additional 30 kg probe can be delivered to Uranus for a total mass penalty of under 100 kg. The dependence of probe mission design on the selection of interplanetary trajectory is also explored and is shown to have a significant impact on the design of the mission and its potential for success.

Understanding the Lunar Nearside–Farside Dichotomy via In Situ Trace Element Measurements: The Scientific Framework of a Prospective Landed Mission

Abstract Trace elements, distinguished by their low abundances (parts per million by weight (ppmw)), track local, regional, and planetary-scale processes in samples sourced from throughout the solar system. Such analyses of lunar samples have provided insights on its surface rocks and interpretations of its deep interior. However, returned samples, sourced from the lunar nearside, cannot be used to address processes responsible for the morphological dichotomy between the lunar nearside and farside. The hemispherical dichotomy points to distinct evolutionary histories of these two domains, rendering our understanding of lunar history incomplete. We outline the scientific justification for a landed, in situ investigation of lunar farside lithologies, focusing on chemical analyses that will constrain the Moon’s bi-hemispherical chemical evolution. Newly developed and heritage spaceflight instruments, capable of measuring low element abundances (limits of detection <10 ppmw ± 20%), can be deployed on the lunar farside and provide constraints on (1) the temperature and pressure of mare basalt crystallization, (2) depth-dependent mineralogical and compositional changes in the lunar mantle, (3) the chronology of major geologic events, and (4) abundances and distributions of refractory and heat-producing elements of the lunar farside mantle. The science return and logistical challenges of targeting four specific landing sites on the lunar farside are identified: Moscoviense, Apollo, Von Kármán, and Leibnitz craters. These sites maximize impact melt basin lithologies and later mare magmatism, and they minimize terrain hazards.

Evidence for SO2 latitudinal variations below the clouds of Venus

Context. Sulphur dioxide (SO2) is highly variable above the clouds of Venus, yet no spatial or temporal variability below the clouds had been known until now. Aims. In order to constrain Venus’s atmospheric circulation and chemistry (including possible volcanic outgassing), more accurate SO2 measurements below the clouds are therefore needed. Methods. We used the high-resolution iSHELL spectrometer located at the NASA IRTF to record thermal night-side spectra, which we fitted using an updated forward radiative transfer model that was previously employed to process SpeX/IRTF and VIRTIS-H/Venus Express spectra. Results. We report, for the first time, an increase in SO2 with increasing latitude (+30% between the minimum near 15°S and > 35°N). This is consistent with the interaction between the Hadley-cell circulation and a postulated vertical profile in SO2 estimated to increase between 30 and 40 km in altitude, as previously suggested by in situ ISAV measurements. Conclusions. This SO2 variability challenges our current understanding of Venus’s tropospheric thermochemistry and underlines the high scientific return from high-resolution spectroscopy from, for example, future orbiters.

The Enceladus Orbilander Mission Concept: Balancing Return and Resources in the Search for Life

Abstract Enceladus’s long-lived plume of ice grains and water vapor makes accessing oceanic material readily achievable from orbit (around Saturn or Enceladus) and from the moon’s surface. In preparation for the National Academies of Sciences, Engineering and Medicine 2023–2032 Planetary Science and Astrobiology Decadal Survey, we investigated four architectures capable of collecting and analyzing plume material from orbit and/or on the surface to address the most pressing questions at Enceladus: Is the subsurface ocean inhabited? Why, or why not? Trades specific to these four architectures were studied to allow an evaluation of the science return with respect to investment. The team found that Orbilander, a mission concept that would first orbit and then land on Enceladus, represented the best balance. Orbilander was thus studied at a higher fidelity, including a more detailed science operations plan during both orbital and landed phases, landing site characterization and selection analyses, and landing procedures. The Orbilander mission concept demonstrates that scientifically compelling but resource-conscious Flagship-class missions can be executed in the next decade to search for life at Enceladus.

Enabling Deep Space Science Missions with Nuclear Thermal Propulsion

Nuclear thermal propulsion (NTP) enables entirely new classes of deep-space science missions to yield scientific returns that, in most cases, are simply not possible with traditional architectures. NTP systems can yield dramatically reduced interplanetary travel times, deliver roughly 2- 3 times (or more) the mass that can be delivered by conventional chemical propulsion systems, or provide a combination of these advantages to further enhance scientific return. Present NASA and DoD-sponsored plans for NTP systems will mature the technology using prototype and flight demonstration engines to prove the designs. These prototype engines will have performance in the correct thrust range so as to permit use as a low-risk propulsion stage in support of high-payoff deep space science missions. Additionally, the use of low-enriched Uranium (LEU) fuels over highly-enriched Uranium (HEU) fuels reduce the costs of engine development, qualification, acceptance and launch, and lowers the risks associated with proliferation management.

Science Return from In Situ Probes in the Atmospheres of the Ice Giants

Science Return from In Situ Probes in the Atmospheres of the Ice Giants