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NASA NTRSDate not supplied

Statistical Classification of Biosignature Information using Multiple Instrument Observations

The accurate identification of biosignatures (indications of life) from data taken from remote or in situ planetary exploration is one of the most important challenges in astrobiology, the interdisciplinary field examining habitability and the potential for extraterrestrial life. This study employs machine learning algorithms to optimize the identification of biosignatures, with an emphasis on those which are agnostic to a specific biochemical basis. We exploit the wealth of terrestrial data available from biogenic and abiogenic systems to enhance efficient feature prioritization. Our dataset, pulled from public databases and laboratory recorded measurements, includes elemental abundance, isotopic fractionation, and VNIR/Raman spectra The data curation process included standardization for detection limits and ranges. Subsequent feature extraction yielded detailed inputs for machine learning, including combinations of elemental content, isotopic ratios, and parameters of spectral peaks and troughs. Feature significance was evaluated across diverse machine learning methodologies, such as k-nearest neighbors, logistic regression, Random Forest, support vector machines, and Gaussian Naïve Bayes, along with a combined voting classifier. We utilized Receiver Operating Characteristic Area Under the Curve (ROC AUC) across 2,000 50% test-train splits as a robust metric of model performance. Results revealed a promising ROC AUC of 0.853 for the combined voting classifier. Removing elemental abundance data notably reduced model accuracy (13% decrease in AUC), highlighting its critical role in biosignature detection. Several other individual data features exhibited significance within their respective data types, offering additional granularity. This research fortifies the relevance of machine learning to astrobiology, potentially enhancing life detection missions by allowing algorithmic prioritization of high-interest samples for further investigation. Future work will refine data standardization, expand the dataset to include more terrestrial systems, and incorporate convolutional neural networks for spectral feature extraction. The potential for public data sharing is also under exploration, reinforcing our commitment to collective scientific advancement.

Statistical↗
NASA NTRS2006

The Space Physics of Life: Searching for Biosignatures on Habitable Icy Worlds Affected by Space Weathering

Accessible surfaces of the most likely astrobiological habitats (Mars, Europa, Titan) in the solar system beyond Earth are exposed to various chemical and hydrologic weathering processes directly or indirectly induced by interaction with the overlying space environment. These processes can be both beneficial, through provision of chemical compounds and energy, and destructive, through chemical dissociation or burial, to detectable presence of biosignatures. Orbital, suborbital, and surface platforms carrying astrobiological instrumentation must survive, and preferably exploit, space environment interactions to reach these habitats and search for evidence of life or its precursors. Experience from Mars suggests that any detection of biosignatures must be accompanied by characterization of the local chemical environment and energy sources including irradiation by solar ultraviolet photons and energetic particles from the space environment. Orbital and suborbital surveys of surface chemistry and astrobiological potential in the context of the space environment should precede targeted in-situ measurements to maximize probability of biosignature detection through site selection. The Space Physics of Life (SPOL) investigation has recently been proposed to the NASA Astrobiology Institute and is briefly described in this presentation. SPOL is the astrobiologically relevant study of the interactions and relationships of potentially? or previously inhabited, bodies of the solar system with the surrounding environments. This requires an interdisciplinary effort in space physics, planetary science, and radiation biology. The proposed investigation addresses the search for habitable environments, chemical resources to support life, and techniques for detection of organic and inorganic signs of life in the context of the space environment.

Cooper, John F.↗
NASA NTRS2018

Biosignature False Positives

In our search for life - whether within the earliest part of Earth's geologic record, on planets within our solar system such Mars, or especially for extrasolar planets - we must infer the presence of life from its impact on the local or global environment. These "biosignatures," often identified from the known influence of terrestrial organisms on the Earth's atmosphere and surface, could be misdiagnosed when we apply them to alien worlds. The so-called false positives may occur when another process or suite of processes masks or mimics a biosignature. Here, we examine several leading biosignatures, then introduce potential false positives for these signals, and finally discuss methods to discriminate between the two using current and future detection technologies. We conclude that it is the astrobiology community's responsibility to thoroughly exhaust all possibilities before we resort to "life" as an explanation.

Harman, Chester E.↗
NASA NTRS2019

The K Dwarf Advantage for Biosignatures on Directly Imaged Exoplanets

Oxygen and methane are considered to be the canonical biosignatures of modern Earth, and the simultaneous detection of these gases in a planetary atmosphere is an especially strong biosignature. However, these gases may be challenging to detect together in the planetary atmospheres because photochemical oxygen radicals destroy methane. Previous work has shown that the photochemical lifetime of methane in oxygenated atmospheres is longer around M dwarfs, but M dwarf planet habitability may be hindered by extreme stellar activity and evolution. Here, we use a 1D photochemical-climate model to show that K dwarf stars also offer a longer photochemical lifetime of methane in the presence of oxygen compared to G dwarfs. For example, we show that a planet orbiting a K6V star can support about an order of magnitude more methane in its atmosphere compared to an equivalent planet orbiting a G2V star. In the reflected-light spectra of worlds orbiting K dwarf stars, strong oxygen and methane features could be observed at visible and near-infrared wavelengths. Because K dwarfs are dimmer than G dwarfs, they offer a better planet-star contrast ratio, enhancing the signal-to-noise ratio (S/N) possible in a given observation. For instance, a 50 hr observation of a planet at 7 pc with a 15 m telescope yields S/N = 9.2 near 1 m for a planet orbiting a solar-type G2V star, and S/N = 20 for the same planet orbiting a K6V star. In particular, nearby mid-late K dwarfs such as 61 Cyg A/B, Epsilon Indi, Groombridge 1618, and HD 156026 may be excellent targets for future biosignature searches.

Arney, Giada N.↗
NASA NTRS2019

The K Dwarf Advantage for Biosignatures on Directly Imaged Exoplanets

Oxygen and methane are considered to be the canonical biosignatures of modern Earth, and the simultaneous detection of these gases in a planetary atmosphere is an especially strong biosignature. However, these gases may be challenging to detect together in the planetary atmospheres because photochemical oxygen radicals destroy methane. Previous work has shown that the photochemical lifetime of methane in oxygenated atmospheres is longer around M dwarfs, but M dwarf planet habitability may be hindered by extreme stellar activity and evolution. Here, we use a 1-D photochemical-climate model to show that K dwarf stars also offer a longer photochemical lifetime of methane in the presence of oxygen compared to G dwarfs. For example, we show that a planet orbiting a K6V star can support about an order of magnitude more methane in its atmosphere compared to an equivalent planet orbiting a G2V star. In the reflected light spectra of worlds orbiting K dwarf stars, strong oxygen and methane features could be observed at visible and near-infrared wavelengths. Because K dwarfs are dimmer than G dwarfs, they offer a better planet-star contrast ratio, enhancing the signal-to-noise (SNR) possible in a given observation. For instance, a 50 hour observation of a planet at 7 pc with a 15-m telescope yields SNR = 9.2 near 1 µm for a planet orbiting a solar-type G2V star, and SNR = 20 for the same planet orbiting a K6V star. In particular, nearby mid-late K dwarfs such as 61 Cyg A/B, Epsilon Indi, Groombridge 1618, and HD 156026 may be excellent targets for future biosignature searches.

Giada N Arney↗
NASA NTRSDate not supplied

The Search for Chiral Asymmetry as a Potential Biosignature in Samples from Mars

The search for evidence of extraterrestrial life in our solar system is currently guided by our understanding of terrestrial biology and its associated biosignatures. The observed homochirality in all life on Earth, that is, the predominance of “left-handed” or L-amino acids and “right-handed” or D-sugars, is a unique property of life that is crucial for molecular recognition, enzymatic function, information storage and structure and is thought to be a prerequisite for the origin or early evolution of life. Therefore, the detection of L- or D-enantiomeric excesses of chiral amino acids and sugars could be a powerful indicator of extant or extinct life on Mars or other habitable environments in our solar system. The exploration of habitable environments on Mars, including an assessment of the preservation potential for complex organics of either abiotic or biological origin, remains a key goal of both current and future Mars missions. Now with the unambiguous detection of indigenous organic matter in sedimentary rocks on Mars [1-3], NASA’s Curiosity rover has significantly advanced our understanding of the preservation of potential chemical biosignatures in the martian near surface. Although amino acids have not yet been identified by in situ measurements on Mars, if they were present, it is expected that amino acid hydrolysis and racemization would be very slow and any chiral or isotopic signatures from an extinct martian biota could be preserved for billions of years, given the extremely cold and dry surface conditions [4]. One of ESA’s Rosalind Franklin rover payload instruments called the Mars Organic Molecule Analyzer (MOMA) includes a wet chemistry package capable of measuring the enantiomeric ratios of any chiral amino acids present at part-per-million concentrations or higher [5]. The complexity and limited duration of spaceflight operations and the known analytical challenges associated with in situ extraction and characterization of trace reduced organic compounds in ancient rocks make it challenging to determine the origins of martian organic matter found to date. Coordinated state-of-the-art laboratory measurements of returned samples from Mars that include spatially resolved chemical, mineralogical, and isotopic studies and molecule-specific isotopic and enantiomeric measurements will be required to firmly establish whether the complex organic matter detected on Mars comes from biotic or abiotic sources. Ultimately, sample return may be our best chance of identifying chemical biosignatures from a past or present martian biota, if one ever existed on Mars. NASA’s Perseverance rover will collect dozens of surface sample cores for possible future return to Earth by NASA and ESA. Here we review our current knowledge of the distributions and enantiomeric and isotopic compositions of non-biological amino acids found in meteorites compared to terrestrial biochemistry and propose a set of measurement criteria that should be used to help establish the origin of any chiral asymmetry detected in samples from Mars [6].

Daniel P Glavin↗
NASA NTRS2021

Identifying Molecules as Biosignatures with Assembly Theory and Mass Spectrometry

The search for evidence of life elsewhere in the universe is hard because it is not obvious what signatures are unique to life. Here we postulate that complex molecules found in high abundance are universal biosignatures as they cannot form by chance. To explore this, we developed the first intrinsic measure of molecular complexity that can be experimentally determined, and this is based upon a new approach called assembly theory which gives the molecular assembly number (MA) of a given molecule. MA allows us to compare the intrinsic complexity of molecules using the minimum number of steps required to construct the molecular graph starting from basic objects, and a probabilistic model shows how the probability of any given molecule forming randomly drops dramatically as its MA increases. To map chemical space, we calculated the MA of ca. 2.5 million compounds, and collected data which showed the complexity of a molecule can be experimentally determined by using three independent techniques including infra-red spectroscopy, nuclear magnetic resonance, and by fragmentation in a mass spectrometer, and this data has an excellent corelation with the values predicted from our assembly theory. We then set out to see if this approach could allow us to identify molecular biosignatures with a set of diverse samples from around the world, outer space, and the laboratory including prebiotic soups. The results show that there is a non-living to living threshold in MA complexity and the higher the MA for a given molecule, the more likely that it had to be produced by a biological process. This work demonstrates it is possible to use this approach to build a life detection instrument that could be deployed on missions to extra-terrestrial locations to detect biosignatures, map the extent of life on Earth, and be used as a molecular complexity scale to quantify the constraints needed to direct prebiotically plausible processes in the laboratory. Such an approach is vital if we are going to find new life elsewhere in the universe or create de-novo life in the lab.

Stuart M Marshall↗
NASA NTRS2022

Understanding Sampling Hardware Cleanliness from Perseverance Lessons Learned, and Forward Approach to Biosignature Missions

The search for biosignatures on other solar system bodies drives the scientific objectives of many ongoing and proposed exploration missions, including the Europa Lander mission concept.[1] The detection of trace and unfamiliar biosignatures in extreme environments necessitates state-of-the-art scientific instrumentation with extraordinary sensitivity – and often, extraordinary susceptibility to terrestrial and spacecraft self-induced contamination vectors.[2] While instruments can be carefully designed to operate remotely at high performance, in situ scientific measurements can only analyze the samples they’re given: samples or sample handling hardware that have been inadvertently tainted by outgassed organic molecules, thruster plume effluents, or other common sources of spacecraft contamination may yield ambiguous or false results. Maintaining and verifying the purity of collected samples and the cleanliness of sample handling hardware throughout the lifecycle of biosignature detection missions like Europa Lander is a primary responsibility of the Contamination Control group at JPL.

Alred, John↗
NASA NTRSDate not supplied

Biosignature Preservation Potential of Sulfate-Rich Rocks From Hogwallow Flats, Jezero Crater, Mars

The Mars 2020 Perseverance Rover discovered fine grained sedimentary rocks in the Hogwallow Flats member of the Shenandoah Formation at the ~3.6- to 3.8-billion-year-old Jezero crater, Mars. Mudstones and sandstones at the 3-meter-thick Hogwallow Flats (HWF) outcrop, and a laterally equivalent outcrop known as “Yori Pass”, show extensive evidence of diagenesis (alteration after deposition). Enhanced preservation of organic matter and other biosignatures can occur in early diagenetic environments associated with aqueous alteration in a lake, floodplain or pro-deltaic setting, as envisaged for HWF and Yori Pass [1]. Three drilled rock cores were collected from HWF-type bedrock as part of the Mars Sample Return Program. They are considered to be the samples with the highest potential to preserve organic compounds and biosignatures out of all samples collected so far by Perseverance (as of mission Sol 1000) [2]. This work outlines the implications of diagenesis for biosignature preservation in rock samples for possible return to Earth.

Mars 2020↗
NASA NTRS2018

Exoplanet Biosignatures: Observational Prospects

Exoplanet hunting efforts have revealed the prevalence of exotic worlds with diverse properties, including Earth-sized bodies, which has fueled our endeavor to search for life beyond the Solar System. Accumulating experiences in astrophysical, chemical, and climatological characterization of uninhabitable planets are paving the way to characterization of potentially habitable planets. In this paper, we review our possibilities and limitations in characterizing temperate terrestrial planets with future observational capabilities through the 2030s and beyond, as a basis of a broad range of discussions on how to advance "astrobiology" with exoplanets. We discuss the observability of not only the proposed biosignature candidates themselves but also of more general planetary properties that provide circumstantial evidence, since the evaluation of any biosignature candidate relies on its context. Characterization of temperate Earth-sized planets in the coming years will focus on those around nearby late-type stars. The James Webb Space Telescope (JWST) and later 30-meter-class ground-based telescopes will empower their chemical investigations. Spectroscopic studies of potentially habitable planets around solar-type stars will likely require a designated spacecraft mission for direct imaging, leveraging technologies that are already being developed and tested as part of the Wide Field InfraRed Survey Telescope (WFIRST) mission. Successful initial characterization of a few nearby targets will be an important touchstone toward a more detailed scrutiny and a larger survey that are envisioned beyond 2030. The broad outlook this paper presents may help develop new observational techniques to detect relevant features as well as frameworks to diagnose planets based on the observables.

Characterization↗
NASA NTRSDate not supplied

Algorithmic Detection of Elemental Biosignatures

Machine learning models that classify a sample as indicative or non-indicative of life could play an important role in life-detection missions. Their predictions result from agnostic algorithms and thereby add redundancy to judgements resulting from human expertise. Additionally, their important features can reveal the most informative measurements within the operational constraints of a life-detection mission. The Ladder of Life Detection (Neveu 2018) identifies the need for an understanding of how combinations of multiple biosignatures affect overall confidence. The present work provides a starting point to answer this need, and future work will expand the data types to obtain even more predictive combinations of features. Elemental abundance was chosen as a starting set of features due to its availability in diverse sample types, which are needed to train a generalizable model. A standardized dataset was collected, including 35 non-indicative, e.g., lunar rock, basalt; 19 indicative mixed, e.g., seawater, agricultural soil; 46 indicative non-alive, e.g., coal, chalk; and 10 indicative alive, e.g., biofilm, bacteria. This dataset could be valuable for complementary biosignature research. The samples were standardized to the same limit of detection of a simulated mission scenario. Four classification models were used: k-nearest neighbors (KNN), logistic regression (LR), linear support vector machines (SVM), and Gaussian naïve Bayes (GNB). To obtain feature importances, KNN was run on three principal components of the training data and LR and SVM were run with L1 and L2 regularization. The performances and feature importances of the six model variants on 40:60 train to validation ratios were assessed with Monte Carlo simulations. ROC AUC and mean accuracy scores ranged between 82% - 94%, with sensitivity greater than specificity. For indicative of life predictors, all models had C and Ca as strong and Cl as medium; a majority of models had N, K, and P as medium. For non-indicative of life predictors, all models had Si as strong, and a majority of models had Mg, Al, and Ti as medium. Varied elements were Fe (slightly non-indicative), H (slightly indicative), O (widely varied), Na, Mn, and S. These results serve as a proof of concept and suggest important elemental signals beyond merely the CHNOPS of Earth-based life.

Algorithmic↗
NASA NTRSDate not supplied

Classifying Agnostic Biosignatures using Raman, VNIR, and Elemental Data

How can we use our current wealth of terrestrial data, encompassing biogenic and abiogenic systems, to determine the distinguishing properties of life? SCOBI (Statistical Classification of Biosignature Information) uses machine learning techniques to algorithmically identify combinations of measurements that are “indicative of life”. A set of ~1000 observations, comprising elemental abundance, isotopic fractionation, VNIR reflectance, and (in progress) Raman spectra, have been assembled from existing literature and databases. The observations cover systems classified as “indicative alive” (e.g., cells, vegetation), “indicative non-alive” (e.g., fossils, teeth), “mixed indicative” (e.g., soil, pond water), or “non-indicative” (e.g., rocks, meteorites). VNIR data was preprocessed by linear interpolation from 400-2100 nm and smoothed with a Savitzky-Golay filter. To limit the amount of Earth-biochemistry-specific (non-agnostic) information included, the first five spectral features extracted were number of peaks, number of troughs, mean reflectance, mean peak width, and broadest peak width. To help further emphasize agnostic biosignatures, Earth-specific features such as chlorophylls have been manually flagged so that feature importance with and without them can be compared. Classifiers including k-nearest neighbors (KNN), Gaussian Naïve Bayes (GNB), logistic regression (LR), random forest (RF), and support vector machine (SVM) were implemented, as was a combination voting classifier. Performance metrics included false positive rates, false negative rates, and AUC with 50-50 test/train splits (Monte Carlo simulations). Key takeaways from this stage, prior to the inclusion of Raman spectra, are (1) the overall success rate of 0.933 AUC was most heavily influenced by the elemental abundance data; and (2) VNIR reflectance had the lowest classification performance with 0.52 AUC (58% of objects correctly classified). The next steps are to complete integration of Raman spectral data and to improve the approach to pre-processing and feature extraction for both types of spectral data, such as automated baseline removal, whole spectrum matching, and dimensionality reduction.

Biosignatures↗
NASA NTRSDate not supplied

Photon Harvesting and Rocky Planet Biosignatures with 3D Climate Models

On the Earth solar photons are collected, sifted, and harvested by life at a scale that has transformed and defined the planet and continues to do so. That transformation is considered to be a key biosignature to look for in the rocky exoplanet population of our galaxy. However, the availability of photons on planetary surfaces depends on orbital and spin configuration as well as shadowing and scattering by clouds and other atmospheric phenomena. We are using a state-of-the-art 3D climate model (ROCKE-3D, Way et al. 2017) to study rocky planet surface irradiances and the implications for biosignatures and future missions such as the Habitable Worlds Observatory.

exoplanets↗
NASA NTRS2004

Optical Detection of Organic Chemical Biosignatures at Hydrothermal Vents

We have developed a non-contact, optical life detection instrument that can detect organic chemical biosignatures in a number of different environments, including dry land, shallow aqueous, deep marine or in ice. Hence, the instrument is appropriate as a biosignature survey tool both for Mars exploration or in situ experiments in an ice-covered ocean such as one might wish to explore on Europa. Here, we report the results we obtained on an expedition aboard the Russian oceanographic vessel Akademik Mstislav Keldysh to hydrothermal vent sites in the Pacific Ocean using our life detection instrument MCDUVE, a multichannel, deep ultraviolet excitation fluorescence detector. MCDUVE detected organic material distribution on rocks near the vent, as well as direct detection of organisms, both microbial and microscopic. We also were able to detect organic material issuing directly from vent chimneys, measure the organic signature of the water column as we ascended, and passively observe the emission of light directly from some vents.

Conrad, P. G.↗
NASA NTRS2002

Remote sensing of planetary properties and biosignatures on extrasolar terrestrial planets

The major goals of NASA's Terrestrial Planet Finder (TPF) and the European Space Agency's Darwin missions are to detect terrestrial-sized extrasolar planets directly and to seek spectroscopic evidence of habitable conditions and life. Here we recommend wavelength ranges and spectral features for these missions. We assess known spectroscopic molecular band features of Earth, Venus, and Mars in the context of putative extrasolar analogs. The preferred wavelength ranges are 7-25 microns in the mid-IR and 0.5 to approximately 1.1 microns in the visible to near-IR. Detection of O2 or its photolytic product O3 merits highest priority. Liquid H2O is not a bioindicator, but it is considered essential to life. Substantial CO2 indicates an atmosphere and oxidation state typical of a terrestrial planet. Abundant CH4 might require a biological source, yet abundant CH4 also can arise from a crust and upper mantle more reduced than that of Earth. The range of characteristics of extrasolar rocky planets might far exceed that of the Solar System. Planetary size and mass are very important indicators of habitability and can be estimated in the mid-IR and potentially also in the visible to near-IR. Additional spectroscopic features merit study, for example, features created by other biosignature compounds in the atmosphere or on the surface and features due to Rayleigh scattering. In summary, we find that both the mid-IR and the visible to near-IR wavelength ranges offer valuable information regarding biosignatures and planetary properties; therefore both merit serious scientific consideration for TPF and Darwin.

Planets↗
NASA NTRS2003

Biosignatures of early earths

A major goal of NASA's Origins Program is to find habitable planets around other stars and determine which might harbor life. Determining whether or not an extrasolar planet harbors life requires an understanding of what spectral features (i.e., biosignatures) might result from life's presence. Consideration of potential biosignatures has tended to focus on spectral features of gases in Earth's modern atmosphere, particularly ozone, the photolytic product of biogenically produced molecular oxygen. But life existed on Earth for about 1(1/2) billion years before the buildup of atmospheric oxygen. Inferred characteristics of Earth's earliest biosphere and studies of modern microbial ecosystems that share some of those characteristics suggest that organosulfur compounds, particularly methanethiol (CH(3)SH, the sulfur analog of methanol), may have been biogenic products on early Earth. Similar production could take place on extrasolar Earth-like planets whose biota share functional chemical characteristics with Earth life. Since methanethiol and related organosulfur compounds (as well as carbon dioxide) absorb at wavelengths near or overlapping the 9.6-microm band of ozone, there is potential ambiguity in interpreting a feature around this wavelength in an extrasolar planet spectrum.

Earth (Planet)↗
NASA NTRS2019

Evaluating Biosignatures for Life Detection

The goal here is to develop a conceptual framework for evaluating the ability of different biosignatures to provide evidence for the presence of life in planned missions or observational studies. The focus is on intrinsic characteristics of biosignatures in a given space environment rather than on their detection, which depends on the current state of technology. Suitable evaluation procedures are based on an extensive body of previous work on related problems in which different options are evaluated to make decisions in business, engineering, medical fields and social or political arena. In these cases, three approaches have proven to be particularly useful. Two of them, signal detection theory (SDT) and Bayesian hypothesis testing are based on probabilities. The third approach, multi-attribute utility (MAU) is based on utility theory.

Pohorille, Andrew↗